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Record W7133284254

An integrated population model for the Belcher Islands - Eastern Hudson Bay (BEL-EHB) Beluga Whale Stock

2025· other· en· W7133284254 on OpenAlexaboutno aff
Joanie Van de Walle, M. Tim Tinker, Caroline C. Sauvé

Bibliographic record

VenueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du Canada · 2025
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsBayBeluga WhaleBelugaStock (firearms)PopulationStock assessmentAerial surveyAbundance (ecology)
DOInot available

Abstract

fetched live from OpenAlex

The Belcher Islands Eastern Hudson Bay (BEL-EHB) beluga stock is one of eight stocks found in Canada. It is one of the least abundant, with Eastern Hudson Bay beluga being currently designated as Threatened by COSEWIC. The BEL-EHB stock is harvested for subsistence by Nunavik communities and the Nunavut community of Sanikiluaq. Population models are used to estimate the population abundance and trend of the BEL-EHB stock, and to provide scientific advice on harvest levels compatible with identified management objectives. The BEL-EHB stock was last assessed using a stochastic Bayesian surplus-production model (SPM) incorporating information on harvest numbers, genetic-based composition of the harvest and aerial survey estimates. Several additional sources of information have now become available and can be used to produce a more comprehensive assessment of the stock. Here, we developed a new Integrated Population Model (IPM) for BEL-EHB beluga that integrates female reproductive status, as well as harvest sex and age composition as additional sources of information into the model structure. In addition, annual stochasticity was incorporated in the IPM as a component of mortality in addition to harvesting. We present the structure of the newly developed IPM and then compare the modeled population trends and abundance estimates to those from the SPM used in previous assessments. The IPM and SPM predicted similar overall population abundances and trends. However, uncertainties in model-based predictions were reduced with the IPM, and the most recent estimates of abundance diverged between modeling approaches. The IPM predicted that the BEL-EHB stock abundance was 3,600 in 2023, with a rate of decline between 2014-2023 corresponding to 2.24%. The 2023 estimate of BEL-EHB abundance using the SPM was 2,600 and the rate of decline between 2014-2023 was 3.82%. Both models yielded similar predictions of BEL-EHB beluga landings and carrying capacity. The IPM provided new information about the BEL-EHB stock that could not be obtained with the SPM. For instance, the IPM yielded insights into age-specific survival and pregnancy rates, as well as temporal trends in those demographic rates. Further, the IPM estimated that mortality resulting from harvest (including struck and lost) accounts for 19% to 43% of total annual mortality, with an increasing trend in recent years.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.870
Threshold uncertainty score0.259

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.260
Teacher spread0.247 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2025
Admission routes1
Has abstractyes

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Same venueFederal Open Science Repository of Canada / Le Dépôt fédéral de science ouverte du CanadaFrench-language works237,207