Restricted inclusion of wild broodstock at a large hatchery does not result in detectable genetic differentiation in a supplemented coho salmon (<i>Oncorhynchus kisutch</i>) population
Bibliographic record
Abstract
Hatchery production is common in salmonid management for harvest and conservation. Many hatcheries employ integrated broodstock programs, where wild-origin fish are included as broodstock and uni- or bi-directional gene flow between wild and hatchery components of the population is encouraged. Such approaches often assume that opportunistically obtained wild fish meet the genetic goals of minimizing hatchery–wild differentiation and maintaining genetic diversity. This may be incorrect if fine-scale spatial genetic structure exists. Here we investigate the population genetic consequences of such hatchery operations in coho salmon ( Oncorhynchus kisutch) in a small river system featuring a large integrated broodstock program. We do so using 11 082 SNPs scored in wild-origin and hatchery-origin fish collected throughout the system. We found no evidence for genetic differentiation between hatchery-origin and wild-origin fish, no evidence of lowered genetic diversity in hatchery-origin fish, and no evidence for genetic differentiation among fish sampled throughout the river system. In addition, we did not detect inbreeding. Collectively, these results are consistent with current practices meeting integrated hatchery program goals of adequately sampling the genetic diversity present in wild-origin fish, although they may slightly reduce the effective population size of the combined population.
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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 | 0.000 |
| 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".