Vegetation cover predicts temperature in nests of the hawksbill sea turtle: implications for beach management and offspring sex ratios
Bibliographic record
Abstract
Whether a sea turtle embryo develops into a male or a female depends, as with many other reptiles, on the temperature during incubation of the eggs. With sea turtles, warm temperatures produce 100% females and, thus, increasing global temperatures have the potential to significantly alter offspring sex ratios. Nest-site selection provides a potential mechanism by which females might adjust the sex of their offspring, but necessitates a reliable cue which provides information about the thermal properties of a nest. Overstory vegetation cover was found to significantly predict temperatures in nests of the hawksbill sea turtle Eretmochelys imbricata. Nests placed under high vegetation cover are significantly cooler and remain within the male-producing range of temperatures throughout incubation. Interestingly, metabolic heating of the developing clutch is less pronounced under vegetation, further reinforcing the importance of this nesting habitat with respect to the production of males. This underscores the importance of preserving natural vegetation cover at hawksbill nesting beaches in order to maintain the thermal diversity of nesting sites and, potentially, mitigate the impacts of increasing global temperatures.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".