Spatial optimization of cropping systems for sustainable intensification in Malawi
Malawi’s agricultural landscape remains heavily dominated by continuous maize cultivation, a system that is increasingly vulnerable to climate variability, soil nutrient depletion, and economic risk. Despite the importance of diversification for sustainable intensification, there is currently no spa...
| Autores principales: | , , , , , |
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| Formato: | Resumen |
| Lenguaje: | Inglés |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/179820 |
| _version_ | 1855537503437586432 |
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| author | Liben, Feyera Kihara, Job Mesfin, Tewodros Abera, Wuletawu Mkuhlani, Siyabusa Tamene, Lulseged |
| author_browse | Abera, Wuletawu Kihara, Job Liben, Feyera Mesfin, Tewodros Mkuhlani, Siyabusa Tamene, Lulseged |
| author_facet | Liben, Feyera Kihara, Job Mesfin, Tewodros Abera, Wuletawu Mkuhlani, Siyabusa Tamene, Lulseged |
| author_sort | Liben, Feyera |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Malawi’s agricultural landscape remains heavily dominated by continuous maize cultivation, a system that is increasingly vulnerable to climate variability, soil nutrient depletion, and economic risk. Despite the importance of diversification for sustainable intensification, there is currently no spatially optimized cropping system design at fine resolution to guide national policy and farm-level decision-making. Furthermore, long-term, plot-based experimental evidence on multi-decadal cropping system performance is extremely limited due to the high cost and time requirements of continuous field research. As a result, critical knowledge gaps persist regarding the long-term productivity, stability, and resilience of alternative cropping systems under Malawi’s variable climate conditions. To address this gap, this study assessed the long-term performance of five major rainfed cropping systems in Malawi using APSIM NextGen simulations spanning 30 years (1994–2024) at 10-km spatial resolution. The systems evaluated were continuous maize, continuous groundnut, continuous soybean, maize–groundnut rotation, and maize–soybean rotation. Analyses focused on spatial yield patterns, temporal trends, interannual variability (risk indicator), stability index (resilience, consistency, and reliability indicator), yield anomalies (shock response indicator), and rotation advantage. Mean simulated maize yields under monocropping ranged from 5.8 to 7.9 Mg ha⁻¹ nationally but exhibited strong spatial heterogeneity and substantial interannual variability, with coefficients of variation frequently exceeding 20% in many areas, alongside a declining national trend of −120 kg ha⁻¹ decade⁻¹. Soybean and groundnut monocrops achieved mean yields of approximately 1.5–3.3 Mg ha⁻¹ and 1.7–3.1 Mg ha⁻¹, respectively, with relatively low spatial variability (<14% for soybean monocrop and <10% for groundnut monocrop for most grids) and better stability with low negative long-term trends. In contrast, maize–legume rotations substantially improved system performance when evaluated using maize equivalent yield (MEY). Maize–groundnut rotations achieved MEY values of approximately 5.5–8.8 Mg ha⁻¹, while maize–soybean rotations ranged from about 5.8 to 8.6 Mg ha⁻¹, consistently outperforming continuous maize across most locations. Rotational systems reduced yield variability, narrowed interannual risk distributions, and generated widespread rotation advantages, with mean values exceeding 1.0 across grid cells. Nevertheless, all cropping systems exhibited negative long-term yield trends, indicating increasing climate pressure over time. The results demonstrate that while maize–legume diversification substantially enhances productivity, stability, and resilience relative to maize monocropping, it does not fully offset long-term climate-driven yield declines. Sustaining and scaling these gains will require complementary investments in soil health restoration, improved legume performance, and spatially targeted, climate-responsive management strategies. |
| format | Abstract |
| id | CGSpace179820 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2025 |
| publishDateRange | 2025 |
| publishDateSort | 2025 |
| record_format | dspace |
