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Record W2543301042 · doi:10.1002/ece3.2480

Sexual size dimorphism in musteloids: An anomalous allometric pattern is explained by feeding ecology

2016· article· en· W2543301042 on OpenAlexfundno aff
Michael Noonan, Paul J. Johnson, Andrew C. Kitchener, Lauren A. Harrington, Chris Newman, David W. Macdonald

Bibliographic record

VenueEcology and Evolution · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaGoddard Space Flight CenterInnovative Research Group Project of the National Natural Science Foundation of China
KeywordsAllometrySexual dimorphismBiologyMatingSexual selectionMating systemEvolutionary ecologyEcologyZoologyTaxonBergmann's rule

Abstract

fetched live from OpenAlex

Rensch's rule states that sexual size dimorphism (SSD) increases with body size in taxa where males are larger, and decreases when females are larger. The dominant explanation for the trend is currently that competitive advantage for males is greater in larger individuals, whereas female size is constrained by the energetics of rearing offspring. This rule holds for a variety of vertebrate taxa, and opposing trends are rare. We examine the allometry of SSD within the Musteloidea and demonstrate a hypo-allometry contrary to Rensch's rule, with lower SSD associated with larger body size. We provide evidence that feeding ecology is involved. Where diet promotes group-living, the optimal strategy for the males of larger species is often not to attempt to defend access to multiple females, obviating any competitive advantage of relatively greater size. We conclude that the effect of feeding ecology on mating systems may be a hitherto neglected factor explaining variation in SSD.

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 score0.361
Threshold uncertainty score0.549

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 head0.015
GPT teacher head0.216
Teacher spread0.201 · 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

Citations31
Published2016
Admission routes1
Has abstractyes

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