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Record W4391025016 · doi:10.5558/tfc2024-002

Growth response to pre-commercial thinning of lodgepole pine is short-term but the effects on size distribution persist for decades

2024· article· en· W4391025016 on OpenAlexafffundvenueabout
Shes Kanta Bhandari, Bradley D. Pinno, Kenneth J. Stadt, Barb R. Thomas

Bibliographic record

VenueThe Forestry Chronicle · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsGovernment of AlbertaUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Alberta
KeywordsThinningEnvironmental sciencePinus contortaTerm (time)ForestryMathematicsGeographyPhysics

Abstract

fetched live from OpenAlex

Pre-commercial thinning in Alberta is a potential option for increasing the growth rate and shortening the rotation age of regenerating forests. Previous studies have focused on the evaluation of either the immediate- or long-term response to thinning after many decades. Our current study compares the pre-commercial thinning response in lodgepole pine for a 10-year period immediately after thinning, and again 38-45 years after thinning, based on 22 paired plots of precommercially thinned trials in Alberta. The first group of plots was pre-commercially thinned in 1984, measured in 1985 and 1995 (short-term) and the second group was pre-commercially thinned between 1962 and 1969 and measured in 2007 and 2017 (long-term). In the short-term, individual tree DBH growth was 56% greater in pre-commercially thinned plots, while in the long-term plots, there were no measured growth differences between pre-commercially thinned and unthinned plots. Small- and medium-sized trees benefited more from pre-commercial thinning than larger trees. However, at the stand level, the number and volume of merchantable-sized trees (≥13.5 cm DBH) were higher in pre-commercially thinned plots than in unthinned plots in both the short- and long-term. Although the growth response of thinning appeared to be a short-term response (number and volume of larger trees), yield at the end of the long-term measurement period was still higher in pre-commercially thinned than in unthinned plots.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.060
Threshold uncertainty score0.120

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)0.0010.000

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 head0.008
GPT teacher head0.255
Teacher spread0.248 · 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

Citations2
Published2024
Admission routes4
Has abstractyes

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