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Record W2612997103 · doi:10.1093/beheco/arx070

Effects of the group’s mix of sizes and personalities on the emergence of alternative mating systems in water striders

2017· article· en· W2612997103 on OpenAlexaff
Pierre‐Olivier Montiglio, Tina W. Wey, Andrew Sih

Bibliographic record

VenueBehavioral Ecology · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversité du Québec à Montréal
FundersNational Science Foundation
KeywordsBiologyMating systemMatingHaremPhenotypic plasticitySexual selectionEcologyPopulationOperational sex ratioZoologyEvolutionary biologyDemography

Abstract

fetched live from OpenAlex

Although much work has analysed how individual behavioural plasticity and adaptations to ecological conditions (e.g. density, sex-ratio, resource distribution) shape mating systems, few studies have assessed the relative importance of multiple factors in explaining why mating systems vary from one sub-population to the next even in the same ecological conditions. Differences among groups in their phenotypic composition, such as their average phenotype, within-group variation in phenotype, or the phenotype of individuals occupying key social roles might shape the mating system emerging at the group level and explain some portion of mating system variability. Here, we take advantage of the mating system flexibility of stream water striders (Aquarius remigis) to investigate how phenotypic composition affects the mating system emerging at the group level. Groups exhibited stable mating systems varying from scramble polygyny with intense sexual conflict, to systems with a clear dominant male guarding a “harem” of females. We found that male size asymmetries and the personality of the largest individuals within groups had important effects on the group’s mating system. The group’s average male and female personality, size, and social plasticity also explained some of the variation in mating systems. Our study is one of the first to quantify significant relationships between group phenotypic composition and mating system variability.

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 score0.580
Threshold uncertainty score0.727

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 head0.041
GPT teacher head0.267
Teacher spread0.226 · 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

Citations11
Published2017
Admission routes1
Has abstractyes

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