Reproductive success in wild and hatchery male coho salmon
Bibliographic record
Abstract
Salmon produced by hatcheries have lower fitness in the wild than naturally produced salmon, but the factors underlying this difference remain an active area of research. We used genetic parentage analysis of alevins produced by experimentally mixed groups of wild and hatchery coho salmon (Oncorhynchus kisutch) to quantify male paternity in spawning hierarchies. We identify factors influencing paternity and revise previously published behavioural estimates of reproductive success for wild and hatchery males. We observed a strong effect of hierarchy size and hierarchy position on paternity: in two-male hierarchies, the first male sired 63% (±29%; s.d.) of the alevins and the second male 37% (±29%); in three-male hierarchies, the first male sired 64% (±26%), the second male 24% (±20%) and the third male 12% (±10%). As previously documented, hatchery males hold inferior positions in spawning hierarchies, but we also discovered that hatchery males had only 55-84% the paternity of wild males when occupying the same position within a spawning hierarchy. This paternity difference may result from inferior performance of hatchery males during sperm competition, female mate choice for wild males, or differential offspring survival. Regardless of its cause, the combination of inferior hierarchical position and inferior success at a position resulted in hatchery males having only half (51%) the reproductive success of wild males.
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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".