Pre-nesting Movements of Leatherback Sea Turtles, Dermochelys coriacea, in the Western Atlantic
Bibliographic record
Abstract
Understanding high-use areas for highly migratory species and their movements within these areas may provide insight into behaviours such as foraging and mating. In the Western Atlantic, the leatherback sea turtle, Demochelys coriacea, has a broad geographic range extending from nesting beaches at low latitudes to foraging areas off the coast of Eastern Canada. Biotelemetry has revealed much about the movements and habitats of leatherbacks. However, the timing and location of leatherback mating behaviour remains unclear. We conducted spatial analyses of the movements of reproductive female leatherbacks prior to their first seasonal nesting events. Using kernel density estimates, high-use areas for seven female turtles originally tagged in Canadian waters were revealed from 50% volume contours depicting pre-nesting movements (120 days prior to confirmed nesting events) and inferred mating behaviour (45 days prior to confirmed nesting events). All individuals initially remained offshore within a relatively small range of latitude (10-15o N) before transiting and residing in coastal waters adjacent to nesting beaches in Colombia (n=2), Trinidad (n=3), Guyana (n=1) and French Guiana (n=1). Comparison of these movement patterns to those of mature male leatherbacks (n=12) revealed similarities. Male and female residency within this offshore high-use area may be indicative of prey exploitation prior to the energetically costly nesting season. While the offshore residency period of three males and one female extended into the interval in which mating is expected to occur, most males and females transited to coastal waters where they resided throughout this period. High-use areas determined through kernel density analysis support and corroborate previous telemetry work indicating that mature male leatherbacks exhibit seasonal residency adjacent nesting beaches for the early portion of the nesting season, presumably to exploit mating opportunities. Fine-scale analyses of fisheries interactions in both coastal and offshore waters and estimation of accompanying mortality rates is required to evaluate fishery threats on this population during the pre-nesting interval.
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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 | 0.001 | 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".