1. Introduction;
Basking sharks (Cetorhinus maximus) are the second largest fish species in the world,
with a circum-global distribution in warm temperate to boreal seas (Cotton et al.
2005). They are associated with continental shelf edge habitats where they often
aggregate to forage on dense patches of zooplankton associated with oceanographic
features (Sims & Quayle, 1998; Sims et al. 2000.)
Life history traits of basking sharks are not fully known, however it has been
suggested that their maturation rate is slow taking between 12-20 years. Females are
ovoviviparous and have long gestation periods (approximately 1-3 years) after which
they give birth to few offspring (Kunzlik, 1988). Consequently basking sharks are
especially vulnerable to over exploitation. In the past they have been exploited for
meat, fins, liver oil (Compagno, 2001) and cartilage (Hoelzel, 2001). The inherent
vulnerability to high levels of exploitation may have resulted in collapse of some
stocks (Anderson, 1990); For example, the fishery for basking shark near Achill
Island off the west coast of Ireland appeared to collapse in the early 1960’s after only
ten years of peak catches (Kunzlik, 1988).
1.1. Legal protection;
In order to address this collapse in stocks the Fisheries and Agriculture Organisation
(FAO, 1999) made international plans of action, the aims of which were to ensure
conservation and management of sharks and their long term sustainable use, however,
participation was voluntary and no new shark management measures were
implemented, it therefore seemed unlikely that the plans would be sufficient to
develop sustainable management (Southall et al. 2006).
1
2001 saw the reduction of the European quota of total allowable catch to zero
(Southall et al. 2006). One year later, on the basis of the UK proposal, listing of the
basking shark in the Convention on International Trade in Endangered Species
(CITES) was upgraded to Appendix II, which requires International trade to be
monitored through a licensing system to ensure that trade can be sustained without
detriment to wild populations. The possibility that numbers may be depleted by
exploitation and lack of scientific knowledge resulted in listing of the species on the
IUCN Red List as vulnerable (A1a, d and 2d) worldwide, and Endangered (EN A1a,
d) in the North-East Atlantic (IUCN, 2004). However, protection for this species is
limited to European waters and varies spatially (Southall et al. 2006.)
Despite concern for the conservation of this species, there is little data on regional
abundance, no estimates for abundance worldwide and no good data on population
trends (Hoelzel et al, 2006). This is particularly damning as it has been stated that
without scientifically based population assessment it is impossible to determine
current population trends and monitor stocks effectively for conservation purposes
(Southall et al. 2005).
1.2. Population assessment;
In order to asses basking shark populations a variety of methods have been used.
Some studies utilize the extensive sighting records gained in coastal waters around the
UK from 1987 onwards (Doyle et al. 2005). These methods are however problematic;
data gathered is variable due to observer bias, plus sighting probability of individuals
is altered due to systematic differences in surfacing behaviour, this changes with
habitat, season and time of day (Southall et al. 2006).
1.3. Satellite tagging;
2
One method to reduce these problems is to use computer derived information. It is
now possible to plot the position of individuals using satellite tagging; Southall et al.
(2006) used pop-up archival transmitting (PAT) tags to assess the annual space-use
patterns of basking sharks within the North-East Atlantic. This analysis indicated that
basking sharks move between economic zones and were not afforded statutory
protection for the majority of time they spent within their preferred habitat; thus
illustrating the limited capacity of the British protection zone to cover the greater part
of shark space utilization.
Satellite tagging does however have limitations; Firstly tags are expensive which
limits the number of samples which can be taken. Secondly, there is some difficulty
in attaching tags for long enough time periods, for example the tags used by Southall
et al. (2006) were released in less than a year. Tags are also not completely reliable,
only 7 tags out of 20 were received the rest were assumed malfunctioning.
Distribution data gained could also be flawed as the accuracy of geolocation is
dependant on the weather and behaviour of the animal. Finally due to intermittence of
transmitting, time gaps are apparent (Southall et al. 2006) in data gathered.
1.4. Genetic analysis;
Another technological breakthrough being used to assess the status of basking sharks
is that of genetic research. The genetic diversity of basking sharks was calculated
using tissue samples acquired from stranded basking sharks and those killed as a
result of by-catch, from this data an approximate population estimate of 8200
individuals was made (Hoelzel et al. 2006). Genetic analysis has a lot of potential for
population assessment, since for individual identification this method is seems
flawless; however samples were restricted to dead animals which could obviously not
be used in mark release-recapture studies. There is also the slight possibility that the
3
sharks sampled were more prone to stranding or becoming a subject of by-catch due
to some genetic disposition, subsequently individuals with alternate genetic make up
were not sampled, consequently the low genetic diversity found by the study may be a
result of sampling bias not low genetic diversity of the entire basking shark
population.
1.5. Mark release-recapture studies;
In order to assess this threatened species it is important that results are gained quickly
and are widely understood. Mark release-recapture techniques have been extensively
applied in animal ecology and are often employed for determining patterns in growth,
survivorship, behaviour and abundance of organisms (Stonehouse, 1978). These
techniques can however be problematic, for example it is not always possible to mark
certain types of animals, either because they are difficult to mark or tag, or because
they are legally protected from disturbance, as is the case with some cetaceans
(Hammond et al. 1990). Tags which are invasive could alter behaviour, growth and
(or) survivorship of the host animal by causing physical hindrance, injury, disease or
physiological interference (Scorrat, 1970; Bergmas et al. 1992; Linnare & Merar,
1998; Courtney et al. 2001).
1.6. Photographic Identification;
One solution to the problem of artificially tagging animals is to identify individuals
using variation in natural marks and (or) polymorphic colour patterns, if these natural
marks occur, photographs taken of individuals at different points of time can be used
for mark-recapture techniques (Frisch and Hobbs, 2007).
Photographic identification has been widely implemented to study vertebrate animals
(e.g. Persal, 1982; Hammond et al. 1990; Doody, 1995; Anderson and Goldman,
1996; Kelly 2001). These techniques have been developed to obtain individual
4
marking data of marine mammals (e.g. Würsig and Würsig, 1977; Katona and Krauss,
1979; Hiby and Lovell, 1990; Beck and Reid, 1995, Forcada and Aguilar, 2000) and
successfully applied to a number of species and populations (e.g. Bigg, 1982;
Clapham and Mayo, 1990; Jones, 1990; Gailey, 2001).
To use photographic identification definitively it is necessary however that individual
can be correctly identified from their photographs. There have been indications from
previous studies that the reliability of photographic identification depends on the
species involved, the sampling strategy and the kind of natural marks used to identify
individuals (Arnbom, 1987; Hiby and Lovell, 1990). Validity of photographic
identification from natural markings has been shown in a number of cetacean studies
by combining photographic identification and tagging techniques (Irvine et al. 1982;
Scott et al, 1990; Gailey, 2001). Photographic identification was also shown to be
appropriately used for capture-recapture abundance estimates of Mediterranean monk
seals (Monachus monachus) (Forcada and Aguilar, 2000). Identification of individual
using photographs has also been applied to some sharks species (Mourier et al. 2007),
for example, the patterning of spots and stripes unique to each whale shark
(Rhincodon typus) (Meeham et al. 2006), was shown to be an accurate method for
identify individuals (Speed et al. 2007). Consequently application of the markrecapture method could be an appropriate method for analysis of basking shark
populations, providing identification is based on features which are unique to each
individual and can be gained for a large sample with little to no difficulty.
Photographic identification of cetacean species often uses natural variation in
pigmentation patterns and notches occurring on their dorsal fins resulting from
interactions with their environment and other animals (Würsig and Würsig, 1977;
Würsig and Jefferson, 1990), it is possible to photograph this feature when cetaceans
5
surface to breathe. Due to the “basking” behaviour displayed by the appropriately
named shark, these animals spend some of their time at the surface with all or part of
the dorsal fin protruding from the water, it is therefore possible to take photographs of
the fin from the shore or at sea. Subsequently this feature may be suitable for
identification of individual basking sharks as is the case with cetaceans.
Worldwide, mark-recapture studies are utilizing photographic databases to document
population trends and estimate demographic rates (Fujiwara & Caswell., 2001; Sterick
et al. 2003; Meekham et al. 2006; Speed et al. 2007; Speed et al. 2008,) however, due
to the large amounts of photographic data which can be gathered, matching
photographs of the same individuals is a time consuming and fatiguing process
(Katona and Beard, 1990); For this reason computer programs have been developed to
select possible matches which can then be confirmed by a human observer, one such
program is EuroPhlukes©. EuroPhlukes© uses the shape of the dorsal fin and nicks or
cuts on the trailing edge to match similar photographs, if the use of photographic
identification is appropriate for the basking sharks, application of the EuroPhlukes©
program may beneficially reduce time spent matching photographs of individuals for
population assessment.
This paper looks at the reliability of photographs of the dorsal fin of basking sharks
for individual identification, using the computer assisted matching program
EuroPhlukes© and human experimenters.
2. Method;
2.1. Study area;
6
The photographic identification material was collected in coastal waters off the Isle of
Man between the 3rd and 30th of June 2008. The study was conducted on the Southern
end of the island between Port St Mary and Peel Harbour, the area surveyed is shown
on Figure 1 highlighted by a black dotted line.
