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Record W2806855124 · doi:10.1139/as-2018-0004

Re-assessing abundance of Southern Hudson Bay polar bears by aerial survey: effects of climate change at the southern edge of the range

2018· article· en· W2806855124 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueArctic Science · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsGovernment of NunavutMinistère des Ressources naturelles et des ForêtsMinistry of Natural Resources and Forestry
FundersEnvironment and Climate Change CanadaMinistère des Forêts, de la Faune et des ParcsOntario Ministry of Natural Resources and ForestryMinistry of Natural ResourcesWorld Wildlife Fund
KeywordsBayAerial surveyAbundance (ecology)Ursus maritimusWildlifeArcticGeographyMark and recaptureWildlife managementPopulationRange (aeronautics)Sea iceClimate changeEcologyPhysical geographyFisheryDemographyBiologyCartographyMeteorology

Abstract

fetched live from OpenAlex

The Southern Hudson Bay polar bear (Ursus maritimus Phipps, 1774) subpopulation is considered stable, but conflicting evidence lends uncertainty to that designation. Capture–recapture studies conducted in 1984–1986 and 2003–2005 and an aerial survey conducted in 2011/2012 suggested that abundance was likely unchanged since the mid-1980s. However, body condition and body size declined since then, and duration of sea ice decreased by about 30 days. Due to the conflicting information on subpopulation status and ongoing changes in sea ice, we conducted another aerial survey in 2016 to determine whether abundance had changed. We collected data via mark–recapture distance sampling and double-observer protocols. Results suggest that abundance declined 17% from 943 bears (95% CI: 658–1350) in 2011/2012 to 780 (95% CI: 590–1029) in 2016. The proportion of yearlings declined from 12% of the population in 2011 to 5% in 2016, whereas the proportion of cubs remained similar (16% in 2011 vs. 19% in 2016) suggesting low survival of the 2015 cohort. In a warming Arctic, duration of sea ice is predicted to continue to decline in Hudson Bay affecting all ice-dependent wildlife; therefore, further monitoring of this subpopulation is warranted. We recommend a conservative approach to harvest management and repeating the aerial survey in 2021.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0010.002
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 head0.023
GPT teacher head0.258
Teacher spread0.235 · 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