Abstract
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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Notes
- 1.
Mapa de cobertura y uso de la tierra del Ecuador continenal año 1990, Ministerio del Ambiente, 2014.
- 2.
The macronutrients are calculated given an activity production based on [13].
- 3.
Deforested pixels are plots where at least 50% of the biomass is missing.
- 4.
We consider as “deforested” pixels belonging to the categories “populated areas” and “agricultural land” of level 1 of Mapa de cobertura y uso de la tierra del Ecuador continenal año 1990, Ministerio del Ambiente (MAE), 2014.
- 5.
It is thus close to the classical Hamming distance [14].
References
An, L.: Modeling human decisions in coupled human and natural systems: review of agent-based models. Ecol. Model. 229, 25–36 (2012)
Bakker, M.M., van Doorn, A.M.: Farmer-specific relationships between land use change and landscape factors: introducing agents in empirical land use modelling. Land Use Policy 26(3), 809–817 (2009)
Bilsborrow, R.E., Barbieri, A.F., Pan, W.: Changes in population and land use over time in the Ecuadorian Amazon. Acta Amaz. 34(4), 635–647 (2004)
Chapotat, W., et al.: An agent-based model of the Amazonian forest colonisation and oil exploitation: the Oriente study case. In: Sauvage, S., Sanchez Perez, J.-M., Rizzoli, A.E. (eds.) iEMSs, vol. 5, pp. 1335. iEMSs (2016)
Edmonds, B., Moss, S.: From KISS to KIDS – an ‘anti-simplistic’ modelling approach. In: Davidsson, P., Logan, B., Takadama, K. (eds.) MABS 2004. LNCS (LNAI), vol. 3415, pp. 130–144. Springer, Heidelberg (2005). https://doi.org/10.1007/978-3-540-32243-6_11
Feola, G., Binder, C.R.: Towards an improved understanding of farmers’ behaviour: the integrative agent-centred (IAC) framework. Ecol. Econ. 69(12), 2323–2333 (2010)
Gaudou, B., et al.: The MAELIA multi-agent platform for integrated analysis of interactions between agricultural land-use and low-water management strategies. In: Alam, S.J., Parunak, H.V.D. (eds.) MABS 2013. LNCS (LNAI), vol. 8235, pp. 85–100. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-642-54783-6_6
Grignard, A., Taillandier, P., Gaudou, B., Vo, D.A., Huynh, N.Q., Drogoul, A.: GAMA 1.6: advancing the art of complex agent-based modeling and simulation. In: Boella, G., Elkind, E., Savarimuthu, B.T.R., Dignum, F., Purvis, M.K. (eds.) PRIMA 2013. LNCS (LNAI), vol. 8291, pp. 117–131. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-44927-7_9
Grimm, V., Berger, U., DeAngelis, D.L., Polhill, J.G., Giske, J., Railsback, S.F.: The ODD protocol: a review and first update. Ecol. Model. 221, 2760–2768 (2010)
Janssen, M.A., Ostrom, E.: Empirically based, agent-based models. Ecol. Soc. 12(2) (2006)
Juteau-Martineau, G., Becerra, S., Maurice, L.: Ambiente, petróleo y vulnerabilidad política en el oriente ecuatoriano: ¿hacia nuevas formas de gobernanza energética? América Lat. Hoy 67, 119–137 (2014)
Kremmydas, D., Athanasiadis, I.N., Rozakis, S.: A review of agent based modeling for agricultural policy evaluation. Agric. Syst. 164, 95–106 (2018)
Laure, J.: Nutrition et population en vue de la planification alimentaire. ORSTOM, PARIS (1983)
MacWilliams, F.J., Sloane, N.J.A.: The Theory of Error-Correcting Codes. Elsevier, Amsterdam (1977)
Mena, C.F., Walsh, S.J., Frizzelle, B.G., Xiaozheng, Y., Malanson, G.P.: Land use change on household farms in the Ecuadorian Amazon: design and implementation of an agent-based model. Appl. Geogr. 31(1), 210–222 (2011)
Saqalli, M., Bielders, C.L., Gerard, B., Defourny, P.: Simulating rural environmentally and socio-economically constrained multi-activity and multi-decision societies in a low-data context: a challenge through empirical agent-based modeling. J. Artif. Soc. Soc. Simul. 13(2), 1 (2010)
Schulze, J., Müller, B., Groeneveld, J., Grimm, V.: Agent-based modelling of social-ecological systems: achievements, challenges, and a way forward. J. Artif. Soc. Soc. Simul. 20(2) (2017)
Voinov, A., Bousquet, F.: Modelling with stakeholders. Environ. Model. Softw. 25(11), 1268–1281 (2010)
Acknowledgment
This study was partly funded by the French research funding agency ANR (Agence Nationale de la Recherche), two French research institutions, the “Institut des Amériques” and “Maison des Sciences de l’Homme et de la Société de Toulouse” (USR CNRS 3414), ECOLAB Funds, Occitanie region and university of Toulouse. The team received logistical support from the IRD.
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Kaced, D., Mejean, R., Richa, A., Gaudou, B., Saqalli, M. (2019). PASHAMAMA: An Agricultural Process-Driven Agent-Based Model of the Ecuadorian Amazon. In: Davidsson, P., Verhagen, H. (eds) Multi-Agent-Based Simulation XIX. MABS 2018. Lecture Notes in Computer Science(), vol 11463. Springer, Cham. https://doi.org/10.1007/978-3-030-22270-3_5
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