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Commercial thinning and its potential for contributionto the timber supply in British Columbia’s Interior forests

2014· article· en· W39259847 on OpenAlexaboutno aff
David R. Christian

Bibliographic record

VenuePancreas · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsThinningForestryLoggingForest managementMountain pine beetleContext (archaeology)SilvicultureAgroforestryBusinessEnvironmental scienceGeographyAgricultural economicsEconomicsArchaeology

Abstract

fetched live from OpenAlex

Thinning is the partial removal of trees in a forest stand prior to final harvest. The term can be divided in pre-commercial thinning where little if any volume is removed from the stand and commercial thinning where removals are intended to provide a positive economic result. From a silvicultural point of view, the goal of thinning is to enhance future crop tree quality by removing low-quality stems and providing sufficient space for the accelerated development of retained ones (Huuskonen & Hynynen, 2006). The goals of this study was to see if commercial thinning could positively affect the short and medium term timber supply (MTTS) in the Interior regions of British Columbia (BC), and whether or not Scandinavian forestry practices could be adopted in the BC context. The mountain pine beetle (Dendroctonus ponderosae Hopkins) has created significant forest planning problems in BC. The annual allowable cut (AAC) was raised to capture beetle-killed timber while still merchantable. These regions face drastic cuts in AAC in the mid-term, and the provincial authority is looking to mitigate the effects of this falldown, and commercial thinning has been suggested. The effects of commercial thinning on the provincial timber supply was analysed in three ways: a literature review, a series of stakeholder interviews, and a case study for the Alex Fraser Research Forest. A review of thinning regimes in Nordic countries shows thinning has beneficial consequences on timber quality, with small decreases in total volume. Merchantable volumes are similar to unthinned stands, ranging from a decrease (ca. 20%) in Scots pine (Pinus sylvestris L.) to a slight increase (0-5%) in Norway spruce (Picea abies L.). Average tree diameters are greater in thinned stands, a determining factor in stand culmination. Thinning provides intermediate sources of timber and income before final harvest. A series of interviews with important stakeholders in the Swedish forest sectors shows that commercial thinning plays an important role for the timber supply and the economy of their industries. All report that thinning is ubiquitous in “proper forest management”. On an area basis, two thirds of the yearly harvest is the result of thinning, producing one third of total volume. In comparison, final harvests are conducted over the remaining one third of the harvested landbase and account for two thirds of the timber supply. The thinning programmes in place are a result of the young age-class structure of the forest. The case study was conducted at The University of British Columbia’s Alex Fraser Research Forest (Beaver Valley, BC). A 2200 ha subset of the Gavin Lake block of was classified by maturity level, with a particular interest for stands suitable for a first thinning. A total of 957 ha have thinning opportunities, with an average of 120 m3/ha available for harvest during at first entry; a total of 102 458 m3 would be made available with thinnings. Partial harvests of these stands could improve the short-term and mid-term timber supply while providing beneficial effects (quality, age-class distribution) in the mid and long-term. Commercial thinning could play a part in filling a MTTS gap, by providing timber before final harvest, by controlling timber flows from thinned stands, by creating more merchantable sawlog volume, by accessing timber in visually sensitive areas, and by using the shelterwood regeneration method in hard to regenerate areas. Certain practices from Nordic countries are currently adaptable to the BC context, while others would require longer-term changes for the industry.

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)0.001
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 score0.205
Threshold uncertainty score0.412

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.006
GPT teacher head0.218
Teacher spread0.212 · 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".

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Citations0
Published2014
Admission routes1
Has abstractyes

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