Using DSSAT-CENTURY Model to Simulate Soil Organic Carbon Dynamics Under a Low-Input Maize Cropping System
Bibliographic record
Abstract
Decline in Soil Organic Carbon (SOC) below the critical levels is one of the major indicators of soil fertility depletion in Sub-Saharan Africa (SSA), with the main causes being poor management practices coupled with low input use. Measures for monitoring long-term impacts of management on SOC dynamics and its restoration can be critical in enhancing sustainable soil productivity. Crop models have proved to be good tools for understanding the influence of management options on soil and crop productivity. The DSSAT-Century model was applied to simulate the influence of management practices on SOC dynamics. Using long-term datasets from Kabete, Kenya (1976-1996 maize-bean) and Kiboga-Uganda (1980-2010 maize), model calibration and evaluation showed a good fit between simulated and observed values of SOC. On simulating continuous tillage with no fertilization for the 1980-2010 antecedent period and 2010-2060 extrapolated period, the model showed high rates of SOC decline in the newly cultivated soil as compared to a degraded soil. The simulated rate of decline is 2129 kg ha-1 yr-1 for newly cultivated soil and 849 kg ha-1 yr-1 for the continuously cultivated soils. The model was sensitive to initial partitioning of SOC pools, with SOC in previously uncultivated soils declining at a higher rate than that in the cultivated ones. The model confirmed that use of continuous tillage is a major threat to SOC building and soil fertility restoration in the tropics. Adopting conservation agriculture is critical for future generations. Overall, the DSSAT CENTURY model is a potential tool for predicting SOC dynamics in low-input farming systems.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".