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Carry‐over effects of winter habitat vary with age and sex in yellow warblers <i>Setophaga petechia</i>

2013· article· en· W2128807159 on OpenAlexaff
Anna Drake, Christine A. Rock, Sam P. Quinlan, David J. Green

Bibliographic record

VenueJournal of Avian Biology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsPhenologyHabitatBiologyRiparian zoneEcologySeasonal breederAvian clutch sizeProductivityReproduction

Abstract

fetched live from OpenAlex

We use stable isotope data to investigate the role of winter habitat use in altering the breeding phenology of yellow warblers Setophaga petechia . We first confirm that δ 13 C and δ 15 N isotopic signatures vary with winter habitat use in this species. We then examine the relationship between winter habitat use, breeding phenology and productivity within four age‐sex‐classes, since life history theory would predict that carry‐over effects should vary with age and gender. The δ 13 C signatures of yellow warblers using riparian habitats over winter were more depleted than the signatures of those using agricultural or scrub habitat. Individuals on the Pacific coast of Mexico were also more δ 15 N enriched than those on the southern Gulf of Mexico. δ 13 C and δ 15 N signatures were only correlated with earlier clutch initiation and subsequent higher productivity in first‐breeding‐season females. We estimate that shifts in δ 13 C equivalent to a shift from scrub to riparian winter habitat would be associated with the production of 0.8 more fledglings by yearling females. Pre‐breeding events that influence the timing of breeding could also influence the reproductive performance of older males and females, but we found little evidence that winter habitat use influenced breeding season phenology in these birds.

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 score0.049
Threshold uncertainty score0.377

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 studies0.0000.001
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 head0.004
GPT teacher head0.203
Teacher spread0.199 · 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

Citations36
Published2013
Admission routes1
Has abstractyes

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