The Composition and Stability of Clay-Associated Organic Matter along a Soil Profile
Bibliographic record
Abstract
Organic carbon in subsoil generally has longer turnover times than that in surface soil, but little is known about how the stability of the specific organic compound classes changes with soil depth. The objective of this study was to analyze the composition and thermal stability of clay-associated organic matter (OM) at varying soil depths in the summit and footslope of a pasture hillslope using C X-ray absorption near edge structure (XANES) and pyrolysis-field ionization mass spectrometry (Py-FIMS). C XANES showed aromatic C was relatively enriched in the subsoil, relative to the surface soil. Py-FIMS demonstrated a relative enrichment of phenols/lignin monomers and alkylaromatics with increasing profile depth in the summit soil, and to a greater extent in the footslope soil, followed by a decreasing abundance of sterols. In surface soil, the thermostability of clay-associated OM increases in the order: carbohydrates and N compounds < phenols/lignin monomers < lignin dimers and alkylaromatics, suggesting the intrinsic chemical nature of OM as a major driver for OM persistent in surface soil. The thermal stability of clay-associated carbohydrates, N compounds, and phenols/lignin monomers increased with profile depth, likely due to stronger organic-organic/organic-mineral binding. In subsoil, the thermal stability of clay-associated carbohydrates and N compounds can be as high as that of alkylaromatic and lignin dimers, implying that persistent subsoil OM could be composed of organic compound classes, like carbohydrates, that were traditionally considered as biochemically labile compounds. In contrast, the thermally-stable compound classes, like lignin dimers and alkylaromatics, showed no changes in the thermal stability with soil depth. This study suggests that stability of the more labile OM compounds may be more strongly influenced by the change in environmental conditions, relative to the more stable forms.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".