Hooman MANSOORİ, Mohammad GHORBANİ, Mohammad Reza KOHANSAL

Determining the Effects of Climate Change and Market Prices on Farm’s Structure by Using an Agent Based Model

In this study, an agent-based model was used to simulate structure change of farms during 20 years period of climate and market price changes in the rural area of Eslamshahr City in Iran. Decision rules that used in the model are based on the information that collected by direct interviews with farmers. So the model includes rules that define the relationship between agents and their environment. Results clearly showed that farmers' behavior patterns and the cover of agricultural land in the region affected by environmental and market factors changes. Comparison of the results of model implementation for various scenarios has shown that the highest yield and income loss has occurred in scenarios where there was a 10% reduction in access to water. Also, there is a less decrease in the crops land size in groups which includes small and medium farmers.

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Acosta L, Rounsevell M, Bakker M, Van Doorn A, Montserrat G & Delgado M (2014). An agent-based assessment of land use and ecosystem changes in the traditional agricultural landscape of Portugal. Journal of Intelligent Information Management 6(2):55- 80 https://doi.org/10.4236/iim.2014.62008
Allen R, Pereira L S, Raes D & Smith M (1998). Crop evapotranspiration, Guidelines for computing crop water requirements. FAO Irrigation and drainage, paper 56, Food and Agriculture Organization of the United Nations
Appel F & Balmann A (2018). Human behavior versus optimizing agents and the resilience of farms-Insights from agent-based participatory experiments with Farm AgriPoliS. Ecplogical Complexity 40(100731) https://doi.org/10.1016/j.ecocom.2018.08.005
Beckers V, Beckers J, Vanmaecke M & Van Hecke, E (2018). Modelling farm growth and its impact on Agricultural land use: A country scale application of an agent-based model. Journal of Land 7(3): 109 https://doi.org/10.3390/land7030109
Bert F, Podesta P, Rovere S & Menendez A (2011). An agent-based model to simulate structural and land-use changes in agricultural systems of the Argentine pampas. Journal of Ecological Modelling 22(19): 3486-3499 https://doi.org/10.1016/j.ecolmodel.2011.08.007
Hailegiorgis A, Crooks A & Cioffi-Revilla C (2018) An agent-based model of rural households’ adaptation to climate change. Journal of Artificial Societies and Social Simulation 21(4): 4 https://doi.org/10.18564/jasss.3812
UNFCC (2017). Iran’s third national report, National climate change office at the department of environment on behalf of the government of the Islamic Republic of Iran
Karimi V, Karami E & Keshavarz M (2017). Climate change and agriculture: Impacts and adaptive responses in Iran. Journal of Integrative Agriculture 17(1): 1-15 https://doi.org/10.1016/s2095-3119(17)61794-5
Lamperti F, Dosi G, Napoletano M, Roventini A & Sapio A (2017). Faraway, so close: Coupled climate and economic dynamics in an agentbased integrated assessment model. Journal of Ecological Economics 150: 315-339 https://doi.org/10.2139/ssrn.2944328
Lobianco A & Esposti R (2010). The regional multi-agent simulator (RegMAS): An open-source spatially explicit model to assess the impact of agricultural policies. Journal of Computers and Electronics in Agriculture 72(1): 14-26 https://doi.org/10.1016/j.compag.2010.02.006
Mitter H, Larcher M, Schonhart M, Stottinger M & Schmid E (2019). Exploring farmers’ climate change perceptions and adaptation intentions: Empirical evidence from Austria. Journal of Environmental management 63(6): 804-821 https://doi.org/10.1007/s00267-019-01158-7
Schindler J (2009). A multi-agent system for simulating land-use and land-cover change in the Atankwidi catchment of Upper East Ghana. Unpublished PhD thesis, Faculty of mathematics and natural sciences, University of Bonn, Germany http://hdl.handle.net/20.500.11811/4160
Seo B, Crown C, Rounsevell M (2018). Evaluation and calibration of an agent based land use model using remotely sensed land cover and primary productivity data. In: proceedings of the IEEE International Geoscience and Remote Sensing Symposium, 22-27 July, Valencia, Spain https://doi.org/10.1109/igarss.2018.8518023
Valbuena D, Verbung P H, Bregt A & Lightenberg A (2010). An agent-based approach to model land-use change at a regional scale. Journal of Landscape Ecology 25(2): 185-199 https://doi.org/10.1007/s10980-009-9380-6
Wossen T, Berger T, Mekbib G H & Troost C (2017). Impacts of climate variability and food price volatility on household income and food security of farm households in East and West Africa. Journal of Agricultural systems 163: 7-15 https://doi.org/10.1016/j.agsy.2017.02.006