DOI: 10.5061/dryad.6hdr7srd7
title: Camera traps: A novel method to estimate numbers of nesting sea turtles

description: Abundance estimates are difficult to obtain for many animal groups, yet
 essential for endangered species management and conservation. For sea
 turtles, estimates are made from ground counts of nesting females, tracks
 and nests, but these are challenging at remote locations. Here we explore
 the applicability of using camera traps to monitor and estimate sea turtle
 nesting tracks at a green turtle (Chelonia mydas) rookery in the Western
 Indian Ocean. Camera traps (n = 13) were deployed to photograph turtle
 tracks daily along a 2.8 km beach in Diego Garcia, Chagos Archipelago in
 2021 and 2022. Foot patrol surveys were conducted in April and May 2021
 and August 2022 (14, 13 and 20 days, respectively). Track counts were
 compared from both methods to validate the use of cameras. From foot
 patrol surveys, we observed an increase in track counts around neap tides
 (mean ± SD: 5.0 ± 4.0 tracks per day; n = 131 tracks) compared to spring
 tides (2.4 ± 1.8 tracks per day; n = 51 tracks). Mean track longevity was
 similar during neap (2.9 ± 2.0 days; n = 39 tracks) and spring tides (2.7
 ± 2.6 days; n = 20 tracks). Mean daily track counts were comparable during
 neap tides (camera traps: 7.3 ± 12.9 tracks cf. patrols: 5.0 ± 4.0 tracks)
 and across the tidal cycle (camera traps: 5.5 ± 13.1 tracks cf. patrols:
 3.9 ± 3.4 tracks). Using simulated data, we found track count variability
 decreased in a power-law relationship with increasing coverage by cameras.
 The disparity in track counts between methods would likely decrease if
 beach coverage increased from 5% to 20%. Camera traps provide a
 complimentary tool to fill data gaps at remote sites that would otherwise
 have little to no assessments. Furthermore, the increased temporal
 coverage from cameras can help identify changes in nesting phenology and
 trends in nesting numbers.
description: # Camera traps: A novel method to estimate numbers of nesting sea turtles
 Dataset DOI: [10.5061/dryad.6hdr7srd7](10.5061/dryad.6hdr7srd7) ##
 Description of the data and file structure *Study area* Diego Garcia
 (7.42°S, 72.45°E) is the largest and only inhabited island in the Chagos
 Archipelago and has 72.1 km of coastline of which 40.5 km (56%) is deemed
 suitable nesting habitat. Our study was undertaken along a 2.8 km stretch
 of beach (Index Beach) identified as one of the highest nesting density
 areas (Figure 1a). In the Chagos Archipelago, green turtles (*Chelonia
 mydas*) nest year-round, mostly between June and October with a peak in
 August, whilst hawksbills (*Eretmochelys imbricata*) nest between October
 and February (Mortimer et al., 2020). 
 
 *Foot patrol surveys and track counts* Turtle tracks, defined as the
 imprint a turtle leaves in the sand, were counted during foot patrol
 surveys. The surveys were conducted during the months of April and May
 2021 and August 2022 (14, 13, and 20 survey days within each month,
 respectively). For every survey, all tracks were counted, and a line drawn
 through the track to avoid double counting. Mean track width was recorded
 from three measurements using a flexible tape measure and used along with
 track characteristics to identify species. Green turtles leave a
 symmetrical track (usually &gt; 100 cm wide) in the sand while hawksbills
 leave an asymmetrical track (typically &lt; 95 cm; see Pritchard &
 Mortimer, 1999 and Mortimer et al., 2020). Mean track count per day was
 calculated using the number of fresh tracks recorded on survey days (n =
 47 days). 
 
 *Camera trap survey design and settings* Camera traps (Apeman H70; n =
 13) were attached to tree trunks or large branches (e.g., 166 Tournefortia
 argentea; Figure A1a) lining the nesting beach. Cameras were positioned to
 be equally spaced along the survey area as far as possible and to capture
 the length of beach. Camera placement was affected by (a) vegetation
 available for attachment and avoidance of (b) vegetation obstructing the
 camera’s field of view, and (c) overlap of images (Figure A1b). There was
 equal potential for cameras to be placed in areas of higher or lower
 nesting activity. The distance observed from each camera trap was measured
 by creating ‘turtle tracks’ in the sand every 5 m until the tracks were no
 longer visible (range from a single camera trap = 5-30 m; Table A1). The
 number of ‘turtle tracks’ visible from each camera was counted both in
 person and from images (Figure A1b). Estimated distances of beach coverage
 differed from each camera (e.g., due to variability in vegetation
 obstruction along the beach) and from the same camera over time (e.g., due
 to the camera falling slightly and altering the angle and view from the
 camera; Table A1; for more detail see Appendix 1). Trigger settings were
 disabled, and camera traps were set to take daily images on timelapse with
 30 min intervals between 0700 and 0800 h. In 2022, ten of the cameras were
 set to take images every 30 s between 0700 and 0830 h from July 13. ###
 Files and variables #### File: Foot_patrol_track_count_2021_2022.csv
 **Description:** Sea turtle track counts from foot patrol surveys. #####
 Variables * Date: Date of the foot patrol survey (dd/mm/yyyy). *
 Fresh_track_count: The number of fresh tracks counted on the survey day.
 NA indicates no survey day. * Tidal_state_daysafterspringtide: Day 0 =
 spring tide. Spring tide being the highest tide with the greatest tidal
 range on or after the most recent full or new moon. Subsequent days are
 the number of days after spring tide. #### File:
 Camera_trap_April_Sept_2021_2022.csv **Description:** Sea turtle track
 counts from camera trap surveys. ##### Variables * Date: Date of the
 camera trap survey (dd/mm/yyyy). * CT_ID: Camera trap ID number (01-13). *
 Track_0_1: 0 = no track, 1 = track. If more than one track was visible in
 the same photograph, the track was recorded in a separate row. *
 Longevity_days: The number of days the turtle track persisted on the beach
 recorded from the camera trap images. *
 Tidal_state_daysafterspringtide: Day 0 = spring tide. Spring tide being
 the highest tide with the greatest tidal range on or after the most recent
 full or new moon. Subsequent days are the number of days after spring
 tide.  * Camera_distance_m: Total observable distance in an image from a
 camera trap. ## Code/software All analyses were conducted in the free
 software R.