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Record W2077839814 · doi:10.1525/auk.2012.12122

Postfledging movements in birds: Do tit families track environmental phenology?

2013· article· en· W2077839814 on OpenAlexaff
Tore Slagsvold, Ane Eriksen, Rosa Ayala, Jan Hušek, Karen L. Wiebe

Bibliographic record

VenueThe Auk · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsPhenologyEcologyParusRange (aeronautics)Nest (protein structural motif)GeographyPredationCyanistesWoodlandBiology

Abstract

fetched live from OpenAlex

Recent research on reproduction in animals has emphasized phenology and prey matching in the long term and on large spatial scales (e.g., linked to global climate change). We studied how individuals within one reproductive cycle and at small spatial scales may try to maximize access to food resources that vary in space and time. Herbivorous mammals are known to track favorable phenological stages of their food plants and move seasonally on the landscape. Whether phenology similarly affects spatial movements of birds on their breeding grounds is largely unknown. We studied postfledging movements of Blue Tits (Cyanistes caeruleus) and Great Tits (Parus major) when the young were escorted by parents during 19 to 43 days posthatching. This was done over 4 years in a 1.6-km2 woodland area in Norway in which an elevational gradient (105–266 m) caused a phenological delay in vegetation and peak abundance of caterpillar prey at the higher elevations. Postfledging movements were similar in the two tit species, with a mean distance moved from the nest to the site of observation of 134 m (range: 6–1,036, n = 104). On average, families moved upslope (mean = 4.8 m, range: -23 to 69 m; P = 0.002, n = 104), which suggests that they were able to track environmental phenology. However, most families did not move far from the nest site, possibly because the parents tried to defend a year-round territory and, therefore, could not afford to leave for longer periods.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.987

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)0.0190.014

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 head0.008
GPT teacher head0.206
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; both teacher heads agree on what is shown here.

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

Citations17
Published2013
Admission routes1
Has abstractyes

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