Crop rotational diversity alters the composition of stabilized soil organic matter compounds in soil physical fractions
Bibliographic record
Abstract
Crop rotational diversity is an important part of sustainable agricultural and soil management to improve crop yield and soil fertility including enhancing soil organic matter (SOM) stabilization. Because of the physical protection via interactions with soil minerals, SOM in mineral-associated fractions is believed to be longer-lived and more stable relative to SOM in particulate (light) fractions. However, it is still unclear how crop rotational diversity alters soil carbon distribution, composition and stabilization in soil physical fractions. To address this, we studied a 37 years’ agricultural site with different crop rotational diversity (from continuous corn or alfalfa up to four species (corn, soybean, winter wheat, and red clover)). Soil carbon analysis, targeted compound analysis and nuclear magnetic resonance spectroscopy methods were used to obtain the distribution and degradation of SOM components in light and mineral-associated (F53–2000 µm, F2–53 µm, and F<2 µm) fractions. Higher soil organic carbon (SOC) concentrations were observed in F<2 µm with relatively high diversified crop rotations (three and four types of crops) compared to monoculture or two crops in the rotations, which suggests that carbon storage is enhanced in mineral-stabilized pools. Higher concentrations of long-chain aliphatic compounds as well as increased accumulation and preservation of lignin-derived compounds in fine aggregates (<53 µm) were also observed with relatively high diversified crop rotations. Overall, the increased concentration and preservation of specific SOM compounds as well as increased SOC in finer mineral-associated fractions (<53 µm) suggests that crop rotational diversity may enhance the long-term stability of SOM in agroecosystems.
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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) | 0.001 | 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".