Effects of hatchery supplementation on abundance and productivity of natural-origin Chinook salmon: two decades of evaluation and implications for conservation programs
Bibliographic record
Abstract
Hatchery supplementation has been developed to conserve salmonid populations and provide fisheries. We evaluated supplemented and reference Chinook salmon (Oncorhynchus tshawytscha) populations prior to, during, and after supplementation ceased for 22 years in two major drainages in Idaho, USA. Basin-level analyses showed supplementation increased abundance at some life stages, but effects did not persist into the postsupplementation phase and had no apparent influence on productivity. Natural-origin juvenile abundance increased during supplementation but results for adults were ambiguous. After supplementation ceased, abundance and productivity in supplemented and reference populations returned to their presupplementation relationships. Intensive analyses of supplemented populations with weirs showed abundance increased at some life stages with the addition of female spawners. However, the rate of increase varied with female origin (natural > supplementation ≥ nontreatment hatchery), and effects diminished through the life cycle. Based on these findings, we provide guidance for conservation programs. Supplementation alone is not a panacea because it does not correct limiting factors, which must be addressed to achieve population levels capable of sustaining ecological function and harvest.
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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 | 0.002 | 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) | 0.001 | 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".