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Record W2163248901 · doi:10.2193/2006-158

Demography of Black Bears in Hunted and Unhunted Areas of the Boreal Forest of Ontario

2008· article· en· W2163248901 on OpenAlexaffabout
Martyn E. Obbard, Eric J. Howe

Bibliographic record

VenueJournal of Wildlife Management · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsDemographyLitterUrsusEconomic shortageBorealTaigaGeographyReproductionVital ratesEcologyBiologyForestryArchaeologyPopulationPopulation growth

Abstract

fetched live from OpenAlex

Abstract: We estimated relative density, survival, and reproduction of American black bears ( Ursus americanus ) from capture‐recapture and telemetry data collected from 1989 to 1999 in the unhunted Chapleau Crown Game Preserve (CCGP) and nearby hunted areas in the boreal forest of Ontario, Canada. We tested for combinations of effects of age class, sex, year, years of food shortage, encumbrance status, and residency (on or off the Game Preserve) on vital rates. Results from live captures, remote captures, and bait‐station hit rates indicated that density was highest inside CCGP. Total survival of adult females, subadults, and cubs were similar among residents and nonresidents of CCGP, but yearling survival was lower among CCGP residents. Adult females were approximately twice as likely to die and nearly 10 times as likely to be cannibalized (risk ratio [RR] = 9.62, 95% CI = 2.088–44.29) while encumbered with cubs of the year. Nonresidents of CCGP had greater risk of being harvested (RR = 4.00, 95% CI = 1.19–13.46) but similar risk of being cannibalized (RR = 0.875, 95% CI = 0.300–2.55) relative to CCGP residents, suggesting that harvest mortality was additive to other forms of mortality. Residents of CCGP had older ages at primiparity and lower litter‐production rates than bears resident in hunted areas. Few litters were produced in years following food shortages, but litter size was unaffected. We recommend that managers allow for additive harvest mortality and reduced survival of bears encumbered with cubs of the year, and we caution that assuming density‐compensatory increases in cub production could optimistically bias estimates of population growth.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

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 head0.009
GPT teacher head0.193
Teacher spread0.185 · 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.

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

Citations58
Published2008
Admission routes2
Has abstractyes

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