Abundance, movements and habitat use of coastal dolphins in the Darwin region
Abundance, movements and
habitat use of coastal dolphins in
the Darwin region
Analysis of the first four primary samples (October 2011 to April 2013)
STATPLAN CONSULTING PTY LTD
November 4, 2013
Lyndon Brooks & Kenneth Pollock (2013). Abundance, movements and habitat use of
coastal dolphins in the Darwin region: Analysis of the first four primary samples (October
2011 to April 2013). Draft report for the Northern Territory Government Department of
Land Resource Management.
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Contents Contents .......................................................................................................................................................... 1
Executive Summary ........................................................................................................................................ 2
Context ........................................................................................................................................................ 2
Methods ...................................................................................................................................................... 2
Results......................................................................................................................................................... 2
Abundance .............................................................................................................................................. 3
Movements.............................................................................................................................................. 3
Apparent Survival ................................................................................................................................... 4
Habitat Use ............................................................................................................................................. 4
Conclusion .................................................................................................................................................. 4
Introduction ..................................................................................................................................................... 5
Methods .......................................................................................................................................................... 6
Sampling ..................................................................................................................................................... 6
Data analysis ............................................................................................................................................... 9
Abundance, apparent survival and movements ....................................................................................... 9
Habitat use ............................................................................................................................................ 12
Results........................................................................................................................................................... 15
Abundance, Apparent Survival and Movements ...................................................................................... 15
Humpback dolphin ................................................................................................................................ 15
Bottlenose dolphin ................................................................................................................................ 16
Snubfin dolphin ..................................................................................................................................... 18
Summary of abundance estimates ......................................................................................................... 19
Habitat use ................................................................................................................................................ 21
Summary of habitat use ........................................................................................................................ 25
Conclusion .................................................................................................................................................... 26
REFERENCES ............................................................................................................................................. 27
Appendix ......................................................................................................................................................... 0
Table A1 Dates of secondary samples by site for each primary sample ..................................................... 1
Table A2 Summary of captures by species, site and primary sample ......................................................... 2
Table A3 Model comparison results for models on each species ............................................................... 4
Table A4 Parameter estimates from selected models for each species ....................................................... 7
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Executive Summary
Context
The Darwin Harbour Coastal Dolphin Monitoring Program was initiated as part of the environmental
approvals under the Commonwealth Environment Protection and Biodiversity Conservation Act 1999 and
the Northern Territory Environmental Assessment Act 1982 for the INPEX Ichthys Gas Field Development
project. The stated aim of the program is:
“To detect change, beyond natural spatial and temporal variation, in coastal dolphin abundance and
distribution during near shore Project construction activities in Darwin Harbour, including pre- and post-
construction phase monitoring.”
Methods
The demographic parameters, abundance and apparent survival, were estimated using an extension of the
Robust Design model known as the Multistate Robust Design model. This model provides an integrated
analysis of the data over the three sites sampled as part of the monitoring program (Bynoe Harbour,
Darwin Harbour and Shoal Bay) including estimates of rates of movement between the three sites between
primary samples.
Sufficient data were available to build a Multistate Robust Design model for all three sites for humpback
dolphins (Sousa sp.). Conversely, for bottlenose dolphins (Tursiops sp.) there were too few data from some
sites to allow analysis, and therefore, the data for Bynoe Harbour and Shoal Bay was pooled to yield
estimates for Darwin Harbour and elsewhere in the local region. Similarly, the data for the Australian
snubfin dolphin (Orcaella heinsohni) were pooled across all three sites to yield a single set of estimates for
the whole local region.
A Binary Logistic Mixed Effects model was employed to estimate the relative rates of use of locations
(sub-sites) in the local region over the four primary samples. The model was fitted to the data for all
species combined as there were too few data on bottlenose and snubfin dolphins to support separate
models for these species.
Results
The ability to model more complex effects or to obtain estimates of demographic parameters for all sites
was limited for snubfin and bottlenose dolphins due to the small sizes of these populations. This limitation
was more acute for snubfin than bottlenose dolphins due to the irregularity of their visitation to the area
and greater difficulty of capturing and recapturing them. The population size and recapture rate for
humpback dolphins were sufficient however to allow models to generate estimates with good precision at
all three sites.
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Abundance
The abundance estimates of the three species have remained relatively stable over the four primary
samples. Humpback dolphins were the most abundant of the three species in the region and at all three
sites. Moreover, their numbers have remained stable with 20-29 using Bynoe Harbour, 37-41 using Darwin
Harbour and 13-21 using Shoal Bay. Overall, around 80 humpback dolphins use the region in a primary
sample (i.e., a three week survey period).
Although the population of bottlenose dolphins in the region is small, capture and recapture rates for this
species were relatively high and consistent over time allowing estimates with good precision to be
obtained. Bottlenose dolphins rarely use Bynoe Harbour and the few data that were available for that site
were pooled with those from Shoal Bay to obtain estimates for Bynoe Harbour/Shoal Bay and Darwin
Harbour. Five to ten bottlenose dolphins were found to use Bynoe Harbour/Shoal Bay and 15-25 were
found to use Darwin Harbour over the primary samples. Overall, 22-31 bottlenose dolphins use the region
during a primary sample.
The Australian snubfin may be least abundant or use the region in about the same numbers as the
bottlenose dolphin. Visitation of the region by this species is irregular, and their capture and recapture rates
are highly variable over time. The snubfin data were the most difficult to model and it was necessary to
pool the data over all three sites to obtain estimates for the region. Around 17-29 snubfin dolphins use the
region in a primary sample.
Movements
There were sometimes substantial movements of humpback dolphins between Bynoe Harbour and Darwin
Harbour, varying between six and 38 percent in one direction or another between successive primary
samples. No movements were observed between either of Darwin Harbour or Bynoe Harbour and Shoal
Bay. We found no evidence of temporary emigration between primary samples.
Movements of bottlenose dolphins between sites were observed in only two intervals between primary
samples but when they occurred, they were quite substantial at 39 and 11 percent. Around six percent of
the Darwin Harbour population were estimated to have temporarily emigrated from the local region
between successive primary samples.
While movements of snubfin between sites were observed, it was not possible to model them. Temporary
emigration of snubfin from the local region between successive primary samples was high at around 63
percent, indicating that they move around a large area and occur in numbers substantially larger than the
number that use the region in a primary sample (perhaps as large as 70 or more). That is, the area sampled
(Bynoe Harbour, Darwin Harbour and Shoal Bay) appears to be smaller than total area used by the snubfin
population that uses the local area, of which only about 37 percent were estimated to be present in the
sample area during a primary sample.
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Apparent Survival
The annual apparent survival rate of humpback dolphins varied markedly between Darwin Harbour at
around 0.93 and Bynoe Harbour and Shoal Bay at around 0.49 each, suggesting substantial emigration
from the latter two sites. Abundance at these sites has remained relatively constant however, suggesting
complementary recruitment to the sites from outside the local region.
The annual apparent survival rate (alive and on site) for bottlenose dolphins was around 0.81, a rate which
is likely to be lower than the true biological survival rate (alive) suggesting some, relatively small rate of
emigration from the local region.
The annual apparent survival rate for snubfin dolphins was around 0.94 which is quite high and may be
close to the true biological survival rate for the species. While the confidence interval was very wide for
this estimate (0.0:99.9), taken at face value, this suggests that, although there is substantial temporary
emigration from the local region between primary samples, most snubfin that use the area at some time are
likely to return at some stage.