Study
area.
Figure 1 Map of the Isle of Man showing the survey area highlighted by a black dotted line.
2.2. Photographic data collection;
Surveys took place aboard a 15ft motor boat, they were conducted at various times of
day for varying lengths of time in different weather conditions, however photographs
were not taken during heavy rain to avoid damage to camera equipment. Data was
7
collected in various sea states but photographs were not taken in sea state five to
ensure the photographer’s safety.
During a survey the boat travelled out of Port St Mary’s Harbour along the coast
towards peel Harbour, at the end of a survey the boat returned to Port St Mary. On
sighting a basking shark the boat approached at an extremely slow speed to a distance
of 20m came to a stop and the engine was put into neutral. Each shark was
photographed using a Cannon 400d, 8 mega pixel digital camera, with a 55mm250mm lens with image stabiliser. On each encounter multiple photographs were
taken of the basking shark’s dorsal fin. The photographer attempted to take at least 10
photographs from both sides, encompassing a large proportion of the fin, at as close to
90º angle as possible. On each sighting, date of sighting, encounter number, time,
position of sighting, an estimation of the basking shark’s size and any distinguishing
features was recorded in order to assist accurate data entry. To ensure photographs
collected were definitely of the same individual, each encounter occasion was
considered to be a different individual.
2.3. Photographic cataloguing and editing;
All photographs taken were transferred to a personal computer, these raw photographs
were catalogued first by date taken, then by encounter number and finally by image
number. Photographs were edited using ACDSee Pro Photograph Manager© version
8.0, this editing involved cropping the images to include only the dorsal fin, images
not showing the dorsal fin were discarded, the edited photographs were catalogued in
the same way as the raw photographs and saved separately as “Cropped BS photos”.
2.4. Photographic Rating;
The quality of these “Cropped BS photos” was then rated. The rating process was
based on that proposed by Hammond (1986) which uses the categories of; focus,
8
glare, angle, distance from the individual and the proportion of the individual
photographed. However the category of glare was replaced by the angle of light on
the fin, where photographs with the light shining onto the fin were rated higher than
those will the light coming from behind. The proportion of individual photographed
was adapted to the proportion of individual’s fin photographed. Distance from the
animal was excluded as this was always within 20m.
Consequently categories for rating the photographs of each shark encounter were;
A) Proportion of fin photographed; within each encounter the photograph showing the
largest area of the basking shark’s fin was selected, all other photographs from this
encounter were then compared to this and rated from 1-5.
Photographs rated 1 showed 100-80% of the area of fin shown in the “largest” photo,
those rated 2 showed 80-60%, and so on with 5 being 20-0%. Photographs from the
top 4 categories were then rated for angle those from category 5 were immediately
discarded.
B) Angle of fin; photographs at 90° to the fin (side on) were rated 1, those rated 2
were at a slight angle of 70° to 89° and 3 being at an abrupt angle 69° to 180°.
Photographs rated 1 or 2 were then rated for focus those rated 3 were discarded.
C) Focus; photographs in focus were rated 1, those out of focus were rated 2. Both
categories were then rated for direction of light.
D) Direction of light; photographs with light shining onto the fin were rated 1, those
with light coming from behind the fin were rated 2.
Once all the photographs were rated in this way the ten images rated highest from
each encounter (from both sides of the fin if possible) were selected. The resulting set
of photographs were again arranged under date taken, then encounter number, then
image number and saved as a new catalogue named “Rated BS photos”.
9
2.5. Individual photographs;
From the “Rated BS photos” catalogue the highest quality photograph for each
encounter was selected these images were again sorted under date taken, then
encounter number, then image number. The resulting catalogue was saved as “Best
Individual BS photos” these photos represent the best image of each individual
basking shark encountered.
2.6. Matching photographs;
2.7. EuroPhlukes© photograph matching;
Initially all photographs from the “Rated BS photos” catalogue were matched using
EuroPhlukes©. Firstly photographs from the same encounter were matched to each
other to check whether photographs which were definitely of the same shark could be
matched. Secondly photographs from all encounters were grouped and matched
together to see if from a selection of photographs, those of the same individual will be
matched together. Thirdly the proportion of incorrect matches was calculated by
removing those matches of sharks within the same encounter from the matches
between all encounters.
2.8. Human Eye photograph matching;
Matching photographs bye eye involved renaming all photographs within the “Rated
BS photos” catalogue with a code; the coded photographs were then mixed up. For
each of the “Best Individual photos” an empty folder was created with the same name.
Each coded photograph was then compared with those within the “Best Individual BS
photos” catalogue. Once a match was decided, the coded photograph was copied and
pasted into the “Best Individual BS photos” folder corresponding to the photograph it
matched.
10
Eye matching was carried out by one experimenter whom had four months of
photograph identification experience and one naïve experimenter whom had no
photographic identification experience.
2.9. Analysis;
Using EuroPhlukes© the threshold for a possible match is any result between 1 and
0.6. Firstly the proportion of possible matches within each encounter was calculated.
Secondly the proportion of possible matches for each encounter out of all the “Rated
BS photos” was calculated. Finally the proportion of incorrect matches was
calculated.
For analysis of the human matched photos, the matched coded photographs were
decoded and their initial name restored. If the photograph had been placed into the
folder corresponding to the encounter in which it had been taken, this was a correct
match, if the photograph had been placed into a folder of an alternate encounter to its
own, this was an incorrect match. The proportion of correct matches was calculated
by dividing the number of correct matches out of the total number of matches for that
occasion (correct plus incorrect matches).
3. Results;
3.1. EuroPhlukes© Matching Results;
Table 1 displays the result of matching photographs within each encounter using
Europhlukes©;
11
Table 1 Summary of photograph matching within encounters using EuroPhlukes©.
Within Encounter
Encounter
number
03-06-08-enc01
03-06-08-enc02
03-06-08-enc03
03-06-08-enc04
03-06-08-enc05
03-06-08-enc06
08-06-08-enc02
08-06-08-enc04
08-06-08-enc05
08-06-08-enc06
08-06-08-enc08
08-06-08-enc09
14-06-08-enc01
Number
photographs
10
3
20
20
10
10
10
19
9
20
10
20
20
of
Number
of
comparisons
45
3
190
190
45
45
45
171
36
192
45
190
190
Possible
matches
(>0.6)
2
0
21
10
6
17
32
73
24
64
25
41
68
Proportion
of
Possible
matches (>0.6)
0.04444444
0
0.11052632
0.05263158
0.13333333
0.37777778
0.71111111
0.42690058
0.66666667
0.33333333
0.55555556
0.21578947
0.35789474
Table 2 shows the results of matching photographs from all encounters with each
other using EuroPhlukes©.
Table 2 Summary of photographic matching from all encounters using EuroPhlukes©.
All Encounters
Encounter
number
03-06-08-enc01
03-06-08-enc02
03-06-08-enc03
03-06-08-enc04
03-06-08-enc05
03-06-08-enc06
08-06-08-enc02
08-06-08-enc04
08-06-08-enc05
08-06-08-enc06
08-06-08-enc08
08-06-08-enc09
14-06-08-enc01
Number
photographs
10
3
20
20
10
10
10
19
9
20
10
20
20
of
Number
of
comparisons
1753
509
3146
2348
1025
925
825
1293
486
790
245
190
2751
Possible
matches
(>0.6)
6
43
284
134
64
64
332
475
174
188
85
41
624
Proportion
of
possible
matches (>0.6)
0.0034227
0.08447937
0.09027336
0.05706985
0.06243902
0.06918919
0.40242424
0.36736272
0.35802469
0.23797468
0.34693878
0.21578947
0.22682661
Figure 2 displays the average proportion of possible matches within each encounter
and the proportion of possible matches comparing all photos taken for each encounter.
12
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Within Encounter
14-06-08-enc01
08-06-08-enc09
08-06-08-enc08
08-06-08-enc06
08-06-08-enc05
08-06-08-enc04
08-06-08-enc02
03-06-08-enc06
03-06-08-enc05
03-06-08-enc04
03-06-08-enc03
03-06-08-enc02
All Encounters
03-06-08-enc01
Average proportion of Possible
matches (>0.6)
Proportion of possible matches using EuroPhlukes©
Encounter number
Figure 2 Proportion of possible matches within encounters and comparing photos from all
encounters using EuroPhlukes©.
Figure 2 shows slightly a slightly higher proportion of possible matches for those
photographs within the same encounter than the proportion of matches between all
photographs.
A T-test was carried out to test if the proportion of possible matches within the same
encounter was significantly different from the proportion of matches between all
encounters using EuroPhlukes© the results of this test are shown the table 3.
Table 3 t-test of diference between proportion of possible matces within each encounter and the
proportion of posible matches each encounters using EuroPhlukes©.
t-Test: Two-Sample Assuming Equal Variances
Within Encounters
Variable 1
Mean
0.306613
Variance
0.05684
Observations
13
Pooled Variance
0.038336
Hypothesized Mean Difference 0
Df
24
t Stat
1.466142
P(T<=t) one-tail
0.077795
t Critical one-tail
1.710882
P(T<=t) two-tail
0.15559
t Critical two-tail
2.063899
13
All Encounters
Variable 2
0.194017
0.019832
13
A P value of 0.05 or below shows a significant difference between values, as a P
value of 0.078 (3.d.p.) was gained this shows there is no significant difference
between the proportion of possible matches gained comparing photographs within the
same encounter or those from all encounters.
