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Record W2078782991 · doi:10.1534/genetics.104.027987

Controlling for the Effects of History and Nonequilibrium Conditions in Gene Flow Estimates in Northern Bullfrog (Rana catesbeiana) Populations

2004· article· en· W2078782991 on OpenAlexaffabout
James D. Austin, Stephen C. Lougheed, Peter T. Boag

Bibliographic record

VenueGenetics · 2004
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic diversity and population structure
Canadian institutionsQueen's University
Fundersnot available
KeywordsGene flowBiologyRange (aeronautics)BullfrogEcologyEvolutionary biologyAllopatric speciationPhylogeographyMicrosatelliteZoologyGeneticsAlleleGenetic variationPopulationGenePhylogenetics

Abstract

fetched live from OpenAlex

Nonequilibrium conditions due to either allopatry followed by secondary contact or recent range expansion can confound measurements of gene flow among populations in previously glaciated regions. We determined the scale at which gene flow can be estimated among breeding aggregations of bullfrogs (Rana catesbeiana) at the northern limit of their range in Ontario, Canada, using seven highly polymorphic DNA microsatellite loci. We first identified breeding aggregations that likely share a common history, determined from the pattern of allelic richness, factorial correspondence analysis, and a previously published mtDNA phylogeography, and then tested for regional equilibrium by evaluating the association between pairwise F(ST) and geographic distance. Regional breeding aggregations in eastern Ontario separated by <100 km were determined to be at or near equilibrium. High levels of gene flow were measured using traditional F-statistics and likelihood estimates of Nm. Similarly high levels of recent migration (past one to three generations) were estimated among the breeding aggregations using nonequilibrium methods. We also show that, in many cases, breeding aggregations separated by up to tens of kilometers are not genetically distinct enough to be considered separate genetic populations. These results have important implications both for the identification of independent "populations" and in assessing the effect of scale in detecting patterns of genetic equilibrium and gene flow.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.598
Threshold uncertainty score0.362

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 head0.012
GPT teacher head0.230
Teacher spread0.218 · 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

Citations55
Published2004
Admission routes2
Has abstractyes

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