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Record W2765345683 · doi:10.5558/tfc2017-034

Precommercial thinning of overtopping aspen to release coniferous regeneration in a boreal mixedwood stand

2017· article· en· W2765345683 on OpenAlexafffundvenue
Marcel Prévost, L. A. Charette

Bibliographic record

VenueThe Forestry Chronicle · 2017
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsMinistère des Ressources naturelles et des Forêts
FundersMinistère des Forêts, de la Faune et des Parcs
KeywordsAbies balsameaBalsamThinningEcological successionUnderstoryCrown (dentistry)Environmental scienceBorealClearcuttingForestryTaigaAgronomyBiologyBotanyEcologyCanopyGeography

Abstract

fetched live from OpenAlex

We used precommercial thinning (PCT) to accelerate natural succession in an 8-year-old, even-aged stratified mixture, in which trembling aspen (Populus tremuloides) overtopped a dense understory of balsam fir (Abies balsamea) and spruce (Picea mariana, P. glauca). In addition to an unthinned control, we applied three residual aspen spacings (2.5, 3.0 and 3.5 m) while retaining all understory conifers, and a 3.0-m spacing retaining only small conifers (<1/3 of the aspen crop tree height). PCT improved survival of spruce, increased diameter growth of aspen by 90% and doubled diameter and height growth of conifers, without differences among spacings or between levels of conifer retention after 10 years. The level of conifer retention did not affect aspen growth response, but appeared to influence the occurrence of browsing on aspen and balsam fir. Retaining only small conifers decreased regeneration density of balsam fir in favour of abundant vegetative reproduction of red maple (Acer rubrum) and beaked hazelnut (Corylus cornuta). Live crown characteristics and stand structure indicate that thinning caused a shift from overtopping of aspen to an intimate mixture of species sharing the growing space. This study confirms PCT as a means of accelerating natural succession in a boreal mixedwood stand, thereby securing the coniferous component at the early stage of development.

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 score0.225
Threshold uncertainty score0.426

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)0.0000.000

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 head0.016
GPT teacher head0.257
Teacher spread0.241 · 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

Citations12
Published2017
Admission routes3
Has abstractyes

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