To account for the possibility that the number of possible matches gained comparing
photographs from all encounters may be incorrect matches; the proportion of possible
incorrect matches was calculated for each encounter by removing the proportion of
correct matches from each encounter, (those matches where photos were matched
within the encounter they were taken). Table 4 shows the results of this calculation.
Table 4 Calculation of the proportion of incorrect possible matches found using EuroPhlukes©.
Between Encounters
Encounter
number
03-06-08-enc01
03-06-08-enc02
03-06-08-enc03
03-06-08-enc04
03-06-08-enc05
03-06-08-enc06
08-06-08-enc02
08-06-08-enc04
08-06-08-enc05
08-06-08-enc06
08-06-08-enc08
08-06-08-enc09
14-06-08-enc01
Number
photographs
10
3
20
20
10
10
10
19
9
20
10
20
20
of
Number
of
comparisons
1708
506
2956
2158
980
880
780
1122
450
598
200
0
2561
Possible
matches
(>0.6)
4
43
263
124
58
47
300
402
150
124
60
0
556
Proportion
of
possible
matches (>0.6)
0.00234192
0.08498024
0.08897158
0.05746061
0.05918367
0.05340909
0.38461538
0.35828877
0.33333333
0.20735786
0.3
0
0.21710269
The difference between the proportion of possible matches using EuroPhlukes©
within encounters and the proportion of possible matches between different
encounters (possible incorrect matches) was calculated using a t-Test; the results of
this calculation are shown in table 5.
14
Table 5 Difference in proportion of possible matches using EuroPhlukes© within encounters and
between encounters.
t-Test: Two-Sample Assuming Equal Variances
Within Encounters
Variable 1
Mean
0.306613
Variance
0.05684
Observations
13
Pooled Variance
0.038326
Hypothesized Mean Difference
0
Df
24
t Stat
1.842169
P(T<=t) one-tail
0.03892
t Critical one-tail
1.710882
P(T<=t) two-tail
0.07784
t Critical two-tail
2.063899
Between Encounters
Variable 2
0.165157
0.019812
13
The difference between the proportions of possible matches within encounters and
between encounters was calculated as 0.04 (2.d.p.) showing a significant difference,
with the proportion of possible matches between encounters (incorrect matches) being
significantly lower.
3.2. Human Eye Matching Results;
The results of the human photographic matching per encounter for both experimenters
are shown in table 6;
15
Table 6 The number of correct and incorrect matches and the proportion of correct matches per
encounter for both experimenters.
Experienced Matcher
Encounter
Number
03-06-08-enc01
03-06-08-enc03
03-06-08-enc04
03-06-08-enc05
03-06-08-enc06
03-06-08-enc08
08-06-08-enc02
08-06-08-enc03
08-06-08-enc04
08-06-08-enc05
08-06-08-enc06
08-06-08-enc08
08-06-08-enc09
08-06-08-enc10
08-06-08-enc11
08-06-08-enc12
08-06-08-enc13
14-06-08-enc01
16-06-08-enc01
16-06-08-enc03
16-06-08-enc04
16-06-08-enc06
20-06-08-enc01
20-06-08-enc02
20-06-08-enc03
Total
CORRECT
INCORRECT
10
20
20
9
7
8
10
8
5
10
9
10
13
16
10
20
9
20
9
9
10
10
11
20
9
292
0
14
2
2
2
1
5
3
0
0
0
9
1
4
0
0
0
0
0
0
1
2
9
1
2
58
Proportion
of correct
Matches
1
0.588235294
0.909090909
0.818181818
0.777777778
0.888888889
0.666666667
0.727272727
1
1
1
0.526315789
0.928571429
0.8
1
1
1
1
1
1
0.909090909
0.833333333
0.55
0.952380952
0.818181818
Inexperienced Matcher
Proportion
of correct
INCORRECT CORRECT Matches
8
2
0.8
10
10
0.5
14
0
1
7
4 0.636363636
3
15 0.166666667
2
13 0.133333333
5
8 0.384615385
5
4 0.555555556
12
7 0.631578947
4
2 0.666666667
8
12
0.4
5
8 0.384615385
14
5 0.736842105
8
15 0.347826087
1
2 0.333333333
15
14 0.517241379
3
6 0.333333333
15
3 0.833333333
3
1
0.75
6
10
0.375
3
0
1
7
5 0.583333333
5
7 0.416666667
8
8
0.5
6
12 0.333333333
177
173
The proportion of correct matches per encounter for each of the observers has been
plotted in Figure 3.
16
1.2
1
Experienced
experimenter
0.8
0.6
Naïve
experimenter
0.4
0.2
0
20-06-08-enc03
20-06-08-enc01
16-06-08-enc04
16-06-08-enc01
08-06-08-enc13
08-06-08-enc11
08-06-08-enc09
08-06-08-enc06
08-06-08-enc04
08-06-08-enc02
03-06-08-enc06
03-06-08-enc04
03-06-08-enc01
Proportion of correct matches
Proportion of correct matches for two human
exerimenters
Encounter number
Figure 3 Proportion of corect matches per encounter for Experianced and Naive experimenter.
Figure 3 shows the number of correct matches for a naïve experimenter are generally
lower than those of an experienced experimenter; the difference between these results
was tested statistically using a t-Test the results of which are shown in table 7.
Table 7 Results of a t-Test between the proportions of correct matches for two experimenters.
t-Test: Two-Sample Assuming Equal Variances
Experienced Experimenter
Variable 1
Mean
0.86776
Variance
0.02351
Observations
25
Pooled Variance
0.038382
Hypothesized Mean Difference
0
Df
48
t Stat
6.045078
P(T<=t) one-tail
1.07E-07
t Critical one-tail
1.677224
P(T<=t) two-tail
2.14E-07
t Critical two-tail
2.010635
Naïve Experimenter
Variable 2
0.532786
0.053254
25
Table 7 shows the proportion of correct matches for a naïve experimenter are
significantly lower than the proportion of correct matches made by an experienced
experimenter with a p value of 1.07-7 (2.d.p.). As well as having a significantly higher
17
proportion of correct matches the number of correct matches per encounter also varied
less when being matched by an experienced experimenter showing more consistent
results than those gained by a naïve experimenter. These findings support Gailey’s
(2001) statement that to reliably identify individuals by subtle natural markings a
degree of learned experience is necessary.
3.3. Comparison of Methods;
To find which method gave more correct matches the proportion of possible matches
estimated using EuroPhlukes© within each encounter was compared with proportion
of correct matches per encounter made by an experienced experimenter by eye. The
number of matches found by an experienced, rather than naïve experimenter were
used as these showed less varience. The encounters used for this comparison and the
proportion of matches estimated using both methods are shown in figure 4;
1
0.9
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
Europhlukes
Matching
Human
Matching
14-06-08-enc01
08-06-08-enc09
08-06-08-enc08
08-06-08-enc06
08-06-08-enc05
08-06-08-enc04
08-06-08-enc02
03-06-08-enc06
03-06-08-enc05
03-06-08-enc04
03-06-08-enc03
03-06-08-enc01
Proportion of estimated matches
Proportion of estimated matches per encounter using
EuroPhlukes© and a Human Matcher
Encounter Number
Figure 4 The proportion of matches within each encounter estimated using EuroPhlukes© and
an experiences human experimenter.
18
The proportion of estimated matches using EuroPhlukes© within each encounter are
lower on 11 out of 12 encounters than those estimated bye eye. The proportion of
matches also vary greatly between the two methods, the difference between these
proportions was calculated statistically using a t-Test, the results of which are shown
in table 8;
Table 8 T-Test of the difference between the proportion of matches estimated using
EuroPhlukes© and the proportion of matches estimated using a human experimenter per
encounter.
t-Test: Two-Sample Assuming Equal Variances
EuroPhlukes© matching
Variable 1
Mean
0.332163743
Variance
0.052748787
Observations
12
Pooled Variance
0.041614332
Hypothesized Mean Difference
0
Df
22
T Stat
-6.232790327
P(T<=t) one-tail
1.42044E-06
T Critical one-tail
1.717144335
P(T<=t) two-tail
2.84088E-06
T Critical two-tail
2.073873058
Human matching
Variable 2
0.851237
0.03048
12
There is a significant difference between the proportion of matches estimated using
EuroPhlukes© and the proportion of correct matches made by a human experimenter
with a p factor of 1.42-6(2.d.p.). The mean proportion of matches found was lower
using EuroPhlukes© than by a human experimenter.
4. Discussion;
Two errors reported in analysis of photographic identification data are missed
matches and falsely identified individuals (IWC, 1990,) this study showed both errors
occur with the use photographic identification of basking sharks.
4.1. EuroPhlukes© Photographic Identification;
19
The mean proportion of possible matches estimated using EuroPhlukes© was
evaluated as 0.33 (2.d.p.), although the probability that these were correct was
significantly higher than that of them being incorrect; the proportion of 0.67(2.d.p)
missed matches equates to an unacceptable loss of data.
