Using photographic identification to monitor sea turtle populations at Perhentian Islands Marine Park in Malaysia

Abstract

Perhentian Islands Marine Park is home to foraging and nesting Green Turtles (Chelonia mydas) and Hawksbill Turtles (Eretmochelys imbricata) but little information is available other than nesting trends and hatching success. We used photographic identification (photo-ID) methods to identify individuals and to determine their sex ratios, habitat use, and site fidelity. We collected 1,826 sightings between 2009 and 2015 from conservation projects (998 in-water sightings, 184 nesting sightings) and members of the public (639 in-water sightings, five nesting sightings), and used NaturePatternMatch (NPM) software and manual visual matching to identify individuals. We identified 120 (minimum) to 131 (maximum) individual Green Turtles, including a maximum of 17 males, 58 females and 56 turtles of unknown sex from both in-water and nesting beach sightings. We identified 20 (minimum) to 23 (maximum) individual Hawksbills of unknown sex from in-water sightings. Green Turtles were sighted most frequently at seagrass beds and Hawksbills only among coral reefs. We resighted 47 Greens and eight Hawksbills between one and 144 times (mean = 23.1 times). Nesting Greens also showed strong site fidelity, although the nesting home range for some individuals included different beaches on adjacent islands within approximately 30 km. We identified boat-related injuries in eight turtles and mortalities of two turtles. Our study suggests that photographs from conservation projects and members of the public were appropriate for photo-ID to provide information on the turtle populations in the Perhentian Islands Marine Park.

Full text

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Herpetological Conservation and Biology 12(2):350–366.
Submitted: 10 September 2016; Accepted: 20 March 2017; Published: 31 August 2017.
Copyright © 2017. Seh-Ling Long
All Rights Reserved.

Basic biological, ecological, and population
demographic information is essential to species
conservation and management. The identication of
individuals within a population allows the study of
growth rates, age structure, sex ratios, survivorship,
residency, distribution, movement patterns, and
population size, which are important for ecological and
behavioral studies (Wells and Scott 1990; Wilson et al.
2006; Holmberg et al. 2009; Bjorndal et al. 2013). In
sea turtles, tagging using ipper tags and/or passive
integrated transponder (PIT) tags are common methods
used to recognize individuals and track their movements
(Luschi et al. 1996; James et al. 2007). Tags of all types
are more often applied to sexually mature female turtles
due to ease of attachment during the nesting process.
However, information on nesting females only may
underestimate the population size due to the paucity of
knowledge on adult males, sub-adults, and juveniles that
spend most of their time at foraging grounds and out at
sea (Schoeld et al. 2008). More recently, photographic
identication (photo-ID) has been increasingly used for
in-water population and behavioral studies of sea turtles
(Jean et al. 2010; Su et al. 2015; Araujo et al. 2016).
Photographic identication has been used in long-
term studies of large and long-lived species (Würsig
and Jeerson 1990; Baird et al. 2008). It is gaining
popularity as a non-invasive alternative to tagging
where animal capture and tag attachment is not feasible
due to nancial, logistical, or ethical reasons (Thompson
and Wheeler 2008; Su et al. 2015). Many species
bear unique markings or natural patterns that allow
individuals to be identied from photographs, e.g.,
Tigers (Panthera tigris; Hiby et al. 2009) and Pink River
Dolphins (Inia goerensis; Gomez-Salazar et al. 2011).
In Cheloniidae, the facial scale patterns are unique to
individuals and stable over a period of at least 3 y for
Hawksbill Turtles (Eretmochelys imbricata; Dunbar et
al. 2014) and up to 11 y for Green Turtles (Chelonia
mydas; Carpentier et al. 2016). The scale patterns on
the top of the head (Lloyd et al. 2012) and scute patterns
on the carapace (Hall and McNeill 2013) are also
useful for recognizing individual turtles. Other distinct
features, such as barnacle patterns, could also help
with identication (Hall and McNeill 2013). Several
T
AI

1,3,42,3
1Institute of Oceanography and Environment, Universiti Malaysia Terengganu, 21030 Kuala Nerus,
Terengganu, Malaysia
2Reef Check Malaysia, Wisma Central, Jalan Ampang, 50450 Kuala Lumpur, Malaysia
3Perhentian Turtle Project, Ecoteer, Kampung Pulau Perhentian, 22300 Kuala Besut, Terengganu, Malaysia
4Corresponding author, email: lsehling@gmail.com
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 
        

Key Words.—Chelonia mydas; citizen science; computer-assisted pattern recognition; Eretmochelys imbricata;
Green Turtle; Hawksbill Turtle; individual identification

