Challenges and implications of incorporating multi-cohort management in northeastern Ontario, Canada: A case study
Bibliographic record
Abstract
In northeastern Ontario, the natural fire cycle is long, resulting in large areas of forest in an uneven-aged condition. Under Ontario forest legislation requiring emulation of natural disturbance regimes, extended rotations and multi-cohort management present options that may meet landscape targets. We used a forest management wood supply model to compare scenarios of current even-aged management, extended rotations, and multi-cohort management (adds partial harvesting). Because science-based information to incorporate late successional forest stages into wood supply modeling is lacking in boreal Ontario, we adjusted the current even-aged inputs to account for mid- and late-seral conditions. Based primarily on expert opinion, adjustments were made to the Forest Resources Inventory age, yield curves, and succession rules; and partial harvesting was added. For modeling, we specified three broad succession groupings (even-aged, two- to three-aged, and all-aged) and established targets of 50%, 25% and 25% of the landscape area, respectively. The current even-aged scenario met even-aged targets but not multi-aged targets. Extended rotations and multi-cohort management scenarios met all the succession grouping targets over the long term. Wood supply was highest for the even-aged scenario, slightly lower for multi-cohort management scenario, and much lower for the extended rotations scenario. Road usage and relative cost was highest for the extendedrotations scenario and lowest for the even-aged scenario. Multi-cohort management may represent a compromise between maximizing harvest levels using even-aged management and retaining mid- and late-succession habitat structures.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".