Fisheries-induced adaptive change in reproductive investment in North Sea plaice (<i>Pleuronectes platessa</i>)?
Bibliographic record
Abstract
Life history theory predicts that fishing may select for increased reproductive investment. A model of the reaction norm for reproductive investment in a capital breeder was developed to disentangle changes in reproductive investment from changes in growth rate in North Sea plaice (Pleuronectes platessa). Trends in reproductive investment since 1960 were estimated as (i) the decrease in body weight of mature males and females between the start and end of the spawning period, (ii) the difference in weight of ripe and spent females, and (iii) the ovary weight of prespawning females. These estimates were related to somatic growth estimated by back-calculation of otoliths and temperature. The ovary weight and weight loss of females that had just started and just finished spawning did not reveal any trends. There was a significant increase in weight loss over the spawning season in both sexes, but much of this increase was likely due to changes in environmental conditions. Evidence for a fisheries-induced change in reproductive investment from our analyses thus remained inconclusive. However, fecundity and ovary-weight data from previous studies tentatively suggest that an increase in reproductive investment occurred between the late 1940s and the 1960s. Such an increase is consistent with a fisheries-induced evolutionary change.
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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 | 0.000 |
| 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 | 0.000 |
| 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".