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Record W2114775800 · doi:10.1139/z04-067

An extensive study of the foraging ecology of beavers (<i>Castor canadensis</i>) in relation to habitat quality

2004· article· en· W2114775800 on OpenAlexfundvenueaboutno aff
Daniel Gallant, Céline H. Bérubé, Éric Tremblay, Liette Vasseur

Bibliographic record

VenueCanadian Journal of Zoology · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsForagingCastor canadensisBeaverHabitatForageEcologyBiologyOptimal foraging theoryNational park

Abstract

fetched live from OpenAlex

The objective of this study was to examine the foraging behaviour of the beaver (Castor canadensis Kuhl, 1820) and to explain its selection of terrestrial woody plant species according to central place foraging theory. Limitations in variety of food items in most studies with regard to size and (or) distance from the central place and information on availability of forage choices give a partial view of the subject. In this study, the theory is tested in a natural environment with high variability in food items with regard to these factors. Foraging choices by beavers were inspected by measuring variables on cut and uncut trees of every species encountered within 1 m of trail systems made by 25 beaver colonies in Kouchibouguac National Park in New Brunswick, Canada, thereby quantifying the availability of the different food items. The effect of habitat quality (food availability) on the foraging behaviour of beavers was also tested. The results of this study suggest that with increasing distance from the pond, beavers in high-quality habitats selected fewer, but larger, trees and are more species selective. This selectivity was diminished in habitats of lower quality. The results of this study are consistent with the predictions of the central foraging theory.

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 score0.868
Threshold uncertainty score0.890

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 head0.017
GPT teacher head0.235
Teacher spread0.219 · 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

Citations74
Published2004
Admission routes3
Has abstractyes

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