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the centroid of these data) for each individual turtle, and for combined individuals each month. For the polygon sam- pling, a 3.5 km2 hexagonal grid was constructed and spatial- ly intersected with locations to derive a count of the total number of unique turtles recorded per grid cell. The mean proportion of locations was also calculated based on the proportion of locations recorded within each grid cell for each individual. Kernel density estimation was used to de- scribe habitat use, and calculated using methods that ac- count for physical barriers that can prevent movement for marine species (i.e. land; Sprogis et al., 2016). The output cell size was 50 × 50 m(0.0025 km2) and the bandwidth (search radius that determines the surrounding locations, which contribute to the estimation) was set to 1,500 m. The choice of a bandwidth selectionmethodmay vary depending on the study goals, sample size and patterns of space use by the study species (Gitzen et al., 2006), and therefore the band- width value was chosen by iterative visual inspection of out- puts (per Sprogis et al., 2016). The output fromkernel density estimation thus represents the estimated density of locations per km that are likely to occur within each grid cell, from which we extracted 95, 75, 50 and 25% utilization distri- butions. Finally, to describe habitat use within Loango Bay we calculated the proportion of locations within 10 seabed depth classes at 10 m intervals, and 10 offshore distance classes at 1 km intervals, for each tagged individual. Seabed depth (m) and offshore distance (km) values were assigned to each daily location using General Bathymetric Chart of the Oceans gridded data (resolution 30 arc-seconds; Weatherall et al., 2015), and fine-scale coastline data extracted from Landsat data (Xu, 2006), respectively.
Results
Deployment summary, size distribution, tracking duration and displacement distance
Of the 10 turtles tagged with satellite PTTs, one tag was excluded from subsequent analyses as it failed ,24 h post deployment (individual D; Table 1). For eight of the remaining nine tagged the turtles’ body size data were available (curved carapace length, CCL: 39.0–90.0 cm, mean 61.2 ± SD 19.8 cm, median 61.1 cm, IQ range 43.2– 75.0 cm; Table 1). These nine individuals were tracked for 9–161 days (mean 80 ± SD 50 days, median 88 days, IQ range 34–111 days; Table 1), with maximum displace- ment distance from release locations within the foraging ground of 10.8–56.0 km (mean 27.3 ± SD 16.5 km, median 20.4 km, IQ range 15.2–38.0 km; Table 1, Supplementary Fig. 1). There was no significant relationship between the size of individuals and tracking duration (days) or max- imum displacement distance (km) from release locations (all P.0.05; Supplementary Fig. 2).
General movements, core areas and habitat use
Of the nine tagged individuals that transmitted location data post deployment, eight remained within the vicinity of Pointe Indienne in Loango Bay (Supplementary Fig. 3) for 9–161 days (Table 1). One individual (I; Supplementary Fig. 3), however, migrated south after 34 days (Table 1). This took the turtle a minimum distance of 505.9 km along the continental shelf (,200 m depth) over a period of c. 16.5 weeks (mean minimum speed 0.5 ± SD 0.5 km/h, median 0.3 km/h, IQ range 0.1–0.8 km/h, n = 18 locations) to foraging grounds in Mussulo Bay, Angola (Supplementary Fig. 4) where it remained for 30 days till cessation of tracking. Prior to analyses of core areas, telemetry data for indi-
vidual I (Table 1) was clipped at 26 March 2013, this being the date this turtle left the Loango Bay foraging ground (Supplementary Fig. 4). Within Loango Bay individual core areas of occupancy (based on 95% MCPs) of the nine individuals were 9.2–191.0 km2 (mean 69.8 ± SD 58.6 km2, median 54.2 km2, IQ range 26.1–81.4 km2; Table 1, Fig. 1). There was, however, no significant relationship between the CCL of individuals and the size of core areas (P.0.05; Supplementary Fig. 2). Analyses of monthly variation revealed that core areas of occupancy (based on MCPs) did not vary systematically and were probably driven more by data volume and ARGOS location quality. MCPs ranged between 6 km2 in November to 168.8 km2 in June (mean 69.0 ± SD 53.6 km2, median 56.9 km2, IQ range 27.7–100.2 km2,n = 11 months; Supplementary Fig. 5). In terms of habitat use, there was no evidence of
size-related niche partitioning, with individuals of all sizes using similar depth zones and distances offshore (Supplementary Fig. 6). Analysis of location data by depth and offshore distance revealed that all size classes had a preference for waters ,10 m deep (mean proportion of locations ,10 m 0.64 ± SD 0.14, median 0.60, IQ range 0.56–0.72; Fig. 2) within 3 km of the coast (mean proportion of locations,3km offshore 0.69 ± SD 0.15,median 0.67,IQ range 0.57–0.81; Fig. 2). Location of high use areas (i.e. areas with high occupancy; .10% of locations, and 50% utiliza- tion distribution) were restricted to shallow waters adjacent to and surrounding Pointe Indienne in Loango Bay (Fig 2).
Discussion
Marine turtles are migratory, often travelling great distances between natal beaches and foraging areas, and/or between foraging areas and reproductive sites (Godley et al., 2008). Yet for many of the world’s marine turtle populations em- pirical data on the distribution and condition of important foraging areas, or the behaviour and ecology of individuals in these habitats, are lacking (Rees et al., 2016; Williams et al., 2017). Describing marine turtle foraging grounds, in- cluding information on species, abundance, size/age classes
Oryx, 2020, 54(3), 299–306 © 2020 Fauna & Flora International doi:10.1017/S0030605319000309
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