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Record W2298102260 · doi:10.1111/jeb.12860

A novel method of comparing mating success and survival reveals similar sexual and viability selection for mobility traits in female tree crickets

2016· article· en· W2298102260 on OpenAlexaff
Kyla Ercit, Darryl Gwynne

Bibliographic record

VenueJournal of Evolutionary Biology · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsGeneral Electric (Canada)University of Toronto
FundersNational Institutes of Health
KeywordsBiologySexual selectionMatingFecunditySperm competitionMate choiceSelection (genetic algorithm)Sexual conflictZoologyCompetition (biology)TraitGerridaeEcologyEvolutionary biologyPopulationDemographyHeteroptera

Abstract

fetched live from OpenAlex

The relationship between sexual and viability selection in females is necessarily different than that in males, as investment in sexual traits potentially comes at the expense of both fecundity and survival. Accordingly, females do not usually invest in sexually selected traits. However, direct benefits obtained from mating, such as nuptial gifts, may encourage competition among females and subsidize investment into sexually selected traits. We compared sexual and viability selection on female tree crickets Oecanthus nigricornis, a species where females mate frequently to obtain nuptial gifts and sexual selection on females is likely. If male choice determines female mating success in this species, we expect sexual selection for fecundity traits, as males of many species prefer more fecund females. Alternatively, intrasexual scramble or combat competition on females may select for larger jumping legs or wider heads (respectively). We estimated mating success in wild caught crickets using microsatellite analysis of stored sperm and estimated relative viability by comparing surviving female O. nigricornis to those captured by a common wasp predator. In support of the scramble competition hypothesis, we found sexual selection for females with larger hind legs and narrower heads. We also found stabilizing viability selection for intermediate head width and hind leg size. As predicted, traits under viability and sexual selection were very similar, and the direction of that selection was not opposing. However, because the shape of sexual and viability selection differs, these episodes of selection may favour slightly different trait sizes.

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)0.001
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 score0.528
Threshold uncertainty score0.116

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.065
GPT teacher head0.321
Teacher spread0.256 · 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

Citations5
Published2016
Admission routes1
Has abstractyes

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