Population genomic structure of a widespread, urban‐dwelling mammal: The eastern grey squirrel (<i>Sciurus carolinensis</i>)
Bibliographic record
Abstract
Urbanization is a persistent and widespread driver of global environmental change, potentially shaping evolutionary processes due to genetic drift and reduced gene flow in cities induced by habitat fragmentation and small population sizes. We tested this prediction for the eastern grey squirrel (Sciurus carolinensis), a common and conspicuous forest-dwelling rodent, by obtaining 44K SNPs using reduced representation sequencing (ddRAD) for 403 individuals sampled across the species' native range in eastern North America. We observed moderate levels of genetic diversity, low levels of inbreeding, and only a modest signal of isolation-by-distance. Clustering and migration analyses show that estimated levels of migration and genetic connectivity were higher than expected across cities and forested areas, specifically within the eastern portion of the species' range dominated by urbanization, and genetic connectivity was less than expected within the western range where the landscape is fragmented by agriculture. Landscape genetic methods revealed greater gene flow among individual squirrels in forested regions, which likely provide abundant food and shelter for squirrels. Although gene flow appears to be higher in areas with more tree cover, only slight discontinuities in gene flow suggest eastern grey squirrels have maintained connected populations across urban areas in all but the most heavily fragmented agricultural landscapes. Our results suggest urbanization shapes biological evolution in wildlife species depending strongly on the composition and habitability of the landscape matrix surrounding urban areas.
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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 | 0.000 |
| 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".