Past, current, and future fire frequencies in Quebec's commercial forests: implications for the cumulative effects of harvesting and fire on age-class structure and natural disturbance-based management
Bibliographic record
Abstract
The past decade has seen an increasing interest in forest management based on historical or natural disturbance dynamics. The rationale is that management that favours landscape compositions and stand structures similar to those found historically should also maintain biodiversity and essential ecological functions. In fire-dominated landscapes, this approach is feasible only if current and future fire frequencies are sufficiently low compared with the preindustrial fire frequency, so a substitution of fire by forest management can occur without elevating the overall frequency of disturbance. We address this question by comparing current and simulated future fire frequency based on 2 × CO 2 and 3 × CO 2 scenarios to historical reconstructions of fire frequency in the commercial forests of Quebec. For most regions, current and simulated future fire frequencies are lower than the historical fire frequency, suggesting that forest management could potentially be used to maintain or recreate the age-class distribution of fire-dominated preindustrial landscapes. Current even-aged management, however, tends to reduce forest variability by, for example, truncating the natural age-class distribution and eliminating mature and old-growth forests from the landscape. Therefore, in the context of sustainable forest management, silvicultural techniques that retain a spectrum of forest compositions and structures at different scales are necessary to maintain this variability and thereby allow a substitution of fire by harvesting.
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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 | 0.001 | 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 | 0.001 |
| 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".