Chemistry and Associations of Carbon in Water-Stable Soil Aggregates from a Long-Term Temperate Agroecosystem and Implications on Soil Carbon Stabilization
Bibliographic record
Abstract
This study aimed to understand the effects of long-term agricultural management on soil organic carbon (SOC) stabilization/storage in aggregates. Carbon near-edge X-ray absorption fine structure spectroscopy (C-NEXAFS), 13 C nuclear magnetic resonance ( 13 C NMR), and wet chemical analyses were employed to characterize SOC and organo-mineral associations. Soils were from a corn system (Kansas, USA; > 22 years), comparing till and no-till, with fertilizer treatments (manure/compost and chemical). Results showed high concentrations of SOC/amorphous Fe and enhanced SOC stabilization in manure/compost added soils. Various degrees of decomposition were evident by C-NEXAFS with aromatic (22%–40%) and carboxylic C (20%–45%) being abundant in all aggregates. Microaggregate-associated SOC showed more enhanced aromaticity than other aggregates. Some aggregates from tilled soils had increased aliphaticity in SOC than its counterpart no-till. Humic acid-associated OC (by 13 C NMR) showed enhanced aliphaticity with decreasing aggregate sizes. Our results showed that the SOC stabilization/storage occurs due to chemical, mineralogical, and biological mechanisms stimulated by management.
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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 | 0.001 | 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".