Gene flow and climate-associated genetic variation in a vagile habitat specialist
Bibliographic record
Abstract
Previous work in landscape genetics suggests that geographic isolation is of greater importance to genetic divergence than variation in environmental conditions. This is intuitive when configurations of suitable habitat are the dominant factor limiting dispersal and gene flow, but has not been thoroughly examined for habitat specialists with strong dispersal capability. Here, we evaluate the effects of geographic and environmental isolation on genetic divergence in a vagile invertebrate with high habitat specificity and a discrete dispersal life stage: Dod’s Old World swallowtail butterfly, Papilio machaon dodi. In Canada, P. m. dodi are generally restricted to eroding habitat along major river valleys where their larval host plant occurs. A series of causal and linear mixed effects models indicate that divergence of genome-wide single nucleotide polymorphisms is best explained by a combination of environmental isolation (variation in summer temperatures) and geographic isolation (Euclidean distance). Interestingly, least-cost path and circuit distances through a resistance surface parameterized as the inverse of habitat suitability were not supported. This suggests that, although habitat associations of many butterflies are specific due to reproductive requirements, habitat suitability and landscape permeability are not equivalent concepts due to considerable adult vagility. We infer that divergent selection related to variation in summer temperatures has produced two genetic clusters within P. m. dodi, differing in voltinism and diapause propensity. Within the next century, temperatures are predicted to rise by amounts greater than the present-day difference between regions of genetic clusters, potentially affecting the persistence of the northern cluster under continued climate change.
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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 | 0.000 | 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".