Precocial male maturation contributes to the introgression of farmed Atlantic salmon into wild populations
Bibliographic record
Abstract
The escape of domesticated Atlantic salmon Salmo salar from aquaculture facilities represents a continued threat to the genetic and demographic stability of wild salmon stocks. Escaped farm-origin salmon have been shown to hybridize with wild conspecifics, yet the long-term genetic impacts are generally unknown. Theoretically, life history variation, specifically precocial maturation of male hybrids, could fast-track introgression, but evidence for this has been sparse. Here, we used empirical and experimental data to examine the role of precocious male maturation in introgression. We examined hybrid class composition using juvenile sampling and genetic assignment over a 5 yr period following an escape event in southern Newfoundland, a region with high rates of natural male precocial maturation. Initially following the escape, the proportion of first-generation (F1) hybrids was high and then decreased annually, contrasting the proportion of backcross wild individuals, which increased over time. The presence and temporal distribution of backcross wild individuals supports the hypothesis that high rates of precocial maturation can fast-track the long-term impacts of escaped farmed salmon on wild populations via interbreeding. This was experimentally tested using lab-created wild, farmed, and F1 parr released and recaptured from a Newfoundland river to assess levels of precocious male maturation. Observed rates of maturation of F1 hybrids were high and similar to wild parr (77 vs. 73%, respectively), indicating that most F1 hybrids mature precocially. Our results suggest that rates of precocial male maturation should be explicitly considered in risk assessments evaluating the genetic impacts of escaped farmed salmon on wild populations.
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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 | 0.001 |
| 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".