Bibliographic record
Abstract
Wildfire is the primary disturbance mechanism in much of the boreal forest, initiating succession and influencing ecosystem processes. While most organic matter is consumed, a small amount is converted to charcoal. Fire derived charcoal is highly resistant to mineralization, acting as a recalcitrant C pool, as well as contributing to ecosystem function through nutrient retention and nitrification. In this study we examined the charcoal content of soils across a 14–208‐year post‐fire chronosequence in the southern boreal forest of North America, and compared wildfire derived charcoal to laboratory produced charcoal. Charcoal stocks averaged 4.09 Mg ha −1 representing 2.19 Mg C ha −1 ; 8–10% of soil C in typical boreal soils. NMR results showed charcoal to be primarily aryl C with smaller amounts of alkyl‐C, O‐alkyl, and methoxyl groups. Charcoal stocks changed substantially over time with C content declining from 56% to 46% and a loss of more labile C groups. Charcoal from stands greater than 140 years old was almost entirely aryl C. Laboratory produced charcoal between 300 and 350°C was found to have comparable properties to wildfire charcoal. Charcoal C stocks in our study are 2–3 times greater than those reported for Eurasian boreal ecosystems, where non‐stand replacing fire is the predominant disturbance; suggesting global estimates of boreal charcoal C stocks may need to be revised upwards to account for greater wildfire intensity in North American boreal forests. Boreal charcoal stocks in this study were found to represent an important long‐term soil C stock, large enough to affect soil processes. Changes in C content and chemical composition, however, occur over time, especially in the first ∼100 years. In the absence of fire, management of boreal charcoal stocks may be required to maintain ecosystem function and C balance.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.002 |
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".