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Record W4411007262 · doi:10.1111/rec.70099

Greater sage‐grouse habitat restoration with range management, revegetation, and herbicide

2025· article· en· W4411007262 on OpenAlexafffundabout
Autumn D. Watkinson, Amalesh Dhar, M. Anne Naeth, Shelley D. Pruss

Bibliographic record

VenueRestoration Ecology · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicRangeland and Wildlife Management
Canadian institutionsParks CanadaTrent UniversityUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of AlbertaParks Canada
KeywordsRevegetationRestoration ecologyHabitatRange (aeronautics)GeographyAgroforestryForestryEnvironmental scienceEcologyBiologyEcological successionEngineering

Abstract

fetched live from OpenAlex

Populations of Greater sage‐grouse ( Centrocercus urophasianus ), an iconic symbol of sagebrush ecosystems, are declining in native grasslands due to habitat loss, degradation, and fragmentation. We conducted a field experiment in Grasslands National Park, Saskatchewan, Canada, to investigate how disturbance and land management (cattle grazed, bison grazed, watered, and ungrazed) affected Greater sage‐grouse habitat and the efficacy of common restoration methods. Restoration treatments consisted of a seed mix of native forbs, grasses, and sagebrush; seeding season (fall and spring); planted sagebrush seedlings; and applications of glyphosate herbicide. Total vegetation cover, moss, and lichen cover, and species richness were greater, and litter cover was less with cattle grazing than with other management treatments. Herbicide increased native forb cover and negatively affected established sagebrush. Seeding season (fall and spring) had little effect on vegetation parameters. Establishment of native forbs and grasses by seed was mostly unsuccessful. Planting sagebrush seedlings was more effective than broadcast seeding; although, after 2 years, seedling survival was very low. There was an abundance of diverse forbs for the dietary requirements of pre‐laying hens, chicks, and juveniles with most management treatments. The proportion of litter cover played a significant role in successful vegetation establishment. All sites had key components of sage‐grouse habitat and showed potential for restoration success given some land management modifications.

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 score0.030
Threshold uncertainty score0.386

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)0.0000.000

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 head0.006
GPT teacher head0.213
Teacher spread0.207 · 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

Citations1
Published2025
Admission routes3
Has abstractyes

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