Dramatic adaptive response of life history trait to reduced commercial harvest in a freshwater fish
Bibliographic record
Abstract
Fisheries-induced evolution of exploited fish stocks toward maturation at smaller sizes and younger ages has been postulated to reduce stock productivity and depress the recovery of stocks after collapse. Moreover, evidence from empirical and modeling research has shown that evolutionary changes in maturation may be very slow or impossible to reverse, even following complete fisheries closures. We evaluated temporal trends in maturation of five Great Lakes stocks of yellow perch (Perca flavescens) using indices that reflect plastic (age at 50% maturity) and adaptive (probabilistic maturation reaction norms; PMRNs) variation in maturation schedules. Four of the populations were fished commercially throughout the time series, while one (Lake Michigan) experienced a fisheries moratorium following collapse of the stock. We documented a dramatic, adaptive increase in PMRNs of the Lake Michigan stock coincident with the closure of the commercial fishery, while populations that were continuously fished showed little change. This evidence is among the first to suggest that fish life history traits have the potential to rapidly respond to fishing moratoriums and recover from previous, fisheries-induced changes, meaning some stocks may retain the evolutionary ability to recover from commercial overexploitation.
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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) | 0.001 | 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".