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Demographic Parameters and Harvest-Explicit Population Viability Analysis for Polar Bears in M'Clintock Channel, Nunavut, Canada

2006· article· en· W2172815931 on OpenAlexafffundabout
Mitchell K. Taylor, Jeff Laake, Philip D. McLoughlin, H. Dean Cluff, François Messier

Bibliographic record

VenueJournal of Wildlife Management · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsGovernment of Northwest TerritoriesUniversity of SaskatchewanGovernment of Nunavut
FundersGovernment of Nunavut
KeywordsUrsus maritimusDemographyPopulationLitterMark and recaptureBiologyGeographyAnimal scienceEcologyArctic

Abstract

fetched live from OpenAlex

Polar bear (Ursus maritimus) numbers in M'Clintock Channel, Nunavut, Canada have decreased significantly since 1972. We used mark–recapture and recovery data collected from 348 marked polar bears from 1972 to 2000 to estimate demographic characteristics and harvest risks of the M'Clintock Channel polar bear population. Total (harvested) survival rates (±1 SE) from mark–recapture analysis were: 0.62 (±0.15) for cubs of the year, 0.90 (±0.04) for subadults (ages 1–4 yr), 0.90 (±0.04) for adult (age ≥5 yr) females, and 0.88 (± 0.04) for adult males. Mean litter size was 1.68 ± 0.15 cubs with a mean reproductive interval of 2.8 ± 0.2 years. By 6 years of age, on average 0.29 ± 0.47 females were producing litters; mean litter production rate for females aged >6 years was 0.93 ± 0.33. We estimated total abundance to average 284 ± 59.3 bears, of which 166.9 ± 35.4 individuals were female and 117.2 ± 26.4 were male. We incorporated our standing age and mark–recapture demographic parameters as input into a harvest risk analysis designed to account for demographic, environmental, and sampling uncertainty. Population growth rate was 0.946 ± 0.038 for the period 1993–1999. A harvest quota not exceeding 3 bears/year is required if the population is to increase in the short term. Slightly higher quota options are available if increased risk and recovery times are accepted by stakeholders.

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)0.001
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 score0.270
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.011
GPT teacher head0.220
Teacher spread0.208 · 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

Citations36
Published2006
Admission routes3
Has abstractyes

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