Influence of nest location and yolkless eggs on the hatching success of leatherback turtle clutches in French Guiana
Bibliographic record
Abstract
The hatching success of leatherback turtles, Dermochelys coriacea (Vandelli, 1761), is influenced by heterogeneously distributed ecological factors. However, the hatching success according to nest-site selection has rarely been studied and little is known about the role of nest-site selection and infertile (yolkless) egg production on the predation rate and development of fertile eggs in leatherback turtle nests laid in French Guiana. A field study of 99 leatherback turtle nests was conducted to quantify the relationships between hatching success and (i) the nest-site selection (i.e., vegetation line, sea tide line) and (ii) the infertile eggs, especially their state after incubation (i.e., hydrated or dehydrated) and their effects on predation rate. We found that hatching success on this beach was very low (38.2%). This study illustrates that nest-site selection influences the predation rate and the dehydration of yolkless eggs, while the production of yolkless eggs by leatherback turtles has consequences on nest success. The proportion of yolkless eggs in the clutch, as well as their status at the end of incubation (hydrated or not, preyed upon), correlates with predation rate, development of yolked eggs, and hatching success. There was a significant relationship between nest location (relative to high tide line and vegetation line) and both the predation rates of eggs and the percentage of dehydrated yolkless eggs within a clutch. The production of yolkless eggs was related to hatching success and supports the hypothesis that yolkless eggs have a positive effect on the future of the clutch.
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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 | 0.001 | 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) | 0.001 | 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 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".