Forest floor fuel consumption and carbon emissions in Canadian boreal forest fires
Bibliographic record
Abstract
In many forest types, over half of the total stand biomass is located in the forest floor. Carbon emissions during wildland fire are directly related to biomass (fuel) consumption. Consumption of forest floor fuel varies widely and is the greatest source of uncertainty in estimating total carbon emissions during fire. We used experimental burn data (59 burns, four fuel types) and wildfire data (69 plots, four fuel types) to develop a model of forest floor fuel consumption and carbon emissions in nonpeatland standing-timber fuel types. The experimental burn and wildfire data sets were analyzed separately and combined by regression to provide fuel consumption models. Model variables differed among fuel types, but preburn fuel load, duff depth, bulk density, and Canadian Forest Fire Weather Index System components at the time of burning were common significant variables. The regression R 2 values ranged from 0.206 to 0.980 (P < 0.001). The log–log model for all data combined explained 79.5% of the regression variation and is now being used to estimate annual carbon emissions from wildland fire. Forest floor carbon content at the wildfires ranged from 40.9% to 53.9%, and the carbon emission rate ranged from 0.29 to 2.43 kg·m –2 .
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".