Fluctuating reproductive output and environmental stochasticity: do years with more reproducing females result in more offspring?
Bibliographic record
Abstract
Reproduction is a key life-history process often constrained by abiotic conditions, which affect resource availability and influence reproductive output, including the number of females in a population that reproduce within a given year. We investigated whether population-level fluctuations in reproductive effort (i.e., the number of nesting females) result in fluctuations in the number of offspring produced under environmentally stochastic conditions. Here we show that timing and frequency of tropical storms constrain reproductive success in green sea turtles ( Chelonia mydas (L., 1758)); in years when storms arrive early or when multiple storms occur most green sea turtle nests are inundated by seawater and fail to hatch. Although equal proportions of the nests were destroyed by tropical storms in peak and non-peak nesting years, significantly more hatchlings emerged from nests during peak nesting years. Thus, the cyclic patterns of green sea turtle reproduction result in cyclic patterns of hatchling emergence under high levels of nest failure owing to seawater inundation. Ultimately, green sea turtle reproductive success is constrained by the timing of tropical storms in relation to the nesting season. Continuing increases in the severity of tropical storms from changing global climates could contribute to a higher proportion of nesting seasons with low reproductive success, such that population growth rates are slowed, which may have long-term negative effects on the ability of this species to recover to historical levels.
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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 | 0.000 | 0.000 |
| 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".