Geography, environment, and colonization history interact with morph type to shape genomic variation in an Arctic fish
Bibliographic record
Abstract
Polymorphic species are useful models for investigating the evolutionary processes driving diversification. Such processes include colonization history as well as contemporary selection, gene flow, and genetic drift, which can vary between intraspecific morphs as a function of their distinct life histories. The interactive and relative influence of such evolutionary processes on morph differentiation critically informs morph-specific management decisions and our understanding of incipient speciation. We therefore investigated how geographic distance, environmental conditions, and colonization history interacted with morph migratory capacity in the highly polymorphic fish species, Arctic Charr (Salvelinus alpinus). Using an 87 k SNP chip we genetically characterized recently evolved anadromous, resident, and landlocked charr collected from 45 locations across a secondary contact zone of three charr glacial lineages in eastern Canada. A strong pattern of isolation by distance across all populations suggested geographic distance principally shaped genetic structure. Landlocked populations had lower genetic diversities and higher genetic differentiation than anadromous populations. However, effective population size was generally temporally stable in landlocked populations in comparison to anadromous populations. Genetic diversity positively correlated with latitude, potentially indicating southern anadromous populations' vulnerability to climate change and greater introgression between the Arctic and Atlantic glacial lineages in northern Labrador. Local adaptation was suggested by the observation of several environmental variables strongly associating with functionally relevant outlier genes including a region on chromosome AC21 potentially associated with anadromy. Our results demonstrate that gene flow, colonization history, and local adaptation uniquely interact to influence the genetic variation and evolutionary trajectory of populations.
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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 | 0.000 |
| 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) | 0.001 | 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".