rajan amin, kevin davey, tim wacher · what does it do? phase 1 •targeted at processing data from...
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ZSL CAMERA TRAP ANALYSIS PACKAGE
RAJAN AMIN, KEVIN DAVEY, TIM WACHER
ZSL CAMERA TRAPPING
• BIODIVERSITY SURVEY AND MONITORING
• RESEARCH IN ANALYTICAL METHODS
• TRAINING IN FIELD IMPLEMENTATION
• ANALYTICAL PROCESSING TOOLS
• RANGE OF SPECIES, HABITATS & CONSERVATION OBJECTIVES
• ALGERIA
• KENYA
• TANZANIA
• LIBERIA
• GUINEA
• NIGER
• SAUDI ARABIA
ZSL CAMERA TRAPPING
• MONGOLIA
• NEPAL
• THAILAND
• INDONESIA
• RUSSIA
• Et al.
KENYA: ADERS’ DUIKER
COASTAL FOREST
• Critically endangered species • Poor knowledge of wildlife in the area
MONGOLIA: GOBI BEAR
DESERT • Highly threatened flagship species • Very little known about it
NEPAL: TIGER
• National level surveys, highly threatened flagship species
GRASSLAND AND FORESTS
SAUDI ARABIA: ARABIAN GAZELLE
• Highly threatened species • Monitoring reintroduction efforts
ZSL CAMERA TRAP ANALYSIS PACKAGE
OCCUPANCY
ACTIVITY
SPECIES RICHNESS
TRAPPING RATE & LOCATION
Why is an analysis tool needed?
WA Large-spotted Genet
0
1
2
3
4
5
6
7
0 2 4 6 8 10 12 14 16 18 20 22
Hr.
Even
ts
Bourlon's Genet
0
1
2
3
4
5
6
7
8
0 2 4 6 8 10 12 14 16 18 20 22
Hr.
Even
ts
0
5
10
15
20
25
30
0 10 20 30 40 50 60
Days of Camera trapping
N S
pe
cie
s
Observed Discovery Rate
Minus 1 sd
Plus 1 sd
Diversity estimate (Jacknife 1)
MANUAL PROCESSING: MULTI-SPECIES STUDIES
45 cameras x 150days x c.30sp
MANUAL PROCESSING: MULTI-SPECIES STUDIES
80 Camera sites x 100 days x c.30sp
Amin, R., Andanje, S., Ogwonka, B., Ali A. H., Bowkett, A., Omar, M. & Wacher, T. 2014 The northern coast forests of Kenya are nationally and globally important for the conservation of Aders’ duiker Cephalophus adersi and other antelope species. Biodivers. Conserv. DOI 10.1007/s10531-014-0842-z
CAMERA TRAP ANALYSIS PACKAGE
• A DATA MANAGEMENT AND ANALYSIS SYSTEM FOR CAMERA TRAP ARRAYS
Starting Point: Camera arrays: Guinea 2008 & Kenya 2010
Why is it needed?
• Camera arrays – Create very large data sets
• Multiple species
• Multiple data manipulations required
• Lack of central data management system
• High potential for errors in manual data handling
• Files tend to proliferate during manual analysis
• Lack of standardisation in manual analysis
• Very slow, loss of data, incomplete analyses/reports
• No equivalent package available (when project started..)
What does it do? Phase 1
• Targeted at processing data from camera arrays
• Manages multiple surveys within a single database
• Provides standardised data model for comparison and monitoring biodiversity over the longer term
• Country species templates
• Enables data filtering, image checking, processing and correction
• All tables and graphs produced can be customised and exported in different formats.
What does it do? Phase 1 Outputs:
– Survey effort reports
– Species list (taxonomically ordered with information on habitat, habit, tropic level, adult body weight, IUCN Red List threat status) with number of images, number of events and number of camera stations detected
– Rarefaction curves and species richness estimates
– Species spatio-temporal plots
– Species trapping rates with standard errors (overall and daily / seasonal)
– Species occupancy modelling (with sites covariates)
– Distribution plots of trapping rates and occupancy (in Google Earth, QGIS and ArcGIS)
– Activity patterns
ZSL– CAMERA TRAP DATA PROCESS
ZSL Camera Trap Tool
Field variables
Ana
Note: The tool requires appropriate ‘R’ packages pre-loaded (but no manipulation of ‘R’ necessary) and computer date/time format harmonised – See manual
Back up
Analysis package
Crowd sourcing?
