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Record W4226048888 · doi:10.1071/wr21060

Grizzly bear response to translocation into a novel environment

2022· article· en· W4226048888 on OpenAlexafffund
Gordon Stenhouse, Terrence A. Larsen, Cameron J. R. McClelland, Abbey E. Wilson, Karen Graham, Dan Wismer, Paul F. Frame, Isobel Phoebus

Bibliographic record

VenueWildlife Research · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsAlberta Environment and Protected AreasUniversity of SaskatchewanGolder Associates (Canada)Agriculture and Agri-Food Canada
FundersfRI ResearchGovernment of Alberta
KeywordsUrsusHabitatWildlifeNational parkGrizzly BearsContext (archaeology)RecreationWildlife managementGeographyEcologyWildlife conservationHuman–wildlife conflictBiologyPopulationDemographyArchaeology

Abstract

fetched live from OpenAlex

Context To mitigate conservation conflicts, some jurisdictions translocate large carnivores into novel environments where they have no previous experience. Behavioural responses of these individuals are not typically monitored to evaluate the impacts of this management approach on the animals or populations. Aims We examined how grizzly bears (Ursus arctos) involved in conservation conflict responded to novel environments after translocation. Methods We used GPS location data to compare grizzly bears translocated to a novel environment (n = 12) with bears resident within the new area (n = 12). Our analyses investigated differences between these groups in relation to exploration behaviour, habitat use and response to human-caused mortality risk. Key results Translocated bears had higher movement rates, greater daily displacement and revisited areas less frequently than did resident bears. They spent more time in poor-quality habitat and the habitat used was of even lower quality in the second year after translocation. Translocated bears selected for agricultural lands and active oil and gas wellsites. They also spent more time in areas with higher potential mortality risk than resident bears. However, translocated bears avoided residential areas, which resident bears selected, and crossed roads at the same rate as did resident bears. Both groups avoided campgrounds and recreation sites. Only 25% of bears engaged in further conflict behaviour after translocation and 67% of translocated bears survived over the 2-year monitoring period. Conclusions This work found differences in exploration behaviour and habitat use between translocated and resident bears, and showed that translocated bears can survive without reoffending during the critical few years following translocation. Implications Managers and the public should recognise potential impacts for translocating grizzly bears. Translocated bears require time to explore and learn within their new environment, a process that can occur without repeating conflict. When conflict behaviour does re-occur, it should be viewed as a part of animal learning and not immediately as failure. On the basis of the amount of time translocated bears spent near humans and anthropogenic features, our findings suggest that translocated bears do not pose a greater threat to humans than do resident bears.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.043
GPT teacher head0.307
Teacher spread0.265 · 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 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

Citations6
Published2022
Admission routes2
Has abstractyes

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