Abrupt, climate-induced increase in wildfires in British Columbia since the mid-2000s
Bibliographic record
Abstract
Abstract In the province of British Columbia, Canada, four of the most severe wildfire seasons of the last century occurred in the past 7 years: 2017, 2018, 2021, and 2023. To investigate trends in wildfire activity and fire-conducive climate, we conducted an analysis of mapped wildfire perimeters and annual climate data for the period of 1919–2021. Results show that after a century-long decline, fire activity increased from 2005 onwards, coinciding with a sharp reversal in the wetting trend of the 20th century. Even as precipitation levels remain high, moisture deficits have increased due to rapid warming and increased evaporative demand. Bottom-up factors further influence fire activity, as the legacy of past wildfires, insect outbreaks, and land-use practices continually influence fire regimes. The compound effects of climate-induced moisture changes and altered fuels now force British Columbians to confront the harsh reality of more frequent years of intense and prolonged wildfire activity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".