Direct carbon emissions from Canadian forest fires, 1959-1999
Bibliographic record
Abstract
Direct emissions of carbon from Canadian forest fires were estimated for all Canada and for each ecozone for the period 19591999. The estimates were based on a data base of large fires for the country and calculations of fuel consumption for each fire using the Canadian Forest Fire Behaviour Prediction System. This technique used the fire locations and start dates to estimate prevailing fire weather and fuel type for each of about 11 000 fires. An average of 2 × 106 ha·year1 was burned in this period, varying from 0.3 × 106 ha in 1978 to 7.5 × 106 ha in 1989. Ecozones of the boreal and taiga areas experienced the greatest area burned, releasing most of the carbon (C). The mean area-weighted fuel consumption for all fires was 2.6 kg dry fuel·m2 (1.3 kg C·m2), but ecozones vary from 1.8 to 3.9 kg dry fuel·m2. The mean annual estimate of direct carbon emissions was 27 ± 6 Tg C·year1. Individual years ranged from 3 to 115 Tg C·year1. These direct fire emissions represent about 18% of the current carbon dioxide emissions from the Canadian energy sector, on average, but vary from 2 to 75% among years. Post-fire effects cause an additional loss of carbon and changes to the forest sink condition.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| 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".