Replicated Landscape Genomics Identifies Evidence of Local Adaptation to Urbanization in Wood Frogs
Bibliographic record
Abstract
Native species that persist in urban environments may benefit from local adaptation to novel selection factors. We used double-digest restriction-side associated DNA (RAD) sequencing to evaluate shifts in genome-wide genetic diversity and investigate the presence of parallel evolution associated with urban-specific selection factors in wood frogs (Lithobates sylvaticus). Our replicated paired study design involved 12 individuals from each of 4 rural and urban populations to improve our confidence that detected signals of selection are indeed associated with urbanization. Genetic diversity measures were less for urban populations; however, the effect size was small, suggesting little biological consequence. Using an FST outlier approach, we identified 37 of 8344 genotyped single nucleotide polymorphisms with consistent evidence of directional selection across replicates. A genome-wide association study analysis detected modest support for an association between environment type and 12 of the 37 FST outlier loci. Discriminant analysis of principal components using the 37 FST outlier loci produced correct reassignment for 87.5% of rural samples and 93.8% of urban samples. Eighteen of the 37 FST outlier loci mapped to the American bullfrog (Rana [Lithobates] catesbeiana) genome, although none were in coding regions. This evidence of parallel evolution to urban environments provides a powerful example of the ability of urban landscapes to direct evolutionary processes.
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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".