Habitat Use
We found no evidence of change in the relative rates of use of ten locations (sub-areas) defined within the
local region between primary samples. It’s notable that the outer Harbour areas (outer Bynoe Harbour,
outer Darwin Harbour and Gunn Point) are relatively well used and that this is consistent with and
complementary to evidence from the capture-recapture models of movement into and out of the Darwin
region: i.e., there is evidently a flow of dolphins not only across the outer Harbour areas in the Darwin
region but also to and from sites west of Bynoe Harbour and east of Shoal Bay.
Conclusion
While the abundances of the three species are quite small, they have remained stable over the duration of
the study so far, and the estimated rates of habitat use show no significant variation between locations over
time.
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Introduction
As part of the environmental approvals under the Commonwealth Environment Protection and
Biodiversity Conservation Act 1999 and the Northern Territory Environmental Assessment Act 1982 for the
INPEX Ichthys Gas Field Development project, a monitoring program for coastal dolphins was required
for Darwin Harbour. The stated aim of the program is: “To detect change, beyond natural spatial and
temporal variation, in coastal dolphin abundance and distribution during near shore Project construction
activities in Darwin Harbour, including pre- and post- construction phase monitoring.”
Three species of coastal dolphin inhabit the Darwin Harbour region (extending from Gunn Point to Bynoe
Harbour): Indo-Pacific humpback (Sousa sp.; hereafter referred to as humpback, see Mendez et al. 2013
for recent taxonomic results), Australian snubfin (Orcaella heinsohni, hereafter referred to as snubfin) and
bottlenose (Tursiops sp., hereafter referred to as bottlenose) dolphins. All three species are listed as marine
and migratory species (and hence are matters of National Environmental Significance) under the
Environment Protection and Biodiversity Conservation Act 1999 (EPBC Act).
Monitoring of the local populations of the three species of dolphin in Darwin Harbour for the Ichthys
project commenced in October 2011. The population sizes of each species in Darwin Harbour have
previously been estimated as small, with approximately 40, 18 and eight individual humpback, bottlenose
and snubfin dolphins, respectively (Brooks and Pollock, 2012). Population sizes in Bynoe Harbour and
Shoal Bay were smaller with approximately 30 humpback, four bottlenose and 10 snubfin in Bynoe
Harbour, and 15 humpback, 11 bottlenose and a small but unknown number of snubfin in Shoal Bay.
The first two primary sample surveys may be viewed as constituting a pre-construction phase baseline as
no construction activity occurred (although shipping activity increased) during this period. Dredging first
began in October 2012 and continued through the 2012/2013 wet season which includes primary samples
three and four.
The objectives for this report are, for the available data, to:
1. Assess changes in population dynamic parameters of the three coastal dolphin species at the three
sites, including population size, losses (mortality + emigration), gains (births + immigration) and
temporary emigration (assumes sufficient population sizes of a species at a site to yield adequate
samples for analysis) before, during and after the construction of the Ichthys LNG facility in
Darwin Harbour.
2. Assess changes in the spatio-temporal distribution (pattern of habitat use) of the three coastal
dolphin species at each of the three sites, including movements between the sites (assumes
adequate data on movements) and site fidelity before, during and after the construction of the
Ichthys LNG facility in Darwin Harbour.
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Methods
Sampling
The sampling design for the Darwin Harbour Dolphin Monitoring Program is based on a Robust Design
sampling structure (Brooks and Pollock 2011, Pollock et al. 1990, Williams et al. 2002) of two primary
samples per year (wet and dry season samples), each consisting of nine secondary samples at each of three
sites (Darwin Harbour, Bynoe Harbour, Shoal Bay). Each secondary sample was defined as a complete set
of transects through a site (Brooks and Pollock 2011, Griffiths and Palmer 2011). It was planned that,
weather permitting, each secondary sample would be taken in one day using four boats in Darwin Harbour,
three in Bynoe Harbour and one in Shoal Bay. The four boats alternate each three days between all four in
Darwin Harbour, and three in Bynoe harbour and one in Shoal Bay.
The principal data collected on survey are the locations and species of dolphin groups, and photographs of
the dorsal fins of individual dolphins. The data on the locations of sighted dolphin groups were used to
model their spatial distribution, while the photographs were used to identify individuals from the nicks and
scars on their dorsal fins to yield capture-recapture data to model abundance, apparent survival and
movements.
Capture-recapture methods have been widely used to estimate demographic parameters for a number of
dolphin species including snubfin, humpback and bottlenose dolphins (Würsig and Jefferson 1990; Parra et
al. 2006; Nicholson et al. 2012). Many cetaceans bear nicks and marks that allow identification of
individuals from photographs, and such identifiers provide a mechanism for population estimation based
on capture-recapture methods, where re-sightings of individuals with distinctive natural marks constitute
re-captures (Hammond and Thompson 1990). A general overview of capture-recapture models is found in
Amstrup et al. (2005) while more detailed coverage is found in Williams et al. (2002). The Robust Design
model is described and its parameters specified in Pollock et al. (1990), Kendall and Nichols (1995), and
Kendall, et al. (1995, 1997).
Figure 1 shows a research crew on survey on a calm morning, Figure 2 shows a humpback dolphin
observing a research crew, Figure 3 shows a crew photographing a dolphin with a distinctively-marked
dorsal fin, and Figure 4 maps the transect lines followed nine times in each primary sample at the three
sites.
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Figure 1 Research crew on survey
Figure 2 A humpback dolphin observing a research crew
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Figure 3 A crew photographing a dolphin with a distinctively-marked dorsal fin
Figure 4 Map of locations of transect lines in Bynoe Harbour, Darwin Harbour and Shoal Bay
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Sampling was completed for the first four primary samples at all sites between:
20th
October and 18th
November 2011 (primary sample one pre-construction),
26th
March and15th
April 2012 (primary sample two – pre-construction),
8th
October 2012 and 27th
October 2012 (primary sample three – dredging season one), and
13th
March 2013 and 2nd
April 2013 (primary sample four – dredging season one).
The dates of the primary samples and their secondary samples at each site are reported in the Appendix,
Table A1.
Data analysis
The number of secondary samples with non-zero captures, the number of individuals captured, the
maximum number of captures per individual and the total number of captures of all individuals are
reported for each species at each site in each primary sample in the Appendix, Table A2.
Abundance, apparent survival and movements
The Multistate Closed Robust Design Model (MSCRD, Nichols & Coffman 1999, Kendall & Nichols
2002, Kendall 2013) was employed for analysis of the capture-recapture data to estimate abundance,
apparent survival, and movements between sites and temporary emigration between primary samples. This
is at once an extension of the Closed Robust Design model (CRD, Pollock 1982, Kendall and Nichols
1995, Kendall et al. 1997) and the multistate model for recapture data (Arnason 1972, 1973; Brownie et al.
1993; Schwarz et al. 1993).
The CRD model was employed in the previous report (Brooks & Pollock 2013) for analysis of abundance
and apparent survival, and a multistate model based on data collapsed to primary samples (i.e., not robust
design) was employed for analysis of movements between the three sites. Here these two kinds of models
are combined in the MSCRD model.
The MSCRD model provides estimates of:
1. Apparent survival between primary samples (probabilities, S parameters)
2. Movements between sites and temporary emigration between primary samples (probabilities, psi
parameters). Whereas temporary emigration is modelled in terms of gamma” and gamma’
parameters in the CRD, temporary emigration is included among the movements (psi parameters)
in the MSCRD by defining an ‘unobservable’ state for dolphins that are temporarily absent in a
primary sample.
3. Abundance at each primary sample (N parameters).
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Whereas the CRD model deals with only one site (here, Bynoe Harbour, Darwin Harbour, Shoal Bay or all
considered as one regional site) at a time, the MSCRD model can simultaneously provide these estimates
for multiple states (here multiple sites, Bynoe Harbour, Darwin Harbour and Shoal Bay).
