Multilocus genetic analyses and spatial modeling reveal complex population structure and history in a widespread resident North American passerine (<i>Perisoreus canadensis</i>)
Bibliographic record
Abstract
Abstract An increasing body of studies of widely distributed, high latitude species shows a variety of refugial locations and population genetic patterns. We examined the effects of glaciations and dispersal barriers on the population genetic patterns of a widely distributed, high latitude, resident corvid, the gray jay (Perisoreus canadensis), using the highly variable mitochondrial DNA (mtDNA) control region and microsatellite markers combined with species distribution modeling. We sequenced 914 bp of mtDNA control region for 375 individuals from 37 populations and screened seven loci for 402 individuals from 27 populations across the gray jay range. We used species distribution modeling and a range of phylogeographic analyses (haplotype diversity, ΦST, SAMOVA, FST, Bayesian clustering analyses) to examine evolutionary history and population genetic structure. MtDNA and microsatellite markers revealed significant genetic differentiation among populations with high concordance between markers. Paleodistribution models supported at least five potential areas of suitable gray jay habitat during the last glacial maximum and revealed distributions similar to the gray jay's contemporary during the last interglacial. Colonization from and prolonged isolation in multiple refugia is evident. Historical climatic fluctuations, the presence of multiple dispersal barriers, and highly restricted gene flow appear to be responsible for strong genetic diversification and differentiation in gray jays.
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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".