Long-term decreasing trend in forest fires in northwestern Canada
Bibliographic record
Abstract
The annual area of forest burned has decreased in recent centuries over large areas of Fennoscandia, Siberia and temperate North America.To determine if this same trend extends to a sparsely populated region of northern Canada, fire scars on living and dead trees, forest stand ages and charred wood were systematically sampled in 85 study plots in an area of 564 000 km 2 in northwestern Canada.A significant negative trend in the occurrence of forest fires was observed: average area burned per year decreased from 2.0% in the first half of the 19th century to 0.33% in the later half of the 20th century.Annually burned areas correlated significantly with a local tree ring based index, July monthly drought code and the Pacific decadal oscillation but not with June-August mean temperature, distance to the nearest road, or the year of road building.None of the climatic indicators or access history (indicative of the start of local fire suppression) could explain the long-term negative trend in fires.Earlier interpretations that humans dominated the causes of forest fires in the past, even in sparsely populated regions, deserve further attention as a possible explanation for the decreasing trend in fires.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".