When bigger is not better: selection against large size, high condition and fast growth in juvenile lemon sharks
Bibliographic record
Abstract
Selection acting on large marine vertebrates may be qualitatively different from that acting on terrestrial or freshwater organisms, but logistical constraints have thus far precluded selection estimates for the former. We overcame these constraints by exhaustively sampling and repeatedly recapturing individuals in six cohorts of juvenile lemon sharks (450 age-0 and 255 age-1 fish) at an enclosed nursery site (Bimini, Bahamas). Data on individual size, condition factor, growth rate and inter-annual survival were used to test the 'bigger is better', 'fatter is better' and 'faster is better' hypotheses of life-history theory. For age-0 sharks, selection on all measured traits was weak, and generally acted against large size and high condition. For age-1 sharks, selection was much stronger, and consistently acted against large size and fast growth. These results suggest that selective pressures at Bimini may be constraining the evolution of large size and fast growth, an observation that fits well with the observed small size and low growth rate of juveniles at this site. Our results support those of some other recent studies in suggesting that bigger/fatter/faster is not always better, and may often be worse.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 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".