Reduced‐Representation Sequencing Detects Trans‐Arctic Connectivity and Local Adaptation in Polar Cod (<i>Boreogadus saida</i>)
Bibliographic record
Abstract
Information on connectivity and genetic structure of marine organisms remains sparse in frontier ecosystems such as the Arctic Ocean. Filling these knowledge gaps becomes increasingly urgent, as the Arctic is undergoing rapid physical, ecological and socio-economic changes. The abundant and widely distributed polar cod (Boreogadus saida) is highly adapted to Arctic waters, and its larvae and juveniles live in close association with sea ice. Through a reduced-representation sequencing approach, this study explored the spatial genetic structure of polar cod at a circum-Arctic scale. Genomic variation was partitioned into neutral and adaptive components to respectively investigate genetic connectivity and local adaptation. Based on 922 high-quality single nucleotide polymorphism (SNP) markers genotyped in 611 polar cod, broad-scale differentiation was detected among three groups: (i) Beaufort -Chukchi seas, (ii) all regions connected by the Transpolar Drift, ranging from the Laptev Sea to Iceland, including the European Arctic and (iii) West Greenland. Patterns of neutral genetic structure suggested broadscale oceanographic and sea ice drift features (i.e., Beaufort Gyre and Transpolar Drift) as important drivers of connectivity. Genomic variation at 35 outlier loci indicated adaptive divergence of the West Greenland and the Beaufort-Chukchi Seas populations, possibly driven by environmental conditions. Sea ice decline and changing ocean currents can alter or disrupt connectivity between polar cod from the three genetic groups, potentially undermining their resilience to climate change, even in putative refugia, such as the Central Arctic Ocean and the Arctic Archipelago.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".