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Recovery of tall cotton–grass following real and simulated feeding by snow geese

2000· article· en· W2062284070 on OpenAlexaboutno aff
Jerry W. Hupp, D. Gordon E. Robertson, Joel A. Schmutz

Bibliographic record

VenueEcography · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsnot available
FundersU.S. Fish and Wildlife ServiceU.S. Geological SurveyDirectorate for Biological Sciences
KeywordsSnowCarexForageGooseAnatidaeWaterfowlAgronomyBiomass (ecology)BiologyBrantaEnvironmental scienceEcologyGrasslandScirpusHabitatWetlandGeography

Abstract

fetched live from OpenAlex

Lesser snow geese Anser caerulescens caeruteseens from the western Canadian Arctic feed on underground parts of tall cotton–grass Eriophorum angustifolium during autumn staging on the coastal plain of the Beaufort Sea in Canada and Alaska. We studied revegetation of sites where cotton–grass had been removed either by human–imprinted snow geese or by hand to simulate snow goose feeding. Aerial cover of cotton–grass at sites (n = 4) exploited by human–imprinted snow geese averaged 60 and 39 Mi lower than in undisturbed control plots during the first and second year after feeding, respectively. Underground biomass of cotton–grass stembases and rhizomes in hand–treated plots was 80 and 62% less than in control plots 2 and 4 yr after removal, respectively (n = 10 yr ‐1 ). Aerial cover and biomass of common non‐forage species such as Carex aquatilis did not increase on treated areas. Removal of cotton‐grass by geese likely reduces forage availability at exploited sites for at least 2–4 yr after feeding but probably does not affect long‐term community composition. Temporal heterogeneity in forage abundance likely contributes to the large spatial requirement of snow geese during staging.

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 score0.054
Threshold uncertainty score0.721

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)0.0010.000

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 head0.003
GPT teacher head0.190
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

Citations3
Published2000
Admission routes1
Has abstractyes

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