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Record W2726433929 · doi:10.1002/wsb.783

Polar bear attacks on humans: Implications of a changing climate

2017· article· en· W2726433929 on OpenAlexaffabout
James M. Wilder, Dag Vongraven, Todd C. Atwood, Bob Hansen, Amalie Jessen, Anatoly A. Kochnev, Geoff York, Rachel Vallender, Daryll Hedman, Melissa M. Gibbons

Bibliographic record

VenueWildlife Society Bulletin · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsParks CanadaEnvironment and Climate Change CanadaGovernment of Nunavut
FundersWorld Wildlife Fund
KeywordsUrsus maritimusUrsusRange (aeronautics)PolarGeographyEcologySea iceBiologyPopulationEnvironmental healthMedicineMeteorology

Abstract

fetched live from OpenAlex

ABSTRACT Understanding causes of polar bear ( Ursus maritimus ) attacks on humans is critical to ensuring both human safety and polar bear conservation. Although considerable attention has been focused on understanding black ( U. americanus ) and grizzly ( U. arctos ) bear conflicts with humans, there have been few attempts to systematically collect, analyze, and interpret available information on human‐polar bear conflicts across their range. To help fill this knowledge gap, a database was developed (Polar Bear‐Human Information Management System [PBHIMS]) to facilitate the range‐wide collection and analysis of human‐polar bear conflict data. We populated the PBHIMS with data collected throughout the polar bear range, analyzed polar bear attacks on people, and found that reported attacks have been extremely rare. From 1870–2014, we documented 73 attacks by wild polar bears, distributed among the 5 polar bear Range States (Canada, Greenland, Norway, Russia, and United States), which resulted in 20 human fatalities and 63 human injuries. We found that nutritionally stressed adult male polar bears were the most likely to pose threats to human safety. Attacks by adult females were rare, and most were attributed to defense of cubs. We judged that bears acted as a predator in most attacks, and that nearly all attacks involved ≤2 people. Increased concern for both human and bear safety is warranted in light of predictions of increased numbers of nutritionally stressed bears spending longer amounts of time on land near people because of the loss of their sea ice habitat. Improved conflict investigation is needed to collect accurate and relevant data and communicate accurate bear safety messages and mitigation strategies to the public. With better information, people can take proactive measures in polar bear habitat to ensure their safety and prevent conflicts with polar bears. This work represents an important first step towards improving our understanding of factors influencing human‐polar bear conflicts. Continued collection and analysis of range‐wide data on interactions and conflicts will help increase human safety and ensure the conservation of polar bears for future generations. © 2017 The Wildlife Society.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.023
GPT teacher head0.273
Teacher spread0.250 · 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; both teacher heads agree on what is shown here.

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

Citations103
Published2017
Admission routes2
Has abstractyes

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