351
Long and Azmi.—Photo-ID to monitor sea turtles at Perhentian Islands of Malaysia.
methods of photo-ID for sea turtles have been developed
(see Reisser et al. 2008; Schoeld et al. 2008; Jean et
al. 2010; Lloyd et al. 2012; Su et al. 2015). Although
not error free, computer-assisted identication systems
can improve identication capability and accelerate the
process, which is especially needed for large databases
(Carter et al. 2014; Dunbar et al. 2014).
In many places, viewing of sea turtles on nesting
beaches and in the water as a major tourist attraction
has created an opportunity to use citizen scientists
(volunteers and members of the public) in data collection
for population studies (Campbell and Smith 2006; Bell
et al. 2009; Williams et al. 2015). Citizen science can
be dened as public participation in scientic research,
often in collaboration with or under the supervision of
researchers (Dickinson et al. 2010). It has educational
value as it promotes knowledge and increases public
awareness, engagement, and appreciation towards
nature (Cohn 2008). Some photo-ID studies on land
and in the water have used citizen scientists to collect
photographs (Wee and Subaraj 2009; Carpentier et al.
2016). However, data gathered by citizen scientists may
be inaccurate, inconsistent, or unreliable due to their
limited or lack of knowledge, training, and motivation
in scientic research, leading to diculties during
data analysis (Cohn 2008). Error and bias could occur
from non-standardized sampling methods, non-uniform
sampling eort across time and space, or erroneous
reporting (Dickinson et al. 2010). Appropriate training
and supervision can enhance the reliability of data
collected by citizen scientists, providing invaluable data
sets for researchers to study populations (Danielsen
et al. 2014). If well trained and supervised, citizen
science provides a cost-eective way of collecting
data through increased manpower and sampling eort,
allowing biodiversity monitoring over greater spatial
and temporal extents (Goredo et al. 2004).
Four species of sea turtles, Leatherback
(Dermochelys coriacea), Olive Ridley (Lepidochelys
olivacea), and Green and Hawksbill turtles, occur in the
State of Terengganu in Malaysia, and only two species,
Green and Hawksbill turtles, nest and reside in the
waters of Perhentian Islands Marine Park (Chan 2006).
Approximately 20–30% of all Green Turtle nesting
reported in Terengganu occurs on these islands (Sarala
Aikanathan and Jeanne Mortimer, unpubl. report).
To protect nesting habitats and increase hatchling
production, the Terengganu State Department of
Fisheries (DoF) set up a hatchery and declared several
high density nesting beaches as turtle sanctuaries
(Siow and Moll 1982; Chan 2006). During the nesting
season from April to October, DoF rangers patrol the
beaches and relocate nests to the hatchery. Nesting data,
such as counts of landings, nests, eggs incubated and
hatchlings, serve as a baseline for monitoring nesting
trends and hatching success. Little is known, however,
about the in-water turtle populations because research
and conservation work have focused mainly on nesting
sites. Moreover, there is a lack of mark-recapture data.
We used photo-ID as an alternative to tagging, and
we integrated citizen science to gather more sighting
data on Green and Hawksbill turtles that is otherwise
not possible with limited resources. The objective
of this study was to assess nesting and in-water
turtle populations of these species in the Perhentian
Islands Marine Park using sightings data collected by
conservation projects and members of the public. We
used photo-ID methods to identify individual turtles
for developing a sea turtle photo-ID database and to
determine their sex ratios, habitat use, and site delity.

 .—The Perhentian Islands Marine Park
(5°53'49''N 102°43'45''E) is a tourist destination located
in the South China Sea, 21 km o the mainland of
Terengganu on the north-eastern coast of west Malaysia
(Fig. 1A). The marine park consists of several islands,
and only Perhentian Besar (867.3 ha) and Perhentian
Kecil (524.8 ha) are inhabited. The islands lie on a
shallow continental shelf extending from the mainland
with an average maximum depth of 30 m (Simon
Harding et al., unpubl. report), and experience a
seasonal weather pattern with higher rainfall during the
Northeast monsoon from October until March (Suhaila
et al. 2010). The water temperature ranges from 26–
31° C (Wetzelhuetter et al. 2014), and a thermocline is
present at dierent depths in dispersed geographic areas
(Simon Harding et al., unpubl. report). The horizontal
underwater visibility varies spatially from 7.1–15.5
m (Simon Harding et al., unpubl. report); however,
during the monsoon, the visibility can decrease. There
are currents owing northward (April to August) and
southward (November to March) along the Terengganu
coastline (Mohd Akhir 2012), but the islands are more
exposed to local tidal currents that show no prevailing
current direction (Simon Harding et al., unpubl. report).
Surrounding the islands are coral reefs, with the
mainly fringing reefs sloping to a sandy bottom at 20
m and seamount type reefs (Toda et al. 2007; Simon
Harding et al., unpubl. report). There are monospecic
seagrass beds of Enhalus acoroides or Halophila minor,
as well as mixed-species of the latter with Halophila
decipiens, Halophila ovalis, and Halodule pinifolia
(Muta Harah and Japar Sidek 2013). Habitat diversity
is high and patchily distributed, ranging from areas
unsuitable for benthic growth to those supporting high
cover of benthic organisms (Simon Harding et al.,
unpubl. report). The islands were protected as a marine
park in 1994 under the Malaysian Fisheries Act of 1985.

352
Herpetological Conservation and Biology
The law prohibits touching or taking of any marine
resources whether alive or dead without permission, and
it bans water skiing, speed boat racing, jet skiing, and
shing activities within a radius of two nautical miles
from the lowest tide level of the islands. Less harmful
activities such as snorkeling, scuba diving, swimming,
underwater photography, and kayaking are allowed
and occur before and after the monsoon from March
to October. Peak tourist season is June to August with
the annual number of tourists arriving to the marine
park exceeding 100,000 since 2012, and increasing to
180,481 in 2015 (Department of Marine Park Malaysia,
unpubl. data). There are at least 30 dive sites at natural
and articial reefs and no fewer than 13 snorkel sites,
mostly around fringing reefs or seagrass areas adjacent
to the beach (Tourism Planning Research Group, unpubl.
report). Some of the sites are for diving and snorkeling,
but snorkelers often stay in shallower areas.
. (A) The Perhentian Islands Marine Park within the Terengganu waters in peninsular Malaysia (SEATURTLE.ORG Maptool.
2002. SEATURTLE.ORG, Inc. Available from http://www.seaturtle.org/maptool/ [Accessed 06 December 2016]), and (B) the location of
turtle sightings in the water and on beaches. Note: The snorkel site in front of Tiga Ruang Beach is also known as Tiga Ruang.

