Juvenile hawksbill residency and habitat use within a Caribbean marine protected area

Selby, Thomas H.; Hart, Kristen M.; Smith, Brian J.; Pollock, Clayton G.; Hillis‐Starr, Zandy; Oli, Madan K.

doi:10.3354/esr00975

Cited by 20 publications

(33 citation statements)

References 48 publications

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“…Consistent with methods provided by Selby et al [58], we reveal a framework for examining relative habitat selection of animals using acoustic telemetry and RSFs. This analytical approach includes inferring initial space use with calculated COAs, overlaying both COAs and random points onto aggregated habitat information, and using RSF GLMMs to examine resource selection.…”

Section: Discussionsupporting

confidence: 80%

“…Within BIRNM, habitats range widely from shallower water to deeper water habitats. From west to east, a high rugosity linear reef surrounds the south side of the island and wraps around Buck Island towards the northwest corner [58]. This reef system encompasses a 50-to 150-m-wide lagoon.…”

Section: Study Sitementioning

confidence: 99%

“…A passive acoustic receiver array, designed to study multiple species [53,61,[65][66][67][68], at BIRNM was expanded from six to 141 Vemco VR2W receivers (Vemco Amirix Systems, NS, Canada) between 2011 and 2018. Receivers were strategically placed on sand screws and some on cement block anchors around the island and its various habitats with the majority being deployed in < 15 m. Receiver data downloads and maintenance were performed twice a year.…”

Section: Study Sitementioning

confidence: 99%

“…Here, monthly MCPs were generated at the detection month level, thus, detection months after release refers to the subsequent months an individual was detected excluding any monthly gaps in detection history. For additional analyses, to ensure enough data to model individual turtle as a random effect and following Selby et al [58], we eliminated individual transmitter datasets with less than 100 COAs. For each individual transmitter dataset, we used KDEs to represent space use.…”

Section: Data Analysis Data Filtering and Organizationmentioning

confidence: 99%

“…Subsequently, RSFs can be used to help predict habitat selection probabilities outside the observable area based on the selected covariates. To understand relative habitat selection and space use of immature green turtles in the BIRNM, we applied RSFs using GLMMs with a binomial distribution similar to the approach presented by Selby et al [58].…”

Section: Rsfs and Glmmsmentioning

confidence: 99%

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Space use and relative habitat selection for immature green turtles within a Caribbean marine protected area

et al. 2020

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Background: A better understanding of sea turtle spatial ecology is critical for the continued conservation of imperiled sea turtles and their habitats. For resource managers to develop the most effective conservation strategies, it is especially important to examine how turtles use and select for habitats within their developmental foraging grounds. Here, we examine the space use and relative habitat selection of immature green turtles (Chelonia mydas) using acoustic telemetry within the marine protected area, Buck Island Reef National Monument (BIRNM), St. Croix, United States Virgin Islands. Results: Space use by turtles was concentrated on the southern side of Buck Island, but also extended to the northeast and northwest areas of the island, as indicated by minimum convex polygons (MCPs) and 99%, 95%, and 50% kernel density estimations (KDEs). On average space use for all categories was < 3 km 2 with mean KDE area overlap ranging from 41.9 to 67.7%. Cumulative monthly MCPs and their proportions to full MCPs began to stabilize 3 to 6 detection months after release, respectively. Resource selection functions (RSFs) were implemented using a generalized linear mixed effects model with turtle ID as the random effect. After model selection, the accuracy of the top model was 77.3% and showed relative habitat selection values were highest at shallow depths, for areas in close proximity to seagrass, and in reef zones for both day and night, and within lagoon zones at night. The top model was also extended to predict across BIRNM at both day and night. Conclusion: More traditional acoustic telemetry analyses in combination with RSFs provide novel insights into animal space use and relative resource selection. Here, we demonstrated immature green turtles within the BIRNM have small, specific home ranges and core use areas with temporally varying relative selection strengths across habitat types. We conclude the BIRNM marine protected area is providing sufficient protection for immature green turtles, however, habitat protection could be focused in both areas of high space use and in locations where high relative selection values were determined. Ultimately, the methodologies and results presented here may help to design strategies to expand habitat protection for immature green turtles across their greater distribution.

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Section: Discussionsupporting

confidence: 80%

Section: Study Sitementioning

confidence: 99%