4.2. Human Photographic Identification;
Human matching of photographic data gave a much higher proportion of correct
matches compared to that estimated using EuroPhlukes© with a mean proportion of
0.85 (2.d.p), however a combined proportion of 0.15 (2.d.p.) false matches and
consequently missed matches show this method is not applicable to mark-recapture
population assessment, since even a small number of mismatches will impact
population estimates considerably (Shweder, 2003.)
4.3. Methodology problems;
One problem with the methodology of this study is the assumption that each
encounter consists of a different shark, although this ensures photographs within the
same encounter are definitely the same shark; it also allows the possibility of false
negatives. For example the photographs in Figure 5 are from separate encounters but
are similar and could possibly be the same shark.
Figure 5 Photographs gathered in separate encounters which show similar fins.
20
It is not possible to prove whether the two photographs in Figure 5 are the same or
different sharks from data gathered in this study. In population assessment using
photographic identification the same problem could occur, either two similar sharks
could be classed as the same shark resulting in underestimation, or as is the case with
this study two similar looking fins could be classed as different individuals when they
may be the same shark resulting in overestimation of population size. This indicates
that the dorsal fin of basking sharks may not be distinctively unique to each individual
and therefore not a suitable feature for individual identification.
4.4. Photographic identification of basking sharks for mark-recapture studies;
A proportion of 0.85(2.d.p) correct matches is not acceptable for accurate application
to mark-recapture studies, however even if this could be increased to the ideal
proportion of 1, there are still problems with the use of photographic identification of
basking sharks for mark-recapture population analysis.
Capture-recapture data derived from photographic identification can be biased and not
easily applied unless carefully designed and validated (e.g. Hammond, 1990; Agler,
1992). The most critical underlying assumptions of capture recapture studies are that
the studied population are; 1) geographically closed, sometimes even demographically
closed; 2) that all individuals have equal capture probabilities; 3) that all observed
marks are reported and 4) that marks are permanent over a given period (IWC, 1990).
1) Geographically and demographically closed;
The assumption that populations analysed are geographically or demographically
closed may be accounted for using population models with open robust multi-strata
design.
2) All individuals have equal capture probabilities:
21
Photographic analysis of populations could violate the assumption that all individuals
are equally catchable if more distinctive individuals are included into the
photographic database despite lower quality photographs; this would result in
distinctive individuals having higher capture frequencies than less distinctive
individuals, thus inducing capture bias (Gailey, 2001).
It has been shown with Mediterranean monk seals (Forcada and Aguilar, 2000), that
marks in juveniles are non-existent or far more subtle than adults as they are acquired
with age as a result of interaction with other animals and the environment, if this is
also the case with basking sharks capture probabilities may be demographically
biased toward the older, more distinctive individuals. The standardised assessment of
quality applied to each photograph regardless of distinctiveness used in this study
reduces the possibility of capture bias towards distinctive individuals.
To reduce the possibility of violating the assumption of equal capture possibilities in
future studies, it is necessary to develop a universal ranking for photographic quality
and individual distinctiveness and apply these independently to all photographs
obtained (Hammond, 1988). However this may be difficult if photographs are to be
matched by humans as “due to the complexity and current lack of understanding of
the human visual system there is no “silver bullet” to measure image quality
(Metravali and Hashell, 1989). In order to account for this there are two options,
either one observer must assess all photographs (as was the case with the current
study) or groups of observers with the same mean opinion score for image quality and
distinctiveness must be used to assess sets of photographs.
Another way by which photographic identification could violate the assumption of
equal capture of individuals is that photographs can only be taken when sharks
22
display basking behaviour which, as stated in the introduction, can be variable
(Southall et al. 2006).
To calculate the extent by which the assumption of equal capture of individuals is
violated by photographic identification, the proportion of tagged individuals correctly
identified using photographic identification could be measured, if satellite tags were
used this could also account for differences in surfacing behaviour, however until
processes of tagging sharks can be applied when the shark is not at the surface this
may never be fully accounted for.
3) All observed marks are reported:
The use of photographs encompassing the whole fin should ensure all marks available
for use in identification are reported; however this is not always possible, collecting
suitable images from a moving platform is a difficult and potentially dangerous task.
The basking shark fin can grow up to 2 meters in height and unless the point where
the fin joins the sharks back is shown in the photograph it is often impossible to
estimate what proportion of the fin is still below the water, the two photographs in
figure 6 show two photographs of the same shark with different proportions of the fin
showing.
Figure 6 Photographs of the same shark which show different proportions of the fin.
Figure 6 shows that if part of the fin is hidden then not all marks are reported.
23
4) That marks are permanent over a given period:
Concerning the use of photographic identification of basking sharks using images of
there dorsal fin, violation of the assumption that marks are permanent over a given
time is potentially high. Even if two photographs of the same animal fulfil all
requirements they can look completely different due to the flexibility of the basking
sharks dorsal fin. The two photographs shown in Figure 7 can be scored highly for all
categories used to rate photographs (shown in the method section of this paper); these
photographs were taken on the same encounter and are therefore definitely the same
shark.
A
B
Figure 7 Photographs of the same shark showing fin flexibility.
Photograph A (see Fig. 7) shows the best photograph within the encounter in which it
was taken, photograph B shows the same individual with the fin flopped over.
Without knowing that the two photographs in Figure 7 were taken during the same
encounter it is unlikely that they would be matched together, this illustrates the
difficulty of using a changeable feature for photographic identification of individuals.
One advantage human matching has over the EuroPhlukes© program is that
EuroPhlukes© is confined to using only the shape of fin and nicks on its trailing edge
which, as displayed in Figure 7, can be dramatically affected by the flexibility of the
24
fin; whereas human observers are able to use scars and pigmentation on the whole fin
to match photographs of the same individual.
For long term photographic identification studies these marks must remain constant or
very similar between capture occasions, however it is not known whether this is the
case with basking sharks. There is no literature which looks closely at the changes in
these marks and scars overtime. Although studies carried out on dolphins and
porpoises show that some body scars and pigmentation patters persist over many
years (Markowitz et al. 2003) and changes in markings of Monk Seals (Monachus
monachus) over three years had no effect on matching of individuals, the skin of the
basking shark is much different from that of marine mammals.
Basking shark skin has a covering of dermal denticles (small tooth like placoid scales)
that protect the skin from parasites and damage (Springer and Gilbert, 1976); their
presence may result in the formation of fewer natural markings for use in
identification. The basking sharks skin is also criss-crossed with varying patterns of
2mm deep creases which are bare of denticles; these creases correspond with lines of
flexure (Mathews and Parker, 1950). Flexibility of skin could result in alteration of
scars and patterns on the dorsal fin reducing the reliability of these marks for
identification.
The ability to use marks and scars on the skin for photographic identification could
also be affected by healing of the skin. As a group, sharks have displayed an
incredible ability to recover from serious injury. During research in French Polynesia
Johann Mourier et al. (2007) found evidence that one sickle fin lemon shark
(Negaprion acutidens) which had its fin sliced open from the tip to half way down,
recovered within a number of months and the fin returned to its original shape.
Although an obvious black scar remained, the length of time this would be visible was
25
unclear. The occurrence of changes in scaring over time was also seen in a study
conducted on Whale Sharks (Rhincodon typus) where a number of healed scars were
observed (Speed et al. 2008).
Although no experimental proof has been provided on changes in marks of basking
sharks over time, it has been observed that markings on the dorsal fin obvious to the
naked eye are not always reliable for identifying individuals; For example dorsal fins
often have abrasions especially on the leading edge probably arising from mating or
swimming through fishing gear, these markings are quite short lived and heal over
time. Similarly lamprey (Lampetra fluviatilis) scars will change from very obvious to
unclear and may even disappear. It was suggested that when looking at characteristic
features of fins, notes on a selection of features should be taken and experimenters
should bear in mind how these characteristics may change over time. It was however
stated that if images are matched within a single year, then it is unlikely that scars
would heal enough to be missed by a human experimenter (A. Reeve personal
communication, 2008). Consequently the use of marks and scars on the dorsal fin of
basking sharks for individual identification could only be a reliable method when used
in conjunction with other features and when photographs are taken within the same
year.
4.5. Reliability of Basking Shark Photographic Identification;
The best results for photographic matching were gained using human eye matching,
however this still has an inacceptable proportion of mismatches, this factor coupled
with; the inability to distinguish similar fins as the same or different individuals; the
possibility of bias towards capture of distinct individuals; the difficulty in obtaining
photographs which report all marks present on the fin; and changes in appearance of
the fin due to its flexibility plus the likelihood that marks and scars may heal over
26
time, shows the use of photographs of the dorsal fin of basking sharks for individual
identification violates many of the underlying assumption of capture recapture
population assessment methods. Photographic identification of basking sharks is
therefore limited to studies of distinct individuals where recapture occasions are
within a year and photographs of the whole dorsal fin when completely up right are
gained.
In conclusion photographic identification of individuals based on the dorsal fin can
not be reliably applied to mark-recapture population assessments of basking sharks.
4.6. Future study;
Satellite tags are being increasingly used in the study of basking sharks, these may
prove very useful in increasing our knowledge of life history traits of the species,
however to use these tags for mark-recapture analysis is impossible as a large
proportion of individuals would need to be tagged and satellite tags are currently very
expensive.
