Relationships between charcoal property and post fire productivity in the boreal forest
Bibliographic record
Abstract
Fire disturbances are increasing under global climate change and ecological transformations of forests are occurring. Specifically, shifts from productive closed-canopy feather moss forests to low-productivity open-canopy lichen ( Cladonia spp.) woodlands have been observed in boreal forests of eastern Canada. It has been hypothesized that high severity of fires would be the cause of this change, but this is difficult to validate a posteriori on mature forest stands. Because charcoal properties are affected by fire severity, we have put forward the hypothesis that the amount and physicochemical properties of charcoal (C, N, H, O, ash, surface area) would be different and indicative of a greater fire severity for open-canopy forests compared to closed canopy ones. Our hypothesis was partly validated in that the amount of charcoal found on the ground of closed-canopy forests was greater than that of open-canopy forests. However, the physicochemical properties were not different, albeit a greater variability of charcoal properties for open canopy stands. These results do not allow us to fully validate or reject our hypothesis on the role of fire severity in the shift between open and closed canopy stands. However, they suggest that the variability in fire conditions as well as the amounts of charcoal produced are different between the two ecosystem types. Furthermore, considering the role that biochar may play in improving soil conditions and promoting vegetation restoration, our results suggest that charcoal may play a role in maintaining these two stable alternative ecosystem states.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".