6 research outputs found

    MASS NESTING IN OLIVE RIDLEY SEA TURTLES: TIMING, NEARSHORE BEHAVIOR, AND POSSIBLE CUES FOR NESTING SYNCHRONIZATION

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    During the mass-nesting of sea turtles (also known as arribadas), thousands of turtles emerge from the ocean to nest simultaneously along a small stretch of beach. The research presented here involves a series of studies to describe the mass-nesting behavior and investigate possible mechanisms for synchronization of nesting. As a first step towards investigating this behavior and whether environmental cues might coordinate nesting, ten years of mass-nesting data were analyzed. Patterns in the behavior were described and statistical models were used to identify environmental variables that influence the onset and size of mass-nesting events. Findings suggest that the onset of synchronized nesting in olive ridley turtles is not triggered by a single environmental cue. Instead, events are likely affected by multiple physiological and environmental variables. In principle, behavioral interactions in the ocean might also play a role in the synchronization of nesting. A drone was used to conduct aerial surveys over the nearshore waters of a mass-nesting site during seven events to observe aggregations of turtles. No clear organization of turtles appeared to occur at sea, although in some cases turtles seem to move gradually shoreward prior to the onset of nesting. Findings reveal considerable variation among individual arribadas, with no universal pattern of group movement reliably preceding group emergence on the beach. A pheromone, or other chemical signal, could also serve as a cue to initiate the mass-nesting behavior. To test whether olfaction plays a role in the timing of nesting, I temporarily disrupted olfaction in olive ridley turtles to determine whether this impairment altered the timing of nesting during a mass-nesting event. Turtles captured at sea before an arribada, treated with an olfactory anesthetic, and released offshore nested significantly later than control turtles treated with saline. The results are consistent with the possibility that olfactory cues play a role in synchronizing nesting, although alternative explanations including effects on navigation or health cannot be excluded. Taken together, these findings provide insight into the possible mechanisms for synchronized nesting in sea turtles and have important implications for conservation management at this and other mass-nesting sites.Doctor of Philosoph

    Quantifying Nearshore Sea Turtle Densities: Applications of Unmanned Aerial Systems for Population Assessments

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    Although sea turtles face significant pressure from human activities, some populations are recovering due to conservation programs, bans on the trade of turtle products, and reductions in bycatch. While these trends are encouraging, the status of many populations remains unknown and scientific monitoring is needed to inform conservation and management decisions. To address these gaps, this study presents methods for using unmanned aerial systems (UAS) to conduct population assessments. Using a fixed-wing UAS and a modified strip-transect method, we conducted aerial surveys along a three-kilometer track line at Ostional, Costa Rica during a mass-nesting event of olive ridley turtles (Lepidochelys olivacea). We visually assessed images collected during six transects for sea turtle presence, resulting in 682 certain detections. A cumulative total of 1091 certain and probable turtles were detected in the collected imagery. Using these data, we calculate estimates of sea turtle density (km-2) in nearshore waters. After adjusting for both availability and perception biases, we developed a low-end estimate of 1299 ± 458 and a high-end estimate of 2086 ± 803 turtles per km-2. This pilot study illustrates how UAS can be used to conduct robust, safe, and cost-effective population assessments of sea turtle populations in coastal marine ecosystems

    Author Correction: Quantifying Nearshore Sea Turtle Densities: Applications of Unmanned Aerial Systems for Population Assessments

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    A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper
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