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Record W3132470125 · doi:10.1111/evo.14200

Allometry constrains the evolution of sexual dimorphism in<i>Drosophila</i>across 33 million years of divergence

2021· article· en· W3132470125 on OpenAlexaff
Jacqueline L. Sztepanacz, David Houle

Bibliographic record

VenueEvolution · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsUniversity of Toronto
FundersNational Science Foundation
KeywordsSexual dimorphismBiologyAllometryEvolutionary biologyEvolvabilityDivergence (linguistics)Sexual selectionNatural selectionZoologyTaxonEcologySelection (genetic algorithm)

Abstract

fetched live from OpenAlex

Sexual dimorphism is widely viewed as adaptive, reflecting the evolution of males and females toward divergent fitness optima. Its evolution, however, may often be constrained by the shared genetic architecture of the sexes, and by allometry. Here, we investigated the evolution of sexual size dimorphism, shape dimorphism, and their allometric relationship, in the wings of 82 taxa in the family Drosophilidae that have been diverging for at least 33 million years. Shape dimorphism among species was remarkably similar, with males characterized by longer, thinner wings than females. There was, however, quantitative variation among species in both size and shape dimorphism, with evidence that they have adapted to different evolutionary optima in different clades on timescales of about 10 million years. Within species, shape dimorphism was predicted by size, and among species, there was a strong relationship between size dimorphism and shape dimorphism. Allometry constrained the evolution of shape dimorphism for the two most variable traits we studied, but dimorphism was evolutionary labile in other traits. The keys for disentangling alternative explanations for dimorphism evolution are studies of natural and sexual selection, together with a deeper understanding of how microevolutionary parameters of evolvability relate to macroevolutionary patterns of divergence.

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 score0.815
Threshold uncertainty score0.208

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.021
GPT teacher head0.243
Teacher spread0.222 · 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

Citations18
Published2021
Admission routes1
Has abstractyes

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