Mineral–organic associations are enriched in both microbial metabolites and plant residues in a subtropical soil profile under no-tillage and legume cover cropping
Why this work is in the frame
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Bibliographic record
Abstract
Context Knowledge of the impacts of no-tillage and cover cropping on carbon accumulation and stabilisation in highly weathered agricultural soils of subtropical regions is scant. We hypothesised that implementation of no-tillage coupled with high-quality legume residues in highly weathered agricultural soils would result in high carbon accumulation rates, mainly as microbe- and plant-derived materials in fine mineral–organic complexes. Aims and methods We sampled soil profiles down to 100 cm in a long-term field experiment and used density and particle size fractionation in combination with carbohydrate analyses to compare the effect of conventional tillage vs no-tillage, combined or not with legume cover cropping, and combined or not with mineral nitrogen fertilisation. Key results Both no-tillage and legume cover crops favoured the accumulation and enrichment in plant-derived carbohydrates in the surface soil layer, due to the accumulation of plant residues. The ratio of microbe- to plant-derived carbohydrates increased with soil depth indicating that the soil carbon (C) was more microbially processed than at the surface. Conservation management systems also increased soil C at depth and this was most visible in the clay fraction. The additional clay-size C accumulating at depth under conservation treatments was of both microbial and plant origin. Conclusions Our results support the hypothesis that mineral-associated C is composed of both plant and microbial residues and is positively influenced by conservation management practices. Implications Our results demonstrate that no-till and legume cover cropping are efficient practises to foster C accumulation and stabilisation in heavily weathered agricultural soil profiles in a subtropical climate.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it