MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa
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Title |
MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa
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Creator |
Mponela, Powell
Le, Quang Bao Snapp, Sieglinde Villamor, Grace Tamene, Lulseged Borgemeister, Christian |
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Subject |
nutrient balance
Maize farm productivity re-orienting farm input subsidy farmer behaviour |
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Description |
The research and development needed to achieve sustainability of African smallholder agricultural and natural systems has led to a wide array of theoretical frameworks for conceptualising socioecological processes and functions. However, there are few analytical tools for spatio-temporal empirical approaches to implement use cases, which is a prerequisite to understand the performance of smallholder farms in the real world. This study builds a multi-agent system (MAS) to operationalise the Sustainable Agricultural Intensification (SAI) theoretical framework (MASSAI). This is an essential tool for spatio-temporal simulation of farm productivity to evaluate sustainability trends into the future at fine scale of a managed plot. MASSAI evaluates dynamic nutrient transfer using smallholder nutrient monitoring functions which have been calibrated with parameters from Malawi and the region. It integrates two modules: the Environmental (EM) and Behavioural (BM) ones. • The EM assess dynamic natural nutrient inputs (sedimentation and atmospheric deposition) and outputs (leaching, erosion and gaseous loses) as a product of bioclimatic factors and land use activities. • An integrated BM assess the impact of farmer decisions which influence farm-level inputs (fertilizer, manure, biological N fixation) and outputs (crop yields and associated grain). • A use case of input subsidies, common in Africa, markedly influence fertilizer access and the impact of different policy scenarios on decision-making, crop productivity, and nutrient balance are simulated. This is of use for empirical analysis smallholder's sustainability trajectories given the pro-poor development policy support. |
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Date |
2023-11-01
2023-11-21T16:21:08Z 2023-11-21T16:21:08Z |
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Type |
Journal Article
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Identifier |
Mponela, P. Le, Q. B. Snapp, S. Villamor, G. B. Tamene, L. Borgemeister, C. 2023. MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa. MethodsX 11, 102467.
2215-0161 https://hdl.handle.net/10568/134580 https://dx.doi.org/10.1016/j.mex.2023.102467 |
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Language |
en
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Rights |
CC-BY-4.0
Open Access |
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Format |
1-15
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Publisher |
Elsevier
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Source |
MethodsX
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