Alternate methods of photographic identification of basking sharks are being explored
such as the use of variation in skin patterns (L. Southwood, personal communication,
2008) however obtaining photographs of suitable quality is a limiting factor with this
method.
Genetic analysis has given estimates of population size of roughly 8200 individuals;
this is deemed to be surprisingly low for a world wide population (Hoelzel et al.
2006.) These studies go on to suggest that further reductions in diversity evolutionary
potential could be affected. However genetic analysis has so far been limited to dead
animals.
For population analysis, mark-recapture data would be highly beneficial, capturerecapture studies on the Hawaiian monk seal (Monachus schauinslandi) show better
27
results than photographic identification using plastic tags to mark animals (Gilmartin
et al. 1993; Craig and Ragen, 1999; Forcada and Aguilar, 2000), as natural markings
are slightly unreliable, robust plastic tags combined with photographic data could give
more accurate population estimations. This method is currently being explored by the
Irish Whale and Dolphin Group.
Individual identification is extremely reliable using genetic analysis, in the past this
was restricted to dead animals, a possible solution to this problem is the use of biopsy
darts, and this method also has the advantage that samples could be taken during
systematic aerial surveys which would reduce the bias of opportunistic surveying.
One draw back however is that this method would require repeated disturbance of the
animal to gain samples for data analysis, if future technological advances allow the
creation of implanted identity chips which could be read by aerial or boat based
systematic surveys, data gained may be more reliable, although the procedure of
implantation would most likely have to be carried out at the waters surface inducing
some bias.
However, it is no longer a case of gaining information to calculate sustainable levels
of exploitation, it is necessary to reduce levels of harvesting, and protect areas
important for reproduction in order to increase numbers in an already dwindling
population.
References;
Agler, B.A., 1992. Testing the reliability of photographic identification of individual fin
whales (Balaenoptera physalus). Report of the International Whaling Commission 42:731737.
Anderson, E.D., 1990. Fishery models as applied to elasmobranch fisheries. In
Elasmobranchs as living resources: advances in the biology, ecology, systematics and status
of the fisheries (ed. H.L. Pratt et al.), pp. 473-484. Seattle, WA: National Oceanic and
Atmospheric Administration. [NOAA Technical Report, no. 90.]
28
Anderson, S.D., Goldman, K.J., 1996. Photographic evidence of white shark movements in
California waters. Calif. Fish Game 82, 182–186.
Arnbom, M. T., 1987. Individual identification of sperm whales. Report of the International
Whaling Commission 37:20 1-204.
Beck, C, A. and Reid. P., 1995. An automated photo-identification catalogue for studies of
the life history of the Florida manatee. Pages 120-134 in T. J. OShea, B. B. Ackerman and H.
F. Percival, eds. Population biology of the Florida manatee. National Biological Service
Information and Technology Report 1, Washington, DC.
Berata, T., and Brooks, S.P. (2005). Dolphin Who’s Who: A Statistical Perspective.
Statistical Laboratory, Centre for Mathematical Sciences, Wilberforce Road, Cambridge,
CB3 0WB, UK
Bergman, P.K., Haw, F., Blankenship, H.L., Buckley, R.M., 1992. Perspectives on design,
use, and misuse of fish tags. Fisheries 17, 20–25.
Bigg, M. A. 1982. An assessment of killer whale (Orcinus orca) stocks off Vancouver Island,
British Columbia. Report of the International Whaling Commission 32: 655-666.
Clapham, P. J., and Mayo, C. A., 1990. Reproduction of humpback whales (Megaptera
novaeangliae) observed in the Gulf of Maine. Report of the International Whaling
Commission (Special Issue 12):171-176
Clapham, P.J., and Mayo, C.A., 1990. Reproduction of humpback whales (Megaptera
novaeangliae) observed in the Gulf of Maine. Report of the International Whaling
Commission (Special issue 12):171-176.
Compagno, L.J.V., 2001. Sharks of the world: an annotated and illustrated catalogue of shark
species known to date. Bullhead, mackerel and carpet sharks (Heterodontiformes,
Lamniformes and Orectolobiformes), vol. 2. Rome, Italy: FAO.
Cotton, P.A., Sims. D.W., Fanshaw, S. and Chadwick, M., (2005). The effects of climate
variability on zooplankton and basking shark (Cetorhinus maximus) relative abundance off
southwest Britain. Fish. Oceanogr. 14:2, 151–155
Courtney, A. J., Cosgrove, M.G., Die, D. J., 2001. Population dynamics of scyllarid lobsters
of the genus Thenus spp. on the Queensland (Australia) east coast I. Assessing the effects of
tagging. Fish. Res. 53, 251–261.
Craig, M.P., and Ragen. T.J., 1999. Body site, survival, and decline of juvenile Hawaiian
monk seals, (Monachus schauinslandi.) Marine Mammal Science 15:786-809.
da-Silva, C.Q., Rodrigues, J., Leite, J.G., and Milan, L.A. (2003) Bayesian Estimation of the
Size of a Closed Population Using Photo-identification Data with Part of the Population
Uncatchable. Communication in Statistics, Simulation and Computation. Vol. 32, NO. 3. pp.
677-696.
Doody, J.S., 1995. A photographic mark–recapture method for patterned amphibians.
29
Herpetol. Rev. 26, 19–21.
FAO. International Plan of Action for reducing incidental catches of seabirds in longline
fisheries. International Plan of Action for the conservation and management of sharks.
International Plan of Action for the management of fishing capacity. Rome, FAO. 1999. 26p.
Forcada, J., Aguilar, A., (2000) Use of Photographic Identification in Capture-Recapture
studies of Mediterranean Monk Seals. Marine Mammal Science, 16(4); 767-793.
Frisch, A. J., 2007a. Short- and long-term movements of painted lobster (Panulirus
versicolor) on a coral reef at Northwest Island, Australia. Coral Reefs 26, 311–317.
Frisch, A.J., Hobbs, J-P.A., (2007). Photographic identification based on unique, polymorphic
colour patterns: A novel method for tracking a marine crustacean. Journal of Experimental
Marine Biology and Ecology 351 (2007) 294–299.
Fujiwara, M. & Caswell, H. (2001). Demography of the endangered North Atlantic right
whale. Nature 414, 537–541.
Gaba, E., 2007. Map in English of the Isle of Man. Available from;
http://upload.wikimedia.org/wikipedia/commons/thumb/9/92/Isle_of_Man_topographic_mapen.svg/300px-Isle_of_Man_topographic_map-en.svg.png. This page was last modified on 4
September 2008, at 14:41.
Gailey, G.A., (2001). Computer Systems For Photo-Identification and Theodolite tracking of
Cetaceans. Texas A&M University Press.
Gilmartin, W.G., Johanos, T.C., Eberhardt, L.L., 1993. Survival rates for the Hawaiian monk
seal (Monachus schauinslandi). Marine Mammal Sciance 9:407-420.
Grellier, K., Hammond, P.S., Wilson, B., Sanders-Reed, C.A., and Thompson, P.M. (2003).
Use of photo-identification data to quantify mother–calf association patterns in bottlenose
dolphins. Can. J. Zool. 81: 1421–1427.
Hammond, P.S., 1986. Estimating the size of naturally marked whale populations using
capture-recapture techniques. Reports of the International Whaling Commission (Special
Issue 8):253-282.
Hammond, P.S., 1988. Some problems in estimating population size from individual
recognition data. British Antarctic Survey Report SC/A88/ID4. Sea Mammal Research Unit,
Cambridge, UK CB30ET.
Hammond, P.S., 1990. Heterogeneity in the Gulf of Maine? Estimating humpback whale
population size when capture probabilities are not equal. Report of the International Whaling
Commission (Special Issue 12): 135-1 39.
Hammond, P.S., Mizroch, S.A., Donovan, G.P., 1990. Individual Recognition of Cetaceans:
Use of Photo-identification and other Techniques to Estimate Population Parameters.
International Whaling Commission, Cambridge.
Harbour Branch Oceanographic Institution, Division of Dolphin Research and Conservation,
30
2003. Advances in Digital Photography and Application for the Study of Marine Mammals.
15th Biennial Conference on the Biology of Marine Mammals Greensboro, North Carolina.
Hiby, A. R., and Lovell, P., 1990. Computer aided matching of natural marks: A prototype
system for gray seals. Report of the International Whaling Commission (Special Issue 12):5762.
Hiby, A. R., and. Jeffery J. S., 1987. Census techniques for small populations, with special
reference to the Mediterranean monk seal. Zoological Symposium 58: 193-210.
Hoelzel, A.R., 2001. Shark fishing in fin soup. Conserv. Genet. 2, 69-72. (doi:10.
1023/A:1011590517389)
Hoelzel, R.A., Shivji, M.S., Magnussen, J., and Francis, M.P., (2006). Low worldwide
genetic diversity in the basking shark (Cetorhinus maximus). Biol.Lett. (2006) 2, pp 639-642.
Irvine, A.B., Wells R.S., and M.D. Scott., 1982. An evaluation of techniques for tagging
small odontocete cetaceans. Fishery Bulletin 80:135-143
IUCN 2004 http://www.redlist.org/.