With three sites (Bynoe Harbour, Darwin Harbour and Shoal Bay) four states were defined: three
observable states (the three sites) and one unobservable state for temporary absence from all three sites.
Dolphins may move between all four states between pairs of primary samples, with such movements being
modelled as transition probabilities. With four primary samples, the complete set of possible between-state
movements (transition probabilities) for the intervals between primary samples one and two, two and three
and three and four is:
1. Movements between Bynoe Harbour and Darwin Harbour.
2. Movements between Bynoe Harbour and Shoal Bay.
3. Movements between Darwin Harbour and Bynoe Harbour.
4. Movements between Darwin Harbour and Shoal Bay.
5. Movements between Shoal Bay and Bynoe Harbour.
6. Movements between Shoal Bay and Darwin Harbour.
7. Movements between Bynoe Harbour and the unobservable state (absent from Bynoe Harbour,
Darwin Harbour and Shoal Bay).
8. Movements between Darwin Harbour and the unobservable state (absent from Bynoe Harbour,
Darwin Harbour and Shoal Bay).
9. Movements between Shoal Bay and the unobservable state (absent from Bynoe Harbour, Darwin
Harbour and Shoal Bay).
10. Movements from the unobservable state to Bynoe Harbour.
11. Movements from the unobservable state to Darwin Harbour.
12. Movements from the unobservable state to Shoal Bay.
Movements between an observable and the unobservable state (temporary emigration, 7 to 12 above) may
be modelled as:
1. Random, where, for each interval, the probability of staying away after an absence from the local
region is equal to the probability of leaving (i.e., is independent of previous state).
2. Markovian, where, for each interval, the probability of staying away after an absence from the
local region is not equal to the probability of leaving (i.e., depends on previous state).
3. Even flow, where, for each interval, the probability of returning to a site after an absence from the
local region is equal to the probability of leaving the site to the unobservable state.
Movements to and from the unobservable state in the MSCRD are equivalent to the temporary emigration
(gamma’’ and gamma’ parameters, for temporary absence given presence or absence respectively in the
last primary sample) in the CRD. Consequently, for Markovian models, in the MSCRD as in the CRD, if
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the probability of apparent survival varies by primary sample (apparent survival varies over intervals
between primary samples), the last transition probability must be constrained to equal a transition
probability from an earlier interval. For such models we’ve set the last transition probability (primary
sample three to primary sample four) equal to the second last transition probability (primary sample two to
primary sample three).
Similarly, in the MSCRD as in the CRD, the probability of apparent survival for temporarily absent
(unobservable) dolphins must be constrained to be equal to the probability of apparent survival for
dolphins in an observable state. In the present, multisite case, this may be any one of the sites: if there is no
temporary emigration, models with apparent survival constrained to any one of the three sites are
equivalent but may differ when temporary emigration is modelled.
The MSCRD model estimates transitions between but not within primary samples, and requires that a
single site be identified for each individual in each primary sample. We nominated the site in which each
dolphin was last observed in a primary sample as its state for that primary sample.
The probabilities of movement between a pair of sites can only be estimated for intervals between primary
samples for which there was at least one observed movement. We’ve set the transition probabilities
between pairs of sites for intervals for which no movements were observed to zero.
The probability of capture (p) may be specified to vary by any or all of site, primary sample and secondary
sample. After elimination of poorly fitting models, we found no need to model the variation over
secondary samples within primary samples for humpback or bottlenose dolphins but this was necessary for
snubfin dolphins due to their very uneven capture rates over time. Models are reported with p varying by
site and by site by primary sample [p(site) and p(site*time] for humpbacks where there were three
observable states, by site or constant over sites [p(site) and p(constant)] for bottlenose where there were
two observable states, and by primary sample by secondary sample [p(primary*secondary)] for snubfin
where there was only one observable state.
The probability of capture (p) may be distinguished from the probability of recapture (c) following first
capture to indicate a behavioural response to first capture to persistent avoidance of recapture (‘trap-
shyness’) or to persistent seeking of recapture (‘trap-happiness’). While this sort of effect has been
observed in classic trapping studies with small mammals for example, it is considered unlikely in the
present situation where the dolphins are not actually trapped or otherwise interfered with and largely
habituated to the presence of vessels prior to their first capture. We consider only models in which the
probabilities of capture and recapture are equal on all occasions.
The modelling process involves fitting a set of models with alternative parameter structures and comparing
them for fit to data and parsimony. Models were compared with the Akaike Information Criterion
corrected for small sample sizes (AICc, Burnham and Anderson 2002), with smaller values of AICc
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indicating better fitting models, and with AICc weights, which measure the relative likelihoods of the
models in the set. When one model in the set had a clearly lower AICc than all others and attracted the
major proportion of the AICc weight, the parameter estimates from this ‘best’ model are reported; when
several models had similar AICc values and shared the AICc weight model-averaging may be applied
(Buckland et al. 1997) whereby a weighted average of the parameter estimates from several models are
reported.
Program MARK (V6.1; White and Burnham 1999) and the Multistate Closed Robust Design model were
employed for the analysis. The models, their AICc values, AICc weights, likelihoods and numbers of
parameters are reported in the Appendix, Table A3. The parameter estimates from the best fitting model or
model averaged estimates for each species at each site in each primary sample are reported in the
Appendix, Table A4.
Habitat use
A dolphin population may change the relative frequency with which different parts of its habitat are used.
We used a Binary Logistic Mixed Effects model to examine changes in spatial habitat use of dolphins in
the three sites. A 3.2 km x 3.2 km grid was placed over a map of the three sites (Bynoe Harbour, Darwin
Harbour and Shoal Bay) and data on sightings of dolphin groups and sampling intensity in each grid cell in
each secondary sample were modelled to estimate the relative probability of sighting at least one dolphin
in a transect pass of a given length in each grid cell.
The grid cells were grouped into 10 coherent locations in the three sites, with three, five and two locations
in Bynoe Harbour, Darwin Harbour and Shoal Bay respectively: in Bynoe Harbour, 18 cells were grouped
as outer, 15 as middle and 13 as upper; in Darwin Harbour, nine cells were grouped as outer, 10 as East
Arm, 12 as Middle Arm, seven as central and nine as West Arm; and in Shoal Bay, seven cells were
grouped as Gunn Point and 10 as Hope Inlet/Buffalo Creek.
The transects through the region moved slightly between primary samples and the interaction of variable
transect locations and fixed grid cells resulted in 110 cells being sampled in at least one of the four primary
samples: 105 cells were sampled in all four primary samples, one was sampled in three and four were
sampled in only one. A map of the grid cells overlaid on the transect lines in primary sample four is shown
in Figure 5.
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Figure 5 Map of grid cells overlaid on transect lines (primary sample four)
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While the data modelled were the binary response ‘dolphin sighted’ / ‘no dolphin sighted’ of each cell in
each secondary sample, the results from the model are estimated binomial means (proportions or
probabilities of sighting a dolphin) based on the binary data accumulated over secondary samples and
locations. The principal factors assessed were the primary sample and the location. Changes in habitat use
between the primary samples are modelled by the primary sample by location interaction effect which
assesses whether the relative rates of usage of the locations varies significantly between primary samples.
A non-significant interaction effect would indicate a lack of evidence of change in the relative rates of use
of the locations over the primary samples. A significant interaction effect indicate a correlation with
potential inference to impact only if the interaction involved locations closer and further way from
construction activities between primary samples.
