Multivariate phenotypic divergence along an urbanization gradient
Bibliographic record
Abstract
Abstract Evidence suggests that natural populations can evolve to better tolerate the novel environmental conditions associated with urban areas. Studies of adaptive divergence in urban areas often examine one or a few traits at a time from populations residing only at the most extreme urban and nonurban habitats. Thus, whether urbanization drives divergence in many traits simultaneously in a manner that varies with the degree of urbanization remains unclear. To address this gap, we generated seed families of white clover (Trifolium repens) collected from 27 populations along an urbanization gradient in Toronto, Canada, grew them in a common garden, and measured 14 phenotypic traits. Families from urban sites had evolved later phenology and germination, larger flowers, thinner stolons, reduced cyanogenesis, greater biomass and greater seed set. Pollinator observations revealed near-complete turnover of pollinator morphological groups along the urbanization gradient, which may explain some of the observed divergences in floral traits and phenology. Our results suggest that adaptation to urban environments involves multiple traits.
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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 | 0.001 | 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) | 0.002 | 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".