Implementing wildfire-based timber harvest guidelines in southeastern Manitoba
Bibliographic record
Abstract
The Manitoba Model Forest and Tembec Industries (Pine Falls Operations) are operationalizing the overall goal of sustainable forest management: maintain forest ecosystem health while harvesting timber. Timber harvest guidelines intended to approximate the effects of a large wildfire were developed for spatial scales that span from the operating area down to the site. Operating area issues are addressed through landscape design guidelines that locate cutblocks and other activities (e.g., roads) within an operating area. Cut-block guidelines determine how harvesting, site preparation and regeneration are completed. These wildfire-based guidelines are being tested in four large-scale harvest trials in southeastern Manitoba. This paper describes the rationale behind the approach taken, the landscape design and cutblock operating guidelines that were developed, operational experiences from the harvest trials, and some of the challenges that arose. Key words: wildfire, operating guidelines, landscape design, timber harvesting, site preparation, regeneration, natural disturbance emulation, ecosystem processes, ecosystem health, maintaining biodiversity, maintaining ecosystem condition
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".