Relationship between fire, climate oscillations, and drought in British Columbia, Canada, 1920–2000
Bibliographic record
Abstract
Abstract Climate oscillations such as El Niño–Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) are known to affect temperature and precipitation regimes and fire in different regions of the world. Understanding the relationships between climate oscillations, drought, and area burned in the past is required for anticipating potential impacts of regional climate change and for effective wildfire‐hazard management. These relationships have been investigated for British Columbia (BC), Canada, either as part of national studies with coarse spatial resolution or for single ecosystems. Because of BC's complex terrain and strong climatic gradients, an investigation with higher spatial resolution may allow for a spatially complete but differentiated picture. In this study, we analyzed the annual proportion burned–climate oscillation–drought relationships for the province's 16 Biogeoclimatic Ecosystem Classification (BEC) zones. Analyses are based on a digital, spatially explicit fire database, climate oscillation indices, and monthly precipitation and temperature data with a spatial resolution of 400 m for the period 1920–2000. Results show that (1) fire variability is better related to summer drought than to climate oscillations, and that (2) fire variability is most strongly related to both, climate oscillations and summer drought in southeastern BC. The relationship of area burned and summer drought is strong for lower elevations in western BC as well. The influence of climate oscillations on drought is strongest and most extensive in winter and spring, with higher indices being related to drier conditions. Winter and spring PDO and additive winter and spring PDO+ENSO indices show BC's most extensive significant relationship to fire variability. Western BC is too wet to show a moisture deficit in summer that would increase annual area burned due to teleconnections.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".