Environmental drivers of diving behavior and space-use of juvenile endangered Caribbean hawksbill sea turtles identified using acoustic telemetry
Bibliographic record
Abstract
Space-use by aquatic ectotherms is closely linked to environmental factors such as temperature due to thermal-mediated metabolism and energy requirements. These factors are important, as they may alter an animal’s exposure to food/predators, hinder physiological function, increase competitive interactions, or even prompt population or biodiversity loss. Using general linear mixed-effects models, we investigated the influence of medium-term (months-years) environmental (diel period, water temperature, season, wind speed, air pressure, habitat type) and biological (turtle size) variation on space-use metrics for the Critically Endangered hawksbill sea turtle Eretmochelys imbricata , including dive duration, activity space, and rate of movement. We tracked 17 resident juveniles between August 2015 and May 2018 with a compact acoustic telemetry array (35-41 receivers in ~1 km 2 ) in Brewers Bay, US Virgin Islands. Diel differences in space-use were significant and highlighted periods of relative inactivity (e.g. resting) during the night and activity (e.g. foraging) during the day. Water temperature was also an important covariate influencing behavior leading to shorter dive durations and higher rates of movement in warmer temperatures. High contribution of random effects (individual and year) to model variation was also apparent, suggesting that juvenile hawksbills can operate outside the relatively narrow environmental range experienced within the study area. Nevertheless, ongoing climate trends (e.g. warmer temperatures and more extreme weather events) pose a significant concern for hawksbill populations, as juveniles spend their developmental period in shallow nearshore areas where environmental impacts will likely be greatest.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".