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Record W2092235587 · doi:10.1139/x07-135

Regeneration development under shelterwoods in a lowland red spruce – balsam fir stand

2008· article· en· W2092235587 on OpenAlexaffvenueabout
David Pothier, Marcel Prévost

Bibliographic record

VenueCanadian Journal of Forest Research · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicSeedling growth and survival studies
Canadian institutionsUniversité LavalMinistère des Ressources naturelles et des ForêtsMinistère des Ressources naturelles et des Forêts (Québec)
Fundersnot available
KeywordsBalsamAbies balsameaDeciduousNatural regenerationCuttingRegeneration (biology)ForestryRed pineBiologyHorticultureSeedlingBotanyAgroforestryGeographyPinus <genus>

Abstract

fetched live from OpenAlex

The shelterwood system can be used to establish regeneration and to improve the growing conditions of seedlings and, thereby, increase their probability of survival after final harvest. To determine the cutting intensity that best promotes the development of red spruce ( Picea rubens Sarg.) regeneration, an experiment, including four repetitions of five treatments (control; low, moderate, and heavy partial cuttings; and clear-cutting), was established in a lowland stand in Quebec, Canada, dominated by red spruce and balsam fir ( Abies balsamea (L.) Mill.). Regeneration development responses to treatments varied according to cutting intensity, species, and position relative to the skidding trails in the residual stands. Ten years after treatment, red spruce seedlings were well established but were smaller than those of balsam fir and deciduous species. Red spruce seedling height was generally greater in partial-cut skidding trails, as was light availability. However, in clearcuts, the size of red spruce seedlings established in skidding trails seemed to be negatively affected by the considerable quantity of woody debris strewn over them. Among the partial-cut treatments, tree regeneration leaf biomass was the highest where 60% of the initial basal area was removed. Thus, this treatment is an attractive alternative to clear-cutting in such lowland stands where watering-up is anticipated after final harvest.

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)0.001
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 score0.442
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.082
GPT teacher head0.299
Teacher spread0.217 · 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

Citations15
Published2008
Admission routes3
Has abstractyes

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