Connor F. White
Donna J. Shaver
Margaret Lamont
Michael Cherkiss
Andrew G. Crowder
Nicholas M. Whitney
Kristen Hart
2025
<p><span id="_mce_caret" data-mce-bogus="1" data-mce-type="format-caret"><span>Quantifying sea turtle nesting behavior is essential for recovery planning and evaluating management actions. Traditional monitoring approaches, based on nest counts from beach surveys, can misclassify non-nesting emergences, obscure true fecundity, and underestimate clutch frequency, metrics that directly influence population models and regulatory decisions. Here, we demonstrate that high-resolution acceleration data loggers (ADLs) can reliably discriminate nesting from non-nesting emergences across four imperiled species of sea turtles at sites in the Gulf of America, southeast USA, and Caribbean. From 60 recovered ADL deployments on green (</span><i>Chelonia mydas</i><span>; N = 10), hawksbill (</span><i>Eretmochelys imbricata</i><span>; N = 7), Kemp’s ridley (</span><i>Lepidochelys kempii</i><span>; N = 21), and loggerhead sea turtles (</span><i>Caretta caretta</i><span>; N = 22) lasting on average 17.5 ± 8.7 days (range 2–43 days), we identified 54 nesting events and 76 non-nesting emergences, with >97% accuracy when compared to direct observations. These data provide the first observer-validated, species-specific behavioral signatures of nesting phases and reveal correlations between egg-laying duration and clutch size. All non-nesting emergences occurred within 72 hours of subsequent nesting, allowing managers to anticipate nest deposition windows. By refining inter-nesting intervals and fecundity estimates, ADLs offer a practical path to reduce error in clutch frequency estimates. The integration of ADL-derived algorithms with satellite-transmitting tags would enable the remote, real-time monitoring of nesting activity, creating a system for the remote monitoring of inter-nesting intervals and nest fecundity that are crucial to quantify the impacts of climate change and other threats to sea turtle nesting habitat.</span></span></p>
application/pdf
10.3389/fmars.2025.1691053
en
Frontiers Media
Biologging to identify nesting and non-nesting emergences for four species of imperiled sea turtles
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