habitat-performance relationships on an island: fitness...
TRANSCRIPT
Habitat-performance relationships on an island fitness
landscape of moose in Oumlland Sweden
Augusta MX Dorey
September 2014
A thesis submitted for the partial fulfilment of the requirements for the degree of Master of Science at
Imperial College London
Formatted in the journal style of Oecologia
Submitted for the MSc in Ecology Evolution and Conservation
2
DECLARATION OF OWN WORK
I declare that this thesis ldquoHabitat ndash performance relationships on an island fitness landscape of moose in
Ӧland Swedenrdquo is entirely my own work and that where material was constructed by others it is fully cited
and referenced andor with appropriate acknowledgement given
This research was funded by Swedish University of Agricultural Sciences Umearing Sweden (SLU)
Data was provided by the Moose Research Group SLU
Codes were conceived and designed by Augusta Dorey Navinder Singh and Andrew Allen
Andrew Allen provided information on the migratory status of moose individuals
Jacobs Index and habitat compositional R code was written by Andrew Allen
The data was analysed by Augusta Dorey
Augusta Dorey wrote the manuscript Navinder Singh and Andrew Allen provided editorial advice
In Collaboration with Swedish University of Agricultural Sciences Umearing Sweden
Word Count 5885
Name of Supervisors
Supervisor Dr Navinder J Singh1
Assistant Supervisor Mr Andrew Allen1
Internal Supervisor Dr David Orme2
1Department of Wildlife Fish and Environmental Studies Swedish University of Agricultural Sciences
Skogsmarksgraumlnd Umearing SE-90183
2Department of Life Sciences Imperial College London Silwood Park Campus Ascot Berkshire SL57PY
3 Contents
Abstract 4
Introduction 5
Materials and Methods 7
Study area 7
Capture and Handling 8
Data Screening 8
Home rangeUtilization distribution 8
Habitat 9
Activity 10
Diet analysis 10
Survival analysis 10
Results 11
Home RangeUtilization Distribution 11
Activity 12
Habitat ndash Proportions 13
Habitat - Selection 14
Diet 17
Calf Survival 18
Discussion 19
Acknowledgements 22
References 23
Appendix A 30
Introduction 30
Appendix B 31
Method and Materials 31
Appendix C 33
Home ranges 33
Appendix D 35
Activity 35
Appendix E 36
Habitat Proportions 36
Habitat Selection 37
Appendix F 50
Background 50
4
Abstract
Moose (Alces alces) the largest among the deer have both high recreational and economic value in
Scandinavia and elsewhere To efficiently manage such a valuable species the key factors affecting their
fitness and performance must be understood Moose generally have high productivity and calf survival in
predator free areas however in recent years populations at the southern edge of their distribution such as on
the predator free island of Ӧland in Sweden there have been reports of low calf survival Individuals are found
to carry Anaplasma phagocytophilum which has been thought to be one of the factors causing the low survival
The aim of this study was to identify what abiotic and biotic factors may also be affecting female moose
performance and their calf survival GPS data from 18 collared moose was used in conjunction with home
range activity diet survival and habitat analysis Moose did not alter the size of their seasonal home ranges
or their activity level Agricultural areas and feeding stations have become the preferred areas in the core home
ranges during the winter season The diet analysis revealed that nearly two thirds of the moosersquos winter diet
contained agricultural produce Moose are having to utilise areas where in other populations individuals tend
to avoid This could probably be one of the reasons for females to be of lower quality and therefore not being
able to ensure calf survival With changing climates and human land use moose continue to be under such
environmental pressures which may therefore jeopardize their future survival and reproduction
Key Words Population dynamics Habitat selection Performance Fitness Climate Survival Alces
alces Sweden Ӧland
Image by Fredrik Stenbacka
5 Introduction
The population size of animals varies in space and time (Turchin 2001) This variation is driven by a
combination of internal as well as external factors that drive changes in survival and reproduction of
individuals (Brown 2011) Internal factors are associated with life history such as sex age body mass and
generation time whereas the external factors include climatic factors (characterised as density independent)
competition food disease (characterised as density dependent) and human influence (appendix A) Long-term
changes in population size therefore determine the long-term fitness of individuals and cohorts in a population
(Albon et al 1987) However little is known about how these factors interact to produce short and long term
variation in demography and population dynamics across space Although difficult understanding causes of
variation of population size is crucial to effective population conservation and management (Lavsund et al
2003 McLoughlin et al 2011) The interplay and relative contribution of the above factors are best shown
from species with short generation times or from long-term monitoring studies
Ungulates are most commonly studied due to their international economic and recreational value large body
sizes and the relative ease of marking handling and capturing them (Forchhammer et al 2002 Bradshaw et
al 2003 Gordon et al 2004 Clutton-Brock and Sheldon 2010) Large herbivores tend to display low fecundity
and high adult survivorship (Gaillard et al 2000a) Past studies have revealed important details about the
factors affecting their population dynamics An ungulate life cycle is usually classified based on defined age
classes new-born weaned young yearlings two-year-olds prime-aged adults and senescent adults (older than
seven years) New-born survival is highly dependent on climatic conditions predation and the level of maternal
care and condition ie quality of milk and reproductive experience (Gaillard et al 2000a Testa 2004 Baringrdsen
et al 2008) Weaned young and yearlings survival tends to be independent of the mothers care and affected
most often by climatic conditions ie severe winters disease and predation (Bartmann et al 1992) Survival
of two-year olds and adults is influenced mainly by predation (Modafferi 1997) Males generally experience a
lower survival rate than females due to the pressure of the rut and male biased hunting (Mysterud et al 2005)
Conditions experienced during a calfrsquos early development not only cause immediate effects on its future
performance but also delayed effects Calf development (weight) affects its future reproductive success
(performance) by effecting adult body size and future calf body size (Albon et al 1987 Lindstroumlm 1999
Forchhammer et al 2002)
The moose (Alces alces) is a large ungulate widely distributed across the northern hemisphere It is the largest
and only solitary member of the deer family (Cervidae) In Sweden it is found throughout the country in boreal
forests with the exception of the island of Gotland (Brandin 2009) Sweden has the largest population of moose
in Europe with approximately 300000-350000 individuals (Singh et al 2014) A part of Swedenrsquos moose
population is influenced to some extent by predators such as brown bears (Ursus arctos) and wolves (Canis
lupus) however in predator free populations individuals are influenced mainly by stochastic environmental
conditions population density traffic and above all hunting (Sӕther 1997) (appendix A) Moose are hunted
all across Scandinavia and the overall value of moose hunting is estimated to be 145 billion SEK per year
6
(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested
providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of
selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove
the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson
et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio
(Laurian et al 2000 Harris et al 2002 Milner et al 2007)
Moose are known to have a generally high calf survival noted through studies from predator free areas in both
North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of
other factors are nevertheless known to affect the survival during their first summer such as climatic variation
malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al
2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival
in single odd years has been attributed to weather and low food quality
During recent years moose populations appear to be under environmental stress across their southern range
ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in
press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in
southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement
between hunters This was due to a fear of population collapse due to poor management strategies in previous
years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex
ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department
of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there
was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study
during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and
158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and
Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and
prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above
rationale in mind this study investigates the habitat performance relationships of female moose on the island
of Oumlland This study also provides a model for examining the factors affecting population dynamics on an
island
7 Materials and Methods
Study area
Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest
island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There
are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest
portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are
dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus
aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed
throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is
made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather
(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated
from each other by agricultural areas which are distributed throughout the island particularly along the coastal
regions and the island centre The most southerly patch of forest was protected from becoming agricultural
due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius
personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like
alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow
nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)
Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-
shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which
were banned from hunting in previous years
Fig 1 Location of Oumlland
8
Capture and Handling
A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars
(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group
SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were
fixed to return GPS locations approximately every 30 minutes
Data Screening
The sample contained both males and females (six males 19 females x female age = 95 years range 4-17
years) An initial inspection revealed that one female individual only returned fixed locations for a period of
eight months Locations ceased during the hunting period so the individual was presumed shot and was
removed from the data along with the males
The exact time between each location varied and sometimes no fix could be made The adehabitatLT package
(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA
was used to place NAs where relocations were missing The function sett0 was used to round the timing of
collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis
consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the
north ten individuals from the centre and six individuals from the south
To address the question and to investigate the influence of climate on the space use patterns of moose the
analysis was performed at two scales The first included all annual movements of moose and the second at a
seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)
and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the
period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing
with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and
end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian
Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is
defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-
Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)
Home rangeUtilization distribution
Variation in ungulate home range size is known to be caused by changes in energy requirements and variation
in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts
in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)
Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al
1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)
The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal
activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to
9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be
described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space
and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are
viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos
movements and space use within their home range (Kranstauber et al 2012) (see appendix A)
Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)
kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is
considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The
BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB
does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos
movement is purely random it moves from a starting point and ends up at the end location randomly By
adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a
certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)
A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and
prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m
scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the
resolution of the data remains consistent between individuals The diffusion coefficient determines the variance
in the location of the kernels between two locations This was calculated from each individualrsquos dataset using
the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB
advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax
and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were
removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from
the UD using the kernelarea function
Habitat
The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape
(second order selection) was studied by comparing the UD95 with available habitats in each of the three study
areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by
comparing the UD50 with the UD95 (UD50UD95)
12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal
coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas
urban areas and younger forests The proportion of area covered by each of these habitat classes was
determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska
Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25
m
Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with
the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not
10
all home ranges contained them This combined approach allowed identification of habitats that are used
disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of
which habitats are important for an individual
119863 = ( 119903minus119901
119903+119901minus2119903119901 ) (eqn1)
r = Proportion of habitat type used
p = Total proportion of habitat available
D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating
the habitat is used in proportion to its availability
Activity
Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals
in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately
only two cows were collared in the north and were therefore left out of this analysis Moose were identified as
migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were
initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed
during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis
One individual was also removed due it its collar not returning relocations during the entirety of the WS
Diet analysis
The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were
shot in the centre and south of the island during the WS of 2013
Survival analysis
The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf
was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving
season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter
Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve
shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick
et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival
function The S(t) of this study is the probability of an individual surviving from birth to after the hunt
(Method summary see appendix B)
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation
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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
2
DECLARATION OF OWN WORK
I declare that this thesis ldquoHabitat ndash performance relationships on an island fitness landscape of moose in
Ӧland Swedenrdquo is entirely my own work and that where material was constructed by others it is fully cited
and referenced andor with appropriate acknowledgement given
This research was funded by Swedish University of Agricultural Sciences Umearing Sweden (SLU)
Data was provided by the Moose Research Group SLU
Codes were conceived and designed by Augusta Dorey Navinder Singh and Andrew Allen
Andrew Allen provided information on the migratory status of moose individuals
Jacobs Index and habitat compositional R code was written by Andrew Allen
The data was analysed by Augusta Dorey
Augusta Dorey wrote the manuscript Navinder Singh and Andrew Allen provided editorial advice
In Collaboration with Swedish University of Agricultural Sciences Umearing Sweden
Word Count 5885
Name of Supervisors
Supervisor Dr Navinder J Singh1
Assistant Supervisor Mr Andrew Allen1
Internal Supervisor Dr David Orme2
1Department of Wildlife Fish and Environmental Studies Swedish University of Agricultural Sciences
Skogsmarksgraumlnd Umearing SE-90183
2Department of Life Sciences Imperial College London Silwood Park Campus Ascot Berkshire SL57PY
3 Contents
Abstract 4
Introduction 5
Materials and Methods 7
Study area 7
Capture and Handling 8
Data Screening 8
Home rangeUtilization distribution 8
Habitat 9
Activity 10
Diet analysis 10
Survival analysis 10
Results 11
Home RangeUtilization Distribution 11
Activity 12
Habitat ndash Proportions 13
Habitat - Selection 14
Diet 17
Calf Survival 18
Discussion 19
Acknowledgements 22
References 23
Appendix A 30
Introduction 30
Appendix B 31
Method and Materials 31
Appendix C 33
Home ranges 33
Appendix D 35
Activity 35
Appendix E 36
Habitat Proportions 36
Habitat Selection 37
Appendix F 50
Background 50
4
Abstract
Moose (Alces alces) the largest among the deer have both high recreational and economic value in
Scandinavia and elsewhere To efficiently manage such a valuable species the key factors affecting their
fitness and performance must be understood Moose generally have high productivity and calf survival in
predator free areas however in recent years populations at the southern edge of their distribution such as on
the predator free island of Ӧland in Sweden there have been reports of low calf survival Individuals are found
to carry Anaplasma phagocytophilum which has been thought to be one of the factors causing the low survival
The aim of this study was to identify what abiotic and biotic factors may also be affecting female moose
performance and their calf survival GPS data from 18 collared moose was used in conjunction with home
range activity diet survival and habitat analysis Moose did not alter the size of their seasonal home ranges
or their activity level Agricultural areas and feeding stations have become the preferred areas in the core home
ranges during the winter season The diet analysis revealed that nearly two thirds of the moosersquos winter diet
contained agricultural produce Moose are having to utilise areas where in other populations individuals tend
to avoid This could probably be one of the reasons for females to be of lower quality and therefore not being
able to ensure calf survival With changing climates and human land use moose continue to be under such
environmental pressures which may therefore jeopardize their future survival and reproduction
Key Words Population dynamics Habitat selection Performance Fitness Climate Survival Alces
alces Sweden Ӧland
Image by Fredrik Stenbacka
5 Introduction
The population size of animals varies in space and time (Turchin 2001) This variation is driven by a
combination of internal as well as external factors that drive changes in survival and reproduction of
individuals (Brown 2011) Internal factors are associated with life history such as sex age body mass and
generation time whereas the external factors include climatic factors (characterised as density independent)
competition food disease (characterised as density dependent) and human influence (appendix A) Long-term
changes in population size therefore determine the long-term fitness of individuals and cohorts in a population
(Albon et al 1987) However little is known about how these factors interact to produce short and long term
variation in demography and population dynamics across space Although difficult understanding causes of
variation of population size is crucial to effective population conservation and management (Lavsund et al
2003 McLoughlin et al 2011) The interplay and relative contribution of the above factors are best shown
from species with short generation times or from long-term monitoring studies
Ungulates are most commonly studied due to their international economic and recreational value large body
sizes and the relative ease of marking handling and capturing them (Forchhammer et al 2002 Bradshaw et
al 2003 Gordon et al 2004 Clutton-Brock and Sheldon 2010) Large herbivores tend to display low fecundity
and high adult survivorship (Gaillard et al 2000a) Past studies have revealed important details about the
factors affecting their population dynamics An ungulate life cycle is usually classified based on defined age
classes new-born weaned young yearlings two-year-olds prime-aged adults and senescent adults (older than
seven years) New-born survival is highly dependent on climatic conditions predation and the level of maternal
care and condition ie quality of milk and reproductive experience (Gaillard et al 2000a Testa 2004 Baringrdsen
et al 2008) Weaned young and yearlings survival tends to be independent of the mothers care and affected
most often by climatic conditions ie severe winters disease and predation (Bartmann et al 1992) Survival
of two-year olds and adults is influenced mainly by predation (Modafferi 1997) Males generally experience a
lower survival rate than females due to the pressure of the rut and male biased hunting (Mysterud et al 2005)
Conditions experienced during a calfrsquos early development not only cause immediate effects on its future
performance but also delayed effects Calf development (weight) affects its future reproductive success
(performance) by effecting adult body size and future calf body size (Albon et al 1987 Lindstroumlm 1999
Forchhammer et al 2002)
