The MAELIA Multi-Agent Platform for Integrated Analysis of Interactions Between Agricultural Land-Use and Low-Water Management Strategies

Gaudou, Benoît; Sibertin-Blanc, Christophe; Thérond, Olivier; Amblard, Frédéric; Auda, Yves; Arcangeli, Jean‐Paul; Balestrat, Maud; Charron-Moirez, Marie-Hélène; Gondet, Etienne; Hong, Yi; Lardy, Romain; Louail, Thomas; Mayor, Eunate; Panzoli, David; Sauvage, Sabine; Sánchez‐Pérez, José‐Miguel; Taillandier, Patrick; Bai, Nguyen Van; Vavasseur, Maroussia; Mazzéga, Pierre

doi:10.1007/978-3-642-54783-6_6

Cited by 28 publications

(22 citation statements)

References 10 publications

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“…At present, a relatively small number of studies have applied agent based modelling to agro food systems, and typically focus on specific system components. For example, past agent based modelling has been applied to the study of environmental changes in farming systems (Acosta Michlik and Espaldon, 2008;Murray Rust et al, 2011;Schreinemachers and Berger, 2011); agricultural markets and policies (Bert et al, 2015;Schouten et al, 2014); land use change (Groeneveld et al, 2017;Le et al, 2010); agricultural water management (Becu et al, 2003;Gaudou et al, 2014); urban and agricultural waste man agement (Bichraoui et al, 2013;Courdier et al, 2002;Xu et al, 2016); and smallholders farming, rural livelihoods and self sufficiency (Iwamura et al, 2014;Magliocca et al, 2013;Villamor et al, 2014;Grillot et al, 2018). To our knowledge, agent based models have not yet been applied to simulate material flows across a broader range of components in agro food networks, including multiple agents and ma terials.…”

Section: Purposementioning

confidence: 99%

Flows in Agro-food Networks (FAN): An agent-based model to simulate local agricultural material flows

Fernández-Mena

Gaudou

Pellerin³

et al. 2020

Agricultural Systems

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Agro-food networks are characterized by complex material exchanges among farms, processors, consumers, and waste managers involved in fertilization, food, feed and bioenergy production. Better coordination of material exchanges at the local scale can facilitate more efficient resource use. Here, we present a new agent-based model, "Flows in Agro-food Networks" (FAN), which simulates the processing and exchange of fertilizers, feed, food and wastes among farms and multiple upstream or downstream partners (feed and fertilizer suppliers, food industries, waste processors, and anaerobic digesters) in small farming regions. FAN includes a series of environmental indicators that can be used to assess alternative scenarios in terms of ecosystem services, nutrient cycling, and resource autonomy. We use a French case study to demonstrate FAN's dynamics and to explore the sensitivity of key parameters. We show a strong influence of spatial distance between agents, their disposition to exchange, and their preference for specific materials on local agro-food network simulations. FAN is powerful theoretical tool to explore and assess opportunities for a circular economy in small farming regions and to unravel interactions between recycling, environmental performance and food production.

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Section: Purposementioning

confidence: 99%

Flows in Agro-food Networks (FAN): An agent-based model to simulate local agricultural material flows

Fernández-Mena

Gaudou

Pellerin³

et al. 2020

Agricultural Systems

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“…In this way, [6] used a specific framework for their agents, that integrate behavioural drivers, in their study of the use of pesticides in Colombia. Similarly, [7] used Belief Function Theory to model yearly decision-making process of cropping plan in the South-East of France. Other models, from a participatory approach, directly involve stakeholders in the modelling process [18].…”

Section: Related Workmentioning

confidence: 99%

PASHAMAMA: An Agricultural Process-Driven Agent-Based Model of the Ecuadorian Amazon

Kaced

Mejean

Richa

et al. 2019

Multi-Agent-Based Simulation XIX

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This article presents the PASHAMAMA model that aims at studying the situation in the northern part of the Amazonian region of Ecuador in which the intensive oil extraction has induced a high rise of population, pollution, agricultural work and deforestation. It simulates these dynamics impacts on both environment and population by examining exposure and demography over time thanks to a retro-prospective and spatially explicit agent-based approach. Based on a previous work that has introduced roads, immigration and pollution (induced by the oil industry) dynamics, we focus here on the agricultural and the oil salaried work sides of the model. Unlike many models that are highly focused on the use of quantitative data, we choose a process-based approach and rest on qualitative data extracted from interviews with the local population: farmers are not represented by highly cognitive agents, but only attempt to fulfill their local objectives by fulfilling sequentially their constraints (e.g. eating before earning money). We also introduce a new evaluation method based on satellite pictures that compares simulated to "real" data on a thematic division of the environment.

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“…The use of passive agents to embed data in the model is a very common modeling choice when dealing with socio-environmental systems (e.g. [3]). It allows the model to be homogeneous in terms of interactions between entities.…”

Section: Entities Variables and Scalesmentioning

confidence: 99%

“…Each day a small rate of the cell mosquito population is thus exchanged with neighbour cells. Although mosquitoes have a very small move range, this represents mosquitoes population at the border of two cells 3 .…”

Section: Submodelsmentioning

confidence: 99%

Exploring Trade and Health Policies Influence on Dengue Spread with an Agent-Based Model

Philippon

Choisy

Drogoul

et al. 2017

Multi-Agent Based Simulation XVII

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OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible. This is an author-deposited version published in : http://oatao.univ-toulouse.fr/ Eprints ID : 18788The contribution was presented at MABS 2016 : https://sites.google.com/site/mabsworkshop2016/ Abstract. With the globalization, several free trade areas have been and are being created all around the world. They usually have positive consequences for increasing economic exchanges, but negative ecological or health side effects. These negative effects are difficult to predict or even to understand due to the complexity of the system and of the number of involved processes. In this article, we focus on the Southeast Asia free trade area (the ASEAN) and specifically in the East-West economic corridor. A significant correlation has been observed in this area between the corridor opening and dengue fever cases, without being able to establish a causality relationship. We choose to tackle this issue by building an agent-based geographically explicit model. We propose an approach coupling dengue fever dynamics, climate data, economic mobility and health policies, following a design methodology decomposing these processes in sub-models and linking them to make one integrated model. In addition, we propose a way to deal with lack of data in the modeling process. Our simulation results show that there is influence of the increase in mobility and application of different control policies on the increase of dengue cases.

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The MAELIA Multi-Agent Platform for Integrated Analysis of Interactions Between Agricultural Land-Use and Low-Water Management Strategies

Abstract: OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible.

Cited by 28 publications

References 10 publications

Flows in Agro-food Networks (FAN): An agent-based model to simulate local agricultural material flows

Flows in Agro-food Networks (FAN): An agent-based model to simulate local agricultural material flows

PASHAMAMA: An Agricultural Process-Driven Agent-Based Model of the Ecuadorian Amazon

Exploring Trade and Health Policies Influence on Dengue Spread with an Agent-Based Model

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