Historical burn area in western Canadian peatlands and its relationship to fire weather indices
Bibliographic record
Abstract
Peatlands store the majority of soil carbon in many northern regions, yet their vulnerability to fire remains poorly understood. We used large‐scale mapping of fire and peatland distributions to explore patterns of burning at two spatial scales. On a landscape scale in central Alberta, we used spatially explicit distributions of peatlands and 50 years of fire perimeter maps to determine whether uplands burn more preferentially than peatlands. Burn area and ignition localities in central Alberta did not occur preferentially in uplands relative to bogs and fens. Extrapolating this result at a regional scale, we used the Peatlands of Canada database and 20 years of historical fire records to estimate annual burn areas for Alberta, British Columbia, Northwest Territories, and Saskatchewan peatlands. Peatland burn areas varied tremendously over time, with high fire activity in the early 1980s and mid‐1990s. On average, fires impacted 1850 km 2 of peatland annually across this region of western Canada. Positive relationships between the area of peatland burned and weather variables calculated for each fire event using the Canadian Fire Weather Index, including maximum air temperatures and the duff moisture code, suggest that drier and/or warmer conditions likely would increase the burning of peatlands in western Canada.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".