Life history effects on hatchery contributions to ocean harvest and natural-area spawning
Bibliographic record
Abstract
Hatcheries can support salmon fisheries but also impact natural populations. We model the proportional hatchery contributions to ocean catch, natural-area spawning, and egg production based on hatchery production, maturation, fecundity, and straying. We develop indices of hatchery-origin catch per stray spawner measuring the trade-off between supplementing harvest and limiting natural-area impacts; higher values indicate success in increasing hatchery ocean harvest contributions relative to strays spawning in natural areas. Hatchery fish maturing early lowers catch per stray (and proportion hatchery-origin catch) by shifting the age distributions of both catch and spawners toward younger ages. Age-dependent fecundity may complicate predicted effects of changing maturation schedules. Increased straying does not affect catch but increases hatchery-origin spawning and decreases catch per stray. Differences in hatchery production affect hatchery contributions to both catch and spawning, exacerbating the trade-off between these conflicting goals but with no net effect on catch per stray. Fishery intensity magnifies the effects of accelerated hatchery fish maturation by reducing spawning contributions of older fish, with contrasting effects depending on whether hatchery fish mature early versus late.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".