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Island breeding and continental feeding: How are diet patterns in adult yellow-legged gulls influenced by landfill accessibility and breeding stages$

2003· article· en· W2541871212 on OpenAlexvenueno aff
Céline Duhem, Éric Vidal, Philip Roche, Jérôme Legrand

Bibliographic record

VenueEcoscience · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsnot available
Fundersnot available
KeywordsForagingHabitatBiologyEcologySeasonal breederPopulationNesting seasonTrophic levelEcological niche

Abstract

fetched live from OpenAlex

We studied the diet of yellow-legged gulls, Larus (cachinnans) michahellis, at six colonies located at different distances from landfills during three breeding stages (territory establishment, pre-laying, and nesting periods) through the analysis of 1,192 pellets. Landfills were the foraging habitat most frequently used by gulls from all six colonies at all stages. Other terrestrial habitats were used with decreasing frequency as the breeding season advanced. Limited but consistent use was also made of the marine habitat. At each stage, landfill accessibility influenced the diet of the colonies, which showed both a varying degree of exploitation of landfills and a varying trophic niche width. We used principal components analysis (PCA) to assess diet variation patterns as the breeding season advanced as well as food accessibility parameters. The PCA revealed that gulls shift their diet toward a diet weakly diversified and increasingly centred on items from landfills and also showed that the diets of colonies were correlated with landfill accessibility and breeding stages.The shift in diet occurred earlier in the breeding season for colonies far from landfills compared to colonies near landfills. In light of these diet patterns, yellow-legged gulls appear to be strongly influenced by landfills; thus, the future closure of landfills is likely to have marked effects on yellow-legged gull population dynamics. Keywords: breeding stages, dependence on landfills, diet, food availability, Larus (cachinnans) michahellis, multivariate analysis.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.697

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.232
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
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

Citations25
Published2003
Admission routes1
Has abstractyes

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