Temperature responses of individual soil organic matter components
Bibliographic record
Abstract
Temperature responses of soil organic matter (SOM) remain unclear partly due to its chemical and compositional heterogeneity. In this study, the decomposition of SOM from two grassland soils was investigated in a 1‐year laboratory incubation at six different temperatures. SOM was separated into solvent extractable compounds, suberin‐ and cutin‐derived compounds, and lignin‐derived monomers by solvent extraction, base hydrolysis, and CuO oxidation, respectively. These SOM components have distinct chemical structures and stabilities and their decomposition patterns over the course of the experiment were fitted with a two‐pool exponential decay model. The stability of SOM components was also assessed using geochemical parameters and kinetic parameters derived from model fitting. Compared with the solvent extractable compounds, a low percentage of lignin monomers partitioned into the labile SOM pool. Suberin‐ and cutin‐derived compounds were poorly fitted by the decay model, and their recalcitrance was shown by the geochemical degradation parameter ( ω − C 16 /∑C 16 ), which was observed to stabilize during the incubation. The temperature sensitivity of decomposition, expressed as Q 10 , was derived from the relationship between temperature and SOM decay rates. SOM components exhibited varying temperature responses and the decomposition of lignin monomers exhibited higher Q 10 values than the decomposition of solvent extractable compounds. Our study shows that Q 10 values derived from soil respiration measurements may not be reliable indicators of temperature responses of individual SOM components.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".