Temperature Dependence of Organic Matter Solubility: Influence of Biodegradation during Soil‐Water Extraction
Bibliographic record
Abstract
Water‐extractable organic matter has been shown to increase as temperature increases (from 20 to 80°C), with the rate of increase being soil dependent. We examined whether biodegradation during overnight soil‐water extraction may influence the temperature response of extractable C and N. Dissolved organic N (DON) and C (DOC), and NH 4 –N were determined after 16 h of soil‐water extraction at either 80 or 50°C (previous work in our laboratory suggested that biodegradation in soil‐water suspensions peaks at ∼50°C). For both DOC and DON, there were large differences among soils in their temperature responses (e.g., the increase in DON between 50 and 80°C ranged from 29 to 148 mg kg −1 ). More NH 4 –N was generated at 50 than at 80°C. Ammonium N produced at 50°C was largely attributable to mineralization (it was almost eliminated when microbial activity was suppressed by extracting with 2 mol L −1 KCl at 50°C). The small amounts of NH 4 –N found at 80°C were probably of abiotic origin (e.g., thermal degradation of soil organic N). Our results suggested that dissolved organic matter (DOM) was mineralized during the 50°C extraction. The release of DOM was thus underestimated at 50°C and, as a consequence, the temperature response of DOM between 50 and 80°C was overestimated (mineralization at 50°C accounted for most of the variability in the temperature response of DOM). We conclude that the temperature response of DOM can be affected by biodegradation during extraction and that an extraction at 80°C has the important merit that biodegradation during extraction should be negligible.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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 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".