MétaCan
Menu
Back to cohort
Record W2168765749 · doi:10.1093/icesjms/fsq067

Changes in diet and trophic position of a top predator 10 years after a mass mortality of a key prey

2010· article· en· W2168765749 on OpenAlexaff
André Chiaradia, Manuela G. Forero, Keith A. Hobson, J. M. Cullen

Bibliographic record

VenueICES Journal of Marine Science · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsPredationTrophic levelBiologyPredatorPopulationEcologyFisheryZoologyDemography

Abstract

fetched live from OpenAlex

Abstract Chiaradia, A., Forero, M. G., Hobson, K. A., and Cullen, J. M. 2010. Changes in diet and trophic position of a top predator 10 years after a mass mortality of a key prey. – ICES Journal of Marine Science, 67: 1710–1720. After the disappearance of primary prey, seabirds exhibit gradually decreased breeding performance, and eventually the population size drops. Results are presented of an investigation into the diet of little penguins (Eudyptula minor) at Phillip Island, Australia, during a period when their key prey, pilchard (Sardinops sagax), declined dramatically. Data from stomach flushing (1982–2006) were used, supported by stable isotope (δ15N, δ13C) analyses of blood samples (2003, 2004, and 2006). The effect of the pilchard mortality on penguin diet was immediate, the birds shifting to a diet almost devoid of pilchard, and this was followed by 2 years of low breeding success, with considerably fewer penguins coming ashore. During periods when pilchard was not part of the diet, penguins consumed prey of a higher trophic level, e.g. higher values of δ15N. Variability in penguin blood δ15N coincided with years of low prey diversity. The disappearance of pilchard resulted in a decrease in prey diversity and led penguins to “fish up” the foodweb, possibly because of the simplified trophic structure. After 1998, however, breeding success re-attained average levels and the numbers of penguins coming ashore increased, probably because of increased abundance of prey other than pilchard after a 3-year period of food scarcity. Although little penguins apparently compensated over time, a less-flexible diet could make them ultimately vulnerable to further changes in their foodweb.

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 score0.079
Threshold uncertainty score0.999

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.011
GPT teacher head0.262
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.

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

Citations78
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueICES Journal of Marine ScienceSame topicMarine and fisheries researchFrench-language works237,207