Assessing the potential of wildfires as a sustainable bioenergy opportunity
Bibliographic record
Abstract
Abstract As the environmental and economic consequences of fossil‐fuel use become clear, land is increasingly targeted as a source of bioenergy. We explore the potential for generating electricity from biomass vulnerable to fires as an ecologic and socioeconomic opportunity that can reduce the risk of greenhouse gas generation from wildfires and help to create incentives to preserve natural and seminatural vegetation and prevent its conversion to agriculture, including biofuel crops. On the basis of a global analysis of the energy generation and spatial distribution of fires, we show that between 2003 and 2010, global fires consumed ~8300 ± 592 PJ yr−1 of energy, equivalent to ~36–44% of the global electricity consumption in 2008 and >100% national consumption in 57 countries. Forests/woodlands, cultivated areas, shrublands, and grasslands contributed 53%, 19%, 16%, and 3.5% of the global energy released by fires. Although many agroecological, socioeconomic, and engineering challenges need to be overcome before diverting the energy lost in fires into more useable forms, done cautiously it could reconcile habitat preservation with economic yields in natural systems.
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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 | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".