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Record W2150028424 · doi:10.1139/b01-072

The effects of logs, stumps, and root throws on understory communities within 28-year-old aspen-dominated boreal forests

2001· article· en· W2150028424 on OpenAlexfundvenueno aff
Philip Lee, Kelly Sturgess

Bibliographic record

VenueCanadian Journal of Botany · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
FundersAlberta Conservation Association
KeywordsUnderstoryMicrositeVascular plantForest floorTaigaOrdinationBorealCoarse woody debrisEcological successionDisturbance (geology)Plant communityEcologyVegetation (pathology)Environmental scienceForestryBiologyGeographySpecies richnessBotanyEcosystemHabitatCanopySeedling

Abstract

fetched live from OpenAlex

This study examined the role of logs, stumps, and root throws on the understory composition of aspen-dominated boreal forests. Measures of microsite coverage and suitability, and vascular plant composition and abundance were taken from 28-year-old wildfire and harvest sites. Larger logs (>20 cm diameter) with soft surfaces were the most suitable for colonization by vascular plants. These logs covered more than five times the area of stumps or root throws in both harvest and wildfire sites. Detrended correspondence analysis revealed that logs and stumps were colonized by a significantly different assemblage of vascular plants than the forest floor of either disturbance type. Contrary to studies in other forest types, assemblages of plants on root throw pits and mounds were similar to those on the forest floor. Initial colonization patterns on logs and stumps in both wildfire and harvest sites were similar. However, on more decayed logs assemblages of vascular plants were more similar to their respective wildfire or harvest forest floor assemblages. Ordination of species suggested that tree seedlings and shade-tolerant herbs were disproportionately more abundant on logs and stumps.Key words: plant community assemblages, deadwood resources, coarse woody debris, root throws, logs, boreal forest.

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 score0.772
Threshold uncertainty score0.995

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 studies0.0010.001
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 head0.014
GPT teacher head0.189
Teacher spread0.175 · 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

Citations36
Published2001
Admission routes2
Has abstractyes

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