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High Grazing Impact, Selectivity, and Local Density of Muskoxen in Central Ellesmere Island, Canadian High Arctic

2000· article· en· W4249115252 on OpenAlexafffundabout
Martin Raillard, Josef Svoboda

Bibliographic record

VenueArctic Antarctic and Alpine Research · 2000
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsAurora CollegeUniversity of TorontoCanadian Forest Service
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto
KeywordsGrazingArcticHerbivoreVegetation (pathology)SnowGeographyEcologyArctic vegetationGrasslandTundraPhysical geographyForestryBiology

Abstract

fetched live from OpenAlex

Grazing activities and densities of muskoxen in Sverdrup Pass, Central Ellesmere Island, were investigated by use of an automatic camera monitoring system from May to August, 1987 and by direct observation from March to May 1988. Average seasonal density of muskoxen was 6.4 ± 1.9 (S.E.M.) animals × km−2 resulting in an average of 48.3 ± 5.1 (S.E.M.) % of available shoots grazed in meadow stands. These figures far surpass previous estimates of density or impact of muskoxen in the High Arctic. It shows that in some high arctic plant communities herbivores can reach high densities and have a high impact, even though aerial survey counts of large areas indicate low average animal densities. Muskoxen selected wet and mesic meadow communities between April and August, except in late June and late July of 1987, when willow herb fields were chosen. In March and early April of 1988 muskoxen grazed valley slopes with little snow cover and little vegetation. In total, 82.8% of the grazing time between 18 May and 18 August 1987, was spent in meadows, despite the fact that these communities covered only 31% of the study area. Muskoxen were therefore highly selective grazers.

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)0.000
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 score0.088
Threshold uncertainty score0.177

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
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 head0.030
GPT teacher head0.283
Teacher spread0.252 · 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

Citations12
Published2000
Admission routes3
Has abstractyes

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