IMAGE PROCESSING
CONVERTS THIS…
TO MANAGED DATA SYSTEM: IMAGE CHECKING, SORTING & EDITING
SUMMARY REPORTS: CAMERA OPERATION
CAMERAS STATION SAMPLING HISTORY : IBEX RESERVE, SAUDI ARABIA
SUMMARY REPORTS: SAMPLE EFFORT
No. CAMERAS WORKING ON EACH DAY OF SURVEY : BONI FOREST, KENYA
15/0
6/2
010
13/0
6/2
010
11/0
6/2
010
09/0
6/2
010
07/0
6/2
010
05/0
6/2
010
03/0
6/2
010
01/0
6/2
010
30/0
5/2
010
28/0
5/2
010
26/0
5/2
010
24/0
5/2
010
22/0
5/2
010
20/0
5/2
010
18/0
5/2
010
16/0
5/2
010
14/0
5/2
010
12/0
5/2
010
10/0
5/2
010
08/0
5/2
010
06/0
5/2
010
04/0
5/2
010
02/0
5/2
010
30/0
4/2
010
28/0
4/2
010
26/0
4/2
010
24/0
4/2
010
22/0
4/2
010
20/0
4/2
010
18/0
4/2
010
16/0
4/2
010
14/0
4/2
010
12/0
4/2
010
10/0
4/2
010
08/0
4/2
010
06/0
4/2
010
04/0
4/2
010
02/0
4/2
010
31/0
3/2
010
29/0
3/2
010
27/0
3/2
010
25/0
3/2
010
23/0
3/2
010
21/0
3/2
010
19/0
3/2
010
17/0
3/2
010
Num
ber
of
Sam
plin
g C
am
era
Sta
tions
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
SUMMARY REPORTS: CAMERA PERFORMANCE
CAMERA PERFORMANCE : BONI FOREST, KENYA
SUMMARY REPORTS: CAMERA LOCATION & PERFORMANCE
CAMERA LOCATIONS AND PERFORMANCE ON GOOGLE EARTH : BONI FOREST, KENYA
Camera Station Latitude Longitude
Ca
me
ra
reco
ve
ry
Ca
me
ra s
etu
p
Oth
er
- b
lan
k
Oth
er
-
ca
me
ra m
ou
nt
mo
ve
me
nt
Oth
er
- in
se
ct
Wild
life
Wild
life
-
un
ide
nti
fia
ble
Wild
life
-
un
ide
nti
fie
d
TOTAL
C1_BN-01-01 001° 39' 11.82" S 041° 16' 25.51" E 26 15 69 6 0 942 0 0 1058
C2_BN-01-02 001° 38' 20.88" S 041° 16' 02.30" E 48 18 57 0 3 945 0 0 1071
C3_BN-01-03 001° 37' 29.87" S 041° 15' 16.32" E 6 12 21 0 0 2358 0 0 2397
C4_BN-01-04 001° 36' 34.56" S 041° 14' 35.83" E 51 15 228 0 0 1332 0 0 1626
C5_BN-01-05 001° 35' 33.80" S 041° 14' 02.13" E 42 12 33 0 0 1227 0 0 1314
C6_BN-01-06 001° 34' 45.37" S 041° 13' 31.94" E 18 18 51 0 0 111 0 0 198
C7_BN-01-07 001° 33' 49.56" S 041° 12' 55.63" E 0 24 30 0 0 672 15 0 741
L1_BN-01-08 001° 39' 49.14" S 041° 15' 34.58" E 24 15 33 0 0 573 24 0 669
L2_BN-01-09 001° 38' 53.46" S 041° 15' 05.06" E 90 12 39 0 0 669 27 0 837
L3_BN-01-10 001° 37' 58.37" S 041° 14' 28.23" E 23 6 24 0 0 462 0 0 515
L4_BN-01-11 001° 37' 09.01" S 041° 13' 49.49" E 34 9 12 0 0 1149 0 0 1204
L5_BN-01-12 001° 36' 14.99" S 041° 13' 15.60" E 25 15 123 0 0 669 39 0 871
L6_BN-01-13 001° 35' 19.15" S 041° 12' 40.04" E 10 5 60 0 0 2685 42 0 2802
R1_BN-01-14 001° 33' 49.53" S 041° 12' 55.59" E 32 24 30 0 0 546 21 0 653
R2_BN-01-15 001° 38' 37.09" S 041° 17' 29.86" E 0 12 15 0 0 390 24 0 441
R3_BN-01-16 001° 37' 47.82" S 041° 16' 51.96" E 0 0 0 0 0 0 0 0 0
R4_BN-01-17 001° 36' 49.29" S 041° 16' 08.53" E 42 12 18 0 0 888 9 0 969
R5_BN-01-18 001° 36' 00.77" S 041° 15' 35.49" E 24 12 189 0 0 5283 54 0 5562
R6_BN-01-19 001° 35' 00.47" S 041° 15' 03.60" E 26 12 36 0 0 1137 9 0 1220
R7_BN-01-20 001° 34' 08.37" S 041° 14' 27.62" E 51 12 21 0 0 1029 9 3 1125
TOTAL: 572 260 1089 6 3 23067 273 3 25273
SUMMARY REPORTS: PHOTO TYPE TOTALS
Camera recovery 4.9 %
Camera setup 3.68 %
Other - blank 4.59 %
Other - camera mount movement 0 %
Other - insect 0 %
Wildlife 83.61 %
Wildlife - unidentif iable 3.22 %
Wildlife - unidentif ied 0 %
Camera Station: R1_BN-01-14
Camera recovery 2.26 %
Camera setup 1.03 %
