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Record W1608804621 · doi:10.1002/ece3.78

Early stages of divergence: phylogeography, climate modeling, and morphological differentiation in the South American lizard <i>Liolaemus petrophilus</i> (Squamata: Liolaemidae)

2012· article· en· W1608804621 on OpenAlexfundno aff
Frank M. Fontanella, Natalia Feltrin, Luciano Javier Ávila, Jack W. Sites, Mariana Morando

Bibliographic record

VenueEcology and Evolution · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicSpecies Distribution and Climate Change
Canadian institutionsnot available
FundersOffice of International Science and EngineeringAgencia Nacional de Promoción Científica y TecnológicaConsejo Nacional de Investigaciones Científicas y TécnicasFondo para la Investigación Científica y TecnológicaDalhousie UniversityBrigham Young UniversityUniversidad Austral de ChileNational Science Foundation
KeywordsPhylogeographyBiologySquamataEcological nicheNicheCladeLizardPopulationEcologyIntraspecific competitionEnvironmental niche modellingEvolutionary biologyPhylogenetics

Abstract

fetched live from OpenAlex

This study examines the phylogeographic structure within the Patagonian lizard Liolaemus petrophilus and tests for patterns of between-clade morphological divergence and sexual dimorphism, as well as demographic and niche changes associated with Pleistocene climate changes. We inferred intraspecific relationships, tested hypotheses for historical patterns of population expansion, and incorporated ecological niche modeling (ENM) with standard morphological and geometric morphometric analyses to examine between-clade divergence as indirect evidence for adaptation to different niches. The two inferred haploclades diverged during the early Pleistocene with the Southern clade depicting the genetic signature of a recent population increase associated with expanding niche envelope, whereas the Northern clade shows stable populations in a shrinking niche envelope. The combination of molecular evidence for postisolation demographic change and ENM, suggest that the two haploclades have responded differently to Pleistocene climatic events.

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 score0.001
Threshold uncertainty score0.657

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)0.0010.000

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 head0.016
GPT teacher head0.230
Teacher spread0.214 · 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

Citations36
Published2012
Admission routes1
Has abstractyes

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