Vulnerability of timber supply to projected changes in fire regime in Canada’s managed forests
Bibliographic record
Abstract
The frequency of forest fires is predicted to increase in Canada, which may affect the availability of timber for industrial purposes. We therefore carried out an evaluation of the timber supply vulnerability to current and future fire risk through simplified calculations involving historical forest growth and harvest rates and current and projected forest burn rates. Calculations were performed at the level of forest management areas (FMAs) across the boreal and montane ecozones of Canada. For some FMAs, the vulnerability of timber supply to fire was estimated to be high to extreme by the middle of the century. For those FMAs, the increases in tree growth necessary to negate these risks were generally unrealistic. A modest simulated decrease in tree growth over time, however, was sufficient to raise the vulnerability of many other FMAs from low to moderate. Known biases in the analysis suggest that our assessment might underestimate the level of vulnerability in all FMAs. Other natural disturbances are not included in the analysis but their impact on timber supply may be additive to that of fire. Some adaptation measures to face these increasing risks are discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".