Genomic islands of divergence and their consequences for the resolution of spatial structure in an exploited marine fish
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
As populations diverge, genomic regions associated with adaptation display elevated differentiation. These genomic islands of adaptive divergence can inform conservation efforts in exploited species, by refining the delineation of management units, and providing genomic tools for more precise and effective population monitoring and the successful assignment of individuals and products. We explored heterogeneity in genomic divergence and its impact on the resolution of spatial population structure in exploited populations of Atlantic cod, Gadus morhua, using genome wide expressed sequence derived single nucleotide polymorphisms in 466 individuals sampled across the range. Outlier tests identified elevated divergence at 5.2% of SNPs, consistent with directional selection in one-third of linkage groups. Genomic regions of elevated divergence ranged in size from a single position to several cM. Structuring at neutral loci was associated with geographic features, whereas outlier SNPs revealed genetic discontinuities in both the eastern and western Atlantic. This fine-scale geographic differentiation enhanced assignment to region of origin, and through the identification of adaptive diversity, fundamentally changes how these populations should be conserved. This work demonstrates the utility of genome scans for adaptive divergence in the delineation of stock structure, the traceability of individuals and products, and ultimately a role for population genomics in fisheries conservation.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 it