353
Long and Azmi.—Photo-ID to monitor sea turtles at Perhentian Islands of Malaysia.
   .—The Perhentian
Turtle Project (PTP) carried out photo-ID surveys at
foraging and nesting grounds between April and mid-
October 2015. In the rst month, we trained four interns
(who stayed for the whole study period) on snorkel
surveys and beach monitoring, where they learned about
species and track identication, biometric sampling,
photo-ID methods, free diving, and record keeping.
Twenty volunteers (who stayed 7–14 d) also received
training but may not have acquired all the skills needed
during their stay. Therefore, we conducted every survey
in a team of two to three people where we and trained
interns led and supervised the volunteers (if any) in data
collection.
We conducted one to two turtle photo-ID surveys a
day for 5–7 d a week. Each survey lasted 2–3 h between
0900–1300 or 1400–1800. We surveyed predominantly
around the seagrass area at Teluk Pauh (Fig. 1B)
with one observer on a kayak to look out for turtles
breathing at the water surface while the rest snorkeled
to look for turtles underwater. The survey area where
we haphazardly looked for turtles was approximately
4 ha and less than 10 m deep. As sightings of turtles
were sporadic elsewhere, we surveyed other sites
opportunistically. When a turtle was sighted, we free
dived to around eye level of the turtle and photographed
the right and left sides of the face from a minimum
distance of 1.5 m. We also photographed the dorsal
view of the turtle. We used four camera models to
photograph in-water turtles (Canon PowerShot G15 and
PowerShot G16 in their respective underwater housings,
Canon, Inc., Ota, Tokyo, Japan; GoPro Hero 3, GoPro,
Inc., San Mateo, California, USA; and Olympus TG-3,
Olympus Corp., Shinjuku, Tokyo, Japan).
Every night during 1900–0800, we surveyed the
beach with DoF rangers at Tiga Ruang Turtle Sanctuary
(Fig. 1B). After encountered turtles had completed the
oviposition process, we checked the turtles for tags
and measured the curved carapace length. We then
used a digital camera (Canon PowerShot G15, Canon
PowerShot G16, or Olympus TG-3) to take facial
photographs at approximately the eye level of the turtle
from a distance of approximately 0.4 m without camera
ash, but by shining a red LED headlight toward the
head. An articial light source was not necessary when
photographing turtles after 0630. For all encountered
in-water and nesting individuals, we recorded the tag
number (if any) and sighting information, such as date,
time, and location. In addition to the photographs
collected in 2015, we also had photographs of in-
water and nesting turtles taken opportunistically since
2012. During the study period, we also gave a brieng
with instruction on photo-ID data collection to project
leaders of three conservation projects who already
had a background in marine biology and conservation,
including beach monitoring experience and knowledge
of species identication. They contributed sightings
of nesting turtles, as well as photographs of turtles that
they encountered during leisure snorkel and dive trips
since 2011.
.—Members of the public could
submit photographs of turtles via the PTP email (turtle@
ecoteer.com) and social media sites (e.g., Facebook
and Instagram). There were posters and banners at
various locations around the islands and at the mainland
jetty to provide information on photo-ID, as well as
illustrated guidelines to watch turtles. Upon receiving
the photographs, we contacted the contributor to verify
sightings information because photographs from social
media sites did not have metadata. We recorded the
sighting location as unknown for sightings with no
location information or vague location descriptions, the
sighting date as the month and year the photographs
were taken if the date was unknown, the sighting time
as day or night if the exact time was unknown, and the
camera model if such information was available.
  .—We
distinguished the sex of in-water turtles using tail length
dimorphism whereby individuals with evidently longer
tails that extended signicantly beyond the carapace
were identied as adult male (Wibbels 1999), otherwise
they were assumed to be of undetermined sex or adult
females if they had a tag from a nesting beach. We used
the software NaturePatternMatch (NPM), which detects,
recognizes, and compares natural patterns for individual
identication (Stoddard et al. 2014). The NPM is a less-
species specic adaptation of the Manta Matcher (MM)
identication software for manta rays (Manta spp.; see
Town et al. 2013). Other computer-aided identication
systems tested on hard-shelled sea turtles require the user
to manually select reference points (Dunbar et al. 2014),
code (Jean et al. 2010), or outline the facial scales (Carter
et al. 2014). Instead, the NPM uses the Scale-Invariant
Feature Transform (SIFT) algorithm to automatically
select distinct features for image matching (Lowe 2004).
The selected features appeared to be robust to changes
in location, scale, rotation, illumination, 3D viewpoint,
noise, and occlusion (Lowe 2004, Stoddard et al. 2014).
For example, the SIFT algorithm could detect distinct
points from the pineal spots of Leatherback Turtles and
recognize the same individual from photographs that
varied in illumination, resolution, and viewing angle
(Pauwels et al. 2008). It could also identify manta rays
correctly despite the presence of occlusions (e.g., sh)
and extreme image noise (Town et al. 2013). Thus,
automated software using the SIFT algorithm could
recognize individuals from photographs taken under
challenging conditions underwater or at night.

354
Herpetological Conservation and Biology
The automated matching process consisted of
(1) image preprocessing; (2) image enhancement;
(3) feature detection and extraction (per left or right
prole); and (4) feature matching. First, we cropped
the left facial scales and rotated the cropped images
to a horizontal angle using GNU Image Manipulation
Program (GIMP) 2.8.14 (Free Software Foundation,
Inc., Boston, Massachusetts, USA; Fig. 2A). Then,
we used NPM, which converted the facial scale images
to grayscale and enhanced the images after noise lter
and contrast adjustment (Fig. 2B). The NPM software
detected and extracted distinct features from the left
facial scales using the SIFT algorithm (Lowe 2004; Fig.
2C), and matched the extracted features against the left
face of all individuals in the database. It then displayed
a ranked list of the left face matches from most to least
similar based on a similarity score (0–1), along with
a condence score (0–1) to indicate how reliable the
rankings are (Fig. 3A). We repeated the process for
the right facial scales to get a ranked list of the right
face matches (Fig. 3B). We visually checked the list
for the correct match (if any) and looked through all the
matches if the condence score was low.
For photographs that did not show the facial scales
clearly enough, we did visual comparison manually
using an identication tree based on the (1) species; (2)
sex; (3) number of post-ocular scales on the right and
left faces; and/or (4) number of temporal and parietal
scales on top of the head (modied from Schoeld et
al. 2008; Lloyd et al. 2012; Su et al. 2015). We used
the facial scale patterns, as well as the natural markings
and scars on the top of the head, shell, and ippers to
identify individuals (Fig. 4). We identied an individual
as a new turtle when we found no match, whereas a
match from either side of the face indicated resighted
turtles. We added every new turtle to a database and
grouped them as identied individuals with photographs
of both sides of the face, left side only, or right side only.
We assigned new turtles an ID to specify the species,
individual, and sex (if known), only if they were sighted
alive with both sides of the face photographed. We gave
new turtles with only one facial prole an ID after seeing
. An example of the photo-ID process for a Green Turtle (Chelonia mydas) where a cropped image of the left facial scale (A)
is converted into grayscale and enhanced (B) before NPM extracts distinct features using SIFT (C). (Photographed by Seh-Ling Long).

