Genetic mixed-stock analysis disentangles spatial and temporal variation in composition of the West Greenland Atlantic Salmon fishery
Bibliographic record
Abstract
Abstract The West Greenland Atlantic Salmon (Salmo salar) fishery represents the largest remaining mixed-stock fishery for Atlantic Salmon in the Northwest Atlantic and targets multi-sea-winter (MSW) salmon from throughout North America and Europe. We evaluated stock composition of salmon harvested in the waters off West Greenland (n = 5684 individuals) using genetic mixture analysis and individual assignment to inform conservation of North American populations, many of which are failing to meet management targets. Regional contributions to this fishery were estimated using 2169 individuals sampled throughout the fishery between 2011 and 2014. Of these, 22% were identified as European in origin. Major North American contributions were detected from Labrador (∼20%), the Southern Gulf/Cape Breton (29%), and the Gaspe Peninsula (29%). Minor contributions (∼5%) were detected from Newfoundland, Ungava, and Quebec regions. Region-specific catches were extrapolated using estimates of composition and fishery catch logs and harvests ranged from 300 to 600 and 2000 to 3000 individuals for minor and major constituents, respectively. To evaluate the temporal stability of the observed fishery composition, we extended the temporal coverage through the inclusion of previously published data (1995–2006, n = 3095) and data from archived scales (1968–1998, n = 420). Examination of the complete time-series (47 years) suggests relative stability in stock proportions since the late 1980s. Genetic estimates of stock composition were significantly associated with model-based estimates of returning MSW salmon (individual years r = 0.69, and overall mean r = 0.96). This work demonstrates that the analysis of both contemporary and archived samples in a mixed-stock context can disentangle levels of regional exploitation and directly inform assessment and conservation of Atlantic Salmon in the West Greenland interceptory Atlantic Salmon fishery.
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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 | 0.002 | 0.001 |
| 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".