IWC. 1990. Report of the workshop on individual recognition and the estimation of cetacean
population parameters. Report of the International Whaling Commission (Special Issue 12):317.
Jones, M. L., 1990 The reproductive cycle in gray whales based on photographic resightings
of females in the breeding grounds from 1977-82. Report of the International Whaling
Commission (Special Issue 12):177-182.
Katona, S.K. and Beard, J.A., 1990. Population size, migrations, and feeding aggregations of
the humpback whale, Megaptera novaeangliae, in the western North Atlantic Ocean
(SC/A88/ID17). Reports of the International Whaling Commission (Special Issue 12):295305.
Katonas., K., and Krauss, S., 1979. Photographic identification of individual humpback
whales (Megaptera novaeangliae): Evaluation and analysis of the technique. US Department
of Commerce, NTIS Publication, Springfield, VA.
Kelly, C., Clegg, G.A., Speedie, C.D., (2004). Management of marine wildlife disturbance.
Ocean & Coastal Management 47 (2004) 1–19.
Kelly, M. J., 2001. Computer-aided photograph matching in studies using individual
identification: An example from the Serengeti cheetahs. J. Mammal. 82, 440–449.
Kunlik, P. A., 1988. The basking shark. Scottish Fisheries Information Pamphlet. Dafs, no.
14, 21pp.
Linnane, A., Mercer, J.P., 1998. A comparison of methods for tagging juvenile lobsters
(Homarus gammarus L.) reared for stock enhancement. Aquaculture 163, 195–202.
Markowitz, T. M., Harlin A. D., and B. Würsig., 2003. Digital photography improves
31
efficiency of individual dolphin identification. Marine Mammal Science 19:217–223.
Mathews, L.H., and Parker, H.W., (1950). Notes on the anatomy and biology of the basking
shark (Cetorhinus maximus). Gunner Proc. Zool. Soc. lond. 120:535-576.
Meekan, M. G., Bradshaw, C. J. A., Press, M., McLean, C., Richards, A., Quasnichka, S. &
Taylor, J. G. (2006). Population size and structure of whale sharks (Rhincodon typus) at
Ningaloo Reef, Western Australia. Marine Ecology Progress Series 319, 275–285.
Mizroch, S.A., (2003) Digital Photography Improves Efficiency of Individual Dolphin
Identification: A Reply to Markowitz et al. Marine Mammal Science, 19(1):612-614.
Mourier, J., Burray, N., Clua, E., Planes, S., (2007). Ecology and behaviour of sickle fin
lemon shark (Negaprions acutidens) population at Moorea Island (French Polynesia). 11th
Annual Science Conference of the European Elasmobranch Association. pp. 23 -26.
Persat, H., 1982. Photographic identification of individual grayling (Thymallus thymallus)
based on the disposition of black dots and scales. Freshwater Biol. 12, 97–101.
Scarrat, D.J., 1970. Laboratory and field tests of modified sphyrion tags on lobsters (Homarus
americanus). J. Fish. Res. Board Can. 27, 257–264.
Schweder, T.,(2003). Abundance Estimation from Multiple Photograph Surveys: Confidence
Distributions and Reduced Likelihoods for Bowhead Whales off Alaska. Biometrics 59, 974983.
Scott, M.D., Wells R.S., Irvine A.B., and. Mate B.R. 1990. Tagging and marking studies on
small cetaceans. Pages 489-514 in S. Leatherwood and R.R. Reeves, eds. The bottlenose
dolphin. Academic Press, San Diego.
Shark Trust, (2008). Basking Shark (Cetorhinus
http://www.baskingsharks.org/default.asp?home=1
maximus).
Available
from:
Sims, D.W. & Quayle, V. A., 1998. Selective foraging behaviour of basking sharks on
zooplankton in a small-scale front. Nature, London, 393, 460-464.
Sims, D.W., (2000). Filter-feeding and cruising swimming speeds of basking sharks
compared with optimal models: they filter-feed slower than predicted for their size. Journal of
Experimental Marine Biology and Ecology. 249 (2000) 65–76.
Southall, E.J., Sims, D.W., Metcalfe, J.D., Doyle, J.I., Fanshawe, S., Lacey, C., Shrimpton, J.,
Solandt, J-L., and Speedie, C.D. (2005). Spatial distribution patterns of basking sharks on the
European shelf: preliminary comparison of satellite-tag geolocation, survey and public
sightings data. J. Mar. Biol. Ass. U.K. (2005), 85, 1083-1088.
Southall, E.J., Sims, D.W., Witt, M.J., Metcalfe, J.D., Seasonal space-use estimates of
basking sharks in relation to protection and political-economic zones in the North-east
Atlantic. Biological Conservation 123(2006)33-39.
Speed, C.W., Meckhan, M.G., Rowat, D., Pierce, S.J., Marshall, A.D. and Bradshaw, C.J.A.
32
(2008). Scarring patterns and relative mortality rates of Indian Ocean Whale sharks
(Rhincodon typus).
Speed, C. W., Meekan, M. & Bradshaw, C. J. A., 2007. Spot the match – wildlife photoidentification using information theory. Frontiers in Zoology 4, 2.
Springer, S., and Gilbert, P.W., 1979.The basking shark, Cetorhinus maximus, from Florida
and California with comments on its biology and systematics, Copeia, Vol 1979 No1, pp. 4754.
Stevick, P. T., Palsbøll, P. J., Smith, T. D., Bravington, M. V. & Hammond, P. S., 2001.
Errors in identification using natural markings: rates, sources, and effects on capture–
recapture estimates of abundance. Canadian Journal of Fisheries and Aquatic Sciences 58,
1861–1870.
Stonehouse, B., 1978. Animal Marking. Macmillan Press, London.
United Kingdom of Great Britain and Northern Ireland (on behalf of the Member States of
the European Community). Inclusion of the Basking Shark (Cetorhinus maximus) on
Appendices I and II Prop. 12.36- pp.1-35
Würsig, B. and T.A. Jefferson. 1990. Methods of photo-identification for small cetaceans.
Reports of the International Whaling Commission (Special Issue 12): 43-52.
Würsig, B., and Würsig, M., (1977). The photographic determination of group size,
composition and stability of coastal porpoises (Tursiops truncatus). Science 198:755-756
Yochem, P. K., Stewart, M., Mina, M., Zorin, A., Sadovov, V., and Yablokov, A., 1990.
Non-metrical analyses of pelage patterns in demographic studies of harbour seals. Report of
the International Whaling Commission (Special Issue 12):87-90.
33
Appendices;
Appendix I: Project Proposal;
June 2008.
Individual Identification of Basking Sharks (Cetorhinus maximus) using digital
photographs of dorsal fins.
Literature review;
Basking sharks (Cetorhinus maximus) are the second largest fish species with a
circum-global distribution in warm temperate to boreal seas (Cotton et al., 2005.)
They are associated with continental shelf edge habitats where they often aggregate to
forage on dense patches of zooplankton associated with oceanographic features (Sims
and Quayle., 1998; Sims et al., 2006.)
Life history traits of basking sharks are not fully known, however it has been
suggested that their maturation rate is slow taking between 12-20 years and females
have long gestation periods (approximately 1-3 years) after which they give birth to
few offspring. Consequently basking sharks are especially vulnerable to over
exploitation. In the past they have been exploited for meat, fins, liver oil (Compagno,
2001) and cartilage (Hoelzel, 2001). The inherent vulnerability to high levels of
exploitation may have resulted in collapse of some stocks (Anderson, 1990). For
example, the fishery for basking shark near Achill Island off the west coast of Ireland
appeared to collapse in the early 1960’s after only ten years of peak catches (Kinzlik,
1988.) In 1999 the FAO made international plans of action their aims were to ensure
conservation and management of sharks and their long term sustainable use however
participation was voluntary and no new shark management measures were
34
implemented it therefore seemed unlikely that the plans would be sufficient to
develop sustainable management.
The possibility that basking shark numbers are depleted by exploitation from fisheries
and lack of scientific knowledge of the species has resulted in their listing as
vulnerable (A1a, d +2d) worldwide, and Endangered (EN A1a,d) in the north east
Atlantic in the IUCN Red List (IUCN, 2004). In 2000, the species was listed in
Appendix III of the Convention on International Trade in Endangered Species (Cites).
In 2002, on the basis of the UK proposal, CITES listing was upgraded to Appendix II
which requires that International tread in these species is monitored through a
licensing system to ensure that trade can be sustained without detriment to wild
populations. 2001 European quota of total allowable catch reduced to 0 (Southall et
al, 2006.) Despite the conservation concern for this species there are few data on
regional abundance, no estimates for abundance worldwide and no good data on
population trends (Hoelzel et al., 2006.) The threatened status of the basking shark
have prompted a need to understand population distribution, habitat preferences and
centers of abundance It has been stated that without scientifically based population
assessment it is impossible to determine current population trends and monitor stocks
effectively for conservation purposes (Southall et al, 2005.)