355
Long and Azmi.—Photo-ID to monitor sea turtles at Perhentian Islands of Malaysia.
them again with both sides of the face photographed.
After the rst observer identied the individual from
a new sighting, a second observer checked to conrm
the identity of the individual. To avoid errors and
misidentication, we checked all of the sightings again
to verify identications.

  .—We gathered 1,826 turtle
sightings from conservation projects (n = 1,182) and
members of the public (n = 644), which consisted of
underwater sightings from 2009 to 2015 (n = 1,637)
and nesting sightings from 2011 to 2015 (n = 189). All
sightings occurred between the late January and early
November. The locations of six underwater sightings
and one nesting sighting were unknown whereas the
remaining sightings were from 13 dive and/or snorkel
sites (n = 1,631) and seven beaches (n = 188; Fig. 5).
Due to inadequate information on sighting per unit eort
and frequency per site, it was not possible to quantify
eorts and abundance based on the number of sightings
per site alone.
   .—In-water
sightings from both conservation projects (n = 998) and
members of the public (n = 639) showed diculties in
capturing photographs from a standardized angle for
observations where animals were moving constantly.
Other factors, such as water visibility, light conditions,
and whether or not the turtle was blocked by sh, also
aected the quality of the photographs. By positioning
the camera around the eye level of turtles, all nesting
photographs (n = 184 sightings) from conservation
projects showed the face of the turtle in close-up.
Meanwhile, members of the public photographed
nesting turtles (ve sightings) from a standing position
using ash. In nesting photographs, sometimes the
retraction of the head of the turtle and sand covered a
small part of the facial scales (90 sightings). Successful
identication of both in-water and nesting sightings
was possible using the NPM, as was manual matching,
. Examples of NPM output showing a ranked list of the left (A) or right face (B) matches based on a similarity score of 1 (perfect
match) to 0 (no match). Every matched image shows the facial scales of a dierent individual. The lename is the turtle ID and the
identity indicates the left (L) or right face prole (R). A high condence score indicates that the query image is signicantly more similar
to the rst-ranked matched image than any other images whereas a low condence requires the user to check a larger number of matches
for the correct match (Town et al. 2013). Here, the fourth-ranked and the rst-ranked matches are the correct match for the left side (A)
and right side (B), respectively, showing that the query images match individual P27.

356
Herpetological Conservation and Biology
so long as photographs were not overly out of focus
and taken at a horizontal and vertical angle of < 45°
where the majority of the facial scales were visible.
For in-water sightings, the scale patterns on top of the
head, scute patterns of the carapace, barnacle patterns,
injuries, and scars, were also useful for identication.
Of the total sightings, 79 (4.3%) were not recognizable
because the photographs were too blurred, including the
only two nesting sightings of Hawksbill Turtles.
The left and right facial patterns were non-identical
for all identied turtles of both species. Identication
of resighted turtles was possible using only one side of
the face, as long as both sides of the facial prole were
already available in the database. Unlike Green Turtles,
the facial scales of Hawksbills showed higher similarity
among individuals and had a smaller number of facial
scales and features for matching. They also showed less
variation in the number and shape of the post-ocular,
. Examples of natural markings and scars used for identication: the number, shape and arrangement of the facial scale patterns
(A, B, C showing the number of post-ocular scales) and at the top of the head (D, E, F showing the number of temporal and parietal scales
surrounding the frontoparietal [FP] scale), the natural markings (G, H) and injuries (I, J) on the shell, or missing a portion of the front (K)
or rear ippers (L). (Fig. 1A photographed by Thomas Brown, Fig. 1B photographed by Charlotte. E. Babbs, Fig. 1C and 1I photographed
by Nicholas J. Tolen, Fig. 1D photographed by Andrea Szalai, Fig. 1E photographed by Kevin Heitzman, Fig. 1F photographed by
Nazirul A. Amin, Fig. 1G photographed by Seh-Ling Long, Fig. 1H and 1L photographed by Petros Persad, Fig. 1J photographed by
William Forster, and Fig. 1K photographed by Rahmat A. Wahab).

357
Long and Azmi.—Photo-ID to monitor sea turtles at Perhentian Islands of Malaysia.
temporal and sub-temporal scales, and thus, required
the combination of all scales including the tympanic and
central scales for identication. Time intervals between
the rst and last sightings of resighted turtles varied from
5–2,212 d for Green Turtles (78 turtles) and 8–490 d for
Hawksbill Turtles (eight turtles). During this period,
there were no changes in the shape and arrangement of
the scales on the face.
Overall, we identied 96.2% of the sightings from
conservation projects and 94.7% from the public, adding
up to 1,747 sightings. This total represented 96.1% of
the Green Turtle sightings (n = 1,766) and 81.7% of the
Hawksbill Turtle sightings (n = 60), which belonged
to 115 turtles with left and right proles (104 Greens
and 11 Hawksbills), 22 turtles with left prole only (13
Greens and nine Hawksbills) and 17 turtles with right
prole only (14 Greens and three Hawksbills; Table
1). There were 1,567 resightings of Green Turtles, of
which 127 were repeated sightings of the same turtles on
the same day. In contrast, all 26 Hawksbill resightings
occurred on dierent days. All the single-prole turtles
were seen only once. The identied turtles in the water
. (A) The distribution of Green Turtles (Chelonia mydas) and (B) Hawksbill Turtles (Eretmochelys imbricata) in the Perhentian
Islands Marine Park based on sightings from conservation projects and public individuals between 2009 and 2015.

