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Record W2164748395 · doi:10.1139/b10-062

Understory species interactions in mature boreal mixedwood forests

2010· article· en· W2164748395 on OpenAlexafffundvenueabout
Virginia Chávez, S. Ellen Macdonald

Bibliographic record

VenueBotany · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsUniversity of Alberta
FundersConsejo Nacional de Ciencia y TecnologíaAlberta Conservation Association
KeywordsUnderstoryShrubHerbaceous plantForbBiologyHerbBiomass (ecology)Competition (biology)BorealBotanyWoody plantAgronomyEcologyCanopyGrassland

Abstract

fetched live from OpenAlex

We explored interactions among plant growth forms in the understory of mature boreal mixedwood forests in western Canada by investigating the competitive influence of erect shrubs on herbs (forbs and grasses). We established 10 pairs of plots; all erect shrubs were removed in one plot of each pair (removals) and left intact in the other plot (controls). Two years later, we harvested all aboveground biomass of the herbaceous layer (herb biomass: this included graminoids, forbs, trailing shrubs, and species with a woody base but not woody stems) from the 20 plots. We tested for significant differences in understory species biomass and composition between control and removal plots and examined the influence of 25 environmental factors on species composition of the herbaceous layer. Competition intensity was measured by the natural logarithm of response ratio (ln RR) index based on herb biomass. After erect shrub removal, there was a significant increase in herb biomass, mostly due to an increase of the most common species (e.g., Cornus canadensis Linnaeus, Linnaea borealis Linnaeus). The values of competition intensity (ln RR) varied among herb species but were, overall, positive, indicating a release from competition following shrub removal. Composition of the herbaceous layer was significantly different between removal and control plots and was also significantly related to seven environmental factors, which explained 40% of the variation in composition. Our study suggests that there is asymmetric competition for light between erect shrub and herb species in boreal ecosystems.

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 score0.150
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 communication0.0000.000
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 head0.011
GPT teacher head0.241
Teacher spread0.230 · 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

Citations12
Published2010
Admission routes4
Has abstractyes

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