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Record W4382751798 · doi:10.1139/as-2023-0003

Spatial and temporal harvest risk to polar bears in the Canadian Beaufort Sea

2023· article· en· W4382751798 on OpenAlexafffundvenueabout
Stephen Hamilton, Erin M. Henderson, Andrew E. Derocher

Bibliographic record

VenueArctic Science · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsUniversity of Alberta
FundersNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaBureau of Ocean Energy ManagementEnvironment and Climate Change CanadaCanadian Wildlife FederationQuark ExpeditionsWorld Wildlife FundU.S. Department of the Interior
KeywordsUrsus maritimusBeaufort seaGeographySea iceBeaufort scaleSubsistence agricultureArcticPhysical geographyArctic ice packOceanographyBayFisheryEcologyEnvironmental scienceBiologyMeteorologyAgricultureGeologyArchaeology

Abstract

fetched live from OpenAlex

Subsistence harvest in Arctic marine ecosystems is influenced by sea ice conditions affecting species distributions, abundance, and accessibility. We tracked 78 polar bears ( Ursus maritimus Phipps, 1774) of different age, sex, and reproductive classes via satellite telemetry in the Canadian Beaufort Sea (2007–2014, n = 71 258). We assessed vulnerability to harvest (no/low/medium/high) based on telemetry data overlap with density of historical harvest locations (1985–1987, n = 121). All classes of polar bears were detected in historical harvest areas of low to high risk in greater proportion than expected from available area during the harvest period (January to ice breakup), and all but solitary adult females had >50% of locations in the risk areas. Subadult males were proportionally more often inside risk areas yet were not observed in the high-risk areas. Other classes were observed <1% of the time in high-risk areas yet still proportionally greater than expected from available area. Landfast ice has declined in the pre-melt (January–March) and end-of-harvest (June–July) seasons (1980–2021), with the rate of decline being greater in lower-risk areas ( p ≤ 0.05). With sea ice predicted to decline in the future, we suggest that polar bears in the Beaufort Sea may become more concentrated into areas of higher harvest risk.

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 score0.018
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.019
GPT teacher head0.247
Teacher spread0.227 · 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

Citations0
Published2023
Admission routes4
Has abstractyes

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