The grid cells were sampled with different intensities, measured here in terms of the total length of transect
through a cell in each secondary sample. A single transect through and aligned with the cell would be 3.2
km long but most transects passed through cells at angles and were not aligned with them, and there was
more than one transect segment through some cells.
Primary sample, location and their interaction were initially fitted together with a linear function of
transect length through the cell to adjust for sampling intensity. The model was systematically reduced by
eliminating non-significant effects (p≥0.05) one at a time in order of their p-value sizes.
We report a model for the sightings of any species of dolphin (i.e., all three species pooled). It may be
possible in future to fit a model for humpbacks but there are too few sightings of bottlenose and snubfin to
model these species separately.
The model was fitted to the sightings data with random factors for the cell and the repeated measures on
the cell with a first order autoregressive structure (AR1) fitted to the repeated measures residuals. The
‘Genlinmixed’ procedure in SPSS V21 was employed for the analysis. Genlinmixed uses a pseudo-
likelihood method to obtain estimates with fixed effects tested by F statistics.
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Results
Abundance, Apparent Survival and Movements
Humpback dolphin
Model selection
Model comparison results are reported for a set of sixteen of the best-fitting (smallest AICc) models in
Table A3. The best fitting model had apparent survival varying by site [S(site)], transitions between Bynoe
Harbour and Darwin Harbour and between Darwin Harbour and Bynoe Harbour varying by primary
sample, and no temporary emigration [psi(a_b*t, b_a*t, No TE] and capture probability varying by both
site and primary sample [p(site*time)]. This model attracted 90% of the AICc weight. The second best-
fitting model attracted a further 8% of the AICc weight and differed from the best-fitting model only in
having variation on capture probability by site but not by primary sample. The parameter estimates from
the best-fitting model are reported in Table A4.
Apparent survival
There was no support for variation in apparent survival (the annual probability of both remaining alive and
on site) of humpback dolphins between successive pairs of the four primary samples, but strong support for
differences among the three sites (Table A3). Apparent survival was greater in Darwin Harbour than either
of Bynoe Harbour or Shoal Bay, with estimated apparent survival in Darwin Harbour = 0.93 (95%CI =
0.74:0.98) per annum, in Bynoe Harbour = 0.49 (95%CI = 0.31:0.67) per annum, and in Shoal Bay = 0.49
(95%CI = 0.24:0.75) per annum.
With no reason to expect differences in biological survival between sites, the lower rates of apparent
survival in Bynoe Harbour and Shoal Bay than in Darwin Harbour indicate emigration from those sites,
and with no observed movements between Bynoe Harbour and Shoal Bay, it seems likely that the
emigration from Bynoe Harbour is to the west and from Shoal Bay to the east.
Movements
No movements were observed between Bynoe Harbour or Darwin Harbour and Shoal Bay in either
direction. Movements were observed between Bynoe Harbour and Darwin Harbour in both directions
between each successive pair of primary samples. A total of fifteen such movements were observed with
most occurring between Bynoe Harbour and Darwin Harbour between primary samples two and three
(five), and between Darwin Harbour and Bynoe Harbour between primary samples three and four (five).
There was significant variation in humpback dolphin movement rates between the four primary samples.
The estimated rates of movement from Bynoe Harbour to Darwin Harbour between primary samples one
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and two, two and three, and three and four were 6% (95%CI = 1:33%), 38% (95%CI = 17:64%) and 13%
(95%CI = 2:53%) respectively. The estimated rates of movement in the opposite direction, from Darwin
Harbour to Bynoe Harbour, between successive primary samples were 10% (95%CI = 2:32%), 4% (95%CI
= 1:21%) and 20% (95%CI = 9:38%) respectively.
These rates indicate movement of occasionally substantial proportions of the population between Darwin
Harbour and Bynoe Harbour in either direction, while no movements were observed between Shoal Bay
and either of the other two sites. Although the population was relatively small in Shoal Bay (see below),
limiting the probability of observing movements to or from this site, these results suggest that the Shoal
Bay population may be relatively independent of the more closely related Bynoe and Darwin populations.
Abundance
The estimated size of the Bynoe Harbour humpback population in primary samples one, two, three and
four was 29 (95%CI=26:41), 29 (95%CI=25:42), 20 (95%CI=14:41), and 29 (95%CI=24-44) respectively.
In Darwin Harbour there were 39 (95%CI=35:51), 37 (95%CI=33:48), 41 (95%CI=36:53), and 37
(95%CI=35:44) respectively, while in Shoal Bay they were 14 (95%CI=12:28), 13 (95%CI=12:22), 21
(95%CI=17:34), and 17 (95%CI=10:42) respectively.
These estimates are quite stable over primary samples, with the total for all three sites varying only slightly
with 82, 79, 82 and 83 over primary samples. The reduction in the Bynoe Harbour estimate between
primary samples two and three corresponds with the larger rate of movement from Bynoe Harbour and
Darwin Harbour than from Darwin Harbour and Bynoe Harbour in the interval between primary samples
two and three. That the Darwin Harbour population increased slightly from primary samples two and three
is consistent with this.
While the Shoal Bay population also increased between primary samples two and three, there were no
observed movements from either Bynoe Harbour or Darwin Harbour to account for it. While some such
movement may have occurred, the increase may also have been due to recruitment into Shoal Bay.
Bottlenose dolphin
Very few bottlenose dolphins were ever observed in Bynoe Harbour, with four observed there in single
secondary samples in each of primary samples one and three (Table A2). There were too few data to derive
estimates for Bynoe Harbour and barely sufficient to derive estimates for Shoal Bay. The data from these
two sites were pooled and Bynoe Harbour and Shoal Bay modelled as a single site (BH&SB).
No movements were observed between Bynoe Harbour or Shoal Bay and Darwin Harbour within any
primary sample.
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Model selection
Model comparison results from a set of eight better fitting (lower AICc; except for models without
temporary emigration which were included for comparison) models are reported in Table A3. All models
have capture probability varying by both site and primary sample [p(site*time)], and all estimate only the
transitions between either Bynoe Harbour or Shoal Bay and Darwin Harbour between primary samples two
and three, and between Darwin Harbour and either Bynoe Harbour or Shoal Bay between primary samples
three and four [psi(ac_b2, b_ac3,…)]. The models vary in whether they estimate temporary emigration as
time-varying and random [psi(…, random)], time-varying and Markovian [psi(…, Markov)], constant and
random [psi(…, constant random)], or as having no temporary emigration [psi(…, No TE)]. The models
also vary in whether they estimate apparent survival as constant over both sites and primary samples
[S(constant)] or as varying by site [S(site)].
The best fitting model had a very simple structure with apparent survival constant over both sites and
primary samples and constant random temporary emigration. This model attracted 97% of the AICc weight
in the set. Models with no temporary emigration fitted very poorly. The parameter estimates from the best-
fitting model are reported in Table A4.
Apparent survival
There was no evidence of apparent survival of bottlenose dolphins differing between each of the four
primary samples or between the two sites (Bynoe and Shoal Bay combined and Darwin Harbour) (Table
A4). The estimated apparent survival was 0.81 (95%CI=0.63:0.91) per annum in both sites over all
intervals between primary samples. This is likely to be lower than the rate of biological survival and
indicates some degree of emigration from the local region.
Movements
Three individuals were observed to have moved between either Bynoe Harbour or Shoal Bay and Darwin
Harbour between primary samples two and three, and one individual was observed to have moved from
Darwin Harbour and either Bynoe Harbour or Shoal Bay between primary samples three and four.
