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Record W2173759684 · doi:10.5558/tfc2013-091

Effects of precommercial thinning on the forest value chain in northwestern New Brunswick: Part 6 – Estimating the economic benefits

2013· article· en· W2173759684 on OpenAlexafffundvenueabout
Doug Pitt, Len Lanteigne, Michael K. Hoepting, Jean Plamondon, Isabelle Duchesne, Paul Bicho, G. C. Warren

Bibliographic record

VenueThe Forestry Chronicle · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsFPInnovationsCanadian Forest ServiceNatural Resources Canada
FundersCanadian Forest ServiceU.S. Forest Service
KeywordsStumpageThinningAbies balsameaForestryBalsamPresent valueEnvironmental scienceDeciduousNet present valueForest inventoryProductivitySite indexSilvicultureAgroforestryAgricultural economicsProduction (economics)Forest managementEconomicsGeographyEcology

Abstract

fetched live from OpenAlex

The Green River precommercial thinning (PCT) trials were established between 1959 and 1961 in naturally regenerating balsam fir (Abies balsamea [L.] Mill.)-dominated stands an average of eight years after overstory removal. Following clearcut harvest of three of the study's six replicates in the fall of 2008, the rotation-length effects of PCT and vegetation management (VM; deciduous tree and brush suppression) on the forest value chain were integrated into a spreadsheet-based model that estimates the net present value (NPV) of these silvicultural treatments. Assuming costs and prices near recent values, both PCT and VM were observed to support positive landowner NPVs through discount rates in excess of 6%. At a discount rate of 4% and an age where sawlog production was maximized, PCT and VM offered similar NPV (>$550/ha). Landowners that can attract buyers willing to pay a premium for wood from thinned stands (equal to the sum of reduced operational overhead charges, harvesting and sawmilling costs and increased pulping costs) could see the value of their stands double. Sensitivity analyses revealed that these results are dependent on site productivity, silvicultural costs and a strong premium on sawlog stumpage rates. Depending on economic circumstances, PCT and VM could be attractive investments on high quality sites that are situated in close proximity to wood processing infrastructure.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.999

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.011
GPT teacher head0.223
Teacher spread0.211 · 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.

Study designSimulation or modeling
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

Citations22
Published2013
Admission routes4
Has abstractyes

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