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Land use change in agricultural systems: an integrated ecological-social simulation model of farmer decisions and cropping system performance based on a cellular automata approach

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  • Diego Ferraro
  • Daniela Blanco
  • Sebasti'an Pessah
  • Rodrigo Castro

Abstract

Agricultural systems experience land-use changes that are driven by population growth and intensification of technological inputs. This results in land-use and cover change (LUCC) dynamics representing a complex landscape transformation process. In order to study the LUCC process we developed a spatially explicit agent-based model in the form of a Cellular Automata implemented with the Cell-DEVS formalism. The resulting model called AgroDEVS is used for predicting LUCC dynamics along with their associated economic and environmental changes. AgroDEVS is structured using behavioral rules and functions representing a) crop yields, b) weather conditions, c) economic profit, d) farmer preferences, e) technology level adoption and f) natural resources consumption based on embodied energy accounting. Using data from a typical location of the Pampa region (Argentina) for the 1988-2015 period, simulation exercises showed that the economic goals were achieved, on average, each 6 out of 10 years, but the environmental thresholds were only achieved in 1.9 out of 10 years. In a set of 50-years simulations, LUCC patterns quickly converge towards the most profitable crop sequences, with no noticeable tradeoff between the economic and environmental conditions.

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  • Diego Ferraro & Daniela Blanco & Sebasti'an Pessah & Rodrigo Castro, 2021. "Land use change in agricultural systems: an integrated ecological-social simulation model of farmer decisions and cropping system performance based on a cellular automata approach," Papers 2109.01031, arXiv.org, revised Sep 2021.
  • Handle: RePEc:arx:papers:2109.01031
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    1. Hare, M & Deadman, P, 2004. "Further towards a taxonomy of agent-based simulation models in environmental management," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 64(1), pages 25-40.
    2. Happe, Kathrin & Balmann, Alfons & Kellermann, Konrad & Sahrbacher, Christoph, 2008. "Does structure matter? The impact of switching the agricultural policy regime on farm structures," Journal of Economic Behavior & Organization, Elsevier, vol. 67(2), pages 431-444, August.
    3. Warren Thorngate & Bruce Edmonds, 2013. "Measuring Simulation-Observation Fit: An Introduction to Ordinal Pattern Analysis," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 16(2), pages 1-4.
    4. Agostinho, Feni & Ambrósio, Luís Alberto & Ortega, Enrique, 2010. "Assessment of a large watershed in Brazil using Emergy Evaluation and Geographical Information System," Ecological Modelling, Elsevier, vol. 221(8), pages 1209-1220.
    5. Meredith J. Soule & Abebayehu Tegene & Keith D. Wiebe, 2000. "Land Tenure and the Adoption of Conservation Practices," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 82(4), pages 993-1005.
    6. Alberto Porto & Agustín Lodola, 2013. "Economic policy and electoral outcomes," Journal of Applied Economics, Universidad del CEMA, vol. 16, pages 333-356, November.
    7. Bert, Federico E. & Rovere, Santiago L. & Macal, Charles M. & North, Michael J. & Podestá, Guillermo P., 2014. "Lessons from a comprehensive validation of an agent based-model: The experience of the Pampas Model of Argentinean agricultural systems," Ecological Modelling, Elsevier, vol. 273(C), pages 284-298.
    8. Castella, Jean-Christophe & Verburg, Peter H., 2007. "Combination of process-oriented and pattern-oriented models of land-use change in a mountain area of Vietnam," Ecological Modelling, Elsevier, vol. 202(3), pages 410-420.
    9. Petra Ahrweiler & Nigel Gilbert, 2005. "Caffè Nero: The Evaluation of Social Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-14.
