The population genetics of urban and rural amphibians in North America
Bibliographic record
Abstract
Human land transformation is one of the leading causes of vertebrate population declines. These declines are thought to be partly due to decreased connectivity and habitat loss reducing animal population sizes in disturbed habitats. With time, this can lead to declines in effective population size and genetic diversity which restrict the ability of wildlife to efficiently cope with environmental change through genetic adaptation. However, it is not well understood whether these effects generally hold across taxa. We address this question by repurposing and synthesizing raw microsatellite data from online repositories for 19 amphibian species sampled at 554 georeferenced sites in North America. For each site, we estimated gene diversity, allelic richness, effective population size, and population differentiation. Using binary urban-rural census designations, and continuous measures of human population density, the Human Footprint Index, and impervious surface cover, we tested for generalizable effects of human land use on amphibian genetic diversity. We found minimal evidence, either positive or negative, for relationships between genetic metrics and urbanization. Together with previous work on focal species that also found varying effects of urbanization on genetic composition, it seems likely that the consequences of urbanization are not easily generalizable within or across amphibian species. Questions about the genetic consequences of urbanization for amphibians should be addressed on a case-by-case basis. This contrasts with general negative effects of urbanization in mammals and consistent, but species-specific, positive and negative effects in birds.
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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 | 0.001 |
| 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".