Fishing-induced versus natural selection in different brown trout (<i>Salmo trutta</i>) strains
Bibliographic record
Abstract
Wild, adfluvial brown trout (Salmo trutta) are iconic targets in recreational fisheries but also endangered in many native locations. We compared how fishing and natural selection affect the fitness-proxies of brown trout from two pure angling-selected strains and experimental crosses between an adfluvial, hatchery-bred strain and three wild, resident strains. We exposed age 1+ parr to predation risk under controlled conditions where their behaviour was monitored with PIT-telemetry, and stocked age 2+ fish in two natural lakes for experimental fishing. Predation mortality (16% of the fish) was negatively size-dependent, while capture probability, also reflecting survival, in the lakes (38.9% of the fish) was positively length- and condition-dependent. Angling-induced selection against low boldness and slow growth rates relative to gillnet fishing indicated gear-dependent potential for fisheries-induced evolution in behaviours and life-histories. Offspring of wild, resident fish showed slower growth rates than the crossbred strains. Strain effects suggested significant heritable scope for artificial selection on life-history traits and demonstrated that choices of fish supplementation by stocking may override the genetic effects induced by angling.
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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".