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Record W2061549958 · doi:10.1111/jeb.12577

Rapid diversification of sexual signals in Hawaiian<i>Nesosydne</i>planthoppers (Hemiptera: Delphacidae): the relative role of neutral and selective forces

2014· article· en· W2061549958 on OpenAlexaff
Kari Roesch Goodman, J. Patrick Kelley, Stephen C. Welter, George Roderick, Damian O. Elias

Bibliographic record

VenueJournal of Evolutionary Biology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of British Columbia
FundersUniversity of California
KeywordsBiologyDelphacidaeDivergence (linguistics)Evolutionary biologyReproductive isolationCharacter displacementContext (archaeology)Genetic algorithmSexual selectionPlanthopperDiversification (marketing strategy)HemipteraEcologySympatric speciationPopulationHomopteraDemographyBotany

Abstract

fetched live from OpenAlex

Changes in sexual signals have the potential to promote rapid divergence and reproductive isolation among populations of animals. Thus, identifying processes contributing to variation in signals is key to understanding the drivers of speciation. However, it is difficult to identify the processes initiating changes in signals in empirical systems because (1) the demographic history of populations under study is usually unclear, and (2) there is no unified hypothesis-testing framework for evaluating the simultaneous contribution of multiple processes. A unique system for study in the Hawaiian Islands, the planthopper species Nesosydne chambersi, offers a clear demographic context to disentangle these factors. By measuring variation in male vibratory sexual signals across different genetic populations on the island of Hawaii, we found that that multiple signal traits varied significantly between populations. We developed a mixed modelling framework to simultaneously test competing hypotheses about which processes contribute to changes in signal traits: genetic drift, sensory drive or reproductive character displacement. Our findings suggest that signal divergence proceeds along different axes for different signal traits under the influence of both neutral and selective processes. They are the first, to our knowledge, to document the relative importance of multiple processes on divergence in sexual signals.

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 score0.643
Threshold uncertainty score0.111

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 head0.021
GPT teacher head0.210
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

Citations17
Published2014
Admission routes1
Has abstractyes

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