There was significant variation in bottlenose dolphin movement rates in the intervals between the four
primary samples. Thirty nine percent (95%CI=13%:73%) of the population present in either Bynoe
Harbour or Shoal Bay in primary sample two were estimated to have moved to Darwin Harbour before
primary sample three, and eleven percent (95%CI=1%:52%) of the population in Darwin Harbour in
primary sample three were estimated to have moved to either Bynoe Harbour or Shoal Bay before primary
sample four.
Temporary emigration from either Bynoe Harbour or Shoal Bay was estimated at zero, while temporary
emigration from Darwin Harbour was estimated at 6% (95%CI=1%:25%). While the estimated rate of
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temporary emigration was relatively small and the confidence interval was wide, there was strong evidence
that it was non-zero from the very poor fit of models in which it was assumed to be zero.
Abundance
The estimated size of the Bynoe Harbour/Shoal Bay population in primary samples one, two, three and
four was 5 (95%CI=5:5), 10 (95%CI=9:19), 6 (95%CI=5:16), and 7 (95%CI=5:21) respectively, while in
Darwin Harbour there were 19 (95%CI=19:25), 15 (95%CI=14:22), 25 (95%CI=20:40), and 15
(95%CI=15:15).
These are small populations but the estimates are reasonably stable over primary samples. There were
slightly more in Bynoe Harbour and Shoal Bay in primary sample two and in Darwin Harbour in primary
sample three. The total for all three sites varied only slightly with 24, 25, 31 and 22 over primary samples.
It was possible to derive these estimates only because of the relatively high capture probability for this
species.
Snubfin dolphin
There were too few data to obtain separate estimates for Darwin Harbour or Shoal Bay, and while there
were more captures in Bynoe Harbour, the rates of capture and recapture there were highly irregular. Only
four snubfin were observed at more than one site over primary samples one, two, three and four. The data
from all three sites were combined and models fitted for the whole local region.
Model selection
Model comparison results from a set of eight better fitting (lower AICc) models are reported in Table A3.
All models have capture probability varying by both primary sample and secondary sample
[p(primary*secondary)].
The best fitting (lowest AICc) model had apparent survival constant over primary samples and constant
random temporary emigration (Table A3). This model attracted 73% of the AICc weight. A model with
constant Markovian temporary emigration attracted a further 15% of the AICc weight. There is good
evidence of temporary emigration with the best-fitting model with no temporary emigration having an
AICc of 5.9 greater than the best-fitting model. We report estimates from the best-fitting random temporary
emigration model and comment on the difference in the temporary emigration estimates between this and
the Markovian temporary emigration model. The estimates from the best fitting model are reported in
Table A4.
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Apparent survival
There was no evidence of variation in apparent survival of snubfin dolphins over the intervals between
successive primary samples. The estimated apparent survival was 0.94 (95%CI=0.00:1.00) per annum with
a very wide confidence interval indicating that this estimate was based on very little information.
Movements
The only movements in this model are movements to and from the unobservable state, or temporary
emigration estimates. The temporary emigration estimate from the best-fitting, random temporary
emigration model was 0.63 (95%CI=0.44:0.79). This model assumes that, for each interval between
successive primary samples, the probability of staying away after an absence is the same as the probability
of leaving. The temporary emigration estimate from the Markovian temporary emigration model indicates
that the probability of staying away after an absence was very slightly lower than the probability of
leaving. There is clearly substantial temporary emigration from the local region for this species, suggesting
that the sample area may be only a small part of the home range of the population that uses it. Only about
37 percent of that population are present in the sample area during a primary sample.
Abundance
The estimated size of the local regional population in primary samples one, two, three and four was 164
(95%CI=65:555), 18 (95%CI=16:28), 29 (95%CI=24:44), and 17 (95%CI=17:17) respectively. The very
large estimate for primary sample one appears to be anomalous with only one of thirty individuals
recaptured. Overall, and discounting the estimate for primary sample one, it appears that while the
numbers vary between primary samples, 30 (the number captured in Bynoe Harbour in primary sample
one) or more snubfin dolphins may use the local region during a primary sample.
Summary of abundance estimates
The abundance estimates at the three sites (Bynoe Harbour, Darwin Harbour, Shoal Bay) for humpback
dolphins, at two sites (Bynoe Harbour and Shoal Bay, Darwin Harbour) for bottlenose dolphins and in the
local region (Bynoe Harbour, Darwin Harbour and Shoal Bay) for snubfin dolphins by primary sample are
summarised in Table 1.
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Table 1 Summary of abundance estimates for the three species over four primary samples
Species Site Primary sample Estimate SE L95%CI U95%CI
Humpback Bynoe Harbour 1 29 3.16 26.27 40.56
2 29 3.78 25.03 41.67
3 20 6.09 13.52 41.02
4 29 4.53 24.37 44.34
Darwin Harbour 1 39 3.73 35.16 51.45
2 37 3.34 33.03 47.56
3 41 3.99 36.25 53.19
4 37 1.72 35.32 43.85
Shoal Bay 1 14 3.31 11.65 27.92
2 13 1.82 12.19 21.86
3 21 3.73 17.33 34.44
4 17 6.76 10.30 41.45
Bottlenose
Tursiops Bynoe Harbour 1 5 0.00 5.00 5.00
and Shoal Bay 2 10 1.77 9.10 19.26
3 6 1.90 5.10 16.10
4 7 2.94 5.29 21.06
Darwin Harbour 1 19 0.92 19.00 25.12
2 15 1.33 14.05 22.14
3 25 4.55 20.42 40.47
4 15 0.00 15.00 15.00
Snubfin Bynoe Harbour, 1 1641 105.58 64.66 554.55
Darwin Harbour 2 18 2.14 16.23 27.55
and Shoal Bay 3 29 4.49 23.92 44.11
4 17 0.00 17.00 17.00
Notes: 1 Estimate appears anomalous and is based on a single recapture
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Habitat use
A map of the sighting positions of dolphin groups over the four primary samples is shown in Figure 6.
Figure 6 Map of sighting positions of dolphin groups over the four primary samples
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Results of the tests of fixed effects for a series of 3 Binary Logistic models are reported in Table 2.
Table 2 Tests of fixed effects in 3 models
Model Effect F df1 df2 p
1 transect length 104.294 1 3802 0.000
primary 1.656 3 3802 0.174
location 2.862 9 3802 0.002
primary * location 1.362 27 3802 0.101
2 transect length 107.259 1 3829 0.000
primary 1.615 3 3829 0.184
location 2.489 9 3829 0.008
3 transect length 107.041 1 3832 0.000
location 2.481 9 3832 0.008
Model 1. The primary sample by location interaction effect was non-significant and was removed to build
model 2.
Model 2. The primary sample effect was non-significant removed to build model 3.
Model 3. Model 3 fitted only the main effects for transect length and location. Both the transect length
(sample intensity) covariate and location effects were clearly significant.
Although the primary by location effect was not significant (p=0.101), the estimated mean probability of
sighting a dolphin group from a secondary sample with the mean transect length of 3.78 km is plotted by
location by primary sample in Figure 7 for descriptive purposes. The estimated mean probability of
sighting a dolphin group from a secondary sample with the mean transect length of 3.78 km is plotted with
95% confidence interval by location in Figure 8.
A map of the region with grid cells colour-coded to show relative rates of habitat usage in the locations is
shown in Figure 9.
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Figure 7 Estimated relative probability of sighting a dolphin group in a secondary sample of transect length
= 3.78 km with 95%CI by location by primary sample.
Figure 8 Estimated relative probability of sighting a dolphin group in a secondary sample of transect length
= 3.78 km by location with 95% confidence intervals.
