Evaluating the long-term per capita productivity benefits and associated costs of supplementation in upper Yakima River Chinook salmon
Bibliographic record
Abstract
Numerous studies in salmonids have demonstrated a fitness cost of producing and releasing hatchery-origin fish into the natural environment. One approach to reduce these fitness costs is to incorporate natural-origin fish into the hatchery broodstock, but this is not always feasible and may not consistently buffer against domestication. In this study, we used 15 years of spawning and genetic data from the upper Yakima River spring Chinook salmon ( Oncorhynchus tshawytscha) population to successfully assign approximately 50 000 returning adult progeny to their parents, allowing us to reconstruct a two-generation pedigree and evaluate reproductive success (RS). We identified consistently lower RS of hatchery-origin compared to natural-origin fish when spawning in nature. However, the hatchery broodstock demonstrated higher per capita productivity than natural spawners into the second generation even after accounting for lower RS by hatchery-origin progeny in the intermediate generation. We also identified fork length and returning timing, in addition to origin, as important components of individual RS in this population. We then discuss the significance of these results in the context of future salmonid supplementation studies.
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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 | 0.000 |
| 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) | 0.000 | 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".