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Agent-based Modelling of Climate Adaptation and Mitigation Options in Agriculture


  • Thomas Berger
  • Christian Troost


type="main" xml:id="jage12045-abs-0001"> Computer simulation models can provide valuable insights for climate-related analysis and help streamline policy interventions for improved adaptation and mitigation in agriculture. Computable general equilibrium (CGE) and partial equilibrium (PE) models are currently being expanded to include land-use change and energy markets so that the effects of various policy measures on agricultural production can be assessed. Agent-based modelling (ABM) or multi-agent systems (MAS) have been suggested as a complementary tool for assessing farmer responses to climate change in agriculture and how these are affected by policies. MAS applied to agricultural systems draw on techniques used for Recursive Farm Programming, but include models of all individual farms, their spatial interactions and the natural environment. In this article, we discuss the specific insights MAS provide for developing robust policies and land-use strategies in response to climate change. We show that MAS are well-suited for uncertainty analysis and can thereby complement existing simulation approaches to advance the understanding and implementation of effective climate-related policies in agriculture.

Suggested Citation

  • Thomas Berger & Christian Troost, 2014. "Agent-based Modelling of Climate Adaptation and Mitigation Options in Agriculture," Journal of Agricultural Economics, Wiley Blackwell, vol. 65(2), pages 323-348, June.
  • Handle: RePEc:bla:jageco:v:65:y:2014:i:2:p:323-348

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    Cited by:

