Colonization from divergent ancestors: glaciation signatures on contemporary patterns of genomic variation in Collared Pikas (<i>Ochotona collaris</i>)
Bibliographic record
Abstract
Identifying the genetic structure of a species and the factors that drive it is an important first step in modern population management, in part because populations evolving from separate ancestral sources may possess potentially different characteristics. This is especially true for climate-sensitive species such as pikas, where the delimitation of distinct genetic units and the characterization of population responses to contemporary and historical environmental pressures are of particular interest. We combined a restriction site-associated DNA sequencing (RADSeq) data set containing 4156 single nucleotide polymorphisms with ecological niche models (ENMs) of present and past habitat suitability to characterize population composition and evaluate the effects of historical range shifts, contemporary climates and landscape factors on gene flow in Collared Pikas, which are found in Alaska and adjacent regions of northwestern Canada and are the lesser-studied of North America's two pika species. The results suggest that contemporary environmental factors contribute little to current population connectivity. Instead, genetic diversity is strongly shaped by the presence of three ancestral lineages isolated during the Pleistocene (~148 and 52 kya). Based on ENMs and genetic data, populations originating from a northern refugium experienced longer-term stability, whereas both southern lineages underwent population expansion - contradicting the southern stability and northern expansion patterns seen in many other taxa. Current populations are comparable with respect to generally low diversity within populations and little-to-no recent admixture. The predominance of divergent histories structuring populations implies that if we are to understand and manage pika populations, we must specifically assess and accurately account for the forces underlying genetic similarity.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".