Other - blank 4.31 %
Other - camera mount movement 0.02 %
Other - insect 0.01 %
Wildlife 91.27 %
Wildlife - unidentif iable 1.08 %
Wildlife - unidentif ied 0.01 %
Camera Station: <All>
BONI FOREST – COASTAL KENYA 2010
COMPILED SPECIES LISTS
SAPO NATIONAL PARK - LIBERIA
Order Family or Subfamily Scientific Name Local NameIUCN
StatusHabitat Habit Trophic Level
Avg.
Adult
Weight
(kg)
Avg.
Home
Range
(km²)
No. of
Images
No. of
Events
No. of
Stations
Detected
in
Mammalia
Carnivora Felidae Caracal aurata African golden cat VU Forest T Carnivore 10 6 3 2
Carnivora Felidae Panthera pardus Leopard NT Mixed T Carnivore 40 6 2 2
Carnivora Herpestidae Atilax paludinosus Marsh mongoose LC Wetland SA Carnivore 3 216 59 16
Carnivora Herpestidae Crossarchus obscurus Common cusimanse LC Forest T Carnivore 1 15 5 4
Carnivora Herpestidae Liberiictis kuhni Liberian mongoose VU Forest T Carnivore 2.3 3 1 1
Carnivora Mustelidae Mellivora capensis Honey badger LC Mixed T Carnivore 10 6 1 1
Carnivora Viverridae Civettictis civetta African civet LC Mixed T Carnivore 11.5 60 9 6
Carnivora Viverridae Genetta bourloni Bourlon's genet NT Forest T Carnivore 1.5 30 10 5
Carnivora Viverridae Genetta pardina Pardine genet LC Forest T Carnivore 1.5 24 4 4
Carnivora Viverridae Genetta sp. Genet sp. Mixed T Carnivore 0 24 8 7
Cetartiodactyla Cephalophinae Cephalophus dorsalis Bay duiker LC Forest T Herbivore 20 63 16 8
Cetartiodactyla Cephalophinae Cephalophus jentinki Jentink's duiker EN Forest T Herbivore 68 30 7 5
Cetartiodactyla Cephalophinae Cephalophus niger Black duiker LC Forest T Herbivore 22 33 10 6
Cetartiodactyla Cephalophinae Cephalophus ogilbyi Ogilby's duiker LC Forest T Herbivore 17 276 71 20
Cetartiodactyla Cephalophinae Cephalophus sp. Duiker sp. Forest T Herbivore 0 84 26 13
Cetartiodactyla Cephalophinae Cephalophus zebra Zebra duiker NT Forest T Herbivore 14 195 51 14
Cetartiodactyla Cephalophinae Philantomba maxwelli Maxwell's duiker LC Woodland T Herbivore 3 339 84 19
Cetartiodactyla Suidae Potamochoerus porcus Red River Hog LC Mixed T Omnivore 53 36 3 2
Cetartiodactyla Tragulidae Hyemoschus aquaticus Water Chevrotain LC Forest SA Herbivore 11 24 7 2
Pholidota Manidae Phataginus tricuspis White-bellied pangolin VU Forest T Insectivore 2.5 9 3 3
Pholidota Manidae Smutsia gigantea Giant pangolin VU Forest T Insectivore 32 15 3 3
Primates Cercopithecidae Cercocebus atys Sooty Mangabey VU Forest G Frugivore 8 944 158 25
Primates Cercopithecidae Cercopithecus campbelli Campbell's monkey LC Woodland Ar Herbivore 3.5 12 4 2
Primates Cercopithecidae Cercopithecus diana Diana monkey VU Forest Ar Herbivore 4.5 3 1 1
Primates Hominidae Pan troglodytes verus Western Chimpanzee EN Forest T Insectivore 50 18 5 5
Proboscidea Elephantidae Loxodonta africana cyclotis African forest elephant VU Forest T Herbivore 1000 51 3 3
SPECIES ACCUMULATION AND RICHNESS CURVES
AUTOMATICALLY LAUNCHES ‘R’ TO RUN CALCULATION Or export processed data e.g to EstimateS - Colwell 2013
SPATIO-TEMPORAL PLOTS
FOUR-TOED SENGI : ARABUKO-SOKOKE FOREST, KENYA
Mean number of independent photographic events per trap-day times 100
Ara
bia
n b
abble
r
Ara
bia
n g
azelle
Ara
bia
n s
pin
y m
ouse
Bat sp.
