Spatiotemporal impacts of wildfire and climate warming on permafrost across a subarctic region, Canada
Bibliographic record
Abstract
Abstract Field observations show significant impacts of wildfires on active layer thickness and ground temperatures. However, the importance of fires to permafrost conditions at regional scales remains unclear, especially with climate warming. This study evaluated the regional impacts of fire on permafrost with climate change from 1942 to 2100 using a process‐based model in a large subarctic region in the Northwest Territories, Canada. Climate warming is shown to be the dominant factor for permafrost reduction. The warming trend of climate reduces permafrost extent in this region from 67% at present to 2% by 2100. For burned areas, fire increases the reduction of permafrost extent by up to 9% on average, with up to 16% for forest, 10% for tundra and bogs, and 4% for fens. Fire accelerates permafrost disappearance by 5 years on average. The effects of fire on active layer thickness and permafrost extent are much larger in forest areas than in tundra, bogs, and fens. Since active layer is thicker after a fire and cannot recover in most of the areas, the fire effects on active layer are widespread. On average, fires thickens active layer by about 0.5 m. The fire effects on active layer increased significantly after 1990 due to climate warming.
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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 | 0.000 |
| 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 | 0.001 | 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".