Consequences of farmed–wild hybridization across divergent wild populations and multiple traits in salmon
Bibliographic record
Abstract
Theory predicts that hybrid fitness should decrease as population divergence increases. This suggests that the effects of human-induced hybridization might be adequately predicted from the known divergence among parental populations. We tested this prediction by quantifying trait differentiation between multigenerational crosses of farmed Atlantic salmon (Salmo salar) and divergent wild populations from the Northwest Atlantic; the former escape repeatedly into the wild, while the latter are severely depleted. Under common environmental conditions and at the spatiotemporal scale considered (340 km, 12 000 years of divergence), substantial cross differentiation had a largely additive genetic basis at behavioral, life history, and morphological traits. Wild backcrossing did not completely restore hybrid trait distributions to presumably more optimal wild states. Consistent with theory, the degree to which hybrids deviated in absolute terms from their parental populations increased with increasing parental divergence (i.e., the collective environmental and life history differentiation, genetic divergence, and geographic distance between parents). Nevertheless, while these differences were predictable, their implications for risk assessment were not: wild populations that were equally divergent from farmed salmon in the total amount of divergence differed in the specific traits at which this divergence occurred. Combined with ecological data on the rate of farmed escapes and wild population trends, we thus suggest that the greatest utility of hybridization data for risk assessment may be through their incorporation into demographic modeling of the short- and long-term consequences to wild population persistence. In this regard, our work demonstrates that detailed hybridization data are essential to account for life-stage-specific changes in phenotype or fitness within divergent but interrelated groups of wild populations. The approach employed here will be relevant to risk assessments in a range of wild species where hybridization with domesticated relatives is a concern, especially where the conservation status of the wild species may preclude direct fitness comparisons in the wild.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".