Inconsistent effects of urbanization on amphibian genetic diversity
Bibliographic record
Abstract
Abstract Habitat loss and fragmentation are leading causes of vertebrate population declines. These declines are thought to be partly due to decreased connectivity and habitat loss reducing population sizes in human transformed habitats. With time this can lead to reduced effective population size and genetic diversity which restricts the ability of wildlife to cope with environmental change through genetic adaptation. However, it is not well understood whether these effects are generally applicable across taxa. Here, we repurposed and synthesized raw microsatellite data from online repositories from 19 amphibian species sampled at 554 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 and the Human Footprint Index, we tested for generalizable effects of human land use on amphibian genetic diversity. We found no consistent relationships for any of our genetic metrics. While we did not detect directional effects for most species, a few generalist species responded positively to urbanization. These results contrast with consistent negative effects of urbanization in mammals and species specific positive and negative effects in birds. In the context of widespread amphibian declines, our results suggest that habitat loss in human transformed habitats is a more immediate concern than declining genetic diversity in populations that persist.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".