.000
.020
.040
.060
.080
.100
.120
.140
.160
.180
.200
BH outer BH
middle
BH
upper
DH
outer
DH East
Arm
DH
Middle
Arm
DH
central
DH
West
Arm
SB Gunn
Point
SB Hope
Inlet /
Buffalo
Creek
P1
P2
P3
P4
.000
.050
.100
.150
.200
.250
BH outer BH
middle
BH upper DH outer DH East
Arm
DH
Middle
Arm
DH
central
DH West
Arm
SB Gunn
Point
SB Hope
Inlet /
Buffalo
Creek
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Figure 9 Map of Darwin region showing relative rates of habitat use over locations
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With 45 pairwise tests between locations, there was no significant difference between any pair of locations
when sequential Bonferroni adjustment was applied. This is a very conservative criterion with many tests
and the closest pairwise difference was a greater probability of sighting in Gunn Point than Darwin central
(p = 0.232 Bonferroni adjusted).
It may be noted however, that probabilities of sighting were relatively high overall in Shoal Bay (Gunn
Point and Hope Inlet/Buffalo Creek) and in the outer Harbours (Bynoe outer, Darwin outer and Gunn
Point), and within Darwin Harbour, in West Arm.
Summary of habitat use
The estimated mean probabilities of sighting in the locations had reasonable precision with coefficients of
variation (CV = standard error/estimate, a measure of precision) ranging from 14% (Bynoe outer) to 20%
(Darwin central) (mean CV = 17% ±1.9%).
We have provided estimates of the relative rates of use of the locations and information about the natural
variation in these estimates over primary samples. It’s notable that the outer harbour areas are relatively
well used and that this is consistent with and complementary to evidence from the capture-recapture
models of movement into and out of the Darwin region: i.e., there is evidently a flow of dolphins not only
across the outer Harbour areas in the Darwin region but also to and from sites west of Bynoe Harbour and
east of Shoal Bay.
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Conclusion The major constraint on obtaining estimates of abundance, movement and apparent survival was the small
sizes of the populations of bottlenose and snubfin dolphins, with the snubfin appearing to have irregular
patterns of visitation to the sampling areas.
Where too few data were available to model for each site separately, estimates were obtained by pooling
the data over sites. Adequate data were available to obtain estimates of abundance for humpback dolphins
in all three sites, to estimate their rates of movement between Bynoe Harbour and Darwin Harbour,
temporary emigration from the local region, and their apparent survival at all three sites.
The data for Bynoe Harbour and Shoal Bay were pooled for bottlenose dolphins and estimates were
obtained of abundance, apparent survival for Bynoe Harbour/Shoal Bay and Darwin Harbour, temporary
emigration from the local region, and rates of movement between the two sites.
The data from all three sites were pooled for snubfin dolphins and estimates were obtained of abundance,
temporary emigration and apparent survival for the whole local region.
While the habitat use model was fitted only for sighting of dolphin groups independently of the species
(i.e., all three species combined), it should be possible in future to fit the model to the data on sightings of
the humpback dolphin. We found no significant change in the relative rates of use of the defined locations
between primary samples and note that, over all primary samples, the outer Harbour areas (outer Bynoe
Harbour, outer Darwin Harbour and Shoal Bay, especially Gunn Point) are relatively well used and that
this is consistent with and complementary to evidence from the capture-recapture models of movement
into and out of the Darwin region: i.e., there is evidently a flow of dolphins not only across the outer
Harbour areas in the Darwin region but also to and from sites west of Bynoe Harbour and east of Shoal
Bay.
Overall, although it was necessary to pool data over some sites for bottlenose and snubfin dolphins, the
sampling design has generated data of a quantity and structure that allows the models to generate
reasonably precise estimates of abundance, movements and other demographic parameters, and of the
relative frequency of use of parts of the sample area.
While the abundances of the three species are small, they have remained stable over the duration of the
study so far, and the relative rates of use of different parts of the habitat have not changed.
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Appendix
Table A1 Dates of secondary samples by site for each primary sample Page 1
Table A2 Summary of captures by species, site and primary sample Pages 2-3
Table A3 Model comparison results for models on each species Pages 4-6
Table A4 Parameter estimates from selected models for each species Pages 7-12
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Table A1 Dates of secondary samples by site for each primary sample
Primary Secondary sample
sample Site 1 2 3 4 5 6 7 8 9
1 Darwin 02.11.2011 03.11.2011 04.11.2011 09.11.2011 10.11.2011 11.11.2011 16.11.2011 17.11.2011 18.11.2011
1 Bynoe 29.10.2011 30.10.2011 31.10.2011 05.11.2011 06.11.2011 07.11.2011 12.11.2011 13.11.2011 14.11.2011
1 Bynoe
15.11.2011
1 Shoal Bay 20.10.2011 21.10.2011 22.10.2011 05.11.2011 06.11.2011 07.11.2011 12.11.2011 13.11.2011 14.11.2011
1 Shoal Bay
08.11.2011
2 Darwin 26.03.2012 27.03.2012 28.03.2012 02.04.2012 03.04.2012 04.04.2012 09.04.2012 10.04.2012 11.04.2012
2 Darwin
12.04.2012
2 Bynoe 29.03.2012 30.03.2012 31.03.2012 05.04.2012 06.04.2012 07.04.2012 13.04.2012 14.04.2012 15.04.2012
2 Shoal Bay 29.03.2012 30.03.2012 31.03.2012 05.04.2012 06.04.2012 07.04.2013 12.04.2012 13.04.2012 14.04.2012
3 Darwin 08.10.2012 09.10.2012 10.10.2012 15.10.2012 16.10.2012 17.10.2012 22.10.2012 23.10.2012 24.10.2012
3 Bynoe 11.10.2012 12.10.2012 13.10.2012 18.10.2012 19.10.2012 20.10.2012 25.10.2012 26.10.2012 27.10.2012
3 Shoal Bay 11.10.2012 12.10.2012 13.10.2012 18.10.2012 19.10.2012 20.10.2013 25.10.2012 26.10.2012 27.10.2012
3 Shoal Bay
19.10.2012
4 Darwin 13.03.2013 14.03.2013 15.03.2013 20.03.2013 21.03.2013 22.03.2013 27.03.2013 28.03.2013 29.03.2013
4 Bynoe 16.03.2013 17.03.2013 18.03.2013 23.03.2013 24.03.2013 25.03.2013 31.03.2013 1.04.2013 2.04.2013
4 Shoal Bay 16.03.2013 17.03.2013 18.03.2013 23.03.2013 24.03.2013 25.03.2013 31.03.2013 1.04.2013 2.04.2013
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Table A2 Summary of captures by species, site and primary sample
Species Site Primary
sample
Secondary
samples1 Individuals Max.Caps.
