Biologging to identify nesting and non-nesting emergences for four species of imperiled sea turtles

Kristen Marie Hart^1*Connor Frederick White²Donna Jill Shaver³Margaret Lamont⁴Michael Cherkiss¹Andrew G. Crowder⁵Nick Whitney²

• ¹United States Geological Survey, Wetland and Aquatic Research Center, Davie, United States
• ²Anderson Cabot Center for Ocean Life, New England Aquarium, Boston, United Kingdom
• ³U.S. National Park Service, Padre Island National Seashore, Corpus Christi, United States
• ⁴US Geological Survey Wetland and Aquatic Research Center Gainesville, Gainesville, United States
• ⁵Xylem, Boca Raton, United States

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 U.S., and Caribbean. From 60 recovered ADL deployments on green (Chelonia mydas; N=10), hawksbill (Eretmochelys imbricata; N=7), Kemp’s ridley (Lepidochelys kempii; N=21), and loggerhead sea turtles (Caretta caretta; 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 h 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. Integration of ADL-derived algorithms with satellite-transmitting tags would enable remote, real-time monitoring of nesting activity, creating a system for 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.