358
were not the same individuals as the turtles identied on
nesting beaches.
  .—There were 57 Green
Turtles with photographs of both facial proles, and of
these, 14 were males, one was female, and the remaining
42 were of unknown sex. Of nine turtles with the left
prole only, one was a male, and of eight turtles with the
right prole only, there were two males (Table 1). The
maximum number of individual turtles was 74, while
the minimum number of individual turtles was 67 if
the right-prole male and unknown sex turtles were the
same individuals as the left-prole male and unknown
sex turtles. About 80% of the Green Turtles occurred
in mixed seagrass beds at depths of about 3–11 m,
mainly feeding at Teluk Pauh and Atas Busong. The rest
occurred on coral reefs at Batu Layar and Shark Point
where the depths varied from 5–15 m. Only two turtles
found at a seagrass area at Teluk Pauh were also sighted
on coral reefs at Batu Layar, which is about 1.1 km
away. Forty seven turtles were resighted up to 144 times
(mean = 23.1, SD = 32.7) at the same site on dierent
days over about 6.1 y. Two of the resighted turtles had
a tag on both front ippers but we could trace the tags
of only one turtle to its original tagging source. One of
them was tagged by the Sea Turtle Research Unit of the
Universiti Malaysia Terengganu (SEATRU UMT) when
it nested approximately 30 km away at Redang Island
(Fig. 1A) between May and July 2013. This turtle was
rst seen in the water at Teluk Pauh in September 2009
and was resighted foraging at the same site every year
during 2012–2015 between April and October, except in
2013 where there was only one sighting in September.
It had an injury on its carapace when photographed in
September 2015 (Fig. 4I). Eight other resighted turtles
also had healed or new injuries with six of them showing
evidence of boat strikes or propeller cuts (Fig. 4J–L).
Furthermore, there were four sightings of dead Green
Turtles, and photographs revealed boat-related injuries
on two of them, while cause of death was unknown
for the other two. Of four mortalities, one turtle had
decomposed beyond recognition. One turtle matched an
individual from the database, which was spotted three
times at Teluk Pauh. We presumed the remaining two
turtles to be new individuals because there was no match
in the photo-ID database.
  .—There were 11
Hawksbill Turtles with both facial proles, nine with
the left prole only and three with the right prole only
(Table 1). There could have been a maximum of 23
individual turtles or a minimum of 20 turtles, if all three
right-prole turtles were the same individuals as the left-
prole turtles. The sex of all the Hawksbill Turtles was
unknown. The observed Hawksbills occurred on coral
reefs that were 5–15 m deep. Eight turtles were seen at
the same site two to six times on dierent days over a
period of 490 d between 2014 and 2015. Only one of the
resighted turtles used two dierent sites that are about
3.7 km apart, namely Teluk Kerma and Teluk Pauh. One
Hawksbill Turtle was missing a portion of the shell at its
left rear ipper.
.—We identied 47 individual
female turtles with photographs of both facial proles,
plus four turtles with the left prole only and six turtles
with the right prole only (Table 1). If all of these turtles
were dierent individuals, there was a maximum of 57
nesting turtles. If all turtles with the left prole only
were the same individuals as the right-prole turtles,
there was a minimum of 53 nesting turtles. There were
no remigrants over the 5-y period. All the turtles were
sighted once, except for 31 turtles that laid between two
to nine nests within a season in 2015. The time interval
between the rst and subsequent sighting of the same
turtle ranged from 1–65 d. Of these renesters, 25 nested
on one specic beach, while the other six turtles nested
on multiple beaches in the Perhentians. Three renesters
had tags from the DoF, and records were found for two
of them. Both were tagged while nesting at Redang
. Numbers of identied Green Turtles (Chelonia mydas) and Hawksbill Turtles (Eretmochelys imbricata) in the water and on
nesting beaches of the Perhentians, Malaysia, based on their facial proles and the minimum (min.) and maximum (max.) numbers of
unique individuals.
Green Turtles Hawksbill Turtles
Facial prole Facial prole
Population Sex
Both
sides
Left
side
Right
side Min. Max.
Both
sides
Left
side
Right
side Min. Max.
In-water Male 14 1 2 16 17 - - - - -
Female 1 - - 1 1 - - - - -
Unknown 42 86 50 56 11 9 3 20 23
Nesting Female 47 4 6 53 57 - - - - -
Total 104 13 14 120 131 11 9 3 20 23
Herpetological Conservation and Biology

359
Island in 2009 and 2010, respectively, and were among
the six females that used multiple nesting sites in the
Perhentians in 2015.

