Saeed HARATI, Université de Montréal, Canada
Liliana PEREZ, Université de Montréal, Canada
