Genetic evidence of local exploitation of Atlantic salmon in a coastal subsistence fishery in the Northwest Atlantic
Bibliographic record
Abstract
Fisheries targeting mixtures of populations risk the overutilization of minor stock constituents unless harvests are monitored and managed. We evaluated stock composition and exploitation of Atlantic salmon (Salmo salar) in a subsistence fishery in coastal Labrador, Canada, using genetic mixture analysis and individual assignment with a microsatellite baseline (15 loci, 11 829 individuals, 12 regional groups) encompassing the species’ western Atlantic range. Bayesian and maximum likelihood mixture analyses of fishery samples over 6 years (2006–2011; 1772 individuals) indicate contributions of adjacent stocks of 96%–97%. Estimates of fishery-associated exploitation were highest for Labrador salmon (4.2%–10.6% per year) and generally <1% for other regions. Individual assignment of fishery samples indicated nonlocal contributions to the fishery (e.g., Quebec, Newfoundland) were rare and primarily in southern Labrador, consistent with migration pathways utilizing the Strait of Belle Isle. This work illustrates how genetic analysis of mixed stock Atlantic salmon fisheries in the Northwest Atlantic using this new baseline can disentangle exploitation and reveal complex migratory behaviours.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".