The moose (Alces alces) is a large ungulate widely distributed across the northern hemisphere It is the largest
and only solitary member of the deer family (Cervidae) In Sweden it is found throughout the country in boreal
forests with the exception of the island of Gotland (Brandin 2009) Sweden has the largest population of moose
in Europe with approximately 300000-350000 individuals (Singh et al 2014) A part of Swedenrsquos moose
population is influenced to some extent by predators such as brown bears (Ursus arctos) and wolves (Canis
lupus) however in predator free populations individuals are influenced mainly by stochastic environmental
conditions population density traffic and above all hunting (Sӕther 1997) (appendix A) Moose are hunted
all across Scandinavia and the overall value of moose hunting is estimated to be 145 billion SEK per year
6
(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested
providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of
selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove
the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson
et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio
(Laurian et al 2000 Harris et al 2002 Milner et al 2007)
Moose are known to have a generally high calf survival noted through studies from predator free areas in both
North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of
other factors are nevertheless known to affect the survival during their first summer such as climatic variation
malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al
2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival
in single odd years has been attributed to weather and low food quality
During recent years moose populations appear to be under environmental stress across their southern range
ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in
press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in
southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement
between hunters This was due to a fear of population collapse due to poor management strategies in previous
years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex
ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department
of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there
was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study
during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and
158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and
Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and
prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above
rationale in mind this study investigates the habitat performance relationships of female moose on the island
of Oumlland This study also provides a model for examining the factors affecting population dynamics on an
island
7 Materials and Methods
Study area
Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest
island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There
are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest
portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are
dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus
aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed
throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is
made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather
(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated
from each other by agricultural areas which are distributed throughout the island particularly along the coastal
regions and the island centre The most southerly patch of forest was protected from becoming agricultural
due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius
personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like
alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow
nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)
Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-
shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which
were banned from hunting in previous years
Fig 1 Location of Oumlland
8
Capture and Handling
A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars
(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group
SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were
fixed to return GPS locations approximately every 30 minutes
Data Screening
The sample contained both males and females (six males 19 females x female age = 95 years range 4-17
years) An initial inspection revealed that one female individual only returned fixed locations for a period of
eight months Locations ceased during the hunting period so the individual was presumed shot and was
removed from the data along with the males
The exact time between each location varied and sometimes no fix could be made The adehabitatLT package
(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA
was used to place NAs where relocations were missing The function sett0 was used to round the timing of
collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis
consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the
north ten individuals from the centre and six individuals from the south
To address the question and to investigate the influence of climate on the space use patterns of moose the
analysis was performed at two scales The first included all annual movements of moose and the second at a
seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)
and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the
period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing
with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and
end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian
Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is
defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-
Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)
Home rangeUtilization distribution
Variation in ungulate home range size is known to be caused by changes in energy requirements and variation
in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts
in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)
Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al
1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)
The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal
activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to
9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be
described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space
and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are
viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos
movements and space use within their home range (Kranstauber et al 2012) (see appendix A)
Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)
kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is
considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The
BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB
does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos
movement is purely random it moves from a starting point and ends up at the end location randomly By
adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a
certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)
A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and
prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m
scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the
resolution of the data remains consistent between individuals The diffusion coefficient determines the variance
in the location of the kernels between two locations This was calculated from each individualrsquos dataset using
the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB
advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax
and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were
removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from
the UD using the kernelarea function
Habitat
The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape
(second order selection) was studied by comparing the UD95 with available habitats in each of the three study
areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by
comparing the UD50 with the UD95 (UD50UD95)
12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal
coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas
urban areas and younger forests The proportion of area covered by each of these habitat classes was
determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska
Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25
m
Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with
the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not
10
all home ranges contained them This combined approach allowed identification of habitats that are used
disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of
which habitats are important for an individual
119863 = ( 119903minus119901
119903+119901minus2119903119901 ) (eqn1)
r = Proportion of habitat type used
p = Total proportion of habitat available
D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating
the habitat is used in proportion to its availability
Activity
Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals
in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately
only two cows were collared in the north and were therefore left out of this analysis Moose were identified as
migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were
initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed
during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis
One individual was also removed due it its collar not returning relocations during the entirety of the WS
Diet analysis
The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were
shot in the centre and south of the island during the WS of 2013
Survival analysis
The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf
was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving
season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter
Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve
shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick
et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival
function The S(t) of this study is the probability of an individual surviving from birth to after the hunt
(Method summary see appendix B)
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
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Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and
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Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet
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Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for
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Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology
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Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict
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Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges
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Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R
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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive
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29
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Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for
conservation of large mammals in a fragmented environment Alces 4965-81
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success in muskoxen Journal of Zoology 24313-20
30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
3 Contents
Abstract 4
Introduction 5
Materials and Methods 7
Study area 7
Capture and Handling 8
Data Screening 8
Home rangeUtilization distribution 8
Habitat 9
Activity 10
Diet analysis 10
Survival analysis 10
Results 11
Home RangeUtilization Distribution 11
Activity 12
Habitat ndash Proportions 13
Habitat - Selection 14
Diet 17
Calf Survival 18
Discussion 19
Acknowledgements 22
References 23
Appendix A 30
Introduction 30
Appendix B 31
Method and Materials 31
Appendix C 33
Home ranges 33
Appendix D 35
Activity 35
Appendix E 36
Habitat Proportions 36
Habitat Selection 37
Appendix F 50
Background 50
4
Abstract
Moose (Alces alces) the largest among the deer have both high recreational and economic value in
Scandinavia and elsewhere To efficiently manage such a valuable species the key factors affecting their
fitness and performance must be understood Moose generally have high productivity and calf survival in
predator free areas however in recent years populations at the southern edge of their distribution such as on
the predator free island of Ӧland in Sweden there have been reports of low calf survival Individuals are found
to carry Anaplasma phagocytophilum which has been thought to be one of the factors causing the low survival
The aim of this study was to identify what abiotic and biotic factors may also be affecting female moose
performance and their calf survival GPS data from 18 collared moose was used in conjunction with home
range activity diet survival and habitat analysis Moose did not alter the size of their seasonal home ranges
or their activity level Agricultural areas and feeding stations have become the preferred areas in the core home
ranges during the winter season The diet analysis revealed that nearly two thirds of the moosersquos winter diet
contained agricultural produce Moose are having to utilise areas where in other populations individuals tend
to avoid This could probably be one of the reasons for females to be of lower quality and therefore not being
able to ensure calf survival With changing climates and human land use moose continue to be under such
environmental pressures which may therefore jeopardize their future survival and reproduction
Key Words Population dynamics Habitat selection Performance Fitness Climate Survival Alces
alces Sweden Ӧland
Image by Fredrik Stenbacka
5 Introduction
The population size of animals varies in space and time (Turchin 2001) This variation is driven by a
combination of internal as well as external factors that drive changes in survival and reproduction of
individuals (Brown 2011) Internal factors are associated with life history such as sex age body mass and
generation time whereas the external factors include climatic factors (characterised as density independent)
competition food disease (characterised as density dependent) and human influence (appendix A) Long-term
changes in population size therefore determine the long-term fitness of individuals and cohorts in a population
(Albon et al 1987) However little is known about how these factors interact to produce short and long term
variation in demography and population dynamics across space Although difficult understanding causes of
variation of population size is crucial to effective population conservation and management (Lavsund et al
2003 McLoughlin et al 2011) The interplay and relative contribution of the above factors are best shown
from species with short generation times or from long-term monitoring studies
Ungulates are most commonly studied due to their international economic and recreational value large body
sizes and the relative ease of marking handling and capturing them (Forchhammer et al 2002 Bradshaw et
al 2003 Gordon et al 2004 Clutton-Brock and Sheldon 2010) Large herbivores tend to display low fecundity
and high adult survivorship (Gaillard et al 2000a) Past studies have revealed important details about the
factors affecting their population dynamics An ungulate life cycle is usually classified based on defined age
classes new-born weaned young yearlings two-year-olds prime-aged adults and senescent adults (older than
seven years) New-born survival is highly dependent on climatic conditions predation and the level of maternal
care and condition ie quality of milk and reproductive experience (Gaillard et al 2000a Testa 2004 Baringrdsen
et al 2008) Weaned young and yearlings survival tends to be independent of the mothers care and affected
most often by climatic conditions ie severe winters disease and predation (Bartmann et al 1992) Survival
of two-year olds and adults is influenced mainly by predation (Modafferi 1997) Males generally experience a
lower survival rate than females due to the pressure of the rut and male biased hunting (Mysterud et al 2005)
Conditions experienced during a calfrsquos early development not only cause immediate effects on its future
performance but also delayed effects Calf development (weight) affects its future reproductive success
(performance) by effecting adult body size and future calf body size (Albon et al 1987 Lindstroumlm 1999
Forchhammer et al 2002)
The moose (Alces alces) is a large ungulate widely distributed across the northern hemisphere It is the largest
and only solitary member of the deer family (Cervidae) In Sweden it is found throughout the country in boreal
forests with the exception of the island of Gotland (Brandin 2009) Sweden has the largest population of moose
in Europe with approximately 300000-350000 individuals (Singh et al 2014) A part of Swedenrsquos moose
population is influenced to some extent by predators such as brown bears (Ursus arctos) and wolves (Canis
lupus) however in predator free populations individuals are influenced mainly by stochastic environmental
conditions population density traffic and above all hunting (Sӕther 1997) (appendix A) Moose are hunted
all across Scandinavia and the overall value of moose hunting is estimated to be 145 billion SEK per year
6
(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested
providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of
selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove
the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson
et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio
(Laurian et al 2000 Harris et al 2002 Milner et al 2007)
Moose are known to have a generally high calf survival noted through studies from predator free areas in both
North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of
other factors are nevertheless known to affect the survival during their first summer such as climatic variation
malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al
2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival
in single odd years has been attributed to weather and low food quality
During recent years moose populations appear to be under environmental stress across their southern range
ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in
press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in
southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement
between hunters This was due to a fear of population collapse due to poor management strategies in previous
years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex
ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department
of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there
was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study
during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and
158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and
Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and
prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above
rationale in mind this study investigates the habitat performance relationships of female moose on the island
of Oumlland This study also provides a model for examining the factors affecting population dynamics on an
island
7 Materials and Methods
Study area
Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest
island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There
are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest
portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are
dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus
aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed
throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is
made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather
(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated
from each other by agricultural areas which are distributed throughout the island particularly along the coastal
regions and the island centre The most southerly patch of forest was protected from becoming agricultural
due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius
personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like
alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow
nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)
Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-
shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which
were banned from hunting in previous years
Fig 1 Location of Oumlland
8
Capture and Handling
A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars
(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group
SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were
fixed to return GPS locations approximately every 30 minutes
Data Screening
The sample contained both males and females (six males 19 females x female age = 95 years range 4-17
years) An initial inspection revealed that one female individual only returned fixed locations for a period of
eight months Locations ceased during the hunting period so the individual was presumed shot and was
removed from the data along with the males
The exact time between each location varied and sometimes no fix could be made The adehabitatLT package
(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA
was used to place NAs where relocations were missing The function sett0 was used to round the timing of
collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis
consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the
north ten individuals from the centre and six individuals from the south
To address the question and to investigate the influence of climate on the space use patterns of moose the
analysis was performed at two scales The first included all annual movements of moose and the second at a
seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)
and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the
period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing
with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and
end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian
Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is
defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-
Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)
Home rangeUtilization distribution
Variation in ungulate home range size is known to be caused by changes in energy requirements and variation
in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts
in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)
Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al
1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)
The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal
activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to
9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be
described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space
and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are
viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos
movements and space use within their home range (Kranstauber et al 2012) (see appendix A)
Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)
kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is
considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The
BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB
does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos
movement is purely random it moves from a starting point and ends up at the end location randomly By
adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a
certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)
A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and
prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m
scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the
resolution of the data remains consistent between individuals The diffusion coefficient determines the variance
in the location of the kernels between two locations This was calculated from each individualrsquos dataset using
the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB
advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax
and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were
removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from
the UD using the kernelarea function
Habitat
The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape
(second order selection) was studied by comparing the UD95 with available habitats in each of the three study
areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by
comparing the UD50 with the UD95 (UD50UD95)
12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal
coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas
urban areas and younger forests The proportion of area covered by each of these habitat classes was
determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska
Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25
m
Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with
the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not
10
all home ranges contained them This combined approach allowed identification of habitats that are used
disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of
which habitats are important for an individual
119863 = ( 119903minus119901
119903+119901minus2119903119901 ) (eqn1)
r = Proportion of habitat type used
p = Total proportion of habitat available
D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating
the habitat is used in proportion to its availability
Activity
Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals
in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately
only two cows were collared in the north and were therefore left out of this analysis Moose were identified as
migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were
initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed
during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis
One individual was also removed due it its collar not returning relocations during the entirety of the WS
Diet analysis
The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were
shot in the centre and south of the island during the WS of 2013
Survival analysis
The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf
was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving
season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter
Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve
shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick
et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival
function The S(t) of this study is the probability of an individual surviving from birth to after the hunt
(Method summary see appendix B)
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
4
Abstract
Moose (Alces alces) the largest among the deer have both high recreational and economic value in
Scandinavia and elsewhere To efficiently manage such a valuable species the key factors affecting their
fitness and performance must be understood Moose generally have high productivity and calf survival in
predator free areas however in recent years populations at the southern edge of their distribution such as on
the predator free island of Ӧland in Sweden there have been reports of low calf survival Individuals are found
to carry Anaplasma phagocytophilum which has been thought to be one of the factors causing the low survival
The aim of this study was to identify what abiotic and biotic factors may also be affecting female moose
performance and their calf survival GPS data from 18 collared moose was used in conjunction with home
range activity diet survival and habitat analysis Moose did not alter the size of their seasonal home ranges
or their activity level Agricultural areas and feeding stations have become the preferred areas in the core home
ranges during the winter season The diet analysis revealed that nearly two thirds of the moosersquos winter diet
contained agricultural produce Moose are having to utilise areas where in other populations individuals tend
to avoid This could probably be one of the reasons for females to be of lower quality and therefore not being
able to ensure calf survival With changing climates and human land use moose continue to be under such
environmental pressures which may therefore jeopardize their future survival and reproduction
Key Words Population dynamics Habitat selection Performance Fitness Climate Survival Alces
alces Sweden Ӧland
Image by Fredrik Stenbacka
5 Introduction
The population size of animals varies in space and time (Turchin 2001) This variation is driven by a
combination of internal as well as external factors that drive changes in survival and reproduction of
individuals (Brown 2011) Internal factors are associated with life history such as sex age body mass and
generation time whereas the external factors include climatic factors (characterised as density independent)
competition food disease (characterised as density dependent) and human influence (appendix A) Long-term
changes in population size therefore determine the long-term fitness of individuals and cohorts in a population
(Albon et al 1987) However little is known about how these factors interact to produce short and long term
variation in demography and population dynamics across space Although difficult understanding causes of
variation of population size is crucial to effective population conservation and management (Lavsund et al
2003 McLoughlin et al 2011) The interplay and relative contribution of the above factors are best shown
from species with short generation times or from long-term monitoring studies
Ungulates are most commonly studied due to their international economic and recreational value large body
sizes and the relative ease of marking handling and capturing them (Forchhammer et al 2002 Bradshaw et
al 2003 Gordon et al 2004 Clutton-Brock and Sheldon 2010) Large herbivores tend to display low fecundity
and high adult survivorship (Gaillard et al 2000a) Past studies have revealed important details about the
factors affecting their population dynamics An ungulate life cycle is usually classified based on defined age
classes new-born weaned young yearlings two-year-olds prime-aged adults and senescent adults (older than
seven years) New-born survival is highly dependent on climatic conditions predation and the level of maternal
care and condition ie quality of milk and reproductive experience (Gaillard et al 2000a Testa 2004 Baringrdsen
et al 2008) Weaned young and yearlings survival tends to be independent of the mothers care and affected
most often by climatic conditions ie severe winters disease and predation (Bartmann et al 1992) Survival
of two-year olds and adults is influenced mainly by predation (Modafferi 1997) Males generally experience a
lower survival rate than females due to the pressure of the rut and male biased hunting (Mysterud et al 2005)
Conditions experienced during a calfrsquos early development not only cause immediate effects on its future
performance but also delayed effects Calf development (weight) affects its future reproductive success
(performance) by effecting adult body size and future calf body size (Albon et al 1987 Lindstroumlm 1999
Forchhammer et al 2002)
The moose (Alces alces) is a large ungulate widely distributed across the northern hemisphere It is the largest
and only solitary member of the deer family (Cervidae) In Sweden it is found throughout the country in boreal
forests with the exception of the island of Gotland (Brandin 2009) Sweden has the largest population of moose
in Europe with approximately 300000-350000 individuals (Singh et al 2014) A part of Swedenrsquos moose
population is influenced to some extent by predators such as brown bears (Ursus arctos) and wolves (Canis
lupus) however in predator free populations individuals are influenced mainly by stochastic environmental
conditions population density traffic and above all hunting (Sӕther 1997) (appendix A) Moose are hunted
all across Scandinavia and the overall value of moose hunting is estimated to be 145 billion SEK per year
6
(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested
providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of
selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove
the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson
et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio
(Laurian et al 2000 Harris et al 2002 Milner et al 2007)
Moose are known to have a generally high calf survival noted through studies from predator free areas in both
North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of
other factors are nevertheless known to affect the survival during their first summer such as climatic variation
malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al
2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival
in single odd years has been attributed to weather and low food quality
During recent years moose populations appear to be under environmental stress across their southern range
ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in
press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in
southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement
between hunters This was due to a fear of population collapse due to poor management strategies in previous
years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex
ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department
of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there
was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study
during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and
158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and
Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and
prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above
rationale in mind this study investigates the habitat performance relationships of female moose on the island
of Oumlland This study also provides a model for examining the factors affecting population dynamics on an
island
7 Materials and Methods
Study area
Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest
island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There
are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest
portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are
dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus
aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed
throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is
made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather
(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated
from each other by agricultural areas which are distributed throughout the island particularly along the coastal
regions and the island centre The most southerly patch of forest was protected from becoming agricultural
due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius
personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like
alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow
nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)
Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-
shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which
were banned from hunting in previous years
Fig 1 Location of Oumlland
8
Capture and Handling
A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars
(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group
SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were
fixed to return GPS locations approximately every 30 minutes
Data Screening
The sample contained both males and females (six males 19 females x female age = 95 years range 4-17
years) An initial inspection revealed that one female individual only returned fixed locations for a period of
eight months Locations ceased during the hunting period so the individual was presumed shot and was
removed from the data along with the males
The exact time between each location varied and sometimes no fix could be made The adehabitatLT package
(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA
was used to place NAs where relocations were missing The function sett0 was used to round the timing of
collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis
consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the
north ten individuals from the centre and six individuals from the south
To address the question and to investigate the influence of climate on the space use patterns of moose the
analysis was performed at two scales The first included all annual movements of moose and the second at a
seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)
and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the
period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing
with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and
end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian
Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is
defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-
Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)
Home rangeUtilization distribution
Variation in ungulate home range size is known to be caused by changes in energy requirements and variation
in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts
in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)
Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al
1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)
The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal
activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to
9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be
described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space
and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are
viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos
movements and space use within their home range (Kranstauber et al 2012) (see appendix A)
Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)
kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is
considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The
BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB
does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos
movement is purely random it moves from a starting point and ends up at the end location randomly By
adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a
certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)
A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and
prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m
scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the
resolution of the data remains consistent between individuals The diffusion coefficient determines the variance
in the location of the kernels between two locations This was calculated from each individualrsquos dataset using
the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB
advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax
and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were
removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from
the UD using the kernelarea function
Habitat
The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape
(second order selection) was studied by comparing the UD95 with available habitats in each of the three study
areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by
comparing the UD50 with the UD95 (UD50UD95)
12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal
coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas
urban areas and younger forests The proportion of area covered by each of these habitat classes was
determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska
Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25
m
Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with
the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not
10
all home ranges contained them This combined approach allowed identification of habitats that are used
disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of
which habitats are important for an individual
119863 = ( 119903minus119901
119903+119901minus2119903119901 ) (eqn1)
r = Proportion of habitat type used
p = Total proportion of habitat available
D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating
the habitat is used in proportion to its availability
Activity
Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals
in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately
only two cows were collared in the north and were therefore left out of this analysis Moose were identified as
migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were
initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed
during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis
One individual was also removed due it its collar not returning relocations during the entirety of the WS
Diet analysis
The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were
shot in the centre and south of the island during the WS of 2013
Survival analysis
The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf
was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving
season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter
Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve
shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick
et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival
function The S(t) of this study is the probability of an individual surviving from birth to after the hunt
(Method summary see appendix B)
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a
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Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-
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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of
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25 Festa-Bianchet M Gaillard JM Jorgenson JT (1998) Mass and density-dependent reproductive success and
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Gaillard JM Festa-Bianchet M Yoccoz NG (1998) Population dynamics of large herbivores variable
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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness
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Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation
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Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and
functional responses in red deer habitat selection Ecology 90699ndash710
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Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for
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Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S
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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive
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29
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
5 Introduction
The population size of animals varies in space and time (Turchin 2001) This variation is driven by a
combination of internal as well as external factors that drive changes in survival and reproduction of
individuals (Brown 2011) Internal factors are associated with life history such as sex age body mass and
generation time whereas the external factors include climatic factors (characterised as density independent)
competition food disease (characterised as density dependent) and human influence (appendix A) Long-term
changes in population size therefore determine the long-term fitness of individuals and cohorts in a population
(Albon et al 1987) However little is known about how these factors interact to produce short and long term
variation in demography and population dynamics across space Although difficult understanding causes of
variation of population size is crucial to effective population conservation and management (Lavsund et al
2003 McLoughlin et al 2011) The interplay and relative contribution of the above factors are best shown
from species with short generation times or from long-term monitoring studies
Ungulates are most commonly studied due to their international economic and recreational value large body
sizes and the relative ease of marking handling and capturing them (Forchhammer et al 2002 Bradshaw et
al 2003 Gordon et al 2004 Clutton-Brock and Sheldon 2010) Large herbivores tend to display low fecundity
and high adult survivorship (Gaillard et al 2000a) Past studies have revealed important details about the
factors affecting their population dynamics An ungulate life cycle is usually classified based on defined age
classes new-born weaned young yearlings two-year-olds prime-aged adults and senescent adults (older than
seven years) New-born survival is highly dependent on climatic conditions predation and the level of maternal
care and condition ie quality of milk and reproductive experience (Gaillard et al 2000a Testa 2004 Baringrdsen
et al 2008) Weaned young and yearlings survival tends to be independent of the mothers care and affected
most often by climatic conditions ie severe winters disease and predation (Bartmann et al 1992) Survival
of two-year olds and adults is influenced mainly by predation (Modafferi 1997) Males generally experience a
lower survival rate than females due to the pressure of the rut and male biased hunting (Mysterud et al 2005)
Conditions experienced during a calfrsquos early development not only cause immediate effects on its future
performance but also delayed effects Calf development (weight) affects its future reproductive success
(performance) by effecting adult body size and future calf body size (Albon et al 1987 Lindstroumlm 1999
Forchhammer et al 2002)
The moose (Alces alces) is a large ungulate widely distributed across the northern hemisphere It is the largest
and only solitary member of the deer family (Cervidae) In Sweden it is found throughout the country in boreal
forests with the exception of the island of Gotland (Brandin 2009) Sweden has the largest population of moose
in Europe with approximately 300000-350000 individuals (Singh et al 2014) A part of Swedenrsquos moose
population is influenced to some extent by predators such as brown bears (Ursus arctos) and wolves (Canis
lupus) however in predator free populations individuals are influenced mainly by stochastic environmental
conditions population density traffic and above all hunting (Sӕther 1997) (appendix A) Moose are hunted
all across Scandinavia and the overall value of moose hunting is estimated to be 145 billion SEK per year
6
(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested
providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of
selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove
the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson
et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio
(Laurian et al 2000 Harris et al 2002 Milner et al 2007)
Moose are known to have a generally high calf survival noted through studies from predator free areas in both
North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of
other factors are nevertheless known to affect the survival during their first summer such as climatic variation
malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al
2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival
in single odd years has been attributed to weather and low food quality
During recent years moose populations appear to be under environmental stress across their southern range
ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in
press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in
southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement
between hunters This was due to a fear of population collapse due to poor management strategies in previous
years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex
ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department
of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there
was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study
during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and
158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and
Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and
prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above
rationale in mind this study investigates the habitat performance relationships of female moose on the island
of Oumlland This study also provides a model for examining the factors affecting population dynamics on an
island
7 Materials and Methods
Study area
Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest
island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There
are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest
portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are
dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus
aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed
throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is
made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather
(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated
from each other by agricultural areas which are distributed throughout the island particularly along the coastal
regions and the island centre The most southerly patch of forest was protected from becoming agricultural
due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius
personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like
alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow
nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)
Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-
shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which
were banned from hunting in previous years
Fig 1 Location of Oumlland
8
Capture and Handling
A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars
(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group
SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were
fixed to return GPS locations approximately every 30 minutes
Data Screening
The sample contained both males and females (six males 19 females x female age = 95 years range 4-17
years) An initial inspection revealed that one female individual only returned fixed locations for a period of
eight months Locations ceased during the hunting period so the individual was presumed shot and was
removed from the data along with the males
The exact time between each location varied and sometimes no fix could be made The adehabitatLT package
(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA
was used to place NAs where relocations were missing The function sett0 was used to round the timing of
collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis
consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the
north ten individuals from the centre and six individuals from the south
To address the question and to investigate the influence of climate on the space use patterns of moose the
analysis was performed at two scales The first included all annual movements of moose and the second at a
seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)
and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the
period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing
with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and
end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian
Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is
defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-
Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)
Home rangeUtilization distribution
Variation in ungulate home range size is known to be caused by changes in energy requirements and variation
in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts
in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)
Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al
1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)
The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal
activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to
9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be
described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space
and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are
viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos
movements and space use within their home range (Kranstauber et al 2012) (see appendix A)
Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)
kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is
considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The
BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB
does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos
movement is purely random it moves from a starting point and ends up at the end location randomly By
adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a
certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)
A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and
prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m
scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the
resolution of the data remains consistent between individuals The diffusion coefficient determines the variance
in the location of the kernels between two locations This was calculated from each individualrsquos dataset using
the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB
advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax
and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were
removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from
the UD using the kernelarea function
Habitat
The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape
(second order selection) was studied by comparing the UD95 with available habitats in each of the three study
areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by
comparing the UD50 with the UD95 (UD50UD95)
12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal
coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas
urban areas and younger forests The proportion of area covered by each of these habitat classes was
determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska
Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25
m
Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with
the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not
10
all home ranges contained them This combined approach allowed identification of habitats that are used
disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of
which habitats are important for an individual
119863 = ( 119903minus119901
119903+119901minus2119903119901 ) (eqn1)
r = Proportion of habitat type used
p = Total proportion of habitat available
D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating
the habitat is used in proportion to its availability
Activity
Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals
in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately
only two cows were collared in the north and were therefore left out of this analysis Moose were identified as
migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were
initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed
during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis
One individual was also removed due it its collar not returning relocations during the entirety of the WS
Diet analysis
The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were
shot in the centre and south of the island during the WS of 2013
Survival analysis
The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf
was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving
season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter
Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve
shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick
et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival
function The S(t) of this study is the probability of an individual surviving from birth to after the hunt
(Method summary see appendix B)
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
6
(158 billion Euro) (Boman et al 2011) Each year in Sweden 90000-100000 individuals are harvested
providing approximately 85 million kilograms of moose meat (Kindberg et al 2009) A common method of
selecting which individuals are to be harvested is to assess the reproductive value of an individual and remove
the lownon-reproductive individuals such as calves bulls and cows without calves (Ball et al 1999 Ericsson
et al 2001) Hunting is biased towards bulls with large trophy antlers often resulting in a skewed sex ratio
(Laurian et al 2000 Harris et al 2002 Milner et al 2007)
Moose are known to have a generally high calf survival noted through studies from predator free areas in both
North America and Europe (Linnell et al 1995 Crecircte and Courtois 1997 Swenson et al 2007) A number of
other factors are nevertheless known to affect the survival during their first summer such as climatic variation
malnutrition abandonment disease and poor maternal investment (Verme and Ullrey 1984 Gaillard et al
2000b Lomas and Bender 2007 Ericsson et al 2002 Herfindal et al 2006 Lenarz et al 2010) Low survival
in single odd years has been attributed to weather and low food quality
During recent years moose populations appear to be under environmental stress across their southern range
ascertained by studies reporting low calf survival from both North America and Sweden (Monteith et al in
press Ericsson et al submitted) A similar situation has been reported recently on the island of Oumlland in
southern Sweden where the harvesting of moose was postponed from 2001 to 2005 by mutual agreement
between hunters This was due to a fear of population collapse due to poor management strategies in previous
years that lead to a suspected unsustainable harvest The four-year harvesting break resulted in a balanced sex
ratio and age distribution (Jonsson 2007) In 2006 however it was brought to the attention of the department
of Pathology and Wildlife Diseases at the Swedish National Veterinary Institute in Uppsala (SVA) that there
was an unusually low number of calves observed on the island Malmsten (2014a) conducted a follow up study
during 2012 and 2013 and found that summer calf survival of individuals from Oumlland was only 318 and
158 respectively When compared to calf survival from two other sites in southern Sweden (Kronoberg and
Soumldermanland) with rates all above 73 for both years this figure was regarded as very worrying and
prompted a need for an in-depth exanimation of the factors determining such low calf survival With this above
rationale in mind this study investigates the habitat performance relationships of female moose on the island
of Oumlland This study also provides a model for examining the factors affecting population dynamics on an
island
7 Materials and Methods
Study area
Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest
island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There
are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest
portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are
dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus
aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed
throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is
made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather
(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated
from each other by agricultural areas which are distributed throughout the island particularly along the coastal
regions and the island centre The most southerly patch of forest was protected from becoming agricultural
due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius
personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like
alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow
nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)
Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-
shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which
were banned from hunting in previous years
Fig 1 Location of Oumlland
8
Capture and Handling
A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars
(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group
SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were
fixed to return GPS locations approximately every 30 minutes
Data Screening
The sample contained both males and females (six males 19 females x female age = 95 years range 4-17
years) An initial inspection revealed that one female individual only returned fixed locations for a period of
eight months Locations ceased during the hunting period so the individual was presumed shot and was
removed from the data along with the males
The exact time between each location varied and sometimes no fix could be made The adehabitatLT package
(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA
was used to place NAs where relocations were missing The function sett0 was used to round the timing of
collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis
consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the
north ten individuals from the centre and six individuals from the south
To address the question and to investigate the influence of climate on the space use patterns of moose the
analysis was performed at two scales The first included all annual movements of moose and the second at a
seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)
and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the
period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing
with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and
end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian
Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is
defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-
Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)
Home rangeUtilization distribution
Variation in ungulate home range size is known to be caused by changes in energy requirements and variation
in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts
in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)
Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al
1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)
The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal
activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to
9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be
described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space
and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are
viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos
movements and space use within their home range (Kranstauber et al 2012) (see appendix A)
Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)
kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is
considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The
BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB
does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos
movement is purely random it moves from a starting point and ends up at the end location randomly By
adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a
certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)
A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and
prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m
scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the
resolution of the data remains consistent between individuals The diffusion coefficient determines the variance
in the location of the kernels between two locations This was calculated from each individualrsquos dataset using
the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB
advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax
and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were
removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from
the UD using the kernelarea function
Habitat
The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape
(second order selection) was studied by comparing the UD95 with available habitats in each of the three study
areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by
comparing the UD50 with the UD95 (UD50UD95)
12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal
coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas
urban areas and younger forests The proportion of area covered by each of these habitat classes was
determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska
Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25
m
Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with
the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not
10
all home ranges contained them This combined approach allowed identification of habitats that are used
disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of
which habitats are important for an individual
119863 = ( 119903minus119901
119903+119901minus2119903119901 ) (eqn1)
r = Proportion of habitat type used
p = Total proportion of habitat available
D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating
the habitat is used in proportion to its availability
Activity
Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals
in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately
only two cows were collared in the north and were therefore left out of this analysis Moose were identified as
migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were
initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed
during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis
One individual was also removed due it its collar not returning relocations during the entirety of the WS
Diet analysis
The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were
shot in the centre and south of the island during the WS of 2013
Survival analysis
The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf
was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving
season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter
Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve
shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick
et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival
function The S(t) of this study is the probability of an individual surviving from birth to after the hunt
(Method summary see appendix B)
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
7 Materials and Methods
Study area
Ӧland (567333deg N 166667deg E) a Baltic island located in Kalmar county (Fig 1) is Swedenrsquos second largest
island (~140km in length) It can be split broadly into three areas the north (N) centre (C) and south (S) There
are three typical habitats found on the island boreal forests Stora Alvaret and agricultural land The largest
portions of boreal forests are found in the far north the centre and a patch in the far south Forest stands are
dominated by birch (Betula pubescens B pendula) and Scots pine (Pinus sylvestris) with rowan (Sorbus
aucuparia) aspen (Populus tremula) grey alder (Alnus incana) and yew (Taxus baccata) interspersed
throughout with willow sp (Salix spp) in areas near water sources (Sӕther and Heim 1993) The field layer is
made up of primarily bilberry (Vaccinium myrtillus) lowbush cranberry (Vaccinium vitis-idӕa) and heather
(Calluna vulgaris) (Cederlund 1989) The patches of boreal forest in the north centre and south are isolated
from each other by agricultural areas which are distributed throughout the island particularly along the coastal
regions and the island centre The most southerly patch of forest was protected from becoming agricultural
due to its status as a royal hunting ground and an important stopover for migratory birds (Lars Edenius
personal communication April 09 2014) The southern part of Oumlland has the largest expanse of steppe-like
alvar grassland (Stora Alvaret) found in the world (~25500 ha) (Roseacuten 2006) which is found over dry shallow
nutrient-poor grazed soil (Bakker et al 1996) on top of superficial Ordovician limestone (Dengler et al 2006)
Conditions on Oumlland are milder than those found in other areas of Sweden as it is positioned in the ldquorain-
shadowrdquo of mainland Sweden (Prentice 2007) The only predators of moose found on Oumlland are hunters which
were banned from hunting in previous years
Fig 1 Location of Oumlland
8
Capture and Handling
A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars
(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group
SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were
fixed to return GPS locations approximately every 30 minutes
Data Screening
The sample contained both males and females (six males 19 females x female age = 95 years range 4-17
years) An initial inspection revealed that one female individual only returned fixed locations for a period of
eight months Locations ceased during the hunting period so the individual was presumed shot and was
removed from the data along with the males
The exact time between each location varied and sometimes no fix could be made The adehabitatLT package
(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA
was used to place NAs where relocations were missing The function sett0 was used to round the timing of
collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis
consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the
north ten individuals from the centre and six individuals from the south
To address the question and to investigate the influence of climate on the space use patterns of moose the
analysis was performed at two scales The first included all annual movements of moose and the second at a
seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)
and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the
period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing
with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and
end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian
Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is
defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-
Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)
Home rangeUtilization distribution
Variation in ungulate home range size is known to be caused by changes in energy requirements and variation
in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts
in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)
Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al
1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)
The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal
activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to
9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be
described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space
and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are
viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos
movements and space use within their home range (Kranstauber et al 2012) (see appendix A)
Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)
kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is
considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The
BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB
does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos
movement is purely random it moves from a starting point and ends up at the end location randomly By
adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a
certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)
A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and
prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m
scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the
resolution of the data remains consistent between individuals The diffusion coefficient determines the variance
in the location of the kernels between two locations This was calculated from each individualrsquos dataset using
the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB
advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax
and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were
removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from
the UD using the kernelarea function
Habitat
The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape
(second order selection) was studied by comparing the UD95 with available habitats in each of the three study
areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by
comparing the UD50 with the UD95 (UD50UD95)
12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal
coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas
urban areas and younger forests The proportion of area covered by each of these habitat classes was
determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska
Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25
m
Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with
the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not
10
all home ranges contained them This combined approach allowed identification of habitats that are used
disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of
which habitats are important for an individual
119863 = ( 119903minus119901
119903+119901minus2119903119901 ) (eqn1)
r = Proportion of habitat type used
p = Total proportion of habitat available
D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating
the habitat is used in proportion to its availability
Activity
Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals
in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately
only two cows were collared in the north and were therefore left out of this analysis Moose were identified as
migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were
initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed
during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis
One individual was also removed due it its collar not returning relocations during the entirety of the WS
Diet analysis
The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were
shot in the centre and south of the island during the WS of 2013
Survival analysis
The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf
was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving
season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter
Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve
shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick
et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival
function The S(t) of this study is the probability of an individual surviving from birth to after the hunt
(Method summary see appendix B)
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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28
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29
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
8
Capture and Handling
A random sample of adult moose (n = 25) were darted sedated and equipped with GPSGSM neck collars
(Vectronic Aerospace GmbH Berlin Germany) during the winter of 2012 by the Moose Research Group
SLU Movement data were collected from GPS collars dating from 22022012 ndash 24042014 Collars were
fixed to return GPS locations approximately every 30 minutes
Data Screening
The sample contained both males and females (six males 19 females x female age = 95 years range 4-17
years) An initial inspection revealed that one female individual only returned fixed locations for a period of
eight months Locations ceased during the hunting period so the individual was presumed shot and was
removed from the data along with the males
The exact time between each location varied and sometimes no fix could be made The adehabitatLT package
(Calenge 2006) was used to standardise the data and overcome the location fixing errors The function setNA
was used to place NAs where relocations were missing The function sett0 was used to round the timing of
collection obtaining a regular trajectory with 30 minute intervals The final dataset used in the analysis
consisted of 302710 regular GPS data points from a sample size of n=18 individuals two individuals from the
north ten individuals from the centre and six individuals from the south
To address the question and to investigate the influence of climate on the space use patterns of moose the
analysis was performed at two scales The first included all annual movements of moose and the second at a
seasonal scale ie summer and winter The seasonal scales were defined according to the growing season (GS)
and winter season (WS) In Scandinavia the current method used to define the start of season (SOS) is the
period when the daily mean air temperature is above 5degC (GS) Methods of calculating SOS are advancing
with the use of the Normalized Difference vegetation Index (NDVI) becoming more popular The start and
end of the GS and WS were derived using the mean start and end dates for Oumlland suggested by the Norwegian
Meteorological Institute (DNMI) Nordic climate map report (Tveito et al 2001) The GS of this study is
defined as the period between 23-April-2012 to 07-Nov-2012 and the WS is defined as the period between 08-
Nov-2012 to 22-April-2013 (based on the current standard normal period 1961-90)
Home rangeUtilization distribution
Variation in ungulate home range size is known to be caused by changes in energy requirements and variation
in food availability (Tufto et al 1996 Kie et al 2010 Moreller et al 2013) With shifting climate causes shifts
in plant phenology and therefore the spatial and temporal distribution of ungulate food (Maringrell et al 2006)
Individuals alter their home ranges to meet their energy requirements to maintain their fitness (Albon et al
1987 White 1997 Festa-Bianchet et al 1998 Forchhammer et al 2001)
The most commonly cited definition of a home range is ldquothat area traversed by the animal during its normal
activities of food gathering mating and caring for youngrdquo (Burt 1943) This has now been expanded to
9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be
described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space
and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are
viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos
movements and space use within their home range (Kranstauber et al 2012) (see appendix A)
Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)
kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is
considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The
BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB
does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos
movement is purely random it moves from a starting point and ends up at the end location randomly By
adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a
certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)
A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and
prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m
scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the
resolution of the data remains consistent between individuals The diffusion coefficient determines the variance
in the location of the kernels between two locations This was calculated from each individualrsquos dataset using
the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB
advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax
and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were
removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from
the UD using the kernelarea function
Habitat
The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape
(second order selection) was studied by comparing the UD95 with available habitats in each of the three study
areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by
comparing the UD50 with the UD95 (UD50UD95)
12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal
coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas
urban areas and younger forests The proportion of area covered by each of these habitat classes was
determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska
Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25
m
Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with
the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not
10
all home ranges contained them This combined approach allowed identification of habitats that are used
disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of
which habitats are important for an individual
119863 = ( 119903minus119901
119903+119901minus2119903119901 ) (eqn1)
r = Proportion of habitat type used
p = Total proportion of habitat available
D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating
the habitat is used in proportion to its availability
Activity
Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals
in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately
only two cows were collared in the north and were therefore left out of this analysis Moose were identified as
migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were
initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed
during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis
One individual was also removed due it its collar not returning relocations during the entirety of the WS
Diet analysis
The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were
shot in the centre and south of the island during the WS of 2013
Survival analysis
The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf
was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving
season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter
Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve
shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick
et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival
function The S(t) of this study is the probability of an individual surviving from birth to after the hunt
(Method summary see appendix B)
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness
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Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation
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Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and
functional responses in red deer habitat selection Ecology 90699ndash710
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Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for
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Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges
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with Rickettsia Helvetica Parasites and Vectors 7128
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Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos
Electivity Index Oecologia 14(4)413-417
Jenkins KJ Manly FJ (2008) A double-observer method for reducing bias in faecal pellet surveys of forest
ungulates Journal of Applied Ecology 451339-1348
Johnson DH (1980) The comparison of usage and availability measurements for evaluating resource
preference Ecology 6165-71
Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental
Studies SLU Examensarbete I aumlmnet biologi vol 20072
Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American
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Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)
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27
Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S
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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive
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28
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29
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
9 incorporate measures of space use using the utilization distribution (UD van Winkle 1975) which can be
described as the ldquorelative frequency distribution of an animalrsquos occurrence in all four dimensions of space
and timerdquo (Keating and Cherry 2009) Home range is viewed as a constant 2D polygon whereas UDs are
viewed as multiple 3D polygons that take into account the distribution as well as the intensity of animalrsquos
movements and space use within their home range (Kranstauber et al 2012) (see appendix A)
Estimations of each individualrsquos annual and seasonal UDs were found using the Biased Random Bridge (BRB)
kernel approach (Benhamou 2011) from the adehabitatHR package (Calenge 2006) in R It was chosen as it is
considered an improvement on the previously preferred Brownian bridge (BB) method (Horne et al 2007) The
BB is purely a diffusive movement process whereas the BRB is an advective-diffusive movement process BB
does not take into account changes in advection direction (drift) or strength BB assumes an animalrsquos
movement is purely random it moves from a starting point and ends up at the end location randomly By
adding the advection component the BRB takes into account that the animalrsquos movement is biased towards a
certain direction This allows for a more biologically relevant analysis (Benhamou and Corneacutelis 2010)
A grid was created using the minmax XY coordinates of all individuals (plusmn 10 km to increase the extent and
prevent the grid directly touching the XY locations) The resolution of the grid was fixed at a 25 m x 25 m
scale to match the resolution of the relevant habitat maps (Hagner et al 2005) By specifying these criteria the
resolution of the data remains consistent between individuals The diffusion coefficient determines the variance
in the location of the kernels between two locations This was calculated from each individualrsquos dataset using
the BRBD function and added to the BRB model (see Benhamou 2011) The strength and direction of BRB
advection can change between bridges whilst having to remaining constant To remain constant an upper Tmax
and lower Lmin time thresholds were set Successive relocations that exceeded Tmax or under Lmin were
removed from the UD calculations The 50 (UD50) and 95 (UD95) isopleths were then calculated from
the UD using the kernelarea function
Habitat
The scale of analysis was further divided following Johnson (1980) Habitat selection within the landscape
(second order selection) was studied by comparing the UD95 with available habitats in each of the three study
areas of Oumlland (UD95Area) Habitat selection within the home range (third order selection) was studied by
comparing the UD50 with the UD95 (UD50UD95)
12 habitat classes were used in the analysis agricultural land broad leaved forests clear felled areas coastal
coniferous forests freshwater areas moorsgrassland miresmarshes mixed forest sparsely vegetated areas
urban areas and younger forests The proportion of area covered by each of these habitat classes was
determined in the UD50 and UD95 Habitat data was obtained from satellite imagery generated by Svenska
Marktaumlckedata (Hagner et al 2005) The habitat maps were last updated in 2002 and have a resolution of 25
m
Compositional analysis ( habitat used habitat available) (Aebischer 1993) was used in conjunction with
the Jacobrsquos index (D) (eqn1) to quantify habitat selection (Jacobs 1974) Coastal areas were removed as not
10
all home ranges contained them This combined approach allowed identification of habitats that are used
disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of
which habitats are important for an individual
119863 = ( 119903minus119901
119903+119901minus2119903119901 ) (eqn1)
r = Proportion of habitat type used
p = Total proportion of habitat available
D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating
the habitat is used in proportion to its availability
Activity
Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals
in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately
only two cows were collared in the north and were therefore left out of this analysis Moose were identified as
migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were
initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed
during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis
One individual was also removed due it its collar not returning relocations during the entirety of the WS
Diet analysis
The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were
shot in the centre and south of the island during the WS of 2013
Survival analysis
The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf
was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving
season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter
Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve
shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick
et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival
function The S(t) of this study is the probability of an individual surviving from birth to after the hunt
(Method summary see appendix B)
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-
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25 Festa-Bianchet M Gaillard JM Jorgenson JT (1998) Mass and density-dependent reproductive success and
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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness
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Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female
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Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-
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Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation
in ovulation patterns of a seasonal breeder the Norwegian moose (Alces alces) The American
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Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia
47278-285
Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and
functional responses in red deer habitat selection Ecology 90699ndash710
Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet
economic conservation and environmental objectives Journal of Applied Ecology 411021-
1031
Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for
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Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology
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Harris RB Wall WA Allendorf FW (2002) Genetic consequences of hunting what do we know and what
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Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict
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Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges
Ecological Society of America Ecology 882354-2363
Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R
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26
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Studies SLU Examensarbete I aumlmnet biologi vol 20072
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The home range concept are traditional estimators still relevant with modern telemetry
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Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement
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27
Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S
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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive
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28
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29
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conservation of large mammals in a fragmented environment Alces 4965-81
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success in muskoxen Journal of Zoology 24313-20
30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
10
all home ranges contained them This combined approach allowed identification of habitats that are used
disproportionally to their availability ie in a non-random manner (Beyer et al 2010) This is an indication of
which habitats are important for an individual
119863 = ( 119903minus119901
119903+119901minus2119903119901 ) (eqn1)
r = Proportion of habitat type used
p = Total proportion of habitat available
D = Jacobs index varies from -1 (strong avoidance) to +1 (strong preference) with values close to 0 indicating
the habitat is used in proportion to its availability
Activity
Activity level is measured as the mean daily movement (MDM) by the individual to investigate if individuals
in an areaseason moved more and hence were more active than those in other areasseasons Unfortunately
only two cows were collared in the north and were therefore left out of this analysis Moose were identified as
migratory using a modelling approach (see Bunnefeld et al 2011 for methods) Migratory individuals were
initially removed from the activity analysis (n=4)The reason is that both migratory journeys were completed
during the winter season thus increasing the mean daily distance travelled and potentially biasing the analysis
One individual was also removed due it its collar not returning relocations during the entirety of the WS
Diet analysis
The Ӧland project team conducted histology diet analysis on the rumen content of five individuals that were
shot in the centre and south of the island during the WS of 2013
Survival analysis
The Ӧland project team measured calf survival using the mark-resight method The presenceabsence of a calf
was recorded by tracking the cows at six occasions throughout the year These were at the start of the calving
season (mid-May to early June) twice through the summer before the hunt after the hunt and after winter
Survival trend was estimated using a Kaplan-Meier curve (Kaplan and Meier 1958) The Kaplan-Meier curve
shows the survival function (S (t)) ie the probability of an individual surviving until at least time t (Bewick
et al 2004) The probability of surviving from one period to the next is multiplied together to give the survival
function The S(t) of this study is the probability of an individual surviving from birth to after the hunt
(Method summary see appendix B)
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a
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Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-
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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of
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Gaillard JM Festa-Bianchet M Yoccoz NG (1998) Population dynamics of large herbivores variable
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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness
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Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female
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Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-
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Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation
