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Record W2140710576 · doi:10.1890/07-1428.1

HABITAT-MEDIATED VARIATION IN PREDATION RISK BY THE AMERICAN MARTEN

2008· article· en· W2140710576 on OpenAlexafffund
Mark Andruskiw, John M. Fryxell, Ian D. Thompson, James A. Baker

Bibliographic record

VenueEcology · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsOntario Forest Research InstituteCanadian Forest ServiceUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaMinistry of Natural Resources
KeywordsMartenPredationEcologyHabitatAbundance (ecology)BiologyVoleMammalSeed predationBiological dispersalPopulationSeed dispersal

Abstract

fetched live from OpenAlex

The probability of prey encounter, attack, capture, and kill are often hypothesized to depend on habitat structure, but field evidence in terrestrial systems is rare. We tested whether predation efficiency by the American marten (Martes americana) and fear of predation by their primary prey, the red-backed vole (Clethrionomys gapperi), differed between 20- to 50-year-old regenerating forest stands and older uncut stands. Our results showed that the frequency of prey encounter, prey attack, and prey kill were higher in old uncut forests, despite the fact that small-mammal density was similar to that in younger logged forests. These differences in predation efficiency were linked to higher abundance of coarse woody debris, which seems to offer sensory cues to martens, thereby increasing the odds of hunting success. Red-backed voles in regenerating forest stands exhibited increased wariness compared to voles living in old uncut forest, suggestive of a behavioral response to habitat-mediated variation in predation risk.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.005
GPT teacher head0.204
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), 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

Citations166
Published2008
Admission routes2
Has abstractyes

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