2 Captures
Snubfin Bynoe 1 5 25 2 26
Snubfin Bynoe 2 3 9 2 12
Snubfin Bynoe 3 4 15 3 25
Snubfin Bynoe 4 1 9 1 9
Snubfin Darwin 1 1 5 1 5
Snubfin Darwin 2 3 7 3 14
Snubfin Darwin 3 0 0 0 0
Snubfin Darwin 4 4 8 3 20
Snubfin Shoal Bay 1 0 0 0 0
Snubfin Shoal Bay 2 0 0 0 0
Snubfin Shoal Bay 3 1 7 1 7
Snubfin Shoal Bay 4 0 0 0 0
Snubfin All sites 1 5 30 2 31
Snubfin All sites 2 4 16 3 26
Snubfin All sites 3 5 22 3 32
Snubfin All sites 4 4 17 3 29
Humpback Bynoe 1 9 26 4 49
Humpback Bynoe 2 8 23 4 37
Humpback Bynoe 3 5 12 2 15
Humpback Bynoe 4 9 23 3 41
Humpback Darwin 1 9 33 4 62
Humpback Darwin 2 9 34 4 66
Humpback Darwin 3 9 34 4 63
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Humpback Darwin 4 9 36 6 90
Humpback Shoal Bay 1 5 11 3 18
Humpback Shoal Bay 2 6 12 3 25
Humpback Shoal Bay 3 8 16 3 25
Humpback Shoal Bay 4 5 8 2 9
Humpback All sites 1 9 69 4 129
Humpback All sites 2 9 66 4 128
Humpback All sites 3 9 60 4 103
Humpback All sites 4 9 65 6 137
Bottlenose Bynoe 1 1 4 1 4
Bottlenose Bynoe 2 0 0 0 0
Bottlenose Bynoe 3 1 4 1 4
Bottlenose Bynoe 4 0 0 0 0
Bottlenose Darwin 1 5 18 4 45
Bottlenose Darwin 2 4 14 4 29
Bottlenose Darwin 3 4 19 2 21
Bottlenose Darwin 4 5 15 4 36
Bottlenose Shoal Bay 1 3 5 3 10
Bottlenose Shoal Bay 2 3 10 3 16
Bottlenose Shoal Bay 3 2 5 2 7
Bottlenose Shoal Bay 4 2 5 2 7
Bottlenose All sites 1 6 23 4 59
Bottlenose All sites 2 5 23 5 45
Bottlenose All sites 3 6 23 2 32
Bottlenose All sites 4 6 20 4 43 1
Number of secondary samples with non-zero captures
2 Maximum number of captures per individual
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Abundance, movements and habitat use of coastal dolphins in the Darwin region
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Table A3 Model comparison results for models on each species Notes:
1. S = probability of apparent survival, psi = probability of transition including temporary emigration, p = probability of capture, c= probability of recapture, *t
indicates variation over primary samples.
2. a indicates Bynoe Harbour (BH), b indicates Darwin Harbour (DH), c indicates Shoal Bay (SB), ab indicates Bynoe Harbour & Shoal Bay, u indicates
unobservable (temporarily absent from region), a_b indicates transition from a to b.
3. S(…, u=b) indicates apparent survival for temporarily absent dolphins set equal to Darwin Harbour.
AICc Model Number of
Species Sites Model AICc ∆AICc Weight Likelihood Parameters
Humpback BH,DH,SB {S(site, u=b), 1625.516 0.000 0.902 1.000 33
psi(a_b*t, b_a*t, No TA),
p(site*time)}
Humpback BH,DH,SB {S(site, u=b), 1630.306 4.790 0.082 0.091 24
psi(a_b*t, b_a*t, No TA),
p(site)}
Humpback BH,DH,SB {S(site*time, u=b), 1634.189 8.673 0.012 0.013 39
psi(a_b*t, b_a*t, No TA),
p(site*time)}
Humpback BH,DH,SB {S(site*time, u=b), 1638.279 12.763 0.002 0.002 30
psi(a_b*t, b_a*t, No TA),
p(site)}
Humpback BH,DH,SB {S(site, u=b), 1640.496 14.980 0.001 0.001 42
psi(a_b*t, b_a*t, a_u*t=u_a*t, b_u*t=u_b*t, c_u*t=u_c*t, a_c=0, b_c=0 - even flow),
p(site*time)}
Humpback BH,DH,SB {S(site, u=c), 1640.509 14.993 0.001 0.001 42
INPEX Doc. Number L384-AH-REP-10009_0
Abundance, movements and habitat use of coastal dolphins in the Darwin region
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psi(a_b*t, b_a*t, a_u*t=u_a*t, b_u*t=u_b*t, c_u*t=u_c*t, a_c=0, b_c=0 - even flow),
p(site*time)}
Humpback BH,DH,SB {S(site, u=a), 1642.350 16.834 0.000 0.000 33
psi(a_b*t, b_a*t, a_u*t=u_a*t, b_u*t=u_b*t, c_u*t=u_c*t, a_c=0, b_c=0 - even flow),
p(site)}
Humpback BH,DH,SB {S(site, u=b), 1642.384 16.868 0.000 0.000 33
psi(a_b*t, b_a*t ,a_u*t=u_a*t, b_u*t=u_b*t, c_u*t=u_c*t, a_c=0, b_c=0 -even flow),
p(site)}
Humpback BH,DH,SB {S(site, u=c), 1642.608 17.092 0.000 0.000 33
psi(a_b*t, b_a*t, a_u*t=u_a*t ,b_u*t=u_b*t, c_u*t=u_c*t, a_c=0, b_c=0 - even flow),
p(site)}
Humpback BH,DH,SB {S(site, u=a), 1642.674 17.158 0.000 0.000 42
psi(a_b*t, b_a*t, a_u*t=u_a*t, b_u*t=u_b*t, c_u*t=u_c*t, a_c=0, b_c=0 - even flow),
p(site*time)}
Humpback BH,DH,SB {S(site, u=b), 1643.496 17.980 0.000 0.000 42
psi(a_b*t, b_a*t, a_u*t=(1-u_a*t), b_u*t=(1-u_b*t), c_u*t=(1-u_c*t), a_c=0, b_c=0 - random),
p(site*time)}
Humpback BH,DH,SB {S(site, u=b), 1643.745 18.228 0.000 0.000 33
psi(a_b*t, b_a*t, a_u*t=(1-u_a*t), b_u*t=(1-u_b*t), c_u*t=(1-u_c*t), a_c=0, b_c=0 - random),
p(site)}
Humpback BH,DH,SB {S(site, u=c), 1644.908 19.392 0.000 0.000 42
psi(a_b*t, b_a*t, a_u*t=(1-u_a*t), b_u*t=(1-u_b*t), c_u*t=(1-u_c*t), a_c=0, b_c=0 - random),
p(site*time)}
Humpback BH,DH,SB {S(site, u=a), 1645.692 20.176 0.000 0.000 33
psi(a_b*t, b_a*t, a_u*t=(1-u_a*t), b_u*t=(1-u_b*t), c_u*t=(1-u_c*t), a_c=0, b_c=0 - random),
p(site)}
Humpback BH,DH,SB {S(site, u=c), 1647.492 21.976 0.000 0.000 33
psi(a_b*t, b_a*t, a_u*t=(1-u_a*t), b_u*t=(1-u_b*t), c_u*t=(1-u_c*t), a_c=0, b_c=0 - random),
INPEX Doc. Number L384-AH-REP-10009_0
Abundance, movements and habitat use of coastal dolphins in the Darwin region
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p(site)}
Humpback BH,DH,SB {S(site, u=a), 1650.865 25.348 0.000 0.000 42
psi(a_b*t, b_a*t, a_u*t=(1-u_a*t), b_u*t=(1-u_b*t), c_u*t=(1-u_c*t), a_c=0, b_c=0 - random),
p(site*time)}
Bottlenose BH&SB,DH {S(constant), psi(ac_b2, b_ac3, constant random), p(site*time)} 1922.371 0.000 0.970 1.000 21
Bottlenose BH&SB,DH {S(constant), psi(ac_b2, b_ac3, random), p(site*time)} 1931.471 9.100 0.010 0.011 25
