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Record W1967777859 · doi:10.1139/z10-102

Long-term feeding ecology of Great Black-backed Gulls (Larus marinus) in the northwest Atlantic: 110 years of feather isotope data

2011· article· en· W1967777859 on OpenAlexaffvenue
Robert G. Farmer, Madeleine Leonard

Bibliographic record

VenueCanadian Journal of Zoology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsDalhousie University
Fundersnot available
KeywordsTrophic levelBiologyGroundfishEcologyFisheryLarusHerringFeatherFishingFisheries managementFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Recent changes to the ecology of the northwest Atlantic are affecting feeding relationships at many trophic levels. With declining fish stocks and fewer fisheries discards, generalist birds such as Great Black-backed Gulls ( Larus marinus L., 1758) may shift their diets. To test whether such a change has occurred, we measured stable nitrogen and carbon isotope ratios of flight feathers collected from modern and museum-preserved birds (1896–2006). We then compared trends in isotope ratios with trends in regional fisheries productivity to determine if gull diets and fisheries changes were associated. We found a significant decline in stable nitrogen isotope ratios of feathers over time, indicating that the gulls’ trophic feeding level has decreased by approximately 2.26‰, or 0.82 trophic units. In contrast, we found no significant change in carbon isotope ratios, giving no clear evidence for a shift to more offshore or terrestrial foraging. The declining stable nitrogen ratio was significantly and positively correlated with both regional groundfish captures and regional fisheries trophic level, and was negatively correlated with each of (i) crab captures and (ii) herring, sardine, and anchovy captures. Our study gives evidence for a shift in diets of Great Black-backed Gulls over time and further suggests that these changes may be related to ongoing changes in fisheries.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.806
Threshold uncertainty score0.995

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 communication0.0000.000
Open science0.0020.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.027
GPT teacher head0.230
Teacher spread0.203 · 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.

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

Citations47
Published2011
Admission routes2
Has abstractyes

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