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Record W3165554349 · doi:10.1111/mec.16005

The population genetics of urban and rural amphibians in North America

2021· article· en· W3165554349 on OpenAlexafffund
Chloé Schmidt, Colin J. Garroway

Bibliographic record

VenueMolecular Ecology · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Manitoba
KeywordsUrbanizationBiologyEcologyPopulationGenetic diversitySpecies richnessAmphibianBiodiversityHabitatWildlifeDemography

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.758

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.192
Teacher spread0.188 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations43
Published2021
Admission routes2
Has abstractyes

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