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Record W2026811272 · doi:10.1086/658910

Limits to Speciation Inferred from Times to Secondary Sympatry and Ages of Hybridizing Species along a Latitudinal Gradient

2011· article· en· W2026811272 on OpenAlexaff
Jason T. Weir, Trevor D. Price

Bibliographic record

VenueThe American Naturalist · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of TorontoThe Scarborough Hospital
FundersNational Science Foundation
KeywordsSympatryAllopatric speciationParapatric speciationBiologyEcologyRange (aeronautics)Biological dispersalSympatric speciationCharacter displacementPopulationGene flowGenetics

Abstract

fetched live from OpenAlex

Range expansions are critical to renewed bouts of allopatric or parapatric speciation. Limits on range expansions-and, by implication, speciation-include dispersal ability and permeability of geographical barriers. In addition, recently diverged taxa may interfere with each other, preventing mutual expansion of each other's range into sympatry, because reproductive isolation is incomplete and/or ecological competition particularly strong. On the basis of geographical distributions and mitochondrial DNA phylogenetic information for 418 recently diverged species of New World birds, we estimate that secondary sympatry takes on the order of millions of years following population splitting and hence could impose an important limit on the rate of range expansion, thereby limiting further rounds of species formation. Average rates of achievement of sympatry have been faster in the temperate region (we estimate 1.7 million years to sympatry at 60°) than in the tropics (3.2 million years to sympatry at the equator). Evidence from the ages of species with hybrid zones implies that one factor associated with the slowed sympatry in the tropics is the rate of accumulation of reproductive isolation.

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 imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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 source (direct Gemma or distilled Codex), 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

Citations185
Published2011
Admission routes1
Has abstractyes

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