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Short‐distance partial migration of Neotropical birds: a community‐level test of the foraging limitation hypothesis

2011· article· en· W1964201647 on OpenAlexaff
W. Alice Boyle

Bibliographic record

VenueOikos · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsWestern University
Fundersnot available
KeywordsFrugivoreForagingEcologyBiologyAbundance (ecology)Montane ecologyProductivityHabitat

Abstract

fetched live from OpenAlex

Partial migration of tropical birds was long believed to be driven by variation in food abundance. Recent evidence from a partially‐migratory species suggests that in contrast, limited foraging opportunities at high elevations during severe wet season storms drives the most metabolically‐challenged individuals down to elevations where rainfall is lighter. Here, I test community‐level predictions of this hypothesis by examining the relationship between high‐elevation rainfall in the second half of the year and counts of migrant birds in lowland forest during late December each year from 1990–2009. I contrast results derived from analysis of all migrant species with both analyses of only the frugivorous migrants, and analyses of resident species. Counts of migrant species were on average positively associated with montane rainfall with differences of up to 72% in the numbers of birds counted in drier or wetter years. Frugivores and smaller birds responded more strongly to variation in rainfall compared to the broader migrant species pool. Interestingly, counts of resident species were also higher following wetter montane wet seasons. Results of analyses exploring the cause of resident responses were not consistent with climatic effects on breeding productivity or short‐term weather effects on detectability. Results were, however, consistent with cryptic down‐slope migration of individuals breeding at higher elevations augmenting lowland resident populations in wet years. These results suggest that changes in rainfall amount, storm intensity, and timing of severe weather events would lead to large increases in or losses of an important behaviour.

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 score0.047
Threshold uncertainty score0.245

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)0.0000.000

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 head0.077
GPT teacher head0.244
Teacher spread0.167 · 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

Citations68
Published2011
Admission routes1
Has abstractyes

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