One group of methods of population assessment which has been extensively in studies
of animal ecology are mark release-recapture techniques these are often employed for
determining patterns in growth, survivorship behaviour and abundance of organisms
(Stonehouse, 1978.) This method can however be problematic as it is not always
possible to mark certain types of animals, either because they are difficult to tag or
because they are legally protected from disturbance as is the case with some cetaceans
(Hammond et al, 1990.) Tags which are invasive could alter behaviour, growth and
35
(or) survivorship of the host animal by causing physical hindrance, injury, disease or
physiological interference (Scorrat, 1970; Bergmas et al., 1992; Linnare + Merar,
1998; Courtney et al., 2001.) One solution to this problem is to identify individual
animals using variation in natural marks and (or) polymorphic colour patterns. If this
is the case photographs taken of individuals at different points of time can be used for
mark recapture techniques (Frisch and Hobbs, 2007.)
Photographic identification has been widely used to study vertebrates (e.g. Persal,
1982; Hammond et al, 1990; Doody, 1995; Anderson and Goldman, 1996; Kelly
2001.) These techniques have been developed to obtain individual marking data of
marine mammals (e.g. Wursig and Wursig, 1977; Katona and Krauss, 1979; Hiby and
Lovell, 1990; Beck and Reid, 1995) and succefully applied to a number of species and
populations (e.g. Bigg, 1982; Chapham and Mayo, 1990; Jones, 1990, Lochem et al,
1990.)
These findings are promising however in some cases capture recapture data derived
from photo id may be biased and can not be easily applied unless carefully designed
and validated (e.g. Hammond, 1990; Agler, 1992.) The most critical underlying
assumptions of capture recapture studies are that the studied population are
geographically closed, sometimes even demographically closed, that all individuals
have equal capture probabilities, that all observed marks are reported and that marks
are permanent over a given period (IWC, 1990.) Using population models with open
robust multi-strata design could take into account the geographic and demographic
variance in population structures. To address the fact that individuals would most
often be photographed at the surface if a significant number of those individuals
photographed were also given satellite tags then individual sight-ability could
possibly be calculated using the number of times it was photographed in an area it
36
was recorded to be in. It is necessary however that individual can be correctly
identified from their photographs. There have been indications from previous studies
that the reliability of photo id methods depend on the species involved, the sampling
strategy and the kind of natural marks used to identify individuals (Arnbom, 1987,
Hiby and Lovell, 1990.)
This paper looks at the use of photographic identification of individual basking sharks
using human experimenters and the computer assisted matching program
EuroPhlukes©.
Method;
Photographic collection and cataloguing;
The photo-identification material will be collected in coastal waters off the Isle of
Man between the 3rd and 30th of June 2008. The study shall be conducted on the
Southern side of the island between Port St Mary and Peel Harbour from a 15ft motor
boat. Surveys will take place at various times of day for varying lengths of time in
different weather conditions, however photographs shall not be taken during heavy
rain to avoid damage to camera equipment, data will be collected in various sea states
but photographs will not be taken in sea state five to ensure the experimenter’s safety.
During a survey the boat shall travel out of Port St Mary’s Harbour along the coast
towards peel Harbour. On sighting basking sharks the boat shall approach at an
extremely slow speed to a distance of 20m come to a stop and the engine shall be put
in neutral. Each shark will be photographed using a Cannon 400d digital camera with
55mm-250mm lens with image stabiliser. On each encounter multiple photographs
will be taken of the basking shark’s dorsal fin. The photographer will attempt to take
37
at least 10 photographs from both sides which encompass a large proportion of the fin
at as close to 90º angle as possible. On each sighting date of sighting, encounter
number, time, position of sighting along with any distinguishing features and an
estimation of the basking shark’s size shall be recorded in order to assist accurate data
entry. In order to ensure photographs collected are definitely of the same individual
each encounter occasion was considered to be a different individual.
For analysis all photo’s shall be transferred to a personal computer, these raw
photographs will be catalogued first by date taken then by encounter number and
finally by image number. Photographs will then be edited using ACDSee Pro Photo
Manager© version 8.0, this editing will involve cropping the images to include only
the dorsal fin, images not showing the dorsal fin shall be disregarded, the resulting
catalogue will be saved separately as cropped raw photo’s.
The quality of these photo’s will then be rated as excellent (1) good (2) or poor (3),
this evaluation will be based on that proposed by Hammond (1986) which uses the
categories of; focus, glare, angle ,distance from the individual and the proportion of
individual photographed. However the category of glare shall be excluded and
replaced by the angle of light on the fin, where photo’s with the light shining onto the
fin will be rated higher than those will the light coming from behind, the proportion of
individual photographed shall also be adapted to the proportion of individuals fin
photographed. Distance from the animal shall also be excluded as this will always be
within 20m. Consequently categories for rating the photographs will be; focus angle
of fin, light direction and the proportion of fin photographed.
Once all the photographs have been rated the ten best images of each encounter (from
both sides of the fin if possible) will be selected and saved in a separate catalogue
named basking shark top ten, this will still be arranged under date taken then
38
encounter number then image number. From this catalogue a third catalogue a third
catalogue will be created by taking the best quality photo from each encounter this
shall be named basking shark best photographs. After all the photographs have been
organised in this way the matching process will begin.
Matching photographs;
Matching the photo’s will involve hiding all the labels of photo’s in the top ten
catalogue, randomising their order and matching them to those in the basking shark
best photographs catalogue. The matching will be carried out firstly by eye and
secondly using the computer assisted matching program EuroPhlukes© which uses
the contour of the fin and nicks in the fin to match photographs of the same
individual.
Analysis;
For analysis the labels of photos from the “basking shark top ten” catalogue shall be
revealed and the proportion of photographs correctly matched will be calculated using
the separate techniques. Pearsons χ2 statistics can be used to test differences in
proportions.
References;
Anderson, E.D., 1990. Fishery models as applied to elasmobranch fisheries. In
Elasmobranchs as living resources: advances in the biology, ecology, systematics and
status of the fisheries (ed. H.L. Pratt et al.), pp. 473^484. Seattle, WA: National
Oceanic and Atmospheric Administration. [NOAA Technical Report, no. 90.]
Anderson, S.D., Goldman, K.J., 1996. Photographic evidence of white shark
movements in California waters. Calif. Fish Game 82, 182–186.
Arnbom, M. T., 1987. Individual identification of sperm whales. Report of the
International Whaling Commission 37:20 1-204.
Beck, C.A. and Reid, P., 1995. An automated photo-identification catalogue for
studies of the life history of the Florida manatee. Pages 120-134 in T. J. OShea, B. B.
Ackerman and H. F. Percival, eds. Population biology of the Florida manatee.
39
National Biological Service Information and Technology Report 1, Washington, DC.
Bergman, P.K., Haw, F., Blankenship, H.L., Buckley, R.M., 1992. Perspectives on
design, use, and misuse of fish tags. Fisheries 17, 20–25.
Bigg, M. A., 1982. An assessment of killer whale (Orcinus orca) stocks off
Vancouver Island, British Columbia. Report of the International Whaling
Commission 32: 655-666.
Clapham, P. J., and Mayo. C. A., 1990. Reproduction of humpback whales
(Megaptera novaeangliae) observed in the Gulf of Maine. Report of the International
Whaling Commission (Special Issue 12):171-176
Courtney, A. J., Cosgrove, M. G., Die, D. J., 2001. Population dynamics of scyllarid
lobsters of the genus Thenus spp. on the Queensland (Australia) east coast I.
Assessing the effects of tagging. Fish. Res. 53, 251–261.
Doody, J. S., 1995. A photographic mark–recapture method for patterned amphibians.
Herpetol. Rev. 26, 19–21.
Frisch, A. J., 2007a. Short- and long-term movements of painted lobster (Panulirus
versicolor) on a coral reef at Northwest Island, Australia. Coral Reefs 26, 311–317.
Hammond, P. S., Mizroch, S.A., Donovan, G.P., 1990. Individual Recognition of
Cetaceans: Use of Photo-identification and other Techniques to Estimate Population
Parameters. International Whaling Commission, Cambridge.
Hammond, P. S., 1990. Heterogeneity in the Gulf of Maine? Estimating humpback
whale population size when capture probabilities are not equal. Report of the
International Whaling Commission (Special Issue 12): 135-1 39.
Hammond, P. S., 1986. Estimating the size of naturally marked whale populations
using capture-recapture techniques. Reports of the International Whaling Commission
(Special Issue 8):253-282.
Hiby, A. R. and Lovell, P., 1990. Computer aided matching of natural marks: A
prototype system for gray seals. Report of the International Whaling Commission
(Special Issue 12):57-62.
Hiby, A. R., and Jeffery, J. S., 1987. Census techniques for small populations, with
special reference to the Mediterranean monk seal. Zoological Symposium 58: 193210.
IWC. 1990. Report of the workshop on individual recognition and the estimation of
cetacean population parameters. Report of the International Whaling Commission
(Special Issue 12):3-17.
Jones, M. L., 1990. The reproductive cycle in gray whales based on photographic
resightings of females in the breeding grounds from 1977-82. Report of the
International Whaling Commission (Special Issue 12):177-182.
40
Katonas, K., and Krauss, S., 1979. Photographic identification of individual
humpback whales (Megaptera novaeangliae): Evaluation and analysis of the
technique. US Department of Commerce, NTIS Publication, Springfield, VA.
