Simulation of Soil Carbon Dioxide Flux During Plant Residue Decomposition
Bibliographic record
Abstract
Based on information obtained from recent studies, we modified the CENTURY model to improve simulation of short‐term soil respiration, especially in soils with surface‐applied crop residues. This involved adding N availability as a factor controlling the decomposition rate. Translocation by filamentous fungi was assumed to be the mechanism supplying mineral N to residues decomposing on the soil surface. When available N is nonlimiting, the N availability factor is 1, otherwise decomposition rates of all pools of soil surface and belowground organic matter are reduced proportionately until N supply meets demand. The modified model was evaluated using CO 2 flux data from a laboratory experiment which included different wheat ( Triticum aestivum L.) straw types (fresh and weathered straw), straw placements (incorporated and surface‐applied) and soil water regimes (continuously moist and alternating moist‐dry conditions). In general, CENTURY successfully simulated daily CO 2 fluxes in these treatments, except for an underestimation in the first day after watering and an overestimation immediately after rewetting dry soil in the moist‐dry water regime. For treatments with surface‐applied straw, CENTURY overestimated soil respiration, while the modified version gave substantially better simulations. The correlation between measured and simulated total (in 77 d) respiration was improved by model modification. CENTURY underestimated the soil mineral N remaining in the soil at the end of the experiment. The modified model gave improved mineral N simulations for the surface straw treatments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".