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Record W4380368549 · doi:10.1002/ecs2.4523

Density and genetic diversity of grizzly bears at the northern edge of their distribution

2023· article· en· W4380368549 on OpenAlexaffabout
Mirjam Barrueto, Tyler D. Jessen, Rianne Diepstraten, Marco Musiani

Bibliographic record

VenueEcosphere · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsRaincoast Conservation FoundationUniversity of VictoriaUniversity of Calgary
Fundersnot available
KeywordsUrsusEcologyRange (aeronautics)Genetic diversityGrizzly BearsTundraPopulationBiologyGeographyEcosystem

Abstract

fetched live from OpenAlex

Abstract Species at the periphery of their range are typically limited in density by poor habitat quality. As a result, the central–marginal hypothesis (CMH) predicts a decline in genetic diversity of populations toward the periphery of a species' range. Grizzly bears ( Ursus arctos ) once ranged throughout most of North America but have been extirpated from nearly half of their former range, mainly in the south. They are considered a species at risk even in Canada's remote North, where they occupy the northernmost edge of the species' continental distribution in a low‐productivity tundra environment. With climate change, one of their main prey species in the tundra (caribou), which has always shown yearly fluctuations, is declining, but simultaneously, grizzlies appear to be expanding their range northward in the same tundra environment. Yet, a lack of population density estimates across the North is hindering effective conservation action. The CMH has implications for the viability of peripheral populations, and the links between population fluctuations, potential bottlenecks, and genetic diversity need to be determined to contribute to species' conservation. Using noninvasive genetic sampling from 2012 to 2014 and autosomal DNA genotyping (via microsatellites), we estimated bear density using a spatial capture–recapture framework and analyzed genetic diversity using observed heterozygosity (Ho), allelic richness (AR), and expected heterozygosity (He). We compared our findings to other studies that used comparable methodologies on grizzly bears and a related species (black bears; Ursus americanus ). We found densities of grizzly bears that were low for the species but characteristic for the region (5.9 ± 0.4 bears/1000 km 2 ), but with high Ho (0.81 ± 0.05), AR (7 ± 0.78), and He (0.71 ± 0.03), despite a signal of recent bottlenecks. In both species, peripherality was not correlated with Ho but was negatively correlated with density. We suggest that the apparent growth of this expanding population of grizzlies offsets the negative impacts of recent bottlenecks on Ho. Indigenous knowledge provides historical context (on the order of centuries, e.g., arctic large mammal fluctuations, grizzly bear bottlenecks) for the current bear population dynamics (on the order of decades, e.g., climate change, northern grizzly bear expansion).

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 score0.009
Threshold uncertainty score0.587

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)0.0010.000

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 head0.009
GPT teacher head0.180
Teacher spread0.171 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

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