Bla
cksta
rt
Bushy-t
aile
d ji
rd
Cam
el
Cape h
are
Com
mon k
estr
el
Desert
eagle
ow
l
Desert
hedgehog
Desert
lark
Dom
estic
cat
Donkey
Eura
sia
n c
olla
red d
ove
Fox s
p.
Gre
y m
onito
r
Gre
y w
olf
Hoopoe
Laughin
g d
ove
Murid s
p.
Nubia
n ib
ex
Red fox
Rock h
yra
x
Sand p
art
ridge
Shoat
Spanis
h s
parr
ow
Str
ioalte
d b
untin
g
Unid
entif
ied b
ird
Unid
entif
ied c
at
White
-cro
wned w
heate
ar
White
-specta
cle
d b
ulb
ul
3.8
3.6
3.4
3.2
3
2.8
2.6
2.4
2.2
2
1.8
1.6
1.4
1.2
1
0.8
0.6
0.4
0.2
0
TRAPPING RATES
WADI NUKHAYLAN : IBEX RESERVE, SAUDI ARABIA
DATA EXPLORATION: TEMPORAL SEQUENCES
Species: Camel
08/0
6/2
013
01/0
6/2
013
25/0
5/2
013
18/0
5/2
013
11/0
5/2
013
04/0
5/2
013
27/0
4/2
013
20/0
4/2
013
13/0
4/2
013
06/0
4/2
013
30/0
3/2
013
23/0
3/2
013
16/0
3/2
013
09/0
3/2
013
02/0
3/2
013
23/0
2/2
013
16/0
2/2
013
09/0
2/2
013
02/0
2/2
013
26/0
1/2
013
19/0
1/2
013
12/0
1/2
013
05/0
1/2
013
29/1
2/2
012
22/1
2/2
012
15/1
2/2
012
08/1
2/2
012
01/1
2/2
012
24/1
1/2
012
17/1
1/2
012
Num
ber
of In
dependent P
hoto
gra
phic
Events
9
8.5
8
7.5
7
6.5
6
5.5
5
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
CAMELS Nov.12 to Jun 13
EVENT FREQUENCY BY DATE
TERMIT - NIGER Nov.12 to Jun 13
Species: Golden jackal
08/0
6/2
013
01/0
6/2
013
25/0
5/2
013
18/0
5/2
013
11/0
5/2
013
04/0
5/2
013
27/0
4/2
013
20/0
4/2
013
13/0
4/2
013
06/0
4/2
013
30/0
3/2
013
23/0
3/2
013
16/0
3/2
013
09/0
3/2
013
02/0
3/2
013
23/0
2/2
013
16/0
2/2
013
09/0
2/2
013
02/0
2/2
013
26/0
1/2
013
19/0
1/2
013
12/0
1/2
013
05/0
1/2
013
29/1
2/2
012
22/1
2/2
012
15/1
2/2
012
08/1
2/2
012
01/1
2/2
012
24/1
1/2
012
17/1
1/2
012
Num
ber
of In
dependent P
hoto
gra
phic
Events
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Species: Dorcas gazelle
08/0
6/2
013
01/0
6/2
013
25/0
5/2
013
18/0
5/2
013
11/0
5/2
013
04/0
5/2
013
27/0
4/2
013
20/0
4/2
013
13/0
4/2
013
06/0
4/2
013
30/0
3/2
013
23/0
3/2
013
16/0
3/2
013
09/0
3/2
013
02/0
3/2
013
23/0
2/2
013
16/0
2/2
013
09/0
2/2
013
02/0
2/2
013
26/0
1/2
013
19/0
1/2
013
12/0
1/2
013
05/0
1/2
013
29/1
2/2
012
22/1
2/2
012
15/1
2/2
012
08/1
2/2
012
01/1
2/2
012
24/1
1/2
012
17/1
1/2
012
Num
ber
of In
dependent P
hoto
gra
phic
Events
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
GOLDEN JACKAL Nov.12 to Jun 13
DORCAS GAZELLE Nov.12 to Jun 13
OCCUPANCY MODELLING
Note: Presence/absence matrices exportable for separate analysis
SELECTED MAMMALS : BONI FOREST, KENYA
OCCUPANCY MODELLING: GRAPHIC OUTPUT
Automatically launches ‘R’ to run calculations
SELECTED MAMMALS : SAPO NP, LIBERIA
OCCUPANCY MODELLING WITH SITE COVARIATES
BLUE DUIKER : ARABUKO-SOKOKE FOREST, KENYA
BLUE DUIKER : ARABUKO-SOKOKE FOREST, KENYA
OCCUPANCY MODELLING WITH SITE COVARIATES
ACTIVITY PATTERNS
GIANT SENGI BONI FOREST Mar – Jun 2010
FOUR-TOED SENGI BONI FOREST Mar – Jun 2010
Species: Golden-rumped sengi ssp.
