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Record W2060303576 · doi:10.5558/tfc78732-5

Windthrow as an important process for white spruce regeneration

2002· article· en· W2060303576 on OpenAlexvenueno aff
Jean‐Claude Ruel, Marius Pineau

Bibliographic record

VenueThe Forestry Chronicle · 2002
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsnot available
Fundersnot available
KeywordsWindthrowBalsamAbies balsameaRegeneration (biology)Natural regenerationCanopyBlack spruceBiologyForestryTaigaEcologyBotanyGeography

Abstract

fetched live from OpenAlex

White spruce (Picea glauca (Moench.) Voss.) is frequently found in association with balsam fir (Abies balsamea (L.) Mill.) in virgin stands. However, its regeneration is less aggressive than that of balsam fir. The persistance of white spruce in the canopy might be explained by differential mortality and windthrow. Windthrow could play an important role in creating favourable seedbeds and providing increased light. This paper examines the contribution of windthrow for white spruce regeneration in balsam fir-dominated forests. Experimental windthrows were created and regeneration establishment monitored for three seasons. Windthrow greatly modified the availability of seedbeds and enhanced white spruce establishment. Older natural windthrows were sampled to conclude that this effect was still evident more than five years after windthrow occured. We also noticed that white spruce benefited more from the disturbance than did balsam fir. Finally, sampling conducted in mature stands showed that mature white spruce stems were more abundant on the mounds created by old uprootings, indicating that this effect is maintained in the long term. Even though balsam fir also benefited from windthrow, the benefit was proportionally greater for white spruce. Key words: Picea glauca, Abies balsamea, windthrow, microtopography, regeneration

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 score0.087
Threshold uncertainty score0.656

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 studies0.0010.000
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 head0.032
GPT teacher head0.237
Teacher spread0.204 · 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

Citations18
Published2002
Admission routes1
Has abstractyes

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