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Record W3040883169 · doi:10.3354/meps13413

Variation in the diet of beluga whales in response to changes in prey availability: insights on changes in the Beaufort Sea ecosystem

2020· article· en· W3040883169 on OpenAlexaff
Emily S. Choy, Carolina Giraldo, Bruno Rosenberg, James D. Roth, AD Ehrman, A Majewski, Heidi H. Swanson, Michael Power, J.D. Reist, Lisa L. Loseto

Bibliographic record

VenueMarine Ecology Progress Series · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of WaterlooFisheries and Oceans CanadaMcGill UniversityUniversity of Manitoba
Fundersnot available
KeywordsCapelinBeluga WhaleBelugaArcticBiologyFisheryPredationWhaleForage fishPopulationEcologyDemography

Abstract

fetched live from OpenAlex

The eastern Beaufort Sea (EBS) beluga whale Delphinapterus leucas population has experienced a 20 yr decline in inferred growth rates of individuals, which is hypothesized to have resulted from changes in prey availability. We used fatty acid signatures and stable isotope ratios to reconstruct the proportional contributions of 14 prey species to the diets of 178 beluga whales from 2011 to 2014. Prey estimates using quantitative fatty acid signature analysis suggest that EBS beluga whales primarily consume Arctic cod Boreogadus saida , a species highly sensitive to climate change. Prey estimates varied with year and sex and size class of the whales, with large males consuming the highest proportions of Arctic cod, and females consuming the highest proportions of capelin Mallotus villosus . Estimated proportional contributions of Arctic cod to beluga diet decreased from 2011 to 2014, coinciding with an increase in capelin. Belugas consumed the highest proportions of capelin and the lowest proportions of cod in 2014, the same year in which body condition indices were lowest in the whales. We hypothesize that changing conditions in the Beaufort Sea ecosystem may result in a decreased consumption of Arctic cod by belugas and increased consumption of capelin, which may result in a decline in condition. This may predominately affect females and juveniles since they consume the highest proportions of capelin; however, long-term monitoring is needed for confirmation. Understanding inter-annual variation in prey, and the longer-term nutritional implications of shifting from an Arctic cod- to a capelin-dominated diet should be a priority for monitoring EBS predators.

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)0.002
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 score0.775
Threshold uncertainty score0.553

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.022
GPT teacher head0.242
Teacher spread0.220 · 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

Citations62
Published2020
Admission routes1
Has abstractyes

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