HOT SPOTS OF GENETIC DIVERSITY DESCENDED FROM MULTIPLE PLEISTOCENE REFUGIA IN AN ALPINE UNGULATE
Bibliographic record
Abstract
Species that inhabit naturally fragmented environments are expected to be spatially structured and exhibit reduced genetic diversity at the periphery of their range. Patterns of differentiation may also reflect historical processes such as recolonization from glacial refugia. We examined the relative importance of these factors in shaping the spatial patterns of genetic differentiation across the range of an alpine specialist, the North American mountain goat (Oreamnos americanus). Contrary to fossil evidence that suggests a single southern refugium, we detected evidence for additional refugia in northern British Columbia and the Alaskan coast using both mitochondrial and microsatellite DNA. A core area of elevated genetic diversity characterized both regions, and molecular dating suggested a recent Pleistocene split was followed by demographic expansion. Across their range, mountain goats were highly genetically structured and displayed the expected pattern of declining diversity toward the periphery. Gene flow was high within contiguous mountain ranges, but cross-assignments paradoxically suggest that long-distance contemporary dispersal movements are not uncommon. These results improve our understanding of how historical vicariance and contemporary fragmentation influence population differentiation, and have implications for conserving the adaptive potential of alpine populations and habitat.
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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 | 0.001 |
| 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 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".