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Record W2142830877 · doi:10.3398/064.073.0402

Impacts from Winter-Early Spring Elk Grazing in Foothills Rough Fescue Grassland

2013· article· en· W2142830877 on OpenAlexaboutno aff
Tanya M. Thrift, Tracy K. Mosley, Jeffrey C. Mosley

Bibliographic record

VenueWestern North American Naturalist · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsnot available
Fundersnot available
KeywordsGrazingFoothillsGrasslandAgronomyFestuca rubraFestucaEnvironmental scienceBiologyEcologyPoaceae

Abstract

fetched live from OpenAlex

Foothills rough fescue (Festuca campestris) grasslands provide important foraging habitat for wildlife and livestock in the northwestern United States and southwestern Canada. Foothills rough fescue is sensitive to grazing during late spring —early summer but is believed to be more tolerant of grazing during winter—early spring. We evaluated vegetation and soil impacts from long-term winter—early spring grazing at 2 intensities (HG = heavy grazing, LG = light grazing). We studied a foothills rough fescue grassland in west central Montana, USA, that had been grazed almost exclusively by Rocky Mountain elk (Cervus elaphus nelsoni ) during winter—early spring for 58 years. Foothills rough fescue tolerated LG but not HG, whereas bluebunch wheatgrass (Pseudoroegneria spicata) and Idaho fescue (Festuca idahoensis) did not tolerate either LG or HG. Decreased productivity of foothills rough fescue in HG was accompanied by decreased herbaceous ground cover and increased abundance of the invasive dense clubmoss (Selaginella densa). Soil nutrient status (OM, C, N, C:N ratio) did not differ between HG and LG; however, soil bulk density was 18% greater in HG, and the Ah horizon was 20% thinner in HG. Overall, our results indicate that long-term elk grazing during winter—early spring degraded this terrestrial ecosystem, and we conclude that periodic rest from ungulate grazing during winter— early spring is necessary to sustain foothills rough fescue grasslands.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.049
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 studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

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