Assessing forest management strategies under a mountain pine beetle attack in Alberta: exploring the impacts
Bibliographic record
Abstract
We explore how forest resource managers can respond to a potential outbreak of mountain pine beetle ( Dendroctonus ponderosae Hopkins, 1902) by assessing how well different forest management strategies achieve various management objectives over time. Strategies include targeting at-risk stands as well as increasing harvest levels. Outcomes are evaluated on the basis of volume flows, net revenues, and the age class structure of the ending inventory. We use a spatially and temporally explicit model to simulate forest management outcomes and consider two different scenarios, one in which the attack occurs early and one where it is delayed. The model utilizes a planning with recourse approach in which the firm can reevaluate its harvesting schedule following the attack. We use company data from west-central Alberta for a 40-year planning exercise. The timing of the attack resulted in small differences in timber supply. However, most strategies performed better financially under an early attack, which limits the harvest of marginal stands. Increasing harvest levels performed better in economic terms but resulted in a very young growing stock with little old forest. The success of any strategy is linked to the timing of the attack and how it affects the growing stock, subsequently impacting timber and revenue flows.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".