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Record W2183915606 · doi:10.82308/54330

Aquatic and terrestrial foraging by a subarctic herbivore: the beaver

2009· article· en· W2183915606 on OpenAlexfundno aff
Heather E. Milligan

Bibliographic record

VenueeScholarship@McGill (McGill) · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and biodiversity studies
Canadian institutionsnot available
FundersArcticNetSocial Sciences and Humanities Research Council of CanadaAssociation of Canadian Universities for Northern StudiesNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaMcGill University
KeywordsSubarctic climateEcologyHabitatTerrestrial ecosystemFood webGeographyBeaverEcosystemForestryBiology

Abstract

fetched live from OpenAlex

Les écosystèmes d'eau douce et terrestres sont liés par les interactions trophiques. Les isotopes stables naturels de carbone et d'azote offrent une méthode pour quantifier les transferts de nutriments entre les frontières écologiques, mais leurs applications aux systèmes d'eau douce-terrestres sont encore limitées. Cette thèse évalue l'efficacité des isotopes stables pour distinguer les plantes vasculaires d'eau douces et terrestres qui forment la base des chaînes alimentaires subarctiques. Nous avons trouvé qu'en général les plantes aquatiques avaient des signatures isotopiques enrichies par rapport aux plantes terrestres. Nous avons ensuite employé les techniques d'isotopes stables pour évaluer la variabilité spatiale et temporale dans le régime alimentaire d'une population de castors (Castor canadensis) subarctiques. Les macrophytes aquatiques semblent avoir une place plus importante dans le régime alimentaire des castors en comparaison avec la littérature disponible. Durant l'hiver, les castors qui habitaient les lacs ont consommé plus de végétation aquatique par rapport aux castors qui habitaient dans les rivières, ceux-ci comptant plutôt sur les provisions de végétation terrestre. L'accumulation de provisions constituées de plantes aquatiques peut permettre aux castors de persister à la limite de leurs aires de distribution où les arbres préférés des castors sont rares. Ainsi, ce phénomène pourrait réduire la pression des herbivores sur ces écosystèmes terrestres à faible productivité.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.609
Threshold uncertainty score1.000

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 studies0.0020.000
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 head0.011
GPT teacher head0.199
Teacher spread0.188 · 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

Citations6
Published2009
Admission routes1
Has abstractyes

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