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Record W3041477061 · doi:10.22621/cfn.v134i1.2421

Diet of St. Lawrence Estuary Beluga (<i>Delphinapterus leucas</i>) in a changing ecosystem

2020· article· en· W3041477061 on OpenAlexaffvenue
Véronique Lesage, Stéphane Lair, Samuel Turgeon, Pierre Béland

Bibliographic record

VenueThe Canadian Field-Naturalist · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversité de MontréalCegep de Saint HyacintheCégep de Saint-LaurentFisheries and Oceans Canada
Fundersnot available
KeywordsBelugaBiologyBeluga WhalePredationLeucasPopulationContext (archaeology)EstuaryFisheryEcologyEcosystemZoologyArcticDemography

Abstract

fetched live from OpenAlex

Ecosystems and community structure fluctuate over time as a result of natural and anthropogenic factors that may affect prey availability and population dynamics. Most of what we know about St. Lawrence Estuary (SLE) Beluga (Delphinapterus leucas) diet comes from stomach contents collected 80 years ago mainly from a hunting site that Beluga no longer use. How reflective these data are of Beluga diet at other sites and at the current time is unknown. In the context of the recent population decline, general information of prey species alone may help identify useful conservation actions for potentially important prey or habitats. Here, we examined the diet of SLE Beluga using digestive tracts collected from carcasses recovered over the past 30 years, in the context of historical diet data and recent changes in the St. Lawrence ecosystem. We showed they have a varied diet composed of fish and invertebrates generally <30 cm in length, and that adult males and females differ in their summer diet in a way that is consistent with the sex segregation observed in this population. Our results also indicate that polychaete worms, squid, and cod are still among the most prevalent prey, and that species such as redfish (Sebastes spp.) might be important prey items. This study shows that Beluga diet has changed since the 1930s, and that prey from digestive tracts identified to species are valuable for making comparisons to the past, and for improving applications of molecular analyses, such as stable isotopes and fatty acids.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.870
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.216
Teacher spread0.202 · 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 designNot applicable
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

Citations16
Published2020
Admission routes2
Has abstractyes

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