Carbon Mineralizability Determines Interactive Effects on Mineralization of Pyrogenic Organic Matter and Soil Organic Carbon
Bibliographic record
Abstract
Soil organic carbon (SOC) is a critical and active pool in the global C cycle, and the addition of pyrogenic organic matter (PyOM) has been shown to change SOC cycling, increasing or decreasing mineralization rates (often referred to as priming). We adjusted the amount of easily mineralizable C in the soil, through 1-day and 6-month preincubations, and in PyOM made from maple wood at 350 °C, through extraction. We investigated the impact of these adjustments on C mineralization interactions, excluding pH and nutrient effects and minimizing physical effects. We found short-term increases (+20-30%) in SOC mineralization with PyOM additions in the soil preincubated for 6 months. Over the longer term, both the 6-month and 1-day preincubated soils experienced net ∼10% decreases in SOC mineralization with PyOM additions. Additionally, the duration of preincubation affected interactions, indicating that there may be no optimal preincubation time for SOC mineralization studies. We show conclusively that mineralizability of SOC in relation to PyOM-C is an important determinant of the effect of PyOM additions on SOC mineralization.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".