| spelling | CGSpace1798202026-01-15T02:17:15Z Spatial optimization of cropping systems for sustainable intensification in Malawi Liben, Feyera Kihara, Job Mesfin, Tewodros Abera, Wuletawu Mkuhlani, Siyabusa Tamene, Lulseged cropping systems modelling Malawi’s agricultural landscape remains heavily dominated by continuous maize cultivation, a system that is increasingly vulnerable to climate variability, soil nutrient depletion, and economic risk. Despite the importance of diversification for sustainable intensification, there is currently no spatially optimized cropping system design at fine resolution to guide national policy and farm-level decision-making. Furthermore, long-term, plot-based experimental evidence on multi-decadal cropping system performance is extremely limited due to the high cost and time requirements of continuous field research. As a result, critical knowledge gaps persist regarding the long-term productivity, stability, and resilience of alternative cropping systems under Malawi’s variable climate conditions. To address this gap, this study assessed the long-term performance of five major rainfed cropping systems in Malawi using APSIM NextGen simulations spanning 30 years (1994–2024) at 10-km spatial resolution. The systems evaluated were continuous maize, continuous groundnut, continuous soybean, maize–groundnut rotation, and maize–soybean rotation. Analyses focused on spatial yield patterns, temporal trends, interannual variability (risk indicator), stability index (resilience, consistency, and reliability indicator), yield anomalies (shock response indicator), and rotation advantage. Mean simulated maize yields under monocropping ranged from 5.8 to 7.9 Mg ha⁻¹ nationally but exhibited strong spatial heterogeneity and substantial interannual variability, with coefficients of variation frequently exceeding 20% in many areas, alongside a declining national trend of −120 kg ha⁻¹ decade⁻¹. Soybean and groundnut monocrops achieved mean yields of approximately 1.5–3.3 Mg ha⁻¹ and 1.7–3.1 Mg ha⁻¹, respectively, with relatively low spatial variability (<14% for soybean monocrop and <10% for groundnut monocrop for most grids) and better stability with low negative long-term trends. In contrast, maize–legume rotations substantially improved system performance when evaluated using maize equivalent yield (MEY). Maize–groundnut rotations achieved MEY values of approximately 5.5–8.8 Mg ha⁻¹, while maize–soybean rotations ranged from about 5.8 to 8.6 Mg ha⁻¹, consistently outperforming continuous maize across most locations. Rotational systems reduced yield variability, narrowed interannual risk distributions, and generated widespread rotation advantages, with mean values exceeding 1.0 across grid cells. Nevertheless, all cropping systems exhibited negative long-term yield trends, indicating increasing climate pressure over time. The results demonstrate that while maize–legume diversification substantially enhances productivity, stability, and resilience relative to maize monocropping, it does not fully offset long-term climate-driven yield declines. Sustaining and scaling these gains will require complementary investments in soil health restoration, improved legume performance, and spatially targeted, climate-responsive management strategies. 2025-12-31 2026-01-14T12:31:25Z 2026-01-14T12:31:25Z Abstract https://hdl.handle.net/10568/179820 en Open Access application/pdf Liben, F.; Kihara, J.; Mesfin, T.; Abera, W.; Mkuhlani, S.; Tamene, L. (2025) Spatial optimization of cropping systems for sustainable intensification in Malawi. 6 p. |
| spellingShingle | cropping systems modelling Liben, Feyera Kihara, Job Mesfin, Tewodros Abera, Wuletawu Mkuhlani, Siyabusa Tamene, Lulseged Spatial optimization of cropping systems for sustainable intensification in Malawi |
| title | Spatial optimization of cropping systems for sustainable intensification in Malawi |
| title_full | Spatial optimization of cropping systems for sustainable intensification in Malawi |
| title_fullStr | Spatial optimization of cropping systems for sustainable intensification in Malawi |
| title_full_unstemmed | Spatial optimization of cropping systems for sustainable intensification in Malawi |
| title_short | Spatial optimization of cropping systems for sustainable intensification in Malawi |
| title_sort | spatial optimization of cropping systems for sustainable intensification in malawi |
| topic | cropping systems modelling |
| url | https://hdl.handle.net/10568/179820 |
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