Does catch and release affect the mating system and individual reproductive success of wild <scp>A</scp>tlantic salmon (<i><scp>S</scp>almo salar </i><scp>L</scp>.)?
Bibliographic record
Abstract
In this study, we documented the breeding system of a wild population of Atlantic salmon (Salmo salar L.) by genetically sampling every returning adult and assessed the determinants of individual fitness. We then quantified the impacts of catch and release (C&R) on mating and reproductive success. Both sexes showed high variance in individual reproductive success, and the estimated standardized variance was higher for males (2.86) than for females (0.73). We found a weak positive relationship between body size and fitness and observed that fitness was positively correlated with the number of mates, especially in males. Mature male parr sired 44% of the analysed offspring. The impact of C&R on the number of offspring was size dependent, as the reproductive success of larger fish was more impaired than smaller ones. Also, there was an interactive negative effect of water temperature and air exposure time on reproductive success of C&R salmon. This study improves our understanding of the complex reproductive biology of the Atlantic salmon and is the first to investigate the impact of C&R on reproductive success. Our study expands the management toolbox of appropriate C&R practices that promote conservation of salmon populations and limit negative impacts on mating and reproductive success.
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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".