Behaviour of foraging marine turtles 309
1999). Turtles were also checked for the presence of fibropa- pillomatosis; only visibly healthy turtles without fibropapil- lomatosis were considered for satellite tag deployment. We deployed Argos-linked Fastloc GPS (Wildlife Computers SPLASH 10-BF-351E, Redmond, USA) tags on two green turtles, one Kemp’s ridley and one loggerhead turtle during 5 May–11 June 2016, prior to the scallop season (Supplementary Table 2). Satellite tags were attached using the methods described by Seney et al. (2010) for small juven- ile turtles, which allows for the increased growth rates of smaller turtles while minimizing transmitter loss. Turtles were kept on board for amaximum of 2 h, to reduce behav- iour disruption. Satellite-derived GPS positions of each tur- tle were extracted from early June until the last location was transmitted. Positions were then filtered to exclude very low accuracy Argos fixes (A, B, Z) and remove temporal/spatial duplicates and locations with unlikely travel and turning speeds, using the data-driven SDL filter (Shimada et al., 2012)in Rv. 3.4.3 (R Core Team, 2017). A second manual filter was applied to remove fixes located on land and obvious erroneous fixes that might not have been depicted by the SDL filter (e.g. too far away). Temporal distribution of filtered fixes is shown in Supplementary Fig. 2.
Data analysis
We used the Kernel Density Analysis tool in ArcGIS 10.3 (ESRI, Redlands, USA) and the isopleth function in GME 0.7.3 (Beyer, 2012) to identify the density, distribution area (where 95% of sightings were recorded) and hotspots (where 50% of sightings were recorded) of harvest vessels and marine turtles. The distribution area of marine turtles before and during the scallop harvest season, and between marine turtles and vessels during the scallop harvest season, were compared qualitatively. To quantify the percentage of overlap between vessels and marine turtle areas during the harvest season, we used the Zonal Statistics as Table tool in ArcGIS. To estimate home ranges and core areas of tracked turtles
we considered all filtered locations for each season (before and during scallop harvest season; Supplementary Table 2), and computed utilization distribution, applying amovement- based kernel density estimation based on a biased ran- dom bridge model (Benhamou, 2011) with the package adehabitatHR (Calenge, 2011)in R. Home ranges were de- fined as the 95% utilization distribution and core areas as the 50% utilization distribution. We employed a Behavioral Change Point Analysis
(Gurarie et al., 2009) to assess potential changes in the movement behaviour of the tracked turtles 2 weeks before and after the beginning of the harvest season (25 June 2016). Change points, which are moments in time in which the Behavioral Change Point Analysis identified a sig- nificant change in behaviour, were assessed based on their
TABLE 1 Size of home ranges (95%utilization distribution) and core areas (50% utilization distribution) of individual green Chelonia mydas, Kemp’s ridley Lepidochelys kempii and loggerhead Caretta caretta turtles tracked with satellite telemetry, before and during scallop harvest season.
Before scallop season Turtle ID
Green turtles Cm_1 Cm_2
Kemp’s ridley turtle Lk_1
Loggerhead turtle Cc_1
Home range (km2)
194.5 5.9
5.4 44.2
Core area (km2)
29.6 1.3
0.8 8.6
During scallop season
Home range (km2)
54.5 2.0
14.5 35.4
Core area (km2)
6.2 0.4
1.7 7.3
proximity to the beginning of season date. The values of the movement parameters (persistence velocity, variability in persistence velocity, tortuosity and travel speed) were compared before and after the significant change points. Persistence velocity is a measure that accounts for speed and directionality of the individual, and tortuosity is ameas- ure of how much an individual turns.
Results
Spatial distribution of marine turtle and vessel sightings We recorded 14.9 ± SD 12.4 marine turtles per day and 36.3 ± SD 33.7 vessels per day before the scallop harvest season, and 12.7 ± SD 10.9 marine turtles per day and 260.1 ± SD 151.8 vessels per day during the scallop season. The majority of vessels observed along the transects were stationary, and were probably engaging in scallop and fishing activities. In terms of turtle–vessel interactions, we did not witness any boat-strikes during the surveys but turtles were commonly observed fleeing from our research vessel. The relative dis- tribution of marine turtles, particularly the distribution of marine turtle hotspots, shifted before and during the scallop harvest season (Fig. 1a). Additionally, during the scallop harvest season 48% of the relative turtle distribution area overlapped with vessels (Fig. 1b), with a mean of 4.5 vessels per 500 m2 grid cell (range 0–33 vessels per cell).
Changes in individual marine turtle distribution
Mean home range size was 70 ± SD 84.6 km2 before the scal- lop harvest season, and 27.5 ± SD 22.6 km2 during the scal- lop harvest season (Table 1; Fig. 2). Average core area was 10.2 ± SD 13.4 km2 before and 4.1 ± SD 3.2 km2 during the scallop harvest season (Table 1; Fig. 2). Home ranges and
Oryx, 2020, 54(3), 307–314 © 2018 Fauna & Flora International. This is a work of the U.S. Government and is not subject to copyright protection in the United States. doi:10.1017/S0030605318000182
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