Anthropogenic factors explain wing colour variation in <i>Colias</i> (Lepidoptera: Pieridae) butterflies across the Toronto urbanization gradient
Bibliographic record
Abstract
Abstract Hybridization, or interbreeding between two previously diverged populations, is increasing due to human influences on the environment. Rates of hybridization might be increasing particularly quickly among urban species, especially those that are known to be sensitive to environmental disturbances. Butterflies are one such taxa, as some species are commonly found in urban areas, despite being sensitive indicators. For example, Colias philodice and C. eurytheme (Lepidoptera: Pieridae) hybridize when their ranges are in contact or overlap and are commonly found in large cities throughout North America. However, it is an open question how variation in urbanization might affect variation in hybridization. Using wild Colias across a gradient of urbanization in Toronto, Ontario, we tested how the variation in Colias colour, as an indicator of hybridization, relates to human disturbance and urbanization. We created an objective numeric classification for both C. eurytheme and C. philodice , against which we categorized Colias samples. We found that some of the urbanization metrics, including distance to road, Julian date, and number of pedestrians affect the variation in Colias colour, suggesting that urbanization affects Colias colouration, and potentially rates of hybridization, in Toronto. This means that human disturbance of the environment could be affecting Colias rates of hybridization.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".