An assessment of critical assumptions supporting the timber supply modelling for mountain-pine-beetle-induced allowable annual cut uplift in thePrince George Timber Supply Area
Bibliographic record
Abstract
To address the mountain pine beetle epidemic, the allowable annual cut (AAC) for the Prince George Timber Supply Area (TSA) has been increased by 5.7 million m3 to 14.944 million m3. Timber supply model forecasts supporting AAC uplift decisions show a significant mid-term timber supply falldown. Timber supply modelling undertaken for the Prince George TSA in support of the recent AAC decision has not incorporated mortality in stands less than 60 years old, has generally considered the shelf life of beetlekilled wood to be 5 years for use as dimension lumber and 5 additional years for use as products of reduced fibre quality, and has assumed that pine timber makes up at least 78% of the total harvest in the short term. Current research suggests that certain of these assumptions may be optimistic. Refinements to these important timber supply analysis assumptions may result in a mid-term timber supply falldown that is deeper and longer than originally forecast. If the current outbreak continues unabated, stands in which lodgepole pine represents over 70% of the volume will provide enough mature growth to satisfy the new AAC for a further 14 years. It may be that the current increased AAC will not be realized for this period of time because of economic and environmental reasons. Greater value may be gained by not harvesting pine-dominated stands that contain significant stand structure or advance regeneration. Retention of these stands could mitigate the negative effects to the environment, hydrology, and wildlife while increasing the volume available in the latter part of the mid-term. Barriers to forest licensees focussing harvest in these stands include current mill requirements, existing traditional operating areas, previously approved cutting permits, stumpage appraisal, accessibility, and other economic considerations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".