Organo-Mineral Interactions Are More Important for Organic Matter Retention in Subsoil Than Topsoil
Bibliographic record
Abstract
Decomposing crop residues contribute to soil organic matter (SOM) accrual; however, the factors driving the fate of carbon (C) and nitrogen (N) in soil fractions are still largely unknown, especially the influence of soil mineralogy and autochthonous organic matter concentration. The objectives of this work were (1) to evaluate the retention of C and N from crop residue in the form of occluded and mineral-associated SOM in topsoil (0–20 cm) and subsoil (30–70 cm) previously incubated for 51 days with 13C-15N-labelled corn residues, and (2) to explore if specific minerals preferentially control the retention of residue-derived C and N in topsoil and subsoil. We used topsoil and subsoil having similar texture and mineralogy as proxies for soils being rich (i.e., topsoil) and poor (i.e., subsoil) in autochthonous organic matter. We performed a sequential density fractionation procedure and measured residue-derived C and N in occluded and mineral-associated SOM fractions, and used X-ray diffraction analysis of soil density fractions to investigate their mineralogy. In accordance with our hypothesis, the retention of C and N from crop residue through organo-mineral interactions was greater in subsoil than topsoil. The same minerals were involved in the retention of residue-derived organic matter in topsoil and subsoil, but the residue-derived organic matter was associated with a denser fraction in the subsoil (i.e., 2.5–2.6 g cm−3) than in the topsoil (i.e., 2.3–2.5 g cm−3). In soils and soil horizons with high clay content and reactive minerals, we find that a low SOM concentration leads to the rapid stabilization of C and N from newly added crop residues.
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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 | 0.001 | 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".