Spatial and temporal dynamics of the soil charcoal pool in relation to fire history in a boreal forest landscape
Bibliographic record
Abstract
Charcoal pools in boreal forest soils constitute considerable amounts of slow cycling organic matter that is important in the global carbon cycle. However, these pools are characterized by spatiotemporal variations that are not well understood. Here, we have analyzed the charcoal pool in 100 soil samples to determine charcoal stock species origin and how the size and age of this pool varies across different spatial scales in a Norwegian boreal forest landscape including forests that differ in terms of tree-species composition, tree density, and recent fire histories. The size of the charcoal pool was site-specific and highly variable, ranging from 0 to 2108 g·m–2. Geostatistical analyses showed that the charcoal pool was only weakly spatially structured at fine spatial scales (metres) and broader between-site scales (100s of metres). Unexpectedly, there was no significant relationship between the amount of charcoal and contemporary forest composition and density, although there was proportionally more charcoal from broadleaved trees in today’s Scots pine forests than in the Norway spruce forests. When relating this information to the fire history, the results indicate that charcoal is lost at a millennial time scale.
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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 | 0.000 | 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) | 0.000 | 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 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".