Kelly, M.J., 2001. Computer-aided photograph matching in studies using individual
identification: An example from the Serengeti cheetahs. J. Mammal. 82, 440–449.
Linnane, A., Mercer, J.P., 1998. A comparison of methods for tagging juvenile
lobsters (Homarus gammarus L.) reared for stock enhancement. Aquaculture 163,
195–202.
Persat, H., 1982. Photographic identification of individual grayling (Thymallus
thymallus) based on the disposition of black dots and scales. Freshw. Biol. 12, 97–
101.
Scarrat, D.J., 1970. Laboratory and field tests of modified sphyrion tags on lobsters
(Homarus americanus). J. Fish. Res. Board Can. 27, 257–264.
Sims, D.W. & Quayle, V. A., 1998. Selective foraging behaviour of basking sharks on
zooplankton in a small-scale front. Nature, London, 393, 460-464.
Stonehouse, B., 1978. Animal Marking. Macmillan Press, London.
Würsig, B., and Würsig, M., 1977. The photographic determination of group size,
composition and stability of coastal porpoises (Tursiops truncatus). Science 198:755756
Yochem, P. K., Stewart, M., Mina, M., Zorin, A., Sadovov, V., and Yablokov, A.,
1990. Non-metrical analyses of pelage patterns in demographic studies of harbour
seals. Report of the International Whaling Commission (Special Issue 12):87-90.
41
APPENDIX II: a) Health and Safety Form;
Name of Employer ………………………………………………………………………………………………
Address …………...............................................................................................…...
...........................................................................................................................
Telephone ..................................................Fax.....................................................
Yes
No
1
Do you have a written Health and Safety policy?


2
Do you have a policy regarding health and safety training for people working in your undertaking, including
use of vehicles, plant and equipment, and will you provide all necessary health and safety training for the
placement student?
























3
Is the organisation registered with:
a - the Health and Safety Executive
b - the Local Authority Environmental Health Department?
4
Insurance
a - Is Employer and Public Liability Insurance held?
b - Will your insurances cover any liability incurred by a placement student as a result of
his/her duties as an employee?
5
Risk Assessment
a - Have you carried out risk assessment of your work practices to identify possible risks whether
to your own employees or to others within your undertaking?
b - Are risk assessments kept under regular review?
c - Are the results of risk assessment implemented?
6
Accidents and Incidents
a - Is there a formal procedure
in accordance with RIDDOR?
for
reporting
and
recording
accidents
and
incidents
b - Have you procedures to be followed in the event of serious and imminent
danger to people at work in your undertaking?
c - Will you report to the university all recorded accidents involving placement students?
d - Will you report to the university any sickness involving placement students which may be
attributable to the work?
Contact Personnel
Who is your nominated contact for compliance with the requirements of health and safety
legislation?
Name and position............................................................Tel.....……..................
The above statements are true to the best of my knowledge and belief.
Signed:...........................................................................…………........................
Position:...........................................................Date...............………...................
Thank you for completing the questionnaire. Please return it as soon as possible to:
Please sign this form and return to :
Dr Gordon Baillie
Safety Adviser
School of Life Sciences
Napier University
10 Colinton Road, Edinburgh, EH10 5DT
Tel: 0131 455 2327
42
APPENDIX II: b) Risk Assessment;
SCHOOL OF LIFE SCIECNES, NAPIER UNIVERSITY
RISK ASSESSMENT FOR EXTERNAL VISITS/ACTIVITIES
NAME: Lucy Norris Green
LS71229
Module:
Activity: MSc Project (Basking Sharks)
Date(s) of activity: June 2008
Summary of Activity: Please indicate whether you consider the activity presents a High/Medium/Low
Risk
This project will be carried out in the Irish sea surrounding the Isle of Man, this involves boat and
water based activities and therefore potentially high risk.
Description of Site: Please indicate whether you consider the site presents a High/Medium/Low Risk
The study site is situate in the coastal waters of the Irish sea surrounding the Isle of Man, weather and
sea states are changeable in this area.
Accommodation is a house with all facilities provided, phone and internet access included.
Overall site assessment – High risk
Physical Hazards: Please indicate whether you consider the hazard(s) Major/Serious/Slight
On board.
Ocean- Sea states are typically changeable in the Irish sea – serious risk
Boat- Possibility of being injured and/or going overboard – serious risk
Water –The Irish sea is dangerously cold – serious risk
Sun – Sunlight is reflected back by the seas surface increasing strength and glare – serious risk
Heat – There is no escape from the sun on a boat so sunstroke, and dehydration is a risk- serious
Cold – wind and rain can dramatically reduce body temperature – serious risk
Dehydration – serious risk
Location – getting lost is a hazard for the inexperienced – serious risk
Fire –boat carries flammable material– serious risk
In the Water.
Ocean/cold- extremely cold-serious risk
Location- possibility of getting swept from the boat – serious risk
Animals – can become aggressive if provoked- serious risk
43
Chemical/Biological Hazards: Please indicate whether you consider the hazard(s)
Major/Serious/Slight
Mammals –cetaceans and pinnipeds can be dangerous if inquisitive and can become violent– serious
risk
Fish– Basking sharks are extremely large and potentially could harm a human – slight risk
Cnidaria – Jellyfish can be poisonous, anemones may be present in places and can be poisonous –
serious risk
Disease – water borne – slight risk
Allergy – histamine reactions to Jelly fish and anemones – serious risk to me as I am allergic to them.
Assessment of Overall Risk: High/ Medium/Low - HIGH RISK
Control Measures:
1. All safety equipment required for instances of emergency such as fire, or boat abandonment
shall be present.
2. Boat handlers fully qualified and boat licensed.
3. Coastguard will be kept informed of our position at sea.
4. GPS position and heading will be repeatedly taken in order to plot our course in case of loss of
satellite signal.
5. Supervisors aware of our activities and locations at all times.
6. Boat trips shall be abandoned in unsuitable weather.
7. Students both qualified divers to PADI Advanced level and above.
8. Water based activities will take place in pairs under the buddy system.
9. Animals shall not be approached too closely or at all if any display of distress or aggression is
observed.
10. First aid equipment will be on the boat.
11. First-world medical facilities are available on the Isle of Man.
12. Participants will be covered by personal insurance including DAN cover which covers rescue
at sea.
13. Participants will carry mobile phones.
14. Radio contact will be maintained on channel 16 at all times.
15. Full site assessment and boat safety instructions will be given to participants before making
the first voyage.
16. Participants must maintain vigilance on each other for signs of exhaustion/ exposure/
dehydration
17. Participants will maintain visual contact with each other at all times
18. Area will be surveyed for Jellyfish and Anemones before entering the water. Adrenalin pen
will be onboard the boat at all times for treatment.
44
19. Warm well gripping footwear is essential as well as warm, waterproof clothes worn in layers.
20. Sun block will be worn at all times.
21. Ample amounts of drinking water will be drunk.
Any Other Comments:
Wildlife Biology is an inherently risky business – you are being trained by professionals in order to
assume the mantle of professional expertise yourselves and part of this is the minimisation of this risk
to acceptable levels. Absolute expertise, clear plans for eventualities and clear safety measures are the
means by which this is achieved. Adherence to instructions, alertness and common sense are critical.
Emergency Procedures:
1. See (8) above
2. Evacuation to high-standard hospitals is available
3. Drugs may be obtained local pharmacy – prescriptions may be required
In case of emergency, Next-of-Kin may contact
Mrs Jackie Hall,
Glen Chass Farm House,
Chasms rd,
Port St Mary,
Isle of Man.
IM9 5PJ
Tel: 01624 833215
First Aid:
Participants trained in basic first aid. Coastguard assistance available.
Assessment of Overall Risk: HIGH RISK
Signed
Signed
(Student)
(Supervisor)
Date 02/06/08
Date
45
Appendix VI: DATA PROTECTION ACT 1998
CONSENT FORM: ALL STUDENTPROJECTS/REPORTS/DISSERTATIONS
[EXCEPT PhDs]
Part A – to be completed by all students
I confirm that this project/report/dissertation (delete as appropriate) is all my own work. I
understand that my written permission is required for the University to make copies of my
project/report/dissertation, available to future students for reference purposes and that
my name may be evident. I hereby give my consent to my named work being made
available. I confirm that my work is not confidential. [see Part B]
Print name………………………………….
Signature……………………………………
Date…………………………
* delete as appropriate
FACULTY: Health & Life Sciences…..SCHOOL: Life Sciences
MODULE NO: LS71221………………………………
SPECIFY PROJECT/REPORT/DISSERTATION: MSc Project
TITLE………………………………………………………………………..
LOCATION IN WHICH TO BE HELD: School of Life Sciences, Merchiston
Part B – to be completed in all cases where the student has had work placement
experience
The above named student has completed his/her project/report/dissertation* whilst on
assignment with our company/firm. I understand that the work is to be made available for
reference purposes and that the company/firm name may be evident. I hereby confirm that
this is acceptable and that the work is not confidential as far as the company/firm is
concerned.
Name of Company/Firm/ Departmental Head…………………………………..
Signature………………………………………… Date……………………………….
Company/firm stamp
Name & Address of External
Supervisor………………………….
……………………………………
46