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Record W4413340931 · doi:10.1101/2025.08.11.669688

Scaling and foraging behavior drive the evolution of humeral shape in hummingbirds

2025· preprint· en· W4413340931 on OpenAlexafffund
Juan Camilo Ríos‐Orjuela, Carlos Daniel Cadena, Alejandro Rico‐Guevara, Ilias Berberi, Lauren Miner, Roslyn Dakin

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2025
Typepreprint
Languageen
FieldMathematics
TopicMorphological variations and asymmetry
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of CanadaGlobal Affairs CanadaLouisiana State UniversityWashington Research Foundation
KeywordsForagingEcologyBehavioral ecologyNectarBiologyFeeding behaviorZoology

Abstract

fetched live from OpenAlex

Abstract Understanding how locomotion-related skeletal elements evolve under biomechanical and ecological constraints is central to animal evolutionary biology. In hummingbirds (Trochilidae), the humerus plays a key role in force transmission during hovering and flapping flight, yet the drivers of its shape evolution have not been examined. We combined geometric morphometrics with phylogenetic comparative analyses to examine humeral shape variation, evolutionary rates, and phenotypic integration in male hummingbirds from 78 species. Our analyses identified humerus allometry as the dominant predictor of shape, revealing a pattern in which larger humeri show broader proximal epiphyses, increased shaft robustness, and reduced curvature. In addition to this scaling pattern, we find that male humerus shape differs subtly among hummingbird species that differ in the use of aggression during nectar foraging. Evolutionary rates of humeral shape were heterogeneous and decoupled from ecological predictors. We also find phenotypic integration between the proximal and distal regions of the humerus, indicating coordinated evolution. Together, these results show that humeral evolution in hummingbirds is governed primarily by biomechanical scaling and internal integration, with foraging ecology introducing secondary, size-dependent modifications. This work highlights the importance of considering scaling and internal integration when interpreting morphological evolution in locomotor systems across vertebrates.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.266
Teacher spread0.242 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2025
Admission routes2
Has abstractyes

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