Photographic identication provided a way to assess
two distinct in-water and nesting sea turtle populations
in the Perhentian Islands Marine Park. Between 2009
and 2015, there were 67–74 Green Turtles including
16–17 adult males and one adult female sighted in the
water, and 20–23 Hawksbill Turtles of undetermined
sex sighted between 2014 and 2015. There were another
53–57 female Green Turtles that nested from 2011 to
2015. For in-water turtles, we could distinguish adult
males using tail length dimorphism and adult females
by tracing tags to a nesting site. The rest could either
be sexually immature males or females of dierent life
stages (i.e., juvenile, sub-adult, or adult). Measuring
turtle carapace length using paired-laser photogrammetry
could provide more information on population structure
and size distributions to determine which size classes
occupy an area (Araujo et al. 2016).
 .—Green Turtles were the
predominant species sighted at seagrass beds, with a
few observed in coral reef areas, whereas sightings
of Hawksbills occurred only in coral reef areas. All
resighted individuals displayed high levels of delity to
a particular site, and only a few were seen at more than
one site. Studies have shown that sea turtle habitat use
and movement patterns within a foraging home range
are related to their diet (León and Bjorndal 2002; Read
and Limpus 2002), the availability of food (Makowski et
al. 2006; Berube et al. 2012), and shelter (Makowski et
al. 2006). Sea turtles may have more than one preferred
site within their foraging range (Semino and Jones
2006) and they can develop delity to specic foraging
areas when there are sucient resources (Makowski et
al. 2006). Green Turtles in the western South Atlantic
spent a longer time in shallow areas where food was
more abundant than turtles in areas where food was less
abundant (Reisser et al. 2013). Although Green Turtles
feed primarily on seagrass, they are known to also feed
on algae found in coral reef areas (Read and Limpus
2002). Hawksbill Turtles were found more frequently
at rocky reef areas compared to sandy bottom areas
o the North Pacic coast of Costa Rica, presumably
because the rocky reefs sustained a higher diversity of
Hawksbill prey species, including sponges, algae, and
invertebrates (Carrión-Cortez et al. 2013). The sighting
of Green Turtles mostly at seagrass beds and Hawksbill
Turtles only in coral reef areas in the Perhentians could
also be related to their diet and the availability of food
within an area to which they repeatedly returned.
One Green Turtle photographed at an in-water site
had ipper tags from a nesting beach 30 km away from
the Perhentians. It nested at Redang Island between
May and July 2013 and was found at the same foraging
site in the Perhentians before (2009 and 2012) and
after (September 2013 onwards) nesting, suggesting
short distance migrations between foraging and nesting
grounds. Previous satellite tracking of ve nesting
Green Turtles from Redang Island showed only long
distance post-nesting migrations over 670 to 1,700
km to foraging grounds in neighboring countries, and
no turtles moved northward (Papi et al. 1995; Luschi
et al. 1996). Post-nesting Green Turtles tracked from
mainland Terengganu had also migrated long distances
to foraging grounds (van de Merwe et al. 2009). Short-
distance migrations are less well known among Green
Turtle populations in our study region, but have been
previously reported elsewhere. One example is the
Green Turtles that Whiting et al. (2008) tracked from
Cocos (Keeling) Islands where all six migrated fewer
than 40 km to foraging areas after nesting. Green
Turtles nesting in the Galapagos Islands have also been
observed to reside within 75 km of the nesting beach
(Semino et al. 2008). In Costa Rica, some post-nesting
Green Turtles moved to foraging grounds as close as 5
km to the nesting beach, while some turtles migrated
as far as 1,086 km (Blanco et al. 2012). Migration
has a high energy cost, and is aected by various
factors, including body size, energy, and mortality
cost (Alerstam et al. 2003). Short-distance migrations
require less energy and can occur if foraging and nesting
grounds are in close proximity (Whiting et al. 2008).
Because the turtle tagged on Redang Island showed
residency at its foraging ground, the Perhentian Islands
probably met its resource needs, such as adequate food
and shelter. It may be a tness strategy for the turtle that
saves energy by performing short-distance migrations
between foraging and nesting grounds.
Photographs showed boat strikes and propeller cut
injuries in eight turtles and mortalities in two turtles
in the Perhentians. With rapid tourism development,
injuries to and mortalities of resident turtles due to
increased boat trac around the islands may aect
breeding populations elsewhere. We did not examine
the nesting turtles for injuries, but they could also
be vulnerable to boat strikes because nesting turtles
usually stay close to the nesting beach during breeding
season (van de Merwe et al. 2009). So far there are no
regulations for speed limits in the Perhentian Islands
Marine Park and beyond two nautical miles from the
islands. As Green Turtles cannot avoid boats moving
faster than 4 km/h (Hazel et al. 2007), designation of
conservation zones to regulate boat activities, such as
limiting the boat speed and boat density, are possible
actions that can be taken, as in National Marine Park of
Long and Azmi.—Photo-ID to monitor sea turtles at Perhentian Islands of Malaysia.

