MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa

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 a...

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Autores principales: Mponela, Powell, Le, Quang Bao, Snapp, Sieglinde, Villamor, Grace B., Tamene, Lulseged D., Borgemeister, Christian
Formato: Journal Article
Lenguaje:Inglés
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://hdl.handle.net/10568/132879
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author Mponela, Powell
Le, Quang Bao
Snapp, Sieglinde
Villamor, Grace B.
Tamene, Lulseged D.
Borgemeister, Christian
author_browse Borgemeister, Christian
Le, Quang Bao
Mponela, Powell
Snapp, Sieglinde
Tamene, Lulseged D.
Villamor, Grace B.
author_facet Mponela, Powell
Le, Quang Bao
Snapp, Sieglinde
Villamor, Grace B.
Tamene, Lulseged D.
Borgemeister, Christian
author_sort Mponela, Powell
collection Repository of Agricultural Research Outputs (CGSpace)
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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spelling CGSpace1328792025-12-08T09:54:28Z MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa Mponela, Powell Le, Quang Bao Snapp, Sieglinde Villamor, Grace B. Tamene, Lulseged D. Borgemeister, Christian sustainability productivity simulation models subsidies nutrient balance behavioural responses agent-based models multi-agent systems maize farm productivity re-orienting farm input subsidy farmer behaviour 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. 2023-12 2023-11-09T14:55:19Z 2023-11-09T14:55:19Z Journal Article https://hdl.handle.net/10568/132879 en Open Access application/pdf Elsevier 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. In MethodsX (Vol. 11, p. 102467). Elsevier BV. https://doi.org/10.1016/j.mex.2023.102467
spellingShingle sustainability
productivity
simulation models
subsidies
nutrient balance
behavioural responses
agent-based models
multi-agent systems
maize
farm productivity
re-orienting farm input subsidy
farmer behaviour
Mponela, Powell
Le, Quang Bao
Snapp, Sieglinde
Villamor, Grace B.
Tamene, Lulseged D.
Borgemeister, Christian
MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa
title MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa
title_full MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa
title_fullStr MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa
title_full_unstemmed MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa
title_short MASSAI: Multi-agent system for simulating sustainable agricultural intensification of smallholder farms in Africa
title_sort massai multi agent system for simulating sustainable agricultural intensification of smallholder farms in africa
topic sustainability
productivity
simulation models
subsidies
nutrient balance
behavioural responses
agent-based models
multi-agent systems
maize
farm productivity
re-orienting farm input subsidy
farmer behaviour
url https://hdl.handle.net/10568/132879
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