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Record W2158902870 · doi:10.5558/tfc2015-010

Growth of planted jack pine (<i>Pinus banksiana</i>) and natural regeneration ten years after pre- and post-harvest spraying and partial cutting in an Ontario boreal mixedwood forest

2015· article· en· W2158902870 on OpenAlexaffvenueabout
Rongzhou Man, G. B. MacDonald

Bibliographic record

VenueThe Forestry Chronicle · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsOntario Forest Research InstituteMinistry of Natural Resources and Forestry
Fundersnot available
KeywordsJack pineSowingEnvironmental scienceBorealPinus <genus>TaigaHorticultureForestryAgronomyBiologyBotanyGeographyEcology

Abstract

fetched live from OpenAlex

The conventional plantation approach to regenerating jack pine (Pinus banksiana) after harvesting maximizes pine growth but may reduce wood quality. In this study we examined growth of planted jack pine and natural regeneration after herbicide spraying and partial cutting treatments on a boreal mixedwood site in northeastern Ontario. Treatments were pre-harvest aerial spray, post-harvest ground spray in strips (partial spray), partial cut, and post-harvest aerial broadcast spray; an untreated reference stand was used for comparison. Pre-harvest spray was as effective as partial cutting and post-harvest broadcast spray in suppressing trembling aspen regeneration and providing adequate light for survival and growth of planted jack pine. Ten years after planting, mortality and growth of pines in the pre-harvest treatment were comparable to those in the partial and broadcast spray treatments. Due to vigorous growth of broadleaf species [mostly red maple; (Acer rubrum)], and shade from the residual overstory, jack pine was smallest in the partial cut treatment; however, based on branch size, branch-free stem length and stem taper, wood quality was highest in this treatment. Considering factors important to forest managers such as growth and quality of planted jack pine, treatment costs, and proportion of the harvested blocks allocated to conifer production, the preferred treatment was pre-harvest spray.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.441
Threshold uncertainty score0.887

Distilled classifier scores by category (both heads)

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 head0.007
GPT teacher head0.206
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), 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

Citations3
Published2015
Admission routes3
Has abstractyes

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