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Record W2164247319 · doi:10.1890/110194

Meta‐population evidence of oriented chain migration in northern gannets (Morus bassanus)

2012· review· en· W2164247319 on OpenAlexaff
Jérôme Fort, Emeline Pettex, Yann Tremblay, Svein‐Håkon Lorentsen, Stefan Garthe, Stephen C. Votier, Jean Baptiste Pons, François Siorat, Robert W. Furness, W. James Grecian, Stuart Bearhop, William A. Montevecchi, David Grémillet

Bibliographic record

VenueFrontiers in Ecology and the Environment · 2012
Typereview
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsMemorial University of Newfoundland
FundersBritish Antarctic SurveyEuropean CommissionScottish Natural Heritage
KeywordsSeabirdFlywayBiodiversityGeographyRange (aeronautics)EcologyPelagic zonePopulationSeasonal breederFisheryBiologyHabitatDemography

Abstract

fetched live from OpenAlex

Although oriented migrations have been identified in many terrestrial bird species, the post‐breeding‐season movements of seabirds are generally regarded as dispersive. We used geolocator tags to reveal post‐breeding movements and winter distribution of northern gannets ( Morus bassanus ) at a meta‐population scale. By focusing on five breeding colonies of European gannets, we show that their breeding and wintering grounds are connected by a major flyway running along the coasts of Western Europe and Africa. Moreover, maximum winter distance to colony was similar across colonies despite their wide latitudinal range. In contrast with the general opinion that large pelagic birds such as gannets have unlimited ranges beyond the breeding season, our findings strongly suggest oriented chain migration in northern gannets (a pattern in which populations move uniformly southward) and highlight the benefit of meta‐population approaches for studying seabird movements. We argue that the inclusion of such processes in ocean management plans is essential to improve efforts in marine biodiversity conservation.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.124
Threshold uncertainty score0.855

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.032
GPT teacher head0.254
Teacher spread0.222 · 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
GenreReview

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

Citations86
Published2012
Admission routes1
Has abstractyes

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