Road Mortality Contributes to the Evolution of an Urban–Rural Cline in Squirrel Coat Color
Bibliographic record
Abstract
ABSTRACT Cities impose unique selection pressures on wildlife and generate clines in phenotypic traits along urban–rural gradients. Roads are a widespread feature of human‐dominated landscapes and are known to cause direct wildlife mortality; however, whether they act as a selective force influencing phenotypic trait variation along urban–rural gradients remains unclear. This study tested the hypothesis that roads influence natural selection of coat color in the eastern gray squirrel ( Sciurus carolinensis ), a species with two distinct coat colors: a gray morph that is common in all areas and a melanic morph more prevalent in urban areas than in rural ones. Vehicular collisions are a significant cause of mortality in eastern gray squirrels, with the melanic morph more visually conspicuous on roads and more easily detected and avoided by drivers than the gray morph. Standardized road cruise surveys along an urbanization gradient in Syracuse, New York, USA, revealed that the prevalence of melanism among living squirrels in Syracuse was negatively related to distance from the city center, whereas there was no urban–rural cline in melanism among road‐killed individuals, with the melanic morph underrepresented among road‐killed squirrels by up to 30% along the urbanization gradient. An examination of the prevalence of each color morph on and off road surfaces in a range‐wide compilation of > 100,000 photographs of S. carolinensis also indicated that the melanic morph was underrepresented among road‐killed squirrels imaged. Our study highlights vehicular collisions as an important source of natural selection on phenotypic traits, suggesting a potential role in shaping patterns of urban evolution and contributing to the maintenance of urban–rural clines.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".