Projected changes in fire size from daily spread potential in Canada over the 21st century
Bibliographic record
Abstract
The broad consensus indicates that climate change will cause larger and more frequent fires, resulting in a growing annual area burned (AAB) in much of Canada. Our ability to predict future changes in fire size (FS) and AAB is limited due to the uncertainty embedded in climate change models and our inability to quantify the complex interactions between the changing environment and fire activity. In this study, we introduce a new method to predict future FS and AAB across Canada over the 21st century based on fire-conducive weather and how it translates to on-the-ground fire spread (i.e. spread days). We found that the potential for an extreme fire year (99th percentile of AAB) could quadruple by the end of the century across Canada, and ≥ 10 times more common in the boreal biome. Specifically, FS and AAB may increase 20%–64% and 25%–93%, respectively, and the average fire year under the extreme climate scenario may burn ∼11 Mha, which is ∼4 Mha higher than the most extreme fire year in Canada’s modern history (∼7 Mha). Our results demonstrate that by accounting for the strong nonlinear expansion of wildfires as a function of number of fire spread days, even conservative climate-change scenarios may yield significant increase in fire activity.
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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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".