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Linking the foraging performance of a marine predator to local prey abundance

2004· article· en· W2017251743 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFunctional Ecology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicAvian ecology and behavior
Canadian institutionsUniversité du Québec à Rimouski
Fundersnot available
KeywordsForagingPredationCormorantBiologySeabirdPredatorAbundance (ecology)EcologyTrophic levelMarine ecosystemOptimal foraging theoryFisheryEcosystem

Abstract

fetched live from OpenAlex

Summary Knowledge of the functional response of predators to prey densities conditions our understanding of food webs. Such links are still poorly understood within the higher trophic levels of marine ecosystems. We present the first field study recording the foraging effort and foraging yield of a seabird (the Great Cormorant, Phalacrocorax carbo ) as well as the abundance and quality of prey within its foraging area. We confirm that Great Cormorants foraging off West‐Greenland show the highest foraging performance recorded for a marine predator (between 17 and 41 g fish caught per minute underwater). Former work suggests that such high foraging yield should be based upon the exploitation of extremely profitable prey patches. Contrary to this hypothesis, average prey abundances estimated within the foraging areas of the cormorants were low (0·03–0·09 prey m −2 , depending on methods), as was the average calorific value of the prey items (4·2 kJ g −1 ). Our study suggests that Great Cormorants remain highly successful predators even when exploiting modest prey resources. These findings have implications for our understanding of predator–prey relationships, and for the management of Great Cormorant populations.

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.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.998

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)0.0030.001

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 head0.009
GPT teacher head0.207
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