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Record W2058235192 · doi:10.5558/tfc80478-4

Divided landbase, overlapping tenures, and fire risk

2004· article· en· W2058235192 on OpenAlexafffundvenueabout
Steven G. Cumming, Glen W. Armstrong

Bibliographic record

VenueThe Forestry Chronicle · 2004
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of Alberta
FundersAlberta-Pacific Forest Industries
KeywordsBusinessTaigaWoodlandForest managementNatural resource economicsEnvironmental resource managementEnvironmental scienceForestryEconomicsAgroforestryGeography

Abstract

fetched live from OpenAlex

The Tardis forest modeling program was used to investigate the effects on timber supply and delivered wood cost of alternative forest tenure policies on a forest management agreement area in northeastern Alberta. Under the current tenure policy (business as usual), the woodlands divisions of one large pulp company and several sawmill companies are responsible for different aspects of planning and forest management on the area. We propose an alternative tenure policy (global planning) whereby one forest management entity is responsible for harvesting timber and delivering it to the various mills. The global planning alternative has several advantages over business as usual, especially for the sawmill companies. With business as usual, the sawmill companies experience shortfalls in timber harvest volume. No shortfall is seen with global planning. Under global planning, delivered wood cost for the sawmill companies is reduced by $2.81 m –3 , on average. Forest fire is an important disturbance affecting timber supply in the area. We examine the joint effects of tenure policy and fire using Monte Carlo simulation. The superiority of global planning is even more apparent with fire incorporated in the model. According to our simulations, many sawmills are very likely to experience persistent sharp decreases in delivered wood volume under business as usual. No such decreases occur under global planning. Key words: forest tenure, simulation modeling, timber harvest scheduling, forest fire, policy analysis, boreal mixedwood, sustainable forest management

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score1.000

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)0.0010.001

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 head0.008
GPT teacher head0.218
Teacher spread0.210 · 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 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

Citations9
Published2004
Admission routes4
Has abstractyes

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