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Food habits of wolverine<i>Gulo gulo</i>in montane ecosystems of British Columbia, Canada

2007· article· es· W2168344345 on OpenAlexfundaboutno aff
Eric C. Lofroth, John A. Krebs, William L. Harrower, Dave Lewis

Bibliographic record

VenueWildlife Biology · 2007
Typearticle
Languagees
FieldEnvironmental Science
TopicWildlife Ecology and Conservation
Canadian institutionsnot available
FundersU.S. Forest ServiceMinistry of EnvironmentParks Canada
KeywordsPredationEcologyBeaverForagingSnowshoe hareCarnivoreGeographyReproductionBiologyMarmotPorcupineReproductive successDemographyPopulation

Abstract

fetched live from OpenAlex

We examined the seasonal food habits of wolverine Gulo gulo in subboreal and interior wet-belt montane environments in British Columbia by analyzing scats collected during the course of two concurrent wolverine studies. Understanding foraging ecology for a wide-ranging carnivore such as the wolverine is important, particularly because reproduction has been demonstrated to be closely linked to food abundance. Wolverine diet was shown to vary regionally and seasonally. Regional variation was related to differences in prey availability between study areas. Moose Alces alces, caribou Rangifer tarandus, and hoary marmots Marmota caligata were abundant and common prey items within both study areas. Mountain goats Oreamnos americanus and porcupine Erithizon dorsatum were more abundant and more frequent prey items in the Columbia Mountains, while snowshoe hare Lepus americanus and beaver Castor canadensis were more abundant and more frequent prey items in the Omineca Mountains. Within the winter season, diet choices by reproductive females were different than other sex and age classes. Caribou, hoary marmots and porcupines were found in significantly higher frequencies in the diet of reproductive females. Foraging observations concurred with the findings of scat analyses. Dependence of reproductive females on a species of current conservation concern (caribou) and one which could be affected by issues related to climate change (hoary marmot) may present conservation issues for wolverines in the future.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.006
GPT teacher head0.194
Teacher spread0.187 · 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

Citations59
Published2007
Admission routes2
Has abstractyes

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