Modeling the effect of changing market conditions on mountain pine beetle salvage harvesting and structural changes in the British Columbia forest products industry
Bibliographic record
Abstract
This paper describes the development and implementation of Cambium, an agent-based forest sector model for strategic analysis. This model is designed as a decision-support tool for assessing the effects that changes in product demand and resource inventories can have on the structure and economic viability of the forest sector. Cambium models aggregate product supply as an emergent property of individual companies’ production decisions and stand-level ecological processes. Modeling the forest-products sector as a group of interacting autonomous economic agents makes it possible to include production capacity dynamics and the potential for mill insolvencies as factors in analyzing the effects of market and forest inventory based disturbances. The utility of this model is tested by assessing the impacts of a market downturn in the US forest products market on forest industry structure and mountain pine beetle ( Dendroctonus ponderosae Hopkins) salvage harvesting in British Columbia, Canada. Simulation results indicate a significant medium-term timber supply shortage; reduced stumpage revenues; intensive cost competition among primary wood-products manufacturers; and a large number of insolvencies in the panel, lumber, and pulp sectors.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".