Changes in mean forest age in Canada’s forests could limit future increases in area burned but compromise potential harvestable conifer volumes
Bibliographic record
Abstract
Forest fire activity is projected to increase with climate change in Canada, but vegetation feedbacks are usually not considered. Using new information on the selectivity or avoidance of fire as a function of stand age and composition, we ran simple simulation models that consider the changes in the regional age matrices induced by fire and harvesting to project future burn rates. We also projected estimated future regional vulnerability of timber supply to fire by considering these new burn rates. The inclusion of age-related feedbacks would have a large impact on projected increases in burn rates, mostly in a very fire active zone under aggressive climate forcing. Projected burn rates would still increase, but would be 50% less in 2100 than if projected without this biotic feedback in some zones. Negative feedbacks would be virtually nonexistent when potential burning rates are below 1%, whereas realized burning rates would be lowered by more than a 0.5 percentage point when potential burning rates exceed 2.5%. Including fire–vegetation feedbacks had virtually no impact on total volume harvested. As fire burns more old-growth coniferous stands, slightly negative impacts were projected on conifer harvested almost everywhere. These results underline the need to incorporate fire–vegetation feedbacks when projecting future burn rates.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".