Chapotat, William, Houssou, Lionel, Saqalli, Mehdi, Gaudou, Benoit, Lerigoleur, Emilie, Maestripieri, Nicolas and Bouadjio Boulic, Audren (2016) An Agent-Based Model of the Amazonian Forest Colonisation and Oil Exploitation: the Oriente Study Case. In: 8th International Environmental Modelling and Software Society : Supporting Sustainable Futures (iEMSs 2016).

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Abstract

Since the 1970s, the northern part of Oriente, the Amazonian region of Ecuador has been colonised, mostly because of an intensive oil extraction which opens up roads and supports the settlement of people coming from the Andes. These dynamics induced important forest cuttings but also huge oil contamination of both soils and waters. The ANR-funded and Ecuador-France joint, MONOIL research project, seeks to evaluate the impacts of these dynamics over environment, society and population health. In this context, we initiated a retro-prospective study through the construction of a spatially-explicit agent-based model, focusing on reconstituting past and present human activities and public policies over this territory, thereby allowing us to define scenarios-based prospective for the future. The present paper aim is to describe this model, implemented, calibrated and simulated under the GAMA platform and which integrates three main dynamics: Oil companies, within their spatial blocks, build roads; create jobs and wealth but also pollution affecting the population health. Rural people, within their farm plots along roads, produce food crops and cash productions (mainly livestock, cocoa & coffee). They follow demographic and social patterns according to anthropological, economical and agricultural data already collected. When they stop farming, plots turn slowly back to forest. Economic interactions between actors are based on productivity, crops and oil prices, and public policies. The expected result of the study is to validate the reconstitution of this human-environment system in order to set several scenarios (price change, public policies and demography), each one corresponding to a possible future.