Genomic Signatures of Within-Generation Selection in Coho Salmon (Oncorhynchus kisutch) under Enriched Hatchery-Rearing Practices and in the Wild
Bibliographic record
Abstract
Salmonids occupy central roles in the ecological and human communities in which they occur. As such, many salmonid populations are heavily managed for conservation and to support their harvest. This often involves hatcheries, which typically use captured mature adults to produce fertilized eggs which are reared to the smolt life-history stage, with resultant smolts released into the wild. Despite a history of over 150 years of hatchery use, fundamental questions remain about the ecological and evolutionary impacts of hatcheries on released fish and on the wild populations released fish interact with. Chief among these questions is the role and impact of selection in hatchery fish compared to wild fish and if domesticating processes are inevitable. In this thesis, I present a detailed investigation of the population genomics of an integrated hatchery-wild coho salmon (Oncorhynchus kisutch) population subjected to long-term experimental rearing under conventional hatchery environments, and under enriched hatchery environments designed to mimic aspects of the wild environment in efforts to mitigate potential effects of hatchery rearing. Specifically, I investigated (1) if spatial genetic structuring occurs among wild fish in this system, (2) if selection is detectable for survival-at-sea and for survival across the lifecycle within a single generation, and (3) if such selection depends on the rearing environment fish experience in the hatchery. I additionally reviewed what is known about gene expression under domestication in salmonids. I found no evidence for spatial genetic structuring among wild fish, indicating the typical strategy of restricted sampling of wild fish for inclusion in the hatchery broodstock should not drive differentiation between hatchery and wild fish. I also found evidence for within-generation selection for both survival-at-sea and survival across the lifecycle, and most importantly, that these signatures of selection differed between hatchery fish reared under different environments. Notably, signatures of selection for fish reared under enriched environments were not more similar to those observed in wild fish, compared to conventionally reared fish, indicating work remains in designing hatchery environments that mimic those aspects of the wild environment required to produce wild-like fish, and with implications for captive rearing programs more broadly.
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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".