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Record W2953618538 · doi:10.1093/beheco/arz108

Male social plasticity influences transient dynamics in the emergence of alternative mating systems in water striders

2019· article· en· W2953618538 on OpenAlexaff
Adrian Perez, Pierre-Olivio Montiglio, Tina W. Wey, Andrew Sih

Bibliographic record

VenueBehavioral Ecology · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversité de SherbrookeUniversité du Québec à Montréal
FundersNational Science Foundation of Sri Lanka
KeywordsBiologyMatingMating systemPhenotypic plasticityEcologyGerridaeZoologyEvolutionary biology

Abstract

fetched live from OpenAlex

Abstract Animal mating systems are often studied with the goal of understanding why species, populations, or groups vary from one another in the system they display. Although these differences are often treated as basically stable, it is also known that mating systems may shift over time (e.g., from one breeding season to the next). There has been some study of how ecological factors correlate with these changes; however, few, if any, studies have investigated how the phenotypic composition of a group governs the timing and probability of these mating system transitions. Groups of stream water striders (Aquarius remigis) can experience rapid changes in mating system dynamics, with small groups often transitioning into a system in which a single, large male monopolizes mating opportunities. We asked if variation in individual- and group-level traits associated with morphology and behavior (e.g., size of the largest individual, average activity behavioral type in the group) could partially explain the variability in how rapidly groups make this transition, if they make it at all. We show that groups with males that exhibit higher social plasticity tended to take longer to transition to a mating system dominated by a single male. Our results, therefore, suggest that groups in identical ecological conditions can diverge in their mating systems based on how much individuals in the group change their behavior in response to the behavior of other members of the group.

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 score0.134
Threshold uncertainty score0.721

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 head0.036
GPT teacher head0.275
Teacher spread0.239 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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