No detectable effect of urbanization on genetic drift or gene flow in specialist herbivorous insects of milkweed
Bibliographic record
Abstract
Urbanization is hypothesized to isolate populations and restrict dispersal, leading to reduced genetic diversity and increased genetic differentiation. We tested this hypothesis in specialist herbivorous insects of milkweed, positing that higher dispersal ability would mitigate the negative effects of urbanization on genetic drift and gene flow, and that these effects would vary with city size. In this study, we collected 383 milkweed insects from urban and rural sites in Toronto, Canada, and five surrounding cities. Using ddRADseq, we generated 145,000 SPNs for monarchs, 10,000 SNPs for beetles, 6,000 SNPs for weevils to quantify genetic diversity, demographic history and population genetic structure. Contrary to our hypotheses, our results indicated no effect of urbanization or dispersal ability on diversity or genetic differentiation. Genetic diversity, measured as π, varied between 0.0013 and 0.0044 across species, with no urban vs. rural component, but with monarchs having >2 X higher diversity compared to beetles and weevils. Similarly, genetic differentiation was generally low, FST varying between 0.01 and 0.28, but there are no consistent trends among urban vs. rural samples for any of the three species. However, demographic analyses revealed a consistent decline in effective population size for all three sampled species, beginning around the last glacial maximum and intensifying over the past 1,000 years. Our findings suggest that both urbanization and dispersal ability have not been a major factor in reducing gene flow or increasing genetic drift among milkweed's herbivorous insect populations. Instead, historical events such as climatic change since the last glacial maximum, and large-scale anthropogenic disturbance in general, have had a more pronounced impact on demography. These results highlight the importance of considering the combined effects of natural and anthropogenic long-term historical processes when studying population genetics in the context of urbanization.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".