Recruitment variation related to fecundity in marine fishes
Bibliographic record
Abstract
An understanding of the processes that control recruitment variation is central to explaining the population dynamics of fishes and predicting their responses to exploitation. Theory predicts that interannual variation in recruitment should be positively correlated with the fecundity of fish species, but empirical studies have not supported this hypothesis. Here, we adopt a phylogenetic comparative approach, which accounts for evolutionary relatedness among stocks and species, to investigate this relationship. We calculated the mean fecundity of fishes from 52 stocks at the mean length of maturity and related this to interannual recruitment variation. We found that in 13 of 14 comparisons between stocks or closely related species, the stocks with higher fecundity have higher recruitment variation. This was true whether or not we controlled for spawning stock size. However, when the analyses were repeated using a traditional cross-species approach, which did not account for the evolutionary relatedness of stocks, the relationships were not significant. This is the first empirical study to link fecundity with recruitment variation and suggests that fecundity is an important component of fish stock dynamics.
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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 | 0.001 | 0.004 |
| 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".