    1. Vera Eory & Cairistiona F. E. Topp & Adam Butler & Dominic Moran, 2018. "Addressing Uncertainty in Efficient Mitigation of Agricultural Greenhouse Gas Emissions," Journal of Agricultural Economics, Wiley Blackwell, vol. 69(3), pages 627-645, September.
    2. Fernandez-Mena, Hugo & Gaudou, Benoit & Pellerin, Sylvain & MacDonald, Graham K. & Nesme, Thomas, 2020. "Flows in Agro-food Networks (FAN): An agent-based model to simulate local agricultural material flows," Agricultural Systems, Elsevier, vol. 180(C).
    3. Huber, Robert & Bakker, Martha & Balmann, Alfons & Berger, Thomas & Bithell, Mike & Brown, Calum & Grêt-Regamey, Adrienne & Xiong, Hang & Le, Quang Bao & Mack, Gabriele & Meyfroidt, Patrick & Millingt, 2018. "Representation of decision-making in European agricultural agent-based models," Agricultural Systems, Elsevier, vol. 167(C), pages 143-160.
    4. Troost, Christian & Berger, Thomas, 2015. "Process-based simulation of regional agricultural supply functions in Southwestern Germany using farm-level and agent-based models," 2015 Conference, August 9-14, 2015, Milan, Italy 211929, International Association of Agricultural Economists.
    5. Krimly, Tatjana & Angenendt, Elisabeth & Bahrs, Enno & Dabbert, Stephan, 2016. "Global warming potential and abatement costs of different peatland management options: A case study for the Pre-alpine Hill and Moorland in Germany," Agricultural Systems, Elsevier, vol. 145(C), pages 1-12.
    6. Utomo, Dhanan Sarwo & Onggo, Bhakti Stephan & Eldridge, Stephen, 2018. "Applications of agent-based modelling and simulation in the agri-food supply chains," European Journal of Operational Research, Elsevier, vol. 269(3), pages 794-805.
    7. Menale Kassie & Zewdu Abro & Tesfamicheal Wossen & Samuel T. Ledermann & Gracious Diiro & Shifa Ballo & Lulseged Belayhun, 2020. "Integrated Health Interventions for Improved Livelihoods: A Case Study in Ethiopia," Sustainability, MDPI, Open Access Journal, vol. 12(6), pages 1-21, March.
    8. Thomas Berger & Christian Troost & Tesfamicheal Wossen & Evgeny Latynskiy & Kindie Tesfaye & Sika Gbegbelegbe, 2017. "Can smallholder farmers adapt to climate variability, and how effective are policy interventions? Agent-based simulation results for Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 48(6), pages 693-706, November.
    9. Kremmydas, Dimitris & Athanasiadis, Ioannis N. & Rozakis, Stelios, 2018. "A review of Agent Based Modeling for agricultural policy evaluation," Agricultural Systems, Elsevier, vol. 164(C), pages 95-106.
    10. Berger, Thomas, 2015. "Adaptation of farm-households to increasing climate variability in Ethiopia: Bioeconomic modeling of innovation diffusion and policy interventions," 2015 Conference, August 9-14, 2015, Milan, Italy 229062, International Association of Agricultural Economists.
    11. Nogueira, Luiz Augusto Horta & Antonio de Souza, Luiz Gustavo & Cortez, Luís Augusto Barbosa & Leal, Manoel Regis Lima Verde, 2017. "Sustainable and Integrated Bioenergy Assessment for Latin America, Caribbean and Africa (SIByl-LACAf): The path from feasibility to acceptability," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 292-308.
    12. van Wijk, Mark T., 2014. "From global economic modelling to household level analyses of food security and sustainability: How big is the gap and can we bridge it?," Food Policy, Elsevier, vol. 49(P2), pages 378-388.
    13. Wagner, Susanne & Angenendt, Elisabeth & Beletskaya, Olga & Zeddies, Jürgen, 2017. "Assessing ammonia emission abatement measures in agriculture: Farmers' costs and society's benefits – A case study for Lower Saxony, Germany," Agricultural Systems, Elsevier, vol. 157(C), pages 70-80.
    14. Mário Amorim Lopes & Álvaro Santos Almeida & Bernardo Almada-Lobo, 2018. "Forecasting the medical workforce: a stochastic agent-based simulation approach," Health Care Management Science, Springer, vol. 21(1), pages 52-75, March.
    15. Cho, Seojin & Antle, John M., 2019. "Impact of Domestic and Trade Policies on Adoption of a Biofuel Crop in Dryland Wheat-Based Farming Systems in U.S. Pacific Northwest," 2019 Annual Meeting, July 21-23, Atlanta, Georgia 290920, Agricultural and Applied Economics Association.
    16. Holderieath, Jason, 2016. "Spatiotemporal management under heterogeneous damage and uncertain parameters. An agent-based approach," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235850, Agricultural and Applied Economics Association.
    17. Wossen, Tesfamicheal & Berger, Thomas & Haile, Mekbib G. & Troost, Christian, 2018. "Impacts of climate variability and food price volatility on household income and food security of farm households in East and West Africa," Agricultural Systems, Elsevier, vol. 163(C), pages 7-15.
    18. Evgeny Latynskiy & Thomas Berger, 2017. "Assessing the Income Effects of Group Certification for Smallholder Coffee Farmers: Agent-based Simulation in Uganda," Journal of Agricultural Economics, Wiley Blackwell, vol. 68(3), pages 727-748, September.
    19. Catherine L. Kling & Raymond W. Arritt & Gray Calhoun & David A. Keiser, 2016. "Research Needs and Challenges in the FEW System: Coupling Economic Models with Agronomic, Hydrologic, and Bioenergy Models for Sustainable Food, Energy, and Water Systems," Center for Agricultural and Rural Development (CARD) Publications 16-wp563, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    20. Trond G. Husby & Elco E. Koks, 2017. "Household migration in disaster impact analysis: incorporating behavioural responses to risk," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 87(1), pages 287-305, May.
    21. Rianne Duinen & Tatiana Filatova & Wander Jager & Anne Veen, 2016. "Going beyond perfect rationality: drought risk, economic choices and the influence of social networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(2), pages 335-369, November.
    22. Huang, Shiyang & Hu, Guiping, 2018. "Biomass supply contract pricing and environmental policy analysis: A simulation approach," Energy, Elsevier, vol. 145(C), pages 557-566.

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