Genomic data support management of anadromous Arctic Char fisheries in Nunavik by highlighting neutral and putatively adaptive genetic variation
Bibliographic record
Abstract
) is an anadromous salmonid and the most harvested fish species by Inuit people, including in Nunavik (Québec, Canada), one of the most recently deglaciated regions in the world. Unlike many other anadromous salmonids, Arctic Char occupy coastal habitats near their natal rivers during their short marine phase restricted to the summer ice-free period. Our main objective was to document putatively neutral and adaptive genomic variation in anadromous Arctic Char populations from Nunavik and bordering regions to inform local fisheries management. We used genotyping by sequencing (GBS) to genotype 18,112 filtered single nucleotide polymorphisms (SNP) in 650 individuals from 23 sampling locations along >2000 km of coastline. Our results reveal a hierarchical genetic structure, whereby neighboring hydrographic systems harbor distinct populations grouped by major oceanographic basins: Hudson Bay, Hudson Strait, Ungava Bay, and Labrador Sea. We found genetic diversity and differentiation to be consistent both with the expected postglacial recolonization history and with patterns of isolation-by-distance reflecting contemporary gene flow. Results from three gene-environment association methods supported the hypothesis of local adaptation to both freshwater and marine environments (strongest associations with sea surface and air temperatures during summer and salinity). Our results support a fisheries management strategy at a regional scale, and other implications for hatchery projects and adaptation to climate change are discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".