Bottlenose BH&SB,DH {S(site, u=b), psi(ac_b2, b_ac3, random), p(site*time)} 1931.793 9.422 0.009 0.009 26
Bottlenose BH&SB,DH {S(site, u=ac), psi(ac_b2, b_ac3, random), p(site*time)} 1931.940 9.569 0.008 0.008 26
Bottlenose BH&SB,DH {S(site, u=b), psi(ac_b2, b_ac3, Markov), p(site*time)} 1934.387 12.016 0.002 0.003 27
Bottlenose BH&SB,DH {S(site, u=ac), psi(ac_b2, b_ac3, Markov), p(site*time)} 1937.154 14.783 0.001 0.001 28
Bottlenose BH&SB,DH {S(site, u=b), psi(ac_b2, b_ac3, No TE), p(site*time)} 3305.358 1382.987 0.000 0.000 20
Bottlenose BH&SB,DH {S(site, u=ac), psi(ac_b2, b_ac3, No TE), p(site*time)} 3305.358 1382.987 0.000 0.000 20
Snubfin BH&DH&SB {S(constant), psi(constant random), p(primary*secondary)} 142.562 0.000 0.728 1.000 24
Snubfin BH&DH&SB {S(constant), psi(constant Markov), p(primary*secondary)} 145.717 3.155 0.150 0.207 25
Snubfin BH&DH&SB {S(primary), psi(No TE), p(primary*secondary)} 148.463 5.901 0.038 0.052 23
Snubfin BH&DH&SB {S(constant), psi(primary random), p(primary*secondary)} 148.631 6.069 0.035 0.048 26
Snubfin BH&DH&SB {S(constant), psi(primary Markov), p(primary*secondary)} 148.915 6.353 0.030 0.042 26
Snubfin BH&DH&SB {S(primary), psi(primary Markov), p(primary*secondary)} 150.456 7.894 0.014 0.019 28
Snubfin BH&DH&SB {S(primary), psi(primary random), p(primary*secondary)} 152.741 10.179 0.004 0.006 28
Snubfin BH&DH&SB {S(constant), psi(No TE), p(primary*secondary)} 169.214 26.652 0.000 0.000 23
INPEX Doc. Number L384-AH-REP-10009_0
Abundance, movements and habitat use of coastal dolphins in the Darwin region
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Table A4 Parameter estimates from selected models for each species
Notes: Notation for the model is described above Table A3
Species Parameter Site Primary sample Secondary Estimate SE LCI UCI
Humpback Model: {S(site, u=b), psi(a_b*t, b_a*t, No TA), p(site*time)}
Apparent survival BH 1 to 2 = 2 to 3 = 3 to 4 0.49 0.09 0.31 0.67
Apparent survival DH 2 to 2 = 2 to 3 = 3 to 4 0.93 0.05 0.74 0.98
Apparent survival SB 3 to 2 = 2 to 3 = 3 to 4 0.49 0.14 0.24 0.75
Transition BH to DH 1 to 2 0.06 0.06 0.01 0.33
Transition BH to DH 2 to 3 0.38 0.13 0.17 0.64
Transition BH to DH 3 to 4 0.13 0.11 0.02 0.53
Transition DH to BH 1 to 2 0.10 0.07 0.02 0.32
Transition DH to BH 2 to 3 0.04 0.03 0.01 0.21
Transition DH to BH 3 to 4 0.20 0.07 0.09 0.38
Capture BH 1 0.18 0.03 0.13 0.25
Capture BH 2 0.15 0.03 0.11 0.21
Capture BH 3 0.08 0.03 0.04 0.15
Capture BH 4 0.14 0.03 0.09 0.20
Capture DH 1 0.18 0.03 0.13 0.24
Capture DH 2 0.18 0.02 0.14 0.23
Capture DH 3 0.16 0.02 0.13 0.20
Capture DH 4 0.27 0.03 0.22 0.33
Capture SB 1 0.14 0.04 0.07 0.25
Capture SB 2 0.20 0.04 0.13 0.29
Capture SB 3 0.14 0.03 0.09 0.22
Capture SB 4 0.07 0.03 0.03 0.14
Abundance BH 1 29 3.16 26.27 40.56
Abundance BH 2 29 3.78 25.03 41.67
Abundance BH 3 20 6.09 13.52 41.02
Abundance BH 4 29 4.53 24.37 44.34
INPEX Doc. Number L384-AH-REP-10009_0
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Abundance DH 1 39 3.73 35.16 51.45
Abundance DH 2 37 3.34 33.03 47.56
Abundance DH 3 41 3.99 36.25 53.19
Abundance DH 4 37 1.72 35.32 43.85
Abundance SB 1 14 3.31 11.65 27.92
Abundance SB 2 13 1.82 12.19 21.86
Abundance SB 3 21 3.73 17.33 34.44
Abundance SB 4 17 6.76 10.30 41.45
Bottlenose Model: {S(constant), psi(ac_b2, b_ac3, constant random), p(site*time)}
Apparent survival BHSB=DH All 0.81 0.07 0.63 0.91
Transition BHSB to DH 2 to 3 0.39 0.18 0.13 0.73
Transition (Random TE) BHSB to Absent 1 to 2 = 2 to 3 = 3 to 4 0.00 0.00 0.00 0.00
Transition DH to BHSB 3 to 4 0.11 0.11 0.01 0.52
Transition (Random TE) DH to Absent 1 to 2 = 2 to 3 = 3 to 4 0.06 0.05 0.01 0.25
Capture BHSB 1 0.29 0.08 0.16 0.45
Capture BHSB 2 0.32 0.08 0.18 0.50
Capture BHSB 3 0.21 0.07 0.10 0.39
Capture BHSB 4 0.16 0.07 0.06 0.35
Capture DH 1 0.39 0.05 0.30 0.48
Capture DH 2 0.40 0.06 0.28 0.53
Capture DH 3 0.18 0.04 0.12 0.26
Capture DH 4 0.39 0.05 0.30 0.50
Abundance BHSB 1 5 0.00 5.00 5.00
Abundance BHSB 2 10 1.77 9.10 19.26
Abundance BHSB 3 6 1.90 5.10 16.10
Abundance BHSB 4 7 2.94 5.29 21.06
Abundance DH 1 19 0.92 19.00 25.12
Abundance DH 2 15 1.33 14.05 22.14
Abundance DH 3 25 4.55 20.42 40.47
Abundance DH 4 15 0.00 15.00 15.00
INPEX Doc. Number L384-AH-REP-10009_0
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Snubfin Model: {S(constant), psi(constant random TE), p(primary*secondary)}
Apparent survival BH&DH&SB 1 to 2 = 2 to 3 = 3 to 4 0.94 0.22 0.00 1.00
Transition (Random TE) 1 to 2 = 2 to 3 = 3 to 4 0.63 0.09 0.44 0.79
Capture 1 2 0.09 0.06 0.02 0.31
Capture 1 3 0.02 0.02 0.00 0.11
Capture 1 5 0.01 0.01 0.00 0.06
Capture 1 7 0.01 0.01 0.00 0.06
Capture 1 9 0.07 0.05 0.02 0.26
Capture 2 2 0.40 0.13 0.19 0.65
Capture 2 4 0.34 0.12 0.15 0.59
Capture 2 6 0.06 0.06 0.01 0.31
Capture 2 8 0.68 0.14 0.39 0.88
Capture 3 3 0.04 0.04 0.00 0.22
Capture 3 5 0.04 0.04 0.00 0.22
Capture 3 7 0.39 0.11 0.21 0.61
Capture 3 8 0.25 0.09 0.12 0.46
Capture 3 9 0.43 0.11 0.24 0.64
Capture 4 1 0.29 0.11 0.13 0.54
Capture 4 2 0.94 0.06 0.67 0.99
Capture 4 5 0.06 0.06 0.01 0.32
Capture 4 8 0.41 0.12 0.21 0.65
Abundance 1 164 105.58 64.66 554.55
Abundance 2 18 2.14 16.23 27.55
Abundance 3 29 4.49 23.92 44.11
Abundance 4 17 0.00 17.00 17.00
INPEX Doc. Number L384-AH-REP-10009_0