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Record W3137252595 · doi:10.1111/1365-2435.13791

Male condition influences female post mating aggression and feeding in <i>Drosophila</i>

2021· article· en· W3137252595 on OpenAlexaff
Eleanor Bath, Daisy Buzzoni, Toby Ralph, Stuart Wigby, Irem Sepil

Bibliographic record

VenueFunctional Ecology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Victoria
FundersBiotechnology and Biological Sciences Research Council
KeywordsBiologyMatingAggressionSexual selectionZoologyCourtshipAntagonistic CoevolutionSexual conflictReproductionMate choiceSpermEcologyPhysiologyDevelopmental psychologyGenetics

Abstract

fetched live from OpenAlex

Abstract Mating changes female behaviour and physiology across a wide range of taxa, with important effects for male and female fitness. These changes are often induced by components of the male ejaculate, such as sperm and seminal fluid proteins. However, males can vary significantly in their ejaculates, due to factors such as age, mating history or nutritional status. This male variation may therefore lead to variation in the strength of responses males can stimulate in females, with alterations in fitness outcomes for both sexes. Using the fruit fly, Drosophila melanogaster , we tested whether three aspects of male condition shape an important, but understudied, post‐mating response—increased female–female aggression. We found that females mated to old males fought less than females mated to young males. This effect was exacerbated in mates of old, sexually active males, but there was no effect of male starvation status on mating‐induced female aggression. There was also a significant effect of age and mating history on female post‐mating feeding duration. Our results add to a growing body of literature that variation in male condition can shape sexual selection through post‐mating responses in females, including female–female interactions. Studying such variation may therefore be useful for understanding how the condition of one sex affects the behaviour of the other. A free plain language summary can be found within the Supporting Information of this article.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.571
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)0.0010.000

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 head0.023
GPT teacher head0.237
Teacher spread0.214 · 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.

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

Citations8
Published2021
Admission routes1
Has abstractyes

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