Hour of the Day0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Num
ber
of
Independent
Photo
gra
phic
Events
20
19
18
17
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
Species: Four-toed sengi
Hour of the Day0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Num
ber
of
Independent
Photo
gra
phic
Events
32
30
28
26
24
22
20
18
16
14
12
10
8
6
4
2
0
Species: Rueppell's fox
Hour of the Day0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Num
ber
of In
dependent P
hoto
gra
phic
Events
8
7.5
7
6.5
6
5.5
5
4.5
4
3.5
3
2.5
2
1.5
1
0.5
0
Species: Golden jackal
Hour of the Day0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
Num
ber
of In
dependent P
hoto
gra
phic
Events
16
15
14
13
12
11
10
9
8
7
6
5
4
3
2
1
0
African ‘golden wolf’
Ruppell’s fox
ACTIVITY PATTERNS
DISTRIBUTION OF RECORDS Google Earth (QGIS & ArcReader)
AUTOMATIC INTERFACE WITH GOOGLE EARTH BARBARY SHEEP – TERMIT
5 DATA INPUTS:
1. CAMERA LOCATION AND SITE COVARIATES
2. CAMERA MAKE & CONFIGURATION DETAILS
3. CAMERA SETUP, SERVICE & RECOVERY DATES
4. IMAGE DATA
5. SITE COVARIATES
(optional)
DATA PREPARATION
1 - IMAGE DATA
META-DATA EXTRACTION
1 - IMAGE DATA
META-DATA EXTRACTION
DATA STANDARDISATION
• STANDARD ‘PHOTO TYPE’ CLASSES
• EXTENSIVE USE OF LOOK-UP TABLES IN THE DATA MODEL (FIXED AND EDITABLE COMPONENTS)
• SPECIES NAMES BASED ON IUCN REDLIST
• SEPARATE ‘COUNTRY TEMPLATES’ FOR SPECIES
1. IMAGE DATA
1) LOAD META DATA FOR EACH CAMERA SEQUENTIALLY : 2) ENTER PHOTO TYPE & SPECIES BY HAND (MUST MATCH LOOK-UP TABLE OPTIONS)
2. CAMERA SITE NAME, POSITION, SITE VARIABLES
3. CAMERA CONFIGURATION
4. SET-UP, SERVICE, RECOVERY & FUNCTIONING HISTORIES
DEMONSTRATION
CAMERA TRAPPING NEEDS
1) PROTOCOLS & BEST PRACTICES
2) TRAINING: SURVEY DESIGN & FIELD SET UP
3) TRAINING : DATA MANAGEMENT & ANALYSIS
4) DATA ANALYSIS AND REPORTING
IMPACT OF TRAINING
STANDARDISING CAMERA POSITION
50% OF CAMERAS BEFORE TRAINING
95% OF CAMERAS AFTER TRAINING
• Image metadata processing tool
• Population density estimates for marked animals (spatially explicit capture-recapture modelling)
• Population density estimates for unmarked animals
• Activity level modelling
• Diversity measures
• Species community structure analyses
• Statistical tests (chi-square, circular statistics etc.)
• Cross survey analyses
• Standardised reports generation in Word and RTF.
VERSION 2 DEVELOPMENT