Seasonality and trends in human- and lightning-caused wildfires ≥ 2 ha in Canada, 1959–2018
Bibliographic record
Abstract
We examined the seasonal distribution of lightning- and human-caused wildfires ≥ 2 ha in Canada for two time periods: 1959–2018 and 1981–2018. Furthermore, we investigated trends in seasonality, number of fires per year and number of days with fire starts per year for human- and lightning-caused fires. Nationally, lightning fires peaked from June to August, whereas human fires peaked during May. There was, however, notable variation in the seasonal distributions of human- and lightning-caused fires between ecozones. Likewise, trends in season start and end dates varied among ecozones and time series, with trends generally being stronger for human-caused fires. Trends in the number of fires from 1959 to 2018 suggested significant increases in the number of lightning-caused fires and days with lightning ignitions across almost all ecozones, while from 1981 to 2018 there was a significantly decreasing trend in the number of human-caused fires and days with human ignitions in almost all ecozones. The highest densities of human-caused fires occurred in the Montane Cordillera and Atlantic Maritime, while the highest density of lightning-caused fires occurred in the Boreal Shield West. The Montane Cordillera and Taiga Shield West showed significant increases in the number of lightning fires and days with lightning ignitions across both time series.
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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".