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Inter-annual variation in American redstart (<I>Setophaga ruticilla</I>) plumage colour is associated with rainfall and temperature during moult: an 11-year study

2015· article· en· W6922303780 on OpenAlexaboutno aff

Bibliographic record

VenueSmithsonian Digital Repository (Smithsonian Institution) · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Behavior and Reproduction
Canadian institutionsnot available
Fundersnot available
KeywordsFeatherPlumageMoultingSeasonal breederPopulationPasserineSexual selectionAbundance (ecology)

Abstract

fetched live from OpenAlex

Carotenoid-based colouration plays an important role in sexual signaling in animals as an honest indicator of individual quality during mate choice and competitive interactions. However, few studies have examined how natural variation in weather conditions influences inter-annual variation in the expression of ornamentation, potentially through affecting the dietary availability of carotenoids. In this study, we examine variation in the expression of carotenoid-based plumage colouration in relation to temperature and rainfall during the pre-moulting and moulting period over 11 years in a population of American redstarts, Setophaga ruticilla, breeding in eastern Canada. We used reflectance spectrometry of tail feathers collected from male and female redstarts to relate feather colour with weather conditions the previous breeding season during the months over which redstarts are likely to moult (June September). At a population level, birds expressed feathers with higher red chroma and lower brightness in years following high July rainfall and low August temperature. The pattern was stronger in males, but was generally consistent across ages and sexes. Analyses of feathers from repeatedly captured birds indicated that the above patterns could be explained by individual change in feather colour. We suggest that higher rainfall during the moulting period may increase insect abundance and the availability of dietary carotenoids. This is among the first studies to show effects of weather conditions on a sexual signalling trait, which may have important consequences for sexual selection, mate choice, and the reliability of putative signals.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
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 head0.009
GPT teacher head0.207
Teacher spread0.198 · 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

Citations0
Published2015
Admission routes1
Has abstractyes

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