Pleistocene glaciations and contemporary genetic diversity in a Beringian fish, the broad whitefish, <i>Coregonus nasus</i> (Pallas): inferences from microsatellite DNA variation
Bibliographic record
Abstract
The contemporary distribution of genetic variation within and among high latitude populations cannot be fully understood without taking into consideration how species responded to the impacts of Pleistocene glaciations. Broad whitefish, Coregonus nasus, a species endemic to northwest North America and the Arctic coast of Russia, was undoubtedly impacted by such events because its geographic distribution suggests that it survived solely within the Beringian refuge from where it dispersed post-glacially to achieve its current range. We used microsatellite DNA to investigate the role of glaciations in promoting intraspecific genetic variation in broad whitefish (N = 14 localities, 664 fish) throughout their North American range and in one Russian sample. Broad whitefish exhibited relatively high intrapopulation variation (average of 11.7 alleles per locus, average H(E) = 0.61) and moderate levels of interpopulation divergence (overall F(ST) = 0.10). The main regions assayed in our study (Russia, Alaska, Mackenzie River and Travaillant Lake systems) were genetically differentiated from each other and there were declines in genetic diversity with distance from putative refugia. Additionally, Mackenzie River system populations showed less developed and more variable patterns of isolation-by-distance than populations occupying former Alaskan portions of Beringia. Finally, our data suggest that broad whitefish dispersed from Beringia using coastal environments and opportunistically via headwater stream connections that once existed between Yukon and Mackenzie River drainages. Our results illustrate the importance of history (e.g. glaciation) and contemporary dispersal ecology in shaping the current genetic population structure of Arctic faunas.
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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 | 0.001 |
| 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) | 0.001 | 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".