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Record W3092964807 · doi:10.1016/j.gecco.2020.e01320

Temporal dynamics of human-polar bear conflicts in Churchill, Manitoba

2020· article· en· W3092964807 on OpenAlex
Sarah Heemskerk, Amy C. Johnson, Daryll Hedman, Vicki Trim, Nicholas J. Lunn, David McGeachy, Andrew E. Derocher

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueGlobal Ecology and Conservation · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsEnvironment and Climate Change CanadaAgriculture Food and Rural DevelopmentUniversity of Alberta
FundersEnvironment and Climate Change CanadaChurchill Northern Studies CentreCanadian Wildlife FederationQuark Expeditions
KeywordsWildlifeGeographyUrsus maritimusPopulationHuman–wildlife conflictRange (aeronautics)Wildlife managementEcologyDemographyBiologySea iceSociology

Abstract

fetched live from OpenAlex

Identifying factors that influence human-wildlife conflicts is essential to the management of these interactions. Polar bears (Ursus maritimus) come into conflict with humans and these conflicts may become more frequent as the bears spend more time on land due to climate warming induced sea ice loss. To reduce human-bear conflicts, polar bears near Churchill, Manitoba, Canada, are deterred from human areas or caught, held temporarily, and relocated by wildlife officials. We evaluated data for 2061 bear captures intended to reduce human-bear conflicts from 1970 to 2018 to understand temporal dynamics relative to population trends and sea ice indices. On average, 42 different conflict bears/year (SE = 3.6, range = 3 to 110) were handled. The number of conflict bears increased up to a 2001 breakpoint with no trend afterwards. The proportion of conflict bears relative to the population size increased until a breakpoint in 1998 with no trend afterwards. The mean age of conflict bears was 5.5 years (SE = 0.01, range = 1 to 31) and increased over time from 2.6 in 1970 to 6.7 in 2018. Pooling years, subadults were the most common group in conflict and comprised 55% of the bears handled. Age/sex class composition varied significantly before and after the 2001 breakpoint, with subadults comprising a lower proportion of conflict bears after the breakpoint. We found different temporal trends in the number of bears caught in each age/sex class, as well as the entire population, suggesting that multiple factors were involved. The number of conflict bears increased with the length of the ice-free period and there was a positive interaction between abundance and year on the number of conflict bears, indicating that when abundance was higher, the effect of year was higher. Observed changes may be associated with increasing effects of climate change on body condition, longer on-land periods, altered migration routes, altered summering habitat, and food-seeking behaviour. Definitive explanations for the patterns, however, are challenged by shifts in management activities.

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)0.000
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 score0.206
Threshold uncertainty score0.992

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.021
GPT teacher head0.239
Teacher spread0.218 · 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