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Record W2203563484 · doi:10.1086/682675

Female Stick Insects Mate Multiply to Find Compatible Mates

2015· article· en· W2203563484 on OpenAlexafffund
Devin Arbuthnott, Bernard J. Crespi, Tanja Schwander

Bibliographic record

VenueThe American Naturalist · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsSimon Fraser University
FundersSimon Fraser UniversitySchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsBiologyFecundityEcologyMatingMate choiceHatchingPredationMating systemOffspringMating preferencesLongevityZoologyEvolutionary ecologyDemographyPopulationGenetics

Abstract

fetched live from OpenAlex

Why females of many species mate multiply in the absence of direct benefits remains an open question in evolutionary ecology. Interacting and mating with multiple males can be costly to females in terms of time, resources, predation risk, and disease transmission. A number of indirect genetic benefits have been proposed to explain such behaviors, but the relative importance of these mechanisms in natural systems remains unclear. We tested for several direct and indirect benefits of polyandry in the walking stick Timema cristinae. We found no evidence of direct benefits with respect to longevity or fecundity. However, male × female genotypic interactions affected egg-hatching success and offspring production independent of relatedness, suggesting that mating with certain males benefits females and that the best male may differ for each female. Furthermore, multiply mated females biased paternity toward one or few males, and the extent of this bias was positively correlated to egg-hatching success. Our data, therefore, provide evidence for indirect benefits through compatibility effects in this species. By mating multiply, females may improve their chances of mating with a compatible male if compatibility cannot be assessed before mating. Such compatibility effects can explain the evolution and maintenance of polyandry in Timema and many other species.

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 score0.881
Threshold uncertainty score1.000

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 head0.051
GPT teacher head0.276
Teacher spread0.225 · 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

Citations25
Published2015
Admission routes2
Has abstractyes

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