360
Zakynthos, Greece, to mitigate boat impacts to turtles
in nearshore foraging grounds (Schoeld et al. 2013).
However, sucient evidence-based information that is
site-specic, such as seasonal dierences in the use of
an area by turtles and boats, is required to appropriately
make such recommendations (Schoeld et al. 2013).
 .—Green Turtles were the most
frequently sighted species in nesting areas. The majority
of renesters showed strong site delity returning to
the same beach, while only some individuals showed
weaker nesting site delity by nesting on multiple
beaches. Evidence from tagged females indicated that
some turtles nesting at Perhentian Islands had nested
at Redang Island in previous years. This suggests that
the nesting season home ranges of some adult females
span across islands within a range of 30 km. It is well-
established that Green Turtles possess a high degree of
delity in returning to previous nesting grounds (Plotkin
2003) as well as their natal rookeries for nesting (Allard
et al. 1994). They may return to a specic nesting site
(Luschi et al. 1996; Ekanayake et al. 2010), or use
multiple nest sites within a considerable area spanning a
few hundred kilometers (Bjorndal et al. 1983). As there
are also other islands in the vicinity of the Perhentians,
it is possible that the rookery consists of a number of
dierent nesting beaches on any of those islands. There
were female Green Turtles returning to the Perhentians
to nest again within one nesting season. However, due
to inadequate and incomplete data prior to 2015, there
was no record showing that nesting females from the
photo-ID database were remigrants returning to the
Perhentians for nesting in subsequent years. Thus,
long-term monitoring initiatives and mark-recapture
data will greatly contribute to understanding the nesting
population in the Perhentians.
   .—Most photo-
ID studies on hard-shelled sea turtles have used facial
scale patterns for recognizing individuals photographed
underwater (Reisser et al. 2008; Jean et al. 2010;
Chassagneux et al. 2013; Su et al. 2015; Carpentier et al.
2016), out of water (Dunbar et al. 2014), and on nesting
beaches at night (Valdés et al. 2014; Chew et al. 2015).
Lloyd et al. (2012), Hall and McNeill (2013), and Dunbar
et al. (2014) showed that individual identication is also
possible using photographs of the dorsal view of the
head and carapace. For nesting turtles, we only used the
facial scale patterns to identify individuals because only
the facial scales of turtles illuminated by the headlight
were visible in nesting photographs. We were also better
able to photograph the face of every nesting turtle close-
up (as close as 0.4 m) compared to constantly moving
in-water turtles. In-water photographs showed facial
scales at varying angles, but other visible features, such
as the scales on the top of the head and scute patterns
of the carapace, could aid with identication. These
features were less available for nesting turtles because
of the diculties in photographing the dorsal view of
the head and shell using headlights as a light source and
when the turtles were camouaging their nests. The
sand that landed on the head and shell further limited
the observation of the scale and scute patterns.
Natural markings need to be stable throughout
the lifespan of an animal to use these features to
consistently identify individuals in a population. In our
study, the facial scales were the most reliable features to
identify in-water and nesting individuals of both species
because the patterns were distinct for every individual
and remained the same over at least 2,212 d for Green
Turtles and 490 d for Hawksbill Turtles. Carpentier et
al. (2016) also showed that individual Green Turtles
were distinguishable from their facial scale patterns
over 3,954 d (almost 11 y), while the longest period
recorded for Hawksbills was 1,155 d (Dunbar et al.
2014). Obtaining both left and right facial proles was
important to avoid double-counting and to successfully
identify a new turtle. Once we had photographically
documented the left and right proles of an individual,
we were able to identify resighted turtles even if only
one side of the face was photographed. Others have also
stressed the importance of photographing both sides of
the face to increase successful identication (Chew et al.
2015; Su et al. 2015).
The head and shell scale patterns, injuries, scars,
coloration, and epibionts (e.g., barnacles) served as
complementary and secondary features to aid with
identication. Instantaneous recognition of certain
individuals with obvious markings was possible.
However, this could lead to a bias towards recognizing
easily identiable individuals in poor-quality
photographs (Davies et al. 2012). These secondary
features helped with the identication of turtles within a
season, but to use them to identify individuals over time
could be challenging because some of these features may
change (Hall and McNeill 2013). For example, some
scars could be permanent, but injuries could change
throughout the healing process. Furthermore, using
solely the scales on the top of the head to recognize
individuals resulted in a lower successful identication
rate, and Lloyd et al. (2012) suggested using the shell
markings for distinguishing individuals sharing similar
head patterns. The secondary features alone might not
be sucient to successfully identify most individuals,
but using them along with the facial scales could
increase successful identication.
For both species, manual matching was faster when
there were fewer than 20 individuals in the database.
Manual matching becomes more time consuming and
labor-intensive with large amounts of photographs
Herpetological Conservation and Biology

361
(Arzoumanian et al. 2005; Chew et al. 2015), in which
the time used to manually match new photographs
is proportional to the size of the database (Dunbar et
al. 2014). When the database increased, automated
matching reduced the amount of time used to manually
search through every individual in the database. The
NPM was less suitable for Hawksbill Turtles due to the
considerably smaller database, and manual matching
was faster. The smaller number of scales and a high
similarity in facial patterns shared by all Hawksbill
Turtles could also possibly result in the NPM producing
fewer distinguishable features between individuals and
a lower successful identication rate.
Automated identication software can deal with
photographs taken under challenging conditions
(Pauwels et al. 2008; Town et al. 2013) while reducing
the time required to match a new photograph against all
individuals in the database (Carter et al. 2014; Dunbar et
al. 2014). However, the quality of photographs is critical
when using software because poor-quality photographs
can reduce the match success (Kelly 2001; Speed et al.
2007). Moreover, software also produced false positive
matches when matching individuals not previously
in the database, whereas visual matching resulted in a
high number of correct matches (Dunbar et al. 2014).
Successful identications were usually possible using
visual matching even if photographs were not clear
enough for software identication (Davies et al. 2012).
Considering the drawbacks and restrictions of both
methods, we combined the use of automated pattern
matching software and manual visual comparison for
matching in-water and nesting photographs of highly
variable quality.
 .—Our results indicated that
photographs gathered by the public can be as useful as
those collected by trained personnel from conservation
projects. Providing information and training on photo-
ID data collection helps ensure that photographs are
suitable for photo-ID. Even so, there are limitations
and biases for using photo-ID and opportunistic citizen
science data. For example, some individuals in the wild
can become accustomed to human presence (Whittaker
and Knight 1998), and therefore are more likely to be
photographed than those that avoid humans (Kostas
2015). Such bias associated with photo-ID could lead
to heterogeneity in sighting probabilities, which will
underestimate the actual population (Sosa-Nishizaki et
al. 2012). The use of citizen science could also result
in observation and geographical biases from uneven
sighting eorts over time (Bell et al. 2009) and at
dierent sites (Dennis and Thomas 2000), depending on
the weather conditions (Koss et al. 2009), availability
and behavior (e.g., motivations and preferences) of
citizen scientists (Koss et al. 2009; Isaac and Pocock
2015; Boakes et al. 2016). In Reunion Island, the
turtle distribution increased with sighting eorts that
were dependent on the weather and tourism activity
(Chassagneux et al. 2013). Similarly, the sighting
eorts by citizen scientists in the Perhentians were
restricted to areas for diving and snorkeling during the
tourist season. Therefore, the turtle distribution patterns
in our study probably did not reect the true distribution
of turtles in the Perhentians.
Furthermore, reporting bias could happen when
citizen scientists provide inadequate or incomplete
information (Isaac and Pocock 2015). In our study,
the sighting information from citizen scientists was
not always available or accurate. Tourists reported the
location using English names that were not standardized
and could be misleading. For example, Turtle Beach
could mean any of the nesting beaches, while Turtle
Point might be the seagrass areas of Teluk Pauh or Atas
Busong. Additionally, tourists from dierent countries
had dierent time zones set on their cameras, which
resulted in incorrect sighting date and time. We could
resolve this, but not always, through conrmation with
the tourists. Although citizen scientists used dierent
types of cameras, identication was possible as long as
the photographs were not blurry, and the facial scales
were visible. Receiving photographs in their original
size could increase successful identication because
there were dierences in the image size and quality
between photographs submitted through email and
social media. The image size of photographs received
through social media had been reduced whereas
photographs received through email remained bit-for-
bit identical to the originals. We also lacked data on
the sighting eorts by citizen scientists (i.e., time per
dive/snorkel and frequency per site), which is often an
issue associated with using citizen science (Richardson
et al. 2012; Williams et al. 2015). Hence, increased
survey time and frequency and/or density of turtles per
site could contribute to a higher number of sightings at
a particular site in the Perhentians, although additional
data are required to determine this.
The photo-ID method is less invasive than capture
and tagging methods, but there might be impacts of
human-sea turtle interactions from photographing sea
turtles. Bell et al. (2009) observed that Hawksbill
Turtles were less disturbed by divers than Green Turtles
in Cayman Islands. At Mayotte Island, Green Turtles
generally avoided snorkelers except for one location
where they seemed to be unaected by human presence
(Roos et al. 2005). The dierent responses to human
presence imply that interactions with humans may alter
(Meadows 2004; Taquet et al. 2006) or even negatively
impact turtle behaviors (e.g., Hawksbills spent less time
searching for food, feeding and breathing when divers
approached them; Hayes et al. 2016). Apart from that,
Long and Azmi.—Photo-ID to monitor sea turtles at Perhentian Islands of Malaysia.