    10. 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.
    11. Giannetti, B.F. & Almeida, C.M.V.B. & Bonilla, S.H., 2010. "Comparing emergy accounting with well-known sustainability metrics: The case of Southern Cone Common Market, Mercosur," Energy Policy, Elsevier, vol. 38(7), pages 3518-3526, July.
    12. Balmann, Alfons, 1997. "Farm-Based Modelling of Regional Structural Change: A Cellular Automata Approach," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 24(1), pages 85-108.
    13. Gilboa,Itzhak & Schmeidler,David, 2001. "A Theory of Case-Based Decisions," Cambridge Books, Cambridge University Press, number 9780521802345, October.
    14. Happe, Kathrin & Kellermann, Konrad & Balmann, Alfons, 2006. "Agent-based analysis of agricultural policies: An illustration of the agricultural policy simulator AgriPoliS, its adaptation and behavior," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 11(1).
    15. Schreinemachers, Pepijn & Berger, Thomas & Aune, Jens B., 2007. "Simulating soil fertility and poverty dynamics in Uganda: A bio-economic multi-agent systems approach," Ecological Economics, Elsevier, vol. 64(2), pages 387-401, December.
    16. Uri Wilensky & William Rand, 2007. "Making Models Match: Replicating an Agent-Based Model," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(4), pages 1-2.
    17. Bert, Federico E. & Podestá, Guillermo P. & Rovere, Santiago L. & Menéndez, Ángel N. & North, Michael & Tatara, Eric & Laciana, Carlos E. & Weber, Elke & Toranzo, Fernando Ruiz, 2011. "An agent based model to simulate structural and land use changes in agricultural systems of the argentine pampas," Ecological Modelling, Elsevier, vol. 222(19), pages 3486-3499.
    18. Günter Küppers & Johannes Lenhard, 2005. "Validation of Simulation: Patterns in the Social and Natural Sciences," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 8(4), pages 1-3.
    19. Berger, Thomas, 2001. "Agent-based spatial models applied to agriculture: a simulation tool for technology diffusion, resource use changes and policy analysis," Agricultural Economics, Blackwell, vol. 25(2-3), pages 245-260, September.
    20. David Manuel-Navarrete & Gilberto Gallopín & Mariela Blanco & Martín Díaz-Zorita & Diego Ferraro & Hilda Herzer & Pedro Laterra & María Murmis & Guillermo Podestá & Jorge Rabinovich & Emilio Satorre &, 2009. "Multi-causal and integrated assessment of sustainability: the case of agriculturization in the Argentine Pampas," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 11(3), pages 621-638, June.
    21. Karl Shell & Joseph E. Stiglitz, 1967. "The Allocation of Investment in a Dynamic Economy," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 81(4), pages 592-609.
    22. Arika Ligmann-Zielinska & Peer-Olaf Siebers & Nicholas R Magliocca & Dawn C. Parker & Volker Grimm & Jing Du & Martin Cenek & Viktoriia Radchuk & Nazia N. Arbab & Sheng Li & Uta Berger & Rajiv Paudel , 2020. "‘One Size Does Not Fit All’: A Roadmap of Purpose-Driven Mixed-Method Pathways for Sensitivity Analysis of Agent-Based Models," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 23(1), pages 1-6.
    23. Grönlund, Erik & Fröling, Morgan & Carlman, Inga, 2015. "Donor values in emergy assessment of ecosystem services," Ecological Modelling, Elsevier, vol. 306(C), pages 101-105.
    24. Grimm, Volker & Berger, Uta & DeAngelis, Donald L. & Polhill, J. Gary & Giske, Jarl & Railsback, Steven F., 2010. "The ODD protocol: A review and first update," Ecological Modelling, Elsevier, vol. 221(23), pages 2760-2768.
    25. Ferraro, D.O. & Benzi, P., 2015. "A long-term sustainability assessment of an Argentinian agricultural system based on emergy synthesis," Ecological Modelling, Elsevier, vol. 306(C), pages 121-129.
    26. Dimitris Kremmydas, 2012. "Agent based modeling for agricultural policy evaluation: A review," Working Papers 2012-3, Agricultural University of Athens, Department Of Agricultural Economics.
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