Phylogenomics of American pika (Ochotona princeps) lineage diversification
Bibliographic record
Abstract
Quaternary climate oscillations have profoundly influenced current species distributions. For many montane species, these fluctuations were a prominent driver in species range shifts, often resulting in intraspecific diversification, as has been the case for American pikas (Ochotona princeps). Range shifts and population declines in this thermally-sensitive lagomorph have been linked to historical and contemporary environmental changes across its western North American range, with previous research reconstructing five mitochondrial DNA lineages. Here, we paired genome-wide data (25,244 SNPs) with range-wide sampling to re-examine the number and distribution of intra-specific lineages, and investigate patterns of within- and among-lineage divergence and diversity. Our results provide genomic evidence of O. princeps monophyly, reconstructing six distinct lineages that underwent multiple rounds of divergence (0.809-2.81 mya), including a new Central Rocky Mountain lineage. We further found evidence for population differentiation across multiple spatial scales, and reconstructed levels of standing variation comparable to those found in other small mammals. Overall, our findings demonstrate the influence of past glacial cycles on O. princeps lineage diversification, suggest that current subspecific taxonomy may need to be revisited, and provide an important framework for investigations of American pika adaptive potential in the face of anthropogenic climate change.
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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 | 0.000 | 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".