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Record W2097473328 · doi:10.5402/2011/926061

Short-Term Plant Community Responses to Warming and Defoliation in a Northern Temperate Grassland

2011· article· en· W2097473328 on OpenAlexafffundabout
Eliza S. Deutsch, Edward W. Bork, James F. Cahill, Scott X. Chang

Bibliographic record

VenueISRN Ecology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of AlbertaAlberta Conservation Association
KeywordsGrasslandTemperate climateBiomass (ecology)Plant communityEnvironmental scienceGlobal warmingEcologyUngulateGrazingVegetation (pathology)AgronomyClimate changeAgroforestrySpecies richnessBiologyHabitat

Abstract

fetched live from OpenAlex

Little is known about the short-term impacts of warming on native plant community dynamics in the northern Canadian prairies. This study examined the immediate effects of elevated temperature and defoliation on plant community diversity, composition, and biomass within a native rough fescue (Festuca hallii(Vasey) Piper) grassland over two growing seasons. We used open-top chambers to simulate climate change and defoliated vegetation in midsummer of the first year to simulate biomass loss associated with periodic ungulate grazing. Warming marginally increased plant species diversity and changed community composition shortly after treatment, but effects were not apparent the second year, and there were no apparent impacts on plant biomass. Nonetheless, warming may have impacted community diversity indirectly through reduced soil moisture content, a pattern that persisted into the second year. Overall, this northern temperate grassland demonstrated limited community-level changes to warming even in the presence of defoliation.

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 score0.188
Threshold uncertainty score0.373

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.254
Teacher spread0.223 · 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
Published2011
Admission routes3
Has abstractyes

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