Fire as a Removal Mechanism of Pyrogenic Carbon From the Environment: Effects of Fire and Pyrogenic Carbon Characteristics
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
Pyrogenic carbon (PyC, charcoal) is produced during vegetation fires at a rate of ~ 116–385 Tg C yr-1 globally. It represents one of the most degradation-resistant organic carbon pools, but its long-term fate and the processes leading to its degradation remain subject of debate. A frequently highlighted potential loss mechanism of PyC is the consumption of PyC in subsequent fires, however, only three studies to date have tested this hypothesis with reported losses of 300C. Mass losses also showed a significant negative correlation (r=-0.38, p=0.05) with thermal recalcitrance (T50) determined using Differential Scanning Calorimetry (DSC) and Tmax with charcoal reflectance (Ro) determined after the fires (r=0.46, p=0.05). Losses in the high-intensity fire were significantly higher (p=0.05) than in the low-intensity fire, but the latter had a higher rate of conversion of fuel to PyC. Our results demonstrate that exposure to fire can indeed be a significant removal mechanism for PyC that remains exposed on the ground fires. The losses found, however, are likely to represent an extreme upper range as most PyC produced in a fire would not remain exposed on the ground surface by the time the next fire occurs. Our data also demonstrate, for real wildfire conditions, the (i) contrasting resistance of different PyC types to combustion and (ii) contrasting net PyC losses between different fire intensities. The DSC and reflectance results support the usefulness of these analyses in reflecting thermal degradation resistance and temperature exposure under actual
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it