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Record W4417105019 · doi:10.2192/ursus-d-24-00012

Quantifying recovery of British Columbia's South Selkirk grizzly bear population

2025· article· W4417105019 on OpenAlexaffabout
Michael F. Proctor, John Boulanger, A. Grant MacHutchon, David Paetkau, Wayne F. Kasworm

Bibliographic record

VenueUrsus · 2025
Typearticle
Language
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsS2G Biochem (Canada)Pacific Insight Electronics (Canada)
Fundersnot available
KeywordsGrizzly BearsPopulationPopulation densityWildlifeUrsusReproductionWildlife managementWildlife conservationDistribution (mathematics)

Abstract

fetched live from OpenAlex

Small, isolated wildlife populations are often at great conservation risk. Quantitative monitoring of their conservation status over time and evidence of recovery is relatively rare. We carried out population surveys of grizzly bears (Ursus arctos) pre– (2005) and post– (2020–2021) conservation management, to assess the efficacy of strategic measures applied to the at-risk Canadian South Selkirk grizzly bear population in southeastern British Columbia. We evaluated our management outcomes by comparing our recent survey results with recovery targets outlined in a 2016 Recovery Management Plan, which included abundance, trend, number and distribution of females, distribution of reproductive females, mortality rates, and inter-population connectivity. Surveys consisted of remote genetic sampling where DNA from hair roots generated genotypes identifying individuals, sex, and family units. In 2020–2021, we identified 73 individuals (41 females, 32 males) that were used in a spatially explicit capture–recapture (SECR) density estimate, and 8 individuals sampled opportunistically at rub sites that were used in our connectivity analysis. We estimated the average number of bears using the area at any one time to be 69 (95% CI = 56–86). This estimate exceeded our closure-corrected recovery target of 60 bears. Densities were highest in the northern and central portions of the area, but the average density was estimated to be 17 grizzly bears/1,000 km2 (95% CI = 14–22). Female distribution and evidence of reproduction varied spatially but occurred in all 6 delineated subunits, which exceeded our target of occurring in 5 subunits. Human-caused female mortality reported over the past 6 years was 0.5 bears/year, well below our target of 1 bear/year. We identified 9 immigrants (1F, 8M) from the Purcell Mountains who bred 27 offspring (12F, 15M) with other South Selkirk mates. This level of connectivity and gene flow represented a substantial increase for this previously fragmented population. Our results suggest that 15 years of conservation management have significantly improved the status of the Canadian South Selkirk grizzly bear population.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.017
GPT teacher head0.233
Teacher spread0.216 · 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.

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
Published2025
Admission routes2
Has abstractyes

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