362
the presence and behavior of tourists, including the use
of ash cameras, could disturb nesting turtles (Jacobson
and Lopez 1994; Waayers et al. 2008). Thus, it requires
training to know when and how to photograph nesting
turtles at night. The use of citizen science in photo-ID
can be useful in studying sea turtles in water and on
nesting beaches but practical guidelines, training, and
supervision are needed to minimize human impacts and
ensure that the data collection is reliable.
.—A photo-
ID database provided information on the in-water and
nesting sea turtle populations in the Perhentian Islands
Marine Park, including the number of individuals, sex
ratios, habitat use, and threats from human-sea turtle
interactions. Photographic identication also provides
mark-recapture data useful for future population models
to estimate population parameters, such as abundance,
survival, recruitment, residency, and population size,
and growth rate, as demonstrated in the studies of
other species, e.g., whales (Gowans et al. 2000) and
sharks (Holmberg et al. 2009; Gore et al. 2016). All
of this information can contribute towards informing
local governments in developing sustainable tourism,
conservation, and management practices in marine
parks. Thus, photo-ID can be a useful tool for long-term
population monitoring, assessing emerging or dominant
threats, and evaluating conservation status. Increased
sighting eorts at other beaches and in other nearshore
and deeper waters, as well as during the o-tourist
season, can enhance understanding of the temporal and
spatial turtle distributions, site delity, and movement
patterns in the marine park. However, due to the weather
conditions during the Northeast monsoon, poor water
visibility could impede the use of photo-ID. Regional
collaboration to share photo-ID databases would enable
the tracking of turtles to determine connectivity between
foraging and nesting sites at a regional scale (Schoeld
et al. 2008; Dunbar et al. 2014; Su et al. 2015). Such
understanding could then be used to assist in the
development of regional management and conservation
plans for sea turtles.
Acknowledgments.—We sincerely thank Daniel
Quilter for his support and invaluable advice, the sta
members, interns and volunteers of the PerhentianTurtle
Project, Blue Temple Conservation, Bubbles Turtle and
Reef Conservation Project and Perhentian Community
and Teaching Project, especially Nicholas John Tolen,
Petros Persad, Charlotte Emily Babbs, Muhammad Azri
Fakrullah Mohd Azhar, Neil Hinds, Sabina Gramaglia-
Hinds, Thomas Horsell, Shauna Tay Siew Li, Ng Chew
Tsann, Csaba Szilvási, and Kevin Heitzman, as well as
the DoF rangers, including Noor Hisam Bin Mohammad,
Ismail Bin Yaakob, Amran Bin Mohammad, Muhammad
Ghazali, Saiful Nizam Bin Ismail, Mohamad Syukiiran
Deraman, and Che Husin Bin Che Harum, for their
support and assistance in the eld, the members of
the public, especially Rahmat Bin Abd Wahab, for the
photographs, Christopher Town for kindly providing
access to the NaturePatternMatch, William Forster and
Thomas Brown for testing the software, and SEATRU
UMT for conrming the tag numbers. We are grateful
for the support from the local communities, government
agencies, resorts, chalets, dive centers, restaurants, and
cafes. This research was conducted in collaboration
with the Terengganu State Department of Fisheries
(Prk. Tr. 2214) and under the research permit from the
Department of Marine Park Malaysia (JTLM 630-7
Jld. 6 (12)). This research was nancially supported
by National Marine Aquarium and Durham University
Charities Kommittee.
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Herpetological Conservation and Biology
  is currently pursuing her Ph.D. research on human-sea turtle
interactions in relation of local livelihoods at Universiti Malaysia Terengganu.
She received her B.A.Sc. in Conservation and Biodiversity Management from
Universiti Malaysia Terengganu and M.Sc. in Conservation and Biodiversity
from University of Exeter. Upon graduation, she was a Research Assistant for the
Green Turtle Program at Tortuguero, Costa Rica. After returning to Malaysia, she
was the Project Leader for the Perhentian Community and Conservation Project,
working with the local communities on environmental and educational outreach
activities to raise public awareness. Her passion for sea turtle conservation has led
her to set up the Perhentian Turtle Project. (Photographed by Björn Johansson).
   received his B.A.Sc. in Biodiversity Conservation and
Management from Universiti Malaysia Terengganu, Malaysia. During his
undergraduate study, he developed a deep passion towards environmental
conservation, especially for the marine environment. In 2014, he obtained his rst
eld experience with turtle conservation while undertaking a summer internship
with Ecoteer in Perhentian Islands, Malaysia. The following year, he helped
to set up the Perhentian Turtle Project with goals of learning and gaining more
experience in the eld. While he is still in his early twenties, he is keen to learn
about turtle conservation work and pursue his Masters degree in the near future.
(Photographed by Charlotte E. Babbs).