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Record W2267524138 · doi:10.1086/683775

Ecological Character Displacement between the Sexes

2015· article· en· W2267524138 on OpenAlexaff
Stephen P. De Lisle, Locke Rowe

Bibliographic record

VenueThe American Naturalist · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSexual dimorphismCompetition (biology)Sexual selectionBiologyEcologyCharacter displacementDivergence (linguistics)Evolutionary ecologySelection (genetic algorithm)Evolutionary biologyEvolution of sexual reproductionScramble competitionZoologyHabitat

Abstract

fetched live from OpenAlex

Theory suggests that the evolution of sexual dimorphism in ecologically relevant traits can evolve purely through competition between the sexes for a shared resource. Although more parsimonious hypotheses exist for the evolution of ecological sexual dimorphisms, there are some underappreciated reasons to expect that competition may often play some role in the evolution of sexual dimorphism. Here, we build on past work to outline a set of sufficient criteria to demonstrate a role for resource competition in the evolution of sexual dimorphism, the most critical of which is that resource competition can be directly linked to sexual divergence along the axis of ecologically relevant dimorphism. We then compare the geometry of fitness surfaces across experimental manipulations of density and sex ratio in a semiaquatic salamander (Notophthalmus viridescens). We find consistent disruptive selection on multivariate sexual dimorphism in feeding morphology, which increases in strength with density. Fitness and the strength of divergent selection are negative-frequency dependent in the manner expected under competition-driven divergence between the sexes. Our results constitute direct evidence of resource competition as a driver of sexually antagonist selection and consequently the evolution of sexual dimorphism, providing an illustration of how cause and effect can be separated in studies of sexual divergence in morphology and ecology. We suggest that resource competition may often contribute to sexual divergence jointly with other sources of sex-biased selection, especially when ecological opportunity is sex specific.

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 score0.360
Threshold uncertainty score0.218

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 head0.043
GPT teacher head0.276
Teacher spread0.233 · 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

Citations41
Published2015
Admission routes1
Has abstractyes

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