Spatial variation of trends in wildfire and summer drought in British Columbia, Canada, 1920–2000
Bibliographic record
Abstract
Owing to large climatic and orographic variation, British Columbia covers a variety of ecosystems extending from temperate rainforests on the Pacific coast to boreal forests in the north-east. The aim of this study is to investigate the spatial variation of trends in wildfire activity and their relationship to summer drought for the entire province of British Columbia. Time series of annual wildfire extent and occurrence, summer self-calibrating Palmer Drought Severity Index and summer Aridity Index were derived from spatially explicit data. Sixteen landscape regions according to the provincial Biogeoclimatic Ecosystem Classification system served as spatial reference. The regional series for 1920–2000 were subjected to trend analysis. Correlations between area burned and summer drought were assessed and tested for significance. The observed decrease in wildfire activity is significantly related to wetter summers with the strength of the relationship considerably varying between British Columbia’s landscapes. Our results suggest that aggregated statistics for large regions with complex topography and climate can hide the spatial variation in direction and strength of changes and may accordingly obscure the relationship between fire and drought. Based on high-spatial-resolution data, our study is the first to provide a differentiated picture for British Columbia.
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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 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".