Microbial transformation and mineral adsorption control chemical evolution of soil organic matter during semi-arid ecosystem development
Bibliographic record
Abstract
The chemical composition and diversity of soil organic matter influence soil organic carbon (SOC) persistence and climate responses, yet their evolution during soil development in drylands remains unclear. We characterized the chemical composition and diversity of bulk SOC and water-extractable organic matter (WEOM) across a 3-million-year-old semi-arid volcanic soil chronosequence, spanning a steep silt and clay concentration gradient. Soils were sampled from beneath pine or juniper tree canopies and inter-canopy spaces covered by grasses and/or shrubs. As soil developed, those beneath pine or juniper canopies became enriched in aromatic C due to a synergistic effect of intensified microbial decomposition of non-aromatic plant material and preferential adsorption of aromatics from WEOM onto minerals in the silt and clay fraction. Consequently, WEOM was depleted in aromatics with soil development. Both bulk SOC and WEOM also showed increasing proportions of microbial carbon, facilitated by higher silt and clay concentrations that mitigated water scarcity and provided suitable pore spaces for microbial proliferation. Inter-canopy soils showed minimal trends with soil development, ascribed to the higher litter quality than tree litter. The WEOM molecular α-diversity remained stable as the influences from microbial transformation and mineral adsorption counteracted each other. However, β-diversity, reflecting compositional dissimilarity of bulk SOC or WEOM across samples at each soil developmental stage, declined as soil developed. This chemical convergence resulted from dominant microbial and mineral interactions overriding vegetation and other influences. Our findings suggest the dual role of silt and clay in controlling SOM chemistry in dryland soils, enhancing accrual of both microbial C and the aromatic portion of the plant-derived C. These new insights can inform process-based models to better describe soil organic C dynamics and persistence in drylands.
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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) | 0.000 | 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".