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Record W2131226771 · doi:10.1139/z01-162

The demographic response of bank-dwelling beavers to flow regulation: a comparison on the Green and Yampa rivers

2001· article· en· W2131226771 on OpenAlexvenueno aff
Stewart W. Breck, Kenneth R. Wilson, Douglas C. Andersen

Bibliographic record

VenueCanadian Journal of Zoology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
FundersNational Park ServiceU.S. Geological Survey
KeywordsBeaverHome rangeHabitatEcologyCastor canadensisWillowRange (aeronautics)ElectrofishingBankBiologyEnvironmental scienceHydrology (agriculture)Geography

Abstract

fetched live from OpenAlex

We assessed the effects of flow regulation on the demography of beavers (Castor canadensis) by comparing the density, home-range size, and body size of bank-dwelling beavers on two sixth-order alluvial river systems, the flow-regulated Green River and the free-flowing Yampa River, from 1997 to 2000. Flow regulation on the Green River has altered fluvial geomorphic processes, influencing the availability of willow and cottonwood, which, in turn, has influenced the demography of beavers. Beaver density was higher on the Green River (0.5–0.6 colonies per kilometre of river) than on the Yampa River (0.35 colonies per kilometre of river). Adult and subadult beavers on the Green River were in better condition, as indicated by larger body mass and tail size. There was no detectable difference in home-range size, though there were areas on the Yampa River that no beavers used. We attribute the improved habitat quality on the Green River to a greater availability of willow. We suggest that the sandy flats and sandbars that form during base flows and the ice cover that forms over winter on the Yampa River increase the energy expended by the beavers to obtain food and increase predation risk and thus lowers the availability of woody forage.

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 score0.130
Threshold uncertainty score0.885

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.203
Teacher spread0.186 · 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

Citations29
Published2001
Admission routes1
Has abstractyes

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