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Record W2166057131 · doi:10.1093/czoolo/59.3.381

Revealing the control of migratory fueling: An integrated approach combining laboratory and field studies in northern wheatears Oenanthe oenanthe

2013· article· en· W2166057131 on OpenAlexaffabout
Franz Bairlein, Volker Dierschke, Julia Delingat, Cas Eikenaar, Ivan Maggini, Marc Bulte, Heiko Schmaljohann

Bibliographic record

VenueCurrent Zoology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsWestern University
Fundersnot available
KeywordsBird migrationGeographyEcologyHabitatNocturnalBiology

Abstract

fetched live from OpenAlex

Abstract Migratory birds rely on fueling prior to migratory flights. Fueling in migrants is controlled by intrinsic as well as extrinsic factors. From captive studies we have started understanding the internal mechanisms controlling bird migration. Field studies have demonstrated the effects of external factors, such as food availability, weather, competitors, parasites or diseases, on the stopover behavior of migrants. However, an integrated approach is still missing to study coherently how the innate migration program interacts with the varying environmental cues and to estimate the contribution of the innate migration program and the environment to realized migration. The northern wheatear Oenanthe oenanthe offers a unique opportunity for integrated studies. It breeds across almost the whole Holarctic with just a “gap” between eastern Canada and Alaska. All breeding populations overwinter in sub-Saharan Africa which makes the northern wheatear one of the most long-distant migratory songbirds with extraordinary long non-stop flights across oceans. It is a nocturnal migrant which travels without parental or social aid/guidance. Thus, young birds rely entirely on endogenous mechanisms of timing, route selection and fueling on their first outbound migration. By establishing indoor housing under controlled conditions the endogenous control mechanisms of northern wheatear migration could be revealed. At the same time, environmental factors controlling fueling could be investigated in the field. On migration wheatears occur in a variety of habitats with sparse vegetation where their stopover behavior could be quantitatively studied in the light of “optimal migration” theory by the use of remote balances, radio-tagging and even experimentally manipulated food availability. The present paper summarizes our approach to understand the control of migration in northern wheatears by combining field and laboratory studies at various spatial and temporal scales, and linking various sub-disciplines.

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 score0.009
Threshold uncertainty score0.352

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 head0.031
GPT teacher head0.284
Teacher spread0.252 · 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

Citations13
Published2013
Admission routes2
Has abstractyes

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