Spatiotemporal analysis of black spruce forest soils and implications for the fate of C
Bibliographic record
Abstract
Post‐fire storage of carbon (C) in organic‐soil horizons was measured in one Canadian and three Alaskan chronosequences in black spruce forests, together spanning stand ages of nearly 200 yrs. We used a simple mass balance model to derive estimates of inputs, losses, and accumulation rates of C on timescales of years to centuries. The model performed well for the surface and total organic soil layers and presented questions for resolving the dynamics of deeper organic soils. C accumulation in all study areas is on the order of 20–40 gC/m2/yr for stand ages up to ∼200 yrs. Much larger fluxes, both positive and negative, are detected using incremental changes in soil C stocks and by other studies using eddy covariance methods for CO2. This difference suggests that over the course of stand replacement, about 80% of all net primary production (NPP) is returned to the atmosphere within a fire cycle, while about 20% of NPP enters the organic soil layers and becomes available for stabilization or loss via decomposition, leaching, or combustion. Shifts toward more frequent and more severe burning and degradation of deep organic horizons would likely result in an acceleration of the carbon cycle, with greater CO2 emissions from these systems overall.
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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 | 0.000 |
| 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 | 0.000 |
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".