in ovulation patterns of a seasonal breeder the Norwegian moose (Alces alces) The American
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Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia
47278-285
Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and
functional responses in red deer habitat selection Ecology 90699ndash710
Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet
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Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for
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Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology
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Harris RB Wall WA Allendorf FW (2002) Genetic consequences of hunting what do we know and what
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Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict
responses in moose body mass to temporal variation in the environment Journal of Animal
Ecology 75 (5) 1110-1118
Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges
Ecological Society of America Ecology 882354-2363
Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R
(2014) Birds as potential reservoirs of tick-borne pathogens first evidence of bacteraemia
with Rickettsia Helvetica Parasites and Vectors 7128
26
Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos
Electivity Index Oecologia 14(4)413-417
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Studies SLU Examensarbete I aumlmnet biologi vol 20072
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Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)
The home range concept are traditional estimators still relevant with modern telemetry
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Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement
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27
Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S
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28
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29
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
11 Results
Home RangeUtilization Distribution
A total of 51 home ranges were estimated (17 annual 17 within growing season 17 within winter season)
Annual x = 9613 ha GS x = 6345 ha and WS x = 6023 ha (appendix C)
At the UD50 scale the largest annual and seasonal mean home ranges were located in the north Mean annual
and seasonal home ranges in the centre were slightly larger than the south This difference was not significant
(F(113)= 22 p= 87) (ANOVA) There was no significant difference between the seasonal home ranges (x
plusmnSD for GS = 116 plusmn38 for WS = 98 plusmn32 ha) (t(11) = 105 p = 32) or the seasonal home ranges in the centre
(t(8) = 101 p = 34 and the south (t(5) = 87 p = 42) (paired-sample t-test) (Table 1)
At the UD95 scale the largest annual and WS mean home ranges were located in the north The largest GS
mean home ranges were located in the centre Mean annual and seasonal home ranges in the centre were
slightly larger than the south This difference was not significant (F(113) = 59 p = 63) (ANOVA) There
was no significant difference between the seasonal home ranges (x plusmnSD for GS = 635 plusmn225 for WS = 602
plusmn161) (t(11) = 373 p = 71) or the seasonal home ranges in the centre (t(8)= 20 p = 84) or south (t(5) = 34
p = 74) (paired-sample t-test) (Table 1)
Table 1 Seasonal and annual mean UD50 and UD95 BRB kernel area in hectares (1ha = 001km2) for the north centre
and south of Oumlland (smoothing factor (h) =100)
Are
a
Annual UD50 GS UD50 WS UD50
n Mean SD Range n Mean SD Range n Mean SD Range
N 2 209 49 139-279 2 1215 39 67-176 2 1615 106 160-163
C 9 178 56 114-277 9 116 44 48-165 9 943 4 61-173
S 6 160 21 142-177 6 1085 51 65-149 6 933 35 69-125
Annual UD95 GS UD95 WS UD95
N 2 10905 5 1084-1097 2 630 199 349-911 2 809 11 794-824
C 9 997 32 682-1536 9 6531 22 295-945 9 637 17 454-941
S 6 9298 30 605-1088 6 5985 373 442-575 6 5526 20 349-679
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of
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25 Festa-Bianchet M Gaillard JM Jorgenson JT (1998) Mass and density-dependent reproductive success and
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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness
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Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation
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Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and
functional responses in red deer habitat selection Ecology 90699ndash710
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Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for
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Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S
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29
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
12
Activity
MDM rates in the three areas (sedentary individuals) during the GS ranged from 14 ndash31 km day During the
WS ranged they ranged from 11-24 km day (Table 2) Movement rates during the GS were higher than the
WS (x plusmnSD for GS = 202 plusmn043 for WS = 161 plusmn043) but it was not statistically significant (t(11) = 200 p=
07) (paired sample t-test)
Table 2 Seasonal mean daily movement rates (km day) for each area and for both areas (total)
Are
a
GS WS
n Mean SE Range n Mean SE Range
C 8 20 003 14-18 8 20 004 12-24
S 4 22 016 17-31 4 12 02 11-13
Total 12 202 003 14-31 12 16 003 11-24
The seasonal MDM rates of all individuals (migratory and sedentary) were not significantly different (x plusmnSD
for GS = 20 plusmn04 for WS = 18 plusmn061) (t(14) = 139 p= 19) (paired sample t-test)
The WS home range size affects the WS MDM (F(110) = 927 p = 01) (ANOVA) The GS home range size
does not affect the GS MDM (F(110) = 36 p = 56) (ANOVA) When the WS home range outlier was
removed the home range size did not affect the WS MDM (F(111) = 186 p= 19) (ANOVA) The MDM was
lowest in February and highest in April (Table 3) there appeared to be no significant pattern in MDM between
the months (appendix D)
Table 3 Mean daily distance moved (km day) for sedentary individuals
Month Season Distance
April GS 0051
May GS 0044
June GS 0039
July GS 0041
August GS 0042
September GS 0044
October GS 0043
November WS 0043
December WS 0038
January WS 0035
February WS 0028
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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29
Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
13 Habitat ndash Proportions
The largest proportion of habitat on the island is agriculture the lowest proportion of habitat (excluding coastal
and freshwater) is urban areas (Fig 2) The largest proportion of habitat in the north was coniferous forests
whilst agricultural areas were the dominant habitat types in the centre and south (Fig 3) The lowest proportion
(excluding coastal and freshwater areas) was urban
Fig 2 Proportion of different types of habitats found on Ӧland
Fig 3 Mean proportion of habitats contained within UD95 in the three areas of Oumlland C = Centre N = North S =
South
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
14
Habitat - Selection
Generally forest habitat types are the highest ranked whilst sparsely vegetated and urban areas are the lowest
ranked Both the second and third order habitat selection analyses gave significant results in the compositional
analysis (Table 4) In the third order analysis (UD50UD95) the centre displayed significant differences
between habitat types The coniferous forests are significantly preferred to sparsely vegetated areas and the
sparsely vegetated areas are significantly preferred to urban areas In the second order analysis (UD95Area)
significance was observed in the north and centre In the north younger forests are significantly preferred to
miresmarshes clear felled areas are significantly preferred to agriculture and freshwater areas are significantly
preferred to sparsely vegetated areas In the centre clear felled areas are significantly preferred to agricultural
land freshwater areas are significantly preferred to urban areas and grasslandmoors are significantly preferred
to sparsely vegetated areas
Table 4 Summary of second (UD95Area bottom) and third order (UD50UD95 top) ranked habitat preferences between
the three areas according to the compositional analysis (see appendix B)
Rank North Centre South
1 Broad Leaf Younger Coniferous
2 Mixed Broad Leaf Younger
3 MiresMarshes Clear Fell GrasslandMoors
4 Younger Mixed Clear Fell
5 Clear Fell GrasslandMoors Mixed
6 Coniferous MiresMarshes Broad Leaf
7 Freshwater Agriculture Freshwater
8 Agriculture Coniferous Agriculture
9 Sparse Veg Sparse Veg MiresMarshes
10 GrasslandMoors Urban Sparse Veg
11 Urban Freshwater Urban
Rank North Centre South
1 Broad Leaf Mixed Coniferous
2 Mixed Younger Clear Fell
3 GrasslandMoors Broad Leaf Younger
4 Younger Coniferous GrasslandMoors
5 MiresMarshes Clear Fell Agriculture
6 Coniferous Agriculture MiresMarshes
7 Clear Fell MiresMarshes Broad Leaf
8 Agriculture Freshwater Freshwater
9 Urban Urban Sparse Veg
10 Freshwater GrasslandMoors Mixed
11 Sparse Veg Sparse Veg Urban
Indicates significantly preferred to the habitat below (significant deviation from random at P lt05)
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
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Calenge C (2006) The package adehabitat for the R software a tool for the analysis of space and habitat use
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Calenge C (2011) Home Range Estimation in R the adehabitatHR package Office national de la classe et de
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Cederlund GN Nystroumlm A (1981) Seasonal differences between moose and roe deer in ability to digest
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Cederlund GN Okarma H (1988) Home range and habitat use of adult female moose Journal of Wildlife
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Cederlund GN Sand H (1994) Home-range size in relation to age and sex in moose American Society of
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Clutton-Brock T Sheldon BC (2010) Individuals and populations the role of long-term individual based
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25(10)562-573
Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
15 The Jacobs index revealed that generally the habitats preferred during the GS within the home range (third
order) are younger (0187) and broad leaf forests (0154) The strongest avoidance was for urban areas (-0627)
During the WS only agricultural areas are preferred (0129) and the strongest avoidance was for urban areas (-
0393) (Fig 4)
Fig 4 Third order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Third order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0218) and mixed forests (0161) The
strongest avoidance was for urban (-1) and sparsely vegetated areas (-05) During the WS the strongest
preference was for miresmarshes (0228) The strongest avoidance was for grasslandmoors (-05)
Centre During the GS the strongest preference was for broad leaf (0233) and younger forests (0223) The
strongest avoidance was for urban (-0527) and agricultural land (-0362) During the WS preference was only
shown for agricultural land (0327) The strongest avoidance was for urban areas (-0679) and miresmarshes
(-0638)
South During the GS the strongest preference was for coniferous (0312) and younger forests (0242) The
strongest avoidance was for urban (-0353) and sparsely vegetated areas (-0330) During the WS
grasslandmoors (0106) were the strongest preference The strongest avoidance was for urban (-0666) and
sparsely vegetated areas (-0351)
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
16
The Jacobs indices revealed that generally the habitats preferred during the GS within the landscape
(UD95Area) are broad leaf (0216) and younger forests (0201) The strongest avoidance was for urban (-
0717) and freshwater areas (-0694) The strongest preference during the WS are coniferous forests (0242)
and the strongest avoidance was for freshwater (-0674) and urban areas (-0648) (Fig 5)
Fig 5 Second order seasonal habitat preference (UD50UD95) all individuals The index ranges from -1 (total avoidance)
to 1 (strongest preference) Close to 0 indicates used in proportion to its availability
Second order habitat preferencesavoidances by area
North During the GS the strongest preference was for broad leaf (0363) and mixed forests (00291) The
strongest avoidance was for sparsely vegetated (-0909) and freshwater areas (-0780) During the WS mixed
(0335) and coniferous forests (0316) were the strongest preference The strongest avoidance was for
freshwater (-0731) and urban areas (-05333)
Centre During the GS the strongest preference for mixed (0394) and younger forests (0286) The strongest
avoidance was for urban (-0733) and sparsely vegetated (-0708) areas During the WS mixed (0404) and
coniferous forests (0255) were the strongest preference The strongest avoidance was for freshwater (-0704)
and sparsely vegetated areas (-0655)
South During the GS the strongest preference for grasslandmoors (0287) and clear fells (0165) The
strongest avoidance was for urban areas (-0678) and mixed forests (-0491) During the WS grasslandmoors
(0425) and coniferous forests (0154) were the strongest preference The strongest avoidance was for urban (-
0876) and freshwater areas (-0587) (appendix E)
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
17 Diet
Diet analysis of the rumen content sampled from five individuals (C=2 S=3) revealed that almost two thirds
(69) of the diet is comprised of agricultural produce (apple winter rape and sugar beet) (Fig 6)
Fig 6 Diet analysis from the rumen samples of five moose individuals that were culled in 2013
31
2117
9
8
5
22
1 1
1
1
1 00 0
0
0Diet (2610-911 2013 5 individuals)
AppleWinter RapeSugar BeetUndefined WoodSallowBroad-leaf GrassPineAshOakCloverCurrantsUndefined plantElderberryJuniperRaspberry
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
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Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation
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Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia
47278-285
Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and
functional responses in red deer habitat selection Ecology 90699ndash710
Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet
economic conservation and environmental objectives Journal of Applied Ecology 411021-
1031
Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for
CORINE land cover in Sweden In Oluić M (ed) New strategies for European remote sensing
Millpress Rotterdam pp 523ndash530
Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology
Wildlife Society Bulletin 25173-182
Harris RB Wall WA Allendorf FW (2002) Genetic consequences of hunting what do we know and what
should we do Wildlife Society Bulletin 30634-643
Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict
responses in moose body mass to temporal variation in the environment Journal of Animal
Ecology 75 (5) 1110-1118
Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges
Ecological Society of America Ecology 882354-2363
Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R
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Studies SLU Examensarbete I aumlmnet biologi vol 20072
Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American
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Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)
The home range concept are traditional estimators still relevant with modern telemetry
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Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement
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Animal Ecology 81738-746
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27
Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S
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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive
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28
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29
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Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for
conservation of large mammals in a fragmented environment Alces 4965-81
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success in muskoxen Journal of Zoology 24313-20
30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
18
Calf Survival
Of the 18 individuals 13 produced calves in which 7 produced twins giving a total of 20 calves A Kaplan-
Meier estimate was conducted to measure the fraction of calves living up to each period of the study (Fig 7)
The mean survival time is until period 235 (midend of summer) At the start of summer 85 of calves
remained (3 still born) The period between summer and before the hunt survival drops to 30 The survival
at the end of the study (after hunt) drops further to 20 leaving 4 calves surviving (see appendix B)
Fig 7 Kaplan-Meier estimate of moose calf survival during the study period Period 0 (Start of summer) period 1
(midend of summer) period 2 (before hunt) period 3 (after hunt) period 4 (after winter)
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
19 Discussion
The results of this study emphasised how strikingly different the habitat composition is along the latitudinal
gradient of Oumlland The three areas show contrasting proportions of the key habitat types The starkest
difference is the high proportion of coniferous forests and lack of agriculture in the north compared to the
centre and south The proportion of coniferous forest in the north is almost 5 times greater than in the centre
and south whereas the proportion of agriculture in the centre and south is more than double that in the north
The north is perceived to be composed of the most suitable habitat for moose (Dussault et al 2006) It has the
largest proportions of each forest type and a low proportion of agricultural land This provides suitable forage
and shelter throughout the year The south has a contrasting habitat composition to the north The proportions
of agricultural and sparsely vegetated areas are the highest between the three areas and the proportions of forest
habitats are the lowest The large proportion of sparsely vegetated areas and low proportions of forest habitat
corresponds to the large area of Stora Alvaret This is perceived to be the least suitable area due to a lack of
shelter (coniferous forest) and suitable forage The strong preference for coniferous and younger forest habitats
in the south would suggest that moose exhibit a functional response in habitat selection (Godvik et al 2009)
ie as the proportion of a particular habitat decreases the selection for that habitat increases in this case
coniferous forests which provide shelter and younger forest which provide good forage Similarly in the centre
moose show strong preference for mixed forests a habitat that is of low proportion
In view of the large variation in habitat proportions between the areas it is surprising that there is not a large
variation in the home range sizes or the activity levels annually or seasonally Home ranges are ultimately
chosen to maximise fitness and meet energy requirements by utilizing the available forage Seasonal conditions
change the availability and necessity of resources (food quality shelter) Unlike the GS during the WS
deciduous trees and shrubs are leafless and low-lying shrubs are under snow cover (Dussault et al 2005)
These changes are well known to cause populations to alter their activity and home ranges to meet energy
requirements (Mysterud et al 2001) Populations have been shown to increase or decrease their home ranges
during the two seasons The GS home ranges are often larger than the WS home ranges (Philips et al 1973
Mysterud et al 2001) In some cases they can be found to be almost double the size of the WS home ranges
(Cederlund and Okarma 1988) In other populations the WS home ranges are double the size of the GS home
ranges (Lynch and Morgantini 1984) or sizes do not significantly differ (Cederlund and Sand 1994)
Previous studies on moose find females generally show increased activity from the start on the GS due to
various factors eg reduced ruminating times increased metabolic needs and increased foraging bursts
(Wattles and DeStefano 2013) Increased metabolic needs during this time are a results of pregnancy and
lactation (Georgii 1980) During the height of the GS they usually show reduced activity levels through times
of increased thermal stress (Renecker and Hudson 1989 van Beest et al 2012) During the WS the depth and
the duration of snow cover are well known to affect the activity level (Telfer 1970 Mysterud and Oslashstbye 1999
Bjoslashrneraas et al 2011) During the WS generally home ranges are smaller and activity less due to lower
metabolic needs Moose activity is constrained by rumination during the WS this period is known to be longer
due to the change in diet (Cederlund 1989 Renecker Hudson 1989) This was not the case on Ӧland activity
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
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Sedetalia) on the island of Ӧland (Sweden) in the context of north and central Europe
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
20
was lowest in February which is a similar result to Cederlundrsquos (1989) paper However Ӧland moose did not
significantly alter their seasonal activity levels The fact that the annual and seasonal activity levels and home
ranges were similar could be a result of the mild winters on Oumlland during the study period (Smhise 2014)
During the study period the average number of snow days was 80 and the mean snow depth was 10cm
(appendix F) (Swedish Meterological and Hydrological Institute- SMHI) These mild conditions do not restrict
the movement of moose or obscure forage Moose are well adapted for movement in deep snow depths of 60-
86cm (Prescott 1968) are needed to truly restrict movement This finding was similar to the Sweanor and
Sandegren (1989) and Cederlund and Sand (1994) where the snow depth at their sites did not reach movement
restricting depths
The survival curve illustrates just how bad the calf survival is on Ӧland Survival falls from 85 at the start to
20 Out of 20 calves only four were alive at the end of the study The sharpest fall in survival was the period
between end of summer and before the hunt so the deaths were not due to hunting Previous calf autopsies
(Malmsten 2014a) have shown that cause of death was starvation mothers possibly either did not have milk
the calf was unable to feed or the mother abandoned the calf Closer field based observations are needed to
attain this knowledge Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus
during late September early October (Garel et al 2009) (appendix F) The diet of the mother influences the
health of the calf and this period is when sodium is hard to find sodium is a key mineral in moose diets for
features such as reproduction (Belovsky and Jordan 1981) Moose gain sodium mainly through aquatic plants
(MacCracken et al 1993) However the compositional analysis shows that freshwater areas are often ranked
as one of the lowest used habitats and coastal areas were removed as the proportion found in the home ranges
was extremely low The Jacobs Index shows that the moose only prefer freshwater areas in the north UD50
during the WS The north individuals again are those that are showing typical moose habitat selection
It is known that habitat selection is hierarchical with habitats that increase fitness selected for and the effects
of limiting factors are reduced (Rettie and Messier 2000) At the UD95 during the GS moose preferred areas
of good forage (forests) and avoided areas of low forage (freshwater and sparsely vegetated areas) and areas
close to humans (urban) This is consistent with other reports (Laurian et al 2008 Torres et al 2011) Within
the UD50 there is a shift in preferences The good forage areas are again preferred during the GS however
during WS the only preferred habitat is often agricultural land During the WS there could be a steady supply
of supplementary feed available hence the high levels of agricultural produce found in the rumen content
samples and the high preference of agricultural areas This diet is unusual for moose previous studies of
Swedish moose diet have found the GS diet was dominated by birch willow and herbaceous plants and the
WS diet dominated by pine and birch (Cederlund and Nystrom 1981) The diet analysis was conducted during
the WS instead of being dominant pine composed just 2 Birch did not appear however unidentified wood
composed only 9 whereas agricultural produce accounted for 69 Supplementary feed may be perceived
by the moose in the centre and south as a vital forage source during the WS In fact in the centre the
agricultural land is the only preferred habitat at the UD50 It is unknown whether there are salt licks provided
in these areas Selection for a critical habitat is often thought to be a fixed factor The Oumlland population from
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
23 References
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Bewick V Cheek L Ball J (2004) Statistics review 12 Survival analysis Critical Care 8(5)389-394
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Bradshaw RHW Hannon GE Lister AM (2003) A long-term perspective on ungulate-vegetation
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Brandin E (2009) Versions of lsquowildrsquo and the importance of fences in Swedish wildlife tourism involving
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Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
21 the three areas are close in proximity however they displayed contrasting preferences This is supported by the
Osko et al (2004) report that found two neighbouring moose populations that had access to the same habitats
displayed contrasting preferences Habitat preferences for populations of the same species are not necessarily
fixed They alter with varying levels of habitat abundance and limiting factors skewing what is preserved to
be critical
The main limitation encountered in this study was with the limited sample There was only data on two
individuals from the north of the island which led it being removed from many of the analysis Similarly due
to a lack of relocations from the collars being turned off at points throughout the year two further individuals
had to be removed from a majority of the analysis This reduced the sample size to 17 or 18 individuals
Similarly only 13 of the individuals from the study produced calves This unfortunately prevented including
survival into models Although the sample size was small it was accurate it was of high resolution over
300000 GPS points In future it would be beneficial to have a more standardised data set An equal sample of
individuals from the three areas would be advised along with ensuring the GPS collars are kept turned on for
the entirety of the growing and winter season to allow comparisons between years It would also be
advantageous to collect coordinates of the feeding sites along with the composition This could then be
compared with high use UD coordinates to look if moose are truly spending a majority of their foraging time
at feeding stations A study on the population densities of moose and the increasing population of roe deer
(Capreolus capreolus) would add the factor of competition into the model
The low calf survival on Ӧland is most likely the result of a combination of factors The lack of suitable habitat
reported in this study in conjunction with Malmstenrsquos (2014a) report on the threat of disease (Anaplasma
phagocytophilum) are probable influences on the calf survival on Ӧland On Ӧland there is an increasing
population of roe deer and large numbers of migratory birds both carriers of ticks and diseases The mild
conditions on Ӧland are advantageous for ticks the carriers of A phagocytophilum Fewer snow days and
shorter periods of snow cover along with dry conditions are favourable for ticks This could probably be one
of the reasons for females to be of lower quality and therefore not being able to ensure calf survival Moose
have to utilise areas where in other populations individuals tend to avoid Finally similar to many studies I
advocate further research using a stronger dataset and longer term monitoring
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
22
Acknowledgements
I am indebted to NJ Singh and A Allen for all their help and guidance through the whole of this study I
thank SLU for the support provided during this study in terms of data finances and facilities Thank you to
everyone at the Department of Wildlife Fish and Environmental Studies for being so friendly and
supportive I would like to thank L Edenius for driving me around the study area and S Michon and H
Khalil for keeping me sane with fika and training
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
24
Bunnefeld N Boumlrger L van Moorter B Rolandsen CM Dettki H Solberg EJ Ericsson G(2011) A model-
driven approach to quantify migration patterns individual regional and yearly differences
Journal of Animal Ecology 80466-476
Brown G (2011) Patterns and causes of demographic variation in a harvested moose population evidence for
the effects of climate and density-dependent drivers Journal of Animal Ecology 80(6)1288-
1298
Calenge C (2006) The package adehabitat for the R software a tool for the analysis of space and habitat use
by animals Ecological Modelling 197 516-519
Calenge C (2011) Home Range Estimation in R the adehabitatHR package Office national de la classe et de
la faune sauvage Saint Benoist ndash 78610 Auffargis ndash France
Cederlund GN Nystroumlm A (1981) Seasonal differences between moose and roe deer in ability to digest
browse Holarctic Ecology 459-65
Cederlund GN Okarma H (1988) Home range and habitat use of adult female moose Journal of Wildlife
Management 52(2)336-343
Cederlund GN (1989) Activity patterns in moose and roe deer in a north boreal forest Holarctic Ecology
1239-45
Cederlund GN Sand H (1994) Home-range size in relation to age and sex in moose American Society of
Mammalogists 75(4)1005-1012
Clutton-Brock T Sheldon BC (2010) Individuals and populations the role of long-term individual based
studies of animals in ecology and evolutionary biology Trends in Ecology and Evolution
25(10)562-573
Cooke SJ Hinch SG Wikelski M Andrews RD Kuchel LJ Wolcott TG Butler PJ (2004) Biotelemerty a
mechanistic approach to ecology Trends in Ecology and Evolution 19334-343
Crecircte M Courtois R (1997) Limiting factors might obscure population regulation of moose (Cervidae Alces
alces) in unproductive boreal forests Journal of Zoology 242(4)765-781
Dengler J Loumlbel L Loumlbel W (2006) The basiphilous dry grasslands of shallow skeletal soils (Alysso-
Sedetalia) on the island of Ӧland (Sweden) in the context of north and central Europe
Phytocoenologia 36343-391
Dussault C Courtois R Ouellet JP Girard I (2005) Space use of moose in relation to food availability
Canadian Journal of Zoology 831431-1437
Dussault C Courtois R Ouellet JP (2006) A habitat suitability index model to assess moose habitat selection
at multiple spatial scales Canadian Journal of Forest Research 361097-1107
Ericsson G Wallin K Ball JP Broberg M (2001) Age-related reproductive effort and senescence in free-
ranging moose Alces alces Ecology 821613-1620
Ericsson G Ball JP Danell K (2002) Moose offspring body mass along an altitudinal gradient Journal of
Wildlife Management 55(1)91-97
Ericsson G Malmsten J Neumann W Singh NJ Dali AM Submitted Summer Calf Survival of
Scandinavian Moose along its Southern Distribution Range
25 Festa-Bianchet M Gaillard JM Jorgenson JT (1998) Mass and density-dependent reproductive success and
reproductive costs in a capital breeder The American Naturalist 152367-379
Forchhammer MC Clutton-Brock TH Lindstroumlm J Albon SD (2001) Climate and population density induce
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Forchhammer MC Post E Stenseth NC Boertmann DM (2002) Long-term responses in arctic ungulate
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Gaillard JM Festa-Bianchet M Yoccoz NG (1998) Population dynamics of large herbivores variable
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Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness
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Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female
ungulate bigger is not always better Proceedings Biological Sciences 267471-477
Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-
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Transactions of the Royal Society B 3652255-2265
Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation
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Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia
47278-285
Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and
functional responses in red deer habitat selection Ecology 90699ndash710
Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet
economic conservation and environmental objectives Journal of Applied Ecology 411021-
1031
Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for
CORINE land cover in Sweden In Oluić M (ed) New strategies for European remote sensing
Millpress Rotterdam pp 523ndash530
Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology
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should we do Wildlife Society Bulletin 30634-643
Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict
responses in moose body mass to temporal variation in the environment Journal of Animal
Ecology 75 (5) 1110-1118
Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges
Ecological Society of America Ecology 882354-2363
Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R
(2014) Birds as potential reservoirs of tick-borne pathogens first evidence of bacteraemia
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26
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Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American
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Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)
The home range concept are traditional estimators still relevant with modern telemetry
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Laurian C Ouellet JP Courtois R Breton L St-Onge S (2000) Effects of intensive harvesting on moose
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Lenarz MS Fieberg J Schrage MW Edwards AJ (2010) Living on the edge viability of moose in
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Linnell JDC Aanes R Andersen R (1995) Who killed Bambi The role of predation in the neonatal
mortality of temperate ungulates Wildlife Biology 1209-223
Lomas LA Bender LC (2007) Survival and cause-specific mortality of neonatal mule deer fawns north-
central New Mexico Journal of Wildlife Management 71884ndash894
Lynch GM Morgantini LE (1984) Sex and age differential in seasonal home range size of moose in
northcentral Alberta 1971-1979 Alces 2061-78
MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or
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27
Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S
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Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive
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Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research
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Maringrell A Hofgaard A Danell K (2006) Nutrient dynamics of reindeer forage species along snowmelt
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McLoughlin PD Vander Wal E Lowe SJ Patterson BR Murray DL (2011) Seasonal shifts in habitat
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12(8) 654-663
Milner JM Nilsen EB and Andreassen HP (2007) Demographic side effects of selective hunting in ungulates
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Monteith KL Klaver R Hersey K Holland A Thomas T Kauffman M In press Effects of climate and
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Morales JM Moorcroft PR Matthiopoulos J Frair JL Kie JG Powell RA Merrill EH Haydon DT (2010)
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Transactions of the Royal Society B 3652289-230
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
25 Festa-Bianchet M Gaillard JM Jorgenson JT (1998) Mass and density-dependent reproductive success and
reproductive costs in a capital breeder The American Naturalist 152367-379
Forchhammer MC Clutton-Brock TH Lindstroumlm J Albon SD (2001) Climate and population density induce
long-term cohort variation in a northern ungulate Journal of Animal Ecology 70721-729
Forchhammer MC Post E Stenseth NC Boertmann DM (2002) Long-term responses in arctic ungulate
dynamics to changes in climatic trophic processes Population Ecology 44113-120
Gaillard JM Festa-Bianchet M Yoccoz NG (1998) Population dynamics of large herbivores variable
recruitment with constant adult survival Trends in Ecology and Evolution 1358-63
Gaillard JM Festa-Bianchet M Yoccoz NG Loison A Toiumlgo C (2000a) Temporal variation in fitness
components and population dynamics of large herbivores Annual Review of Ecology and
Systematics 31367-393
Gaillard JM Festa-Bianchet M Delorme D Jorgenson J (2000b) Body mass and individual fitness in female
ungulate bigger is not always better Proceedings Biological Sciences 267471-477
Gaillard JM Hearingblewhite M Loison A Fuller M Powell R Basille M van Moorter B (2010) Habitat-
performance relationships finding the right metric at a given Spatial scale Philosophical
Transactions of the Royal Society B 3652255-2265
Garel M Solberg EJ Sӕther B-E Groslashtan V Tufto J Heim M (2009) Age size and spatiotemporal variation
in ovulation patterns of a seasonal breeder the Norwegian moose (Alces alces) The American
Naturalist 173(1)89-104
Georgii B (1980) Home range patterns of female red deer (Cervus elaphus L) in the Alps Oecologia
47278-285
Godvik IMR Loe LE Vik JO Veiberg V Langvatn R Mysterud A (2009) Temporal scales trade-offs and
functional responses in red deer habitat selection Ecology 90699ndash710
Gordon IJ Hester AJ Festa-Bianchet M (2004) Review The management of wild large herbivores to meet
economic conservation and environmental objectives Journal of Applied Ecology 411021-
1031
Hagner O Nilsson M Reese H Egberth M Olsson H (2005) Procedure for classification of forests for
CORINE land cover in Sweden In Oluić M (ed) New strategies for European remote sensing
Millpress Rotterdam pp 523ndash530
Hall LS Krausman PR Morrison ML (1997) The habitat concept and a plea for standard terminology
Wildlife Society Bulletin 25173-182
Harris RB Wall WA Allendorf FW (2002) Genetic consequences of hunting what do we know and what
should we do Wildlife Society Bulletin 30634-643
Herfindal I Saeligther B-E Solberg EJ Andersen R Hoslashgda KA (2006) Population characteristics predict
responses in moose body mass to temporal variation in the environment Journal of Animal
Ecology 75 (5) 1110-1118
Horne JS Garton ED Krone SM Lewis JS (2007) Analysing animal movements using Brownian bridges
Ecological Society of America Ecology 882354-2363
Hornok S Kovaacutets D Csoumlrgo T Meli M Goumlnczi E Hadnagy Z Takaacutecs N Farkas R Hofmann-Lehmann R
(2014) Birds as potential reservoirs of tick-borne pathogens first evidence of bacteraemia
with Rickettsia Helvetica Parasites and Vectors 7128
26
Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos
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Studies SLU Examensarbete I aumlmnet biologi vol 20072
Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American
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Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)
The home range concept are traditional estimators still relevant with modern telemetry
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Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement
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Animal Ecology 81738-746
Laurian C Ouellet JP Courtois R Breton L St-Onge S (2000) Effects of intensive harvesting on moose
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road network The Journal of Wildlife Management 72(7)1550-1557
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northeastern Minnesota The Journal of Wildlife Management 74(5)1013-1023
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14343-348
Linnell JDC Aanes R Andersen R (1995) Who killed Bambi The role of predation in the neonatal
mortality of temperate ungulates Wildlife Biology 1209-223
Lomas LA Bender LC (2007) Survival and cause-specific mortality of neonatal mule deer fawns north-
central New Mexico Journal of Wildlife Management 71884ndash894
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northcentral Alberta 1971-1979 Alces 2061-78
MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or
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27
Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S
Dalin AM (2013) Temporal and spatial variation in Anaplasma phagocytophilum infection in
Swedish moose (Alces alces) Epidemiology and Infection 1421205-1213
Malmsten J (2014a) lsquoReproduction and health of moose in southern Swedenrsquo Doctoral thesis Swedish
University of Agricultural Sciences (SLU) Umearing
Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive
characteristics in female Swedish moose (Alces alces) with emphasis on puberty timing of
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Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research
experimental tests with red-backed salamanders Animal Behaviour 681425-1433
Maringrell A Hofgaard A Danell K (2006) Nutrient dynamics of reindeer forage species along snowmelt
gradients as different ecological scales Basic and Applied Ecology 713-30
McLoughlin PD Vander Wal E Lowe SJ Patterson BR Murray DL (2011) Seasonal shifts in habitat
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12(8) 654-663
Milner JM Nilsen EB and Andreassen HP (2007) Demographic side effects of selective hunting in ungulates
and carnivores Conservation Biology 2136-47
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south-central Alaska The Journal of Wildlife Management 61(2)540-549
Monfort SL Schwartz CC Wasser SK (1993) Monitoring reproduction in captive moose using urinary and
faecal steroid metabolites The Journal of Wildlife Management 57400-407
Monteith KL Klaver R Hersey K Holland A Thomas T Kauffman M In press Effects of climate and
plant phenology on recruitment of moose at the southern extent of their range
Morales JM Moorcroft PR Matthiopoulos J Frair JL Kie JG Powell RA Merrill EH Haydon DT (2010)
Building the bridge between animal movement and population dynamics Philosophical
Transactions of the Royal Society B 3652289-230
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levels of intrasexual competition Journal of Animal Ecology 74742-754
Osko TJ Hiltz MN Hudson RJ Wasel SM (2004) Moose habitat preferences in response to changing
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29
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Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania
Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
26
Jacobs J (1974) Quantitative measurement of food selection a modification of the forage ratio and Ivlevrsquos
Electivity Index Oecologia 14(4)413-417
Jenkins KJ Manly FJ (2008) A double-observer method for reducing bias in faecal pellet surveys of forest
ungulates Journal of Applied Ecology 451339-1348
Johnson DH (1980) The comparison of usage and availability measurements for evaluating resource
preference Ecology 6165-71
Jonsson F (2007) rsquoDen oumllaumlndska aringlgstammens foumlrvaltingrsquo Departement of Wildlife Fish and Environmental
Studies SLU Examensarbete I aumlmnet biologi vol 20072
Kaplan EL Meier P (1958) Nonparametric estimation from incomplete observation Journal of the American
Statistical Association 53457-481
Keating KA Cherry S (2009) Modelling utilization distributions in space and time Ecology 90(7)1971-
1980
Kie JG Matthiopolos J Fieberg J Powell RA Cagnacci F Mitchell SM Gaillard JM Moorcroft PR (2010)
The home range concept are traditional estimators still relevant with modern telemetry
technology Philosophical Transactions of the Royal Society B 3652221-2231
Kindberg J Holmqvist N Bergqvist G (2009) Hunting bag statistics 2007-2008 [In Swedish] In
Viltoumlvervakningen 20072008 (Annual wildlife surveillance report) Viltforum Svenska
Jaumlgarefoumlrbundet Oumlster-Malma 20092
Kranstauber B Kays R LaPoint SD Wikelski M Safi K (2012) A dynamic Brownian bridge movement
model to estimate utilization distributions for heterogeneous Animal movement Journal of
Animal Ecology 81738-746
Laurian C Ouellet JP Courtois R Breton L St-Onge S (2000) Effects of intensive harvesting on moose
reproduction Journal of Applied Ecology 37515-531
Laurian C Dussault C Ouellet JP Courtois R Poulin M Breton L (2008) Behaviour of moose relative to a
road network The Journal of Wildlife Management 72(7)1550-1557
Lavsund S Nygreacuten T Solberg EJ (2003) Status of moose populations and challenges to moose management
in Fennoscandia Alces 39109-130
Lenarz MS Fieberg J Schrage MW Edwards AJ (2010) Living on the edge viability of moose in
northeastern Minnesota The Journal of Wildlife Management 74(5)1013-1023
Lindstroumlm J (1999) Early development and fitness in birds and mammals Trends in Ecology and Evolution
14343-348
Linnell JDC Aanes R Andersen R (1995) Who killed Bambi The role of predation in the neonatal
mortality of temperate ungulates Wildlife Biology 1209-223
Lomas LA Bender LC (2007) Survival and cause-specific mortality of neonatal mule deer fawns north-
central New Mexico Journal of Wildlife Management 71884ndash894
Lynch GM Morgantini LE (1984) Sex and age differential in seasonal home range size of moose in
northcentral Alberta 1971-1979 Alces 2061-78
MacCracken JG Ballenberghe VV Peek JM (1993) Use of aquatic plants by moose sodium hunger or
foraging efficiency Canadian Journal of Zoology 71(12)2345-2351
27
Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S
Dalin AM (2013) Temporal and spatial variation in Anaplasma phagocytophilum infection in
Swedish moose (Alces alces) Epidemiology and Infection 1421205-1213
Malmsten J (2014a) lsquoReproduction and health of moose in southern Swedenrsquo Doctoral thesis Swedish
University of Agricultural Sciences (SLU) Umearing
Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive
characteristics in female Swedish moose (Alces alces) with emphasis on puberty timing of
oestrus and mating Acta Veterinaria Scandinavica 5623
Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research
experimental tests with red-backed salamanders Animal Behaviour 681425-1433
Maringrell A Hofgaard A Danell K (2006) Nutrient dynamics of reindeer forage species along snowmelt
gradients as different ecological scales Basic and Applied Ecology 713-30
McLoughlin PD Vander Wal E Lowe SJ Patterson BR Murray DL (2011) Seasonal shifts in habitat
selection of a large herbivore and the influence of human activity Basic and Applied Ecology
12(8) 654-663
Milner JM Nilsen EB and Andreassen HP (2007) Demographic side effects of selective hunting in ungulates
and carnivores Conservation Biology 2136-47
Modafferi RD and Becker EF (1997) Survival of radio collared adult moose in lower Susitna River Valley
south-central Alaska The Journal of Wildlife Management 61(2)540-549
Monfort SL Schwartz CC Wasser SK (1993) Monitoring reproduction in captive moose using urinary and
faecal steroid metabolites The Journal of Wildlife Management 57400-407
Monteith KL Klaver R Hersey K Holland A Thomas T Kauffman M In press Effects of climate and
plant phenology on recruitment of moose at the southern extent of their range
Morales JM Moorcroft PR Matthiopoulos J Frair JL Kie JG Powell RA Merrill EH Haydon DT (2010)
Building the bridge between animal movement and population dynamics Philosophical
Transactions of the Royal Society B 3652289-230
Morellet N Bonenfant C Boumlrger L Ossi F Cagnacci F Heurich M Kjellander P Linnell JDC Nicoloso S
Sustr P Urbano F Mysterud A (2013) Seasonality weather and climate affect home range
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Mysterud A Oslashstbye E (1999) Cover as a habitat element for temperate ungulates effects on habitat selection
and demography Wildlife Society Bulletin 27(2)385-394
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Mysterud A Solberg EJ Yoccoz NG (2005) Ageing and reproductive effort in male moose under variable
levels of intrasexual competition Journal of Animal Ecology 74742-754
Osko TJ Hiltz MN Hudson RJ Wasel SM (2004) Moose habitat preferences in response to changing
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Philips RL Berg WE Siniff DB (1973) Moose movement patterns and range use in northern Minnesota The
Journal of Wildlife Management 37(3)266-278
28
Prentice HC Jonsson BO Sykes MT Ihse M Kindstroumlm M (2007) Fragmented grasslands on the Baltic
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studies Revista Brasileira de Zootecnia 3663-70
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Predation on moose calves by European brown bears The Journal of Wildlife Management
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29
Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate
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Udina IG Danilkin AA Boeskorov GG (2002) Genetic diversity of moose (Alces ales L) in Eurasia
Russian Journal of Genetics 38951-957
van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat
sensitive northern ungulate Animal Behaviour 84(3)723-735
van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife
Management 39118-123
Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By
Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania
Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for
conservation of large mammals in a fragmented environment Alces 4965-81
White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving
success in muskoxen Journal of Zoology 24313-20
30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
27
Malmsten J Wideacuten DG Rydevik G Yon L Hutchings MR Thulin CG Soumlderquist L Aspan A Stuen S
Dalin AM (2013) Temporal and spatial variation in Anaplasma phagocytophilum infection in
Swedish moose (Alces alces) Epidemiology and Infection 1421205-1213
Malmsten J (2014a) lsquoReproduction and health of moose in southern Swedenrsquo Doctoral thesis Swedish
University of Agricultural Sciences (SLU) Umearing
Malmsten J Soumlderquist L Thulin C Wideacuten DG Yon L Hutchings MR Dalin A (2014b) Reproductive
characteristics in female Swedish moose (Alces alces) with emphasis on puberty timing of
oestrus and mating Acta Veterinaria Scandinavica 5623
Marsh DM Hanlon TJ (2004) Observer gender and observation bias in animal behaviour research
experimental tests with red-backed salamanders Animal Behaviour 681425-1433
Maringrell A Hofgaard A Danell K (2006) Nutrient dynamics of reindeer forage species along snowmelt
gradients as different ecological scales Basic and Applied Ecology 713-30
McLoughlin PD Vander Wal E Lowe SJ Patterson BR Murray DL (2011) Seasonal shifts in habitat
selection of a large herbivore and the influence of human activity Basic and Applied Ecology
12(8) 654-663
Milner JM Nilsen EB and Andreassen HP (2007) Demographic side effects of selective hunting in ungulates
and carnivores Conservation Biology 2136-47
Modafferi RD and Becker EF (1997) Survival of radio collared adult moose in lower Susitna River Valley
south-central Alaska The Journal of Wildlife Management 61(2)540-549
Monfort SL Schwartz CC Wasser SK (1993) Monitoring reproduction in captive moose using urinary and
faecal steroid metabolites The Journal of Wildlife Management 57400-407
Monteith KL Klaver R Hersey K Holland A Thomas T Kauffman M In press Effects of climate and
plant phenology on recruitment of moose at the southern extent of their range
Morales JM Moorcroft PR Matthiopoulos J Frair JL Kie JG Powell RA Merrill EH Haydon DT (2010)
Building the bridge between animal movement and population dynamics Philosophical
Transactions of the Royal Society B 3652289-230
Morellet N Bonenfant C Boumlrger L Ossi F Cagnacci F Heurich M Kjellander P Linnell JDC Nicoloso S
Sustr P Urbano F Mysterud A (2013) Seasonality weather and climate affect home range
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Mysterud A Oslashstbye E (1999) Cover as a habitat element for temperate ungulates effects on habitat selection
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Mysterud A Solberg EJ Yoccoz NG (2005) Ageing and reproductive effort in male moose under variable
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Osko TJ Hiltz MN Hudson RJ Wasel SM (2004) Moose habitat preferences in response to changing
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Philips RL Berg WE Siniff DB (1973) Moose movement patterns and range use in northern Minnesota The
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28
Prentice HC Jonsson BO Sykes MT Ihse M Kindstroumlm M (2007) Fragmented grasslands on the Baltic
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Renecker LA Hudson RJ (1989) Seasonal activity budgets of moose in Aspen-dominated boreal forests The
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29
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Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By
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Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for
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30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
28
Prentice HC Jonsson BO Sykes MT Ihse M Kindstroumlm M (2007) Fragmented grasslands on the Baltic
island of Ӧland Plant community composition and land-use history
R Core Team (2003) R A language and environment for statistical computing R Foundation for Statistical
Computing Vienna Austria URL httpwwwR-projectorg
Rettie WJ Messier F (2000) Hierarchical habitat selection by woodland caribou its relationship to limiting
factors Ecography 23(4)466-478
Renecker LA Hudson RJ (1989) Seasonal activity budgets of moose in Aspen-dominated boreal forests The
Journal of Wildlife Management 53(2)296-302
Roseacuten E (2006) Alvar Vegetation of Ӧland ndash Changes Monitoring and Restoration Biology and
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Rutter SM (2007) The integration of GPS vegetation mapping and GIS in ecological and behavioural
studies Revista Brasileira de Zootecnia 3663-70
Sӕther B-E (1997) Environmental stochasticity and population dynamics of large herbivores a search for
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Alaska Ecology 851439-1452
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Ecological Research 26(4)781-789
Tufto J Andersen R Linnell J (1996) Habitat use and ecological correlates of home range size in a small
cervid the roe deer Journal of Animal Ecology 65(6)715-724
Turchin P (2001) Complex population dynamics a theoreticalempirical synthesis New Jersey Princeton
University Press
29
Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate
maps Norway CICERO
Udina IG Danilkin AA Boeskorov GG (2002) Genetic diversity of moose (Alces ales L) in Eurasia
Russian Journal of Genetics 38951-957
van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat
sensitive northern ungulate Animal Behaviour 84(3)723-735
van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife
Management 39118-123
Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By
Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania
Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for
conservation of large mammals in a fragmented environment Alces 4965-81
White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving
success in muskoxen Journal of Zoology 24313-20
30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
29
Tveito OE Foslashrland EJ Alexandersson H Drebs A Jonsson T Vaarby-Laursen E (2001) Nordic climate
maps Norway CICERO
Udina IG Danilkin AA Boeskorov GG (2002) Genetic diversity of moose (Alces ales L) in Eurasia
Russian Journal of Genetics 38951-957
van Beest FM van Moorter B Milner JM (2012) Temperature-mediated habitat use and selection by a heat
sensitive northern ungulate Animal Behaviour 84(3)723-735
van Winkle W (1975) Comparision of several probabilistic home-range models Journal of Wildlife
Management 39118-123
Verme LJ Ullrey DE (1984) Physiology and nutrition White-tailed deer ecology and management (Ed By
Halls LK) pp 91-118 Stackpole Harrisburg Pennsylvania
Wattles DW DeStefano (2013) Space use and movements of moose in Massachusetts Implications for
conservation of large mammals in a fragmented environment Alces 4965-81
White RG Rowell JE Hauer WE (1997) The role of nutrition body condition and lactation on calving
success in muskoxen Journal of Zoology 24313-20
30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
30
Appendix A
Introduction
Fig 1 Summary chart of factors affecting the life history and therefore the long term fitness of a population
Fig 2 Summary chart 2
Movement
Habitat
Climate
Topography
Competition
FoodWater
Disease
Die
Survive
Reproduce
Population long term fitness
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
31 Appendix B
Method and Materials
Fig 1 Summary of processes
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
32
Fig 2 Examples of classical kernel home range output and Brownian bridge kernel home range (Calenge 2011) The
right image includes the area between relocations ie the movement path in contrast to the classic kernel home range
in the left image
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
33 Appendix C
Home ranges
Fig 1 Example of a non-migratory (ID006) individuals BRB kernel area From top left annual growing and winter
season UD50 (black contour) and UD95 (red contour)
Fig 2 Example of a migratory (ID012) individuals BRB kernel area From the left annual growing and winter season
UD50 (black contour) and UD95 (red contour)
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
34
Table 1 Annual and seasonal UD50 and UD95 areas (ha) for all individuals
ID Annual GS WS
UD50 UD95 UD50 UD95 UD50 UD95
ID004 190 924 93 531 173 941
ID005 230 1364 132 945 72 682
ID006 162 1036 89 736 70 611
ID008 277 1536 156 809 78 738
ID009 137 834 48 295 126 653
ID010 114 682 83 448 96 488
ID012 177 963 123 544 76 545
ID014 160 1018 87 575 89 662
ID015 172 858 128 532 109 679
ID016 156 1047 65 455 92 534
ID017 153 1088 149 1043 69 349
ID019 279 1097 176 911 163 824
ID020 139 1084 67 349 160 794
ID022 159 811 131 638 61 454
ID023 187 1061 147 771 72 705
ID024 146 725 165 705 101 458
ID026 142 605 99 442 125 547
ID027 126 567 75 461 48 277
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
35 Appendix D
Activity
Fig 1 Mean daily movement during the study period GS 23-April-2012 to 07-Nov-2012 WS 08-Nov-2012 to
22-April-2013 (number indicates month)
Fig 2 Mean daily movement in the centre and south during the GS and WS
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
36
Appendix E
Habitat Proportions
Fig 1 All individualsrsquo seasonal habitat proportions within the UD95
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
37 Habitat Selection
Table 1 Simplified ranking matrices comparing proportional habitat use within the second order (UD95Area) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North A
gri
cult
ure
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- - +++ --- --- --- +++ +++ --- 8
Broad Leaf +++ 0 +++ + +++ +++ +++ + +++ +++ +++ 1
Clear Fell +++ --- 0 + +++ - - --- +++ +++ --- 7
Coniferous + - - 0 +++ - - --- +++ +++ - 6
Freshwater --- --- --- --- 0 --- --- --- +++ - --- 10
Grassland
Moors +++ --- + + +++ 0 +++ - +++ +++ + 3
MiresMarshes +++ --- + + +++ --- 0 - +++ +++ --- 5
Mixed +++ - +++ +++ +++ + + 0 +++ +++ + 2
Sparse Veg --- --- --- --- --- --- --- --- 0 --- --- 11
Urban --- --- --- --- + --- --- --- +++ 0 --- 9
Younger +++ --- +++ + +++ - +++ - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt GrasslandMoorsgt Youngergtgtgt MiresMarshesgt Coniferousgt
Clear Fellgtgtgt Agriculturegtgtgt Urbangt Freshwatergtgtgt Sparse Veg
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- + +++ + --- +++ +++ --- 6
Broad Leaf +++ 0 +++ + +++ +++ + - +++ +++ - 3
Clear Fell +++ --- 0 - +++ +++ + --- +++ +++ --- 5
Coniferous +++ - + 0 +++ +++ + --- +++ +++ - 4
Freshwater - --- --- --- 0 +++ - --- +++ +++ --- 8
Grassland
Moors --- --- --- --- --- 0 --- --- +++ - --- 10
MiresMarshes - - - - + +++ 0 - +++ +++ - 7
Mixed +++ + +++ +++ +++ +++ + 0 +++ +++ + 1
Sparse Veg --- --- --- --- --- --- --- --- 0 - --- 11
Urban --- --- --- --- --- + --- --- + 0 --- 9
Younger +++ + +++ + +++ +++ + - +++ +++ 0 2
Rank Order and
Significance
Mixedgt Youngergt Broad Leafgt Coniferousgt Clear Fellgtgtgt Agriculturegt
MiresMarshesgt Freshwatergtgtgt Urbangt GrasslandMoorsgtgtgt Sparse Veg
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
38
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 + - - + - + +++ +++ +++ - 5
Broad Leaf - 0 - - + - - +++ + +++ - 7
Clear Fell + + 0 - + + + +++ + +++ + 2
Coniferous + + + 0 +++ + + +++ + +++ + 1
Freshwater - - - --- 0 - - + + +++ - 8
Grassland
Moors + + - - + 0 + + +++ + - 4
MiresMarshes - + - - + - 0 +++ + +++ - 6
Mixed --- --- --- --- - - --- 0 + + --- 10
Sparse Veg --- - - - - --- - - 0 + - 9
Urban --- --- --- --- --- - --- - - 0 --- 11
Younger + + - - + + + +++ + +++ 0 3
Rank Order
and
Significance
Coniferousgt Clear Fellgt Youngergt GrasslandMoorsgt Agriculturegt MiresMarshesgt Broad Leafgt
Freshwatergt Sparse Veggt Mixedgt Urban
Table 2 Simplified ranking matrices comparing proportional habitat use within the third order (UD50UD95) with
proportions of total available habitat types Mean value on the matrix was replaced by a sign a triple sign represents
significant deviation from random at P lt05 Highlighted habitat is ranked 1st
North
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- --- - + --- --- + +++ --- 8
Broad Leaf +++ 0 +++ + + + + + +++ +++ + 1
Clear Fell +++ --- 0 + + + - - + +++ - 5
Coniferous +++ - - 0 + + --- --- +++ +++ - 6
Freshwater + - - - 0 +++ - - +++ +++ - 7
GrasslandMoors - - - - --- 0 - - - + - 10
MiresMarshes +++ - + +++ + + 0 - +++ +++ + 3
Mixed +++ - + +++ + + + 0 +++ +++ + 2
Sparse Veg - --- - --- --- + --- --- 0 +++ --- 9
Urban --- --- --- --- --- - --- --- --- 0 --- 11
Younger +++ - + + + + - - +++ +++ 0 4
Rank Order and
Significance
Broad Leafgt Mixedgt MiresMarshesgt Youngergt Clear Fellgt Coniferousgt Freshwatergt
Agriculturegt Sparse Veggt GrasslandMoorsgt Urban
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
39
Central
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 --- --- + + - - - + +++ --- 7
Broad Leaf +++ 0 + +++ + + + + + +++ - 2
Clear Fell +++ - 0 +++ + + + + + +++ - 3
Coniferous - --- --- 0 + - - --- +++ + --- 8
Freshwater - - - - 0 --- - - --- - - 11
GrasslandMoors + - - + +++ 0 + - + +++ - 5
MiresMarshes + - - + + - 0 + + +++ - 6
Mixed + - - +++ + + - 0 +++ +++ - 4
Sparse Veg - - - --- +++ - - --- 0 +++ - 9
Urban --- --- --- - + --- --- --- --- 0 --- 10
Younger +++ + + +++ + + + + + +++ 0 1
Rank Order and
Significance
Youngergt Broad Leafgt Clear Fellgt Mixedgt GrasslandMoorsgt MiresMarshesgt
Agriculturegt Coniferousgtgtgt Sparse Veggtgtgt Urbangt Freshwater
South
Ag
ricu
ltu
re
Bro
ad L
eaf
Cle
ar F
ell
Co
nif
ero
us
Fre
shw
ater
Gra
ssla
nd
Mo
ors
Mir
es
Mar
shes
Mix
ed
Sp
arse
Veg
Urb
an
Yo
un
ger
Ra
nk
Agriculture 0 - - - - - + - +++ + --- 8
Broad Leaf + 0 - --- + - + - +++ + - 6
Clear Fell + + 0 - + - + - +++ + - 4
Coniferous + +++ + 0 + + +++ + +++ + + 1
Freshwater + - - - 0 - - + + + - 7
GrasslandMoors + + + - + 0 + + + + - 3
MiresMarshes - - - --- + - 0 - + + - 9
Mixed + + + - - - + 0 + + - 5
Sparse Veg --- --- --- --- - - - - 0 + --- 10
Urban - - - - - - - - - 0 - 11
Younger +++ + + - + + + + +++ + 0 2
Rank Order and
Significance
Coniferousgt Youngergt GrasslandMoorsgt Clear Fellgt Mixedgt Broad Leafgt Freshwatergt
Agriculturegt MiresMarshesgt Sparse Veggt Urban
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
40
Table 3 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the GS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Broad
Leaf Urban Broad Leaf Sparse Veg
Broad
Leaf Urban Mixed Urban Coniferous Urban
Grassland
Moors Urban
2 Mixed Sparse Veg Mixed Freshwater Younger Agriculture Younger Sparse Veg Younger Sparse Veg Clear Fell Mixed
3 Mires
Agriculture Grassland
Urban Clear
Fell Coniferous Broad Leaf
Grassland
Moors
Clear Fell Agriculture Coniferous Sparse Veg
Marshes Moors
4 Younger Grassland
Younger Agriculture
Freshwater Coniferous Freshwater
Broad Leaf Mires
Younger Freshwater
Moors Marshes
5 Clear
Fell Freshwater
Mires Coniferous
Sparse Veg Clear Fell Agriculture
Freshwater Agriculture
Marshes
6 Coniferous Clear Fell
Mires
Marshes
Mires
Grassland
Moors
Mires
Marshes Marshes
7 Mixed Mixed Broad Leaf
8 Grassland
Moors
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
41
Table 4 Summary of the habitats preferred (+) and avoided (-) by area (N C S) in the WS according to Jacobs index
Ran
k North Centre South
50 95 50 95 50 95
+ - + - + - + - + - + -
1 Mires
Marshes
Grassland
Moors Mixed Freshwater Agriculture Urban Mixed Freshwater
Grassland
Moors Urban GrasslandMoors Urban
2 Freshwater Mixed Coniferous Urban Mires
Marshes Coniferous Sparse Veg Agriculture
Sparse
Veg Coniferous Freshwater
3 Urban Coniferous Younger Grassland
Moors Freshwater Younger Urban Freshwater
Broad
Leaf Agriculture Mixed
4 Younger Agriculture Sparse Veg Broad
Leaf
Broad
Leaf
Grassland
Moors Mixed Broad Leaf
5 Clear Fell Agriculture Coniferous Agriculture Mires
Marshes Clear Fell
6 Sparse
Veg
Mires
Marshes Mixed
Mires
Marshes
Clear
Fell
Mires
Marshes
7 Broad
Leaf Clear Fell Younger Clear Fell Younger Sparse Veg
8 Clear Fell Younger
9 Sparse
Veg
10 Grassland
Moors
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
42
Table 5 Second order (UD95Area) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Younger Sparsely Vegetated MiresMarshes Sparsely Vegetated
ID005 MiresMarshes Sparsely Vegetated Coniferous GrasslandMoors
ID006 Coniferous Sparsely Vegetated Mixed Freshwater
ID008 Mixed Sparsely Vegetated Mixed Freshwater
ID009 Mixed Sparsely Vegetated Mixed GrasslandMoors
ID010 MiresMarshes Freshwater GrasslandMoors Freshwater
ID012 Broad Leaf Sparsely Vegetated Coniferous Urban
ID014 Clear Fell Sparsely Vegetated GrasslandMoors Sparsely Vegetated
ID015 GrasslandMoors Urban GrasslandMoors Freshwater
ID016 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID017 GrasslandMoors Mixed Sparsely Vegetated Mixed
ID019 Mixed Sparsely Vegetated Mixed Urban
ID020 Broad Leaf Sparsely Vegetated Coniferous GrasslandMoors
ID022 MiresMarshes Freshwater MiresMarshes Freshwater
ID023 MiresMarshes GrasslandMoors Mixed Freshwater
ID024 Broadleaf Urban Broad Leaf Urban
ID026 GrasslandMoors Freshwater GrasslandMoors Freshwater
ID027 GrasslandMoors Urban Sparsely Vegetated Freshwater
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
43 Table 6 Third order (UD50UD95) individual selectionavoidance for the GS and WS according to the Jacobs index
ID GS WS
Select Avoid Select Avoid
ID004 Broad Leaf Mixed GrasslandMoors Freshwater
ID005 Broad Leaf Freshwater Agriculture Freshwater
ID006 Clear Fell Freshwater Agriculture MiresMarshes
ID008 MiresMarshes Freshwater Agriculture Urban
ID009 Freshwater Agriculture Agriculture Freshwater
ID010 Mixed Urban Sparsely Vegetated Urban
ID012 Coniferous GrasslandMoors Freshwater Urban
ID014 Urban Agriculture Freshwater Urban
ID015 Mixed Forest Urban Clear Fell Urban
ID016 Freshwater Urban GrasslandMoors Mixed
ID017 Coniferous Mixed Coniferous Broad Leaf
ID019 Broad Leaf GrasslandMoors Urban GrasslandMoors
ID020 Freshwater Urban Freshwater Agriculture
ID022 MiresMarshes Urban Broad Leaf GrasslandMoors
ID023 Freshwater Mixed Agriculture Freshwater
ID024 Mixed Freshwater Mixed Freshwater
ID026 Mixed MiresMarshes Sparsely Vegetated GrasslandMoors
ID027 Freshwater MiresMarshes GrasslandMoors Broad Leaf
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
44
Fig 2 North third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
45
Fig 3 Centre third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
46
Fig 4 South third order (UD50UD95) habitat preferences during the GS (orange) and WS (blue)
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
47
Fig 5 North second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
48
Fig 6 Centre second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
49
Fig 7 South second order (UD95Area) habitat preferences during the GS (orange) and WS (blue)
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality
50
Appendix F
Background
Fig 1 Daily mean snow depth and duration during the study period (Andrew Allen)
Female Moose Reproduction
Moose are seasonal polyoestral mammals (Monfort et al 1993) coming into oestrus during late September
early October (Garel et al 2009) The Swedish moose cow population reaches puberty between the ages 25
and 35 (Sand and Cederlund 1993) during which the reproductive period begins with the onset of ovulation
The age an individual reaches puberty is dependent on their body condition they have to reach a weight
threshold to reach puberty and become reproductive (Sand 1996) If she is over the weight threshold she will
go into oestrus in the autumn If she does not reach the weight threshold then she will go into oestrus the
following autumn if successful she will give birth to individual or twin calves in late May to early June
(Ericsson et al 2001) and therefore reach sexual maturity (Malmsten et al 2014b) Fecundity is related to
both the condition and the age of the cow Cows go through senescence at 12 years of age (Ericsson et al
2001) Providing calves with the required level of nutrition demands high energy and protein resources from
the mother during senescence this becomes harder to achieve leading to decreased levels of parental care
and higher levels of calf mortality