Lightning ignition efficiency in Canadian forests
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Background: Lightning-caused fires have a driving influence on Canadian forests, being responsible for approximately half of all wildfires and 90% of the area burned. We created a climatology (2000-2020) of daily lightning efficiency (i.e., the ratio of cloud-to-ground lightning flashes to lightning-caused wildfires that occurred) over the meteorological summer for four ecozones and a subset of British Columbia (BC) ecoprovinces. We estimated lightning efficiency using data from the Canadian Lightning Detection Network and the Canadian National Fire Database. We used the ERA5 reanalysis as inputs for fuel moisture variables (i.e., Fine Fuel Moisture Code (FFMC), Duff Moisture Code (DMC), and Drought Code (DC)) from the Canadian Forest Fire Weather Index (FWI) System, as well as variables relating to the amount of precipitation and lightning flashes. We examined relationships between lightning efficiency, day-of-year, and the above variables using a combination of linear models, Spearman's correlations, and Random Forest (RF) regression. Results: Lightning efficiency increased non-linearly (i.e., quadratic) over the summer in the Montane Cordillera Ecozone, and decreased linearly in the Boreal Plains and Boreal Shield West. Lightning efficiency in the Boreal Shield East showed a slight decline over the summer; however, this model was not significant. DMC and DC were more strongly correlated with lightning efficiency than FFMC in most zones. We ran RF regression both with and without DC (because of multicollinearity with day-of-year), and day-of-year, DMC, and DC (when present) were the most important variables for all ecozones, while results were more variable for the ecoprovinces. Conclusions: Lightning efficiency, and, thus, the probability of a lightning strike igniting a wildfire, changes over the summer and varies by region. Therefore, models predicting lightning-caused fire occurrence, or other similar applications involving lightning ignition, may benefit by accounting for seasonal lightning efficiency in addition to the traditional fuel moisture variables. Our work is generally consistent with findings from more localized studies relating to lightning-caused fires. Supplementary Information: The online version contains supplementary material available at 10.1186/s42408-025-00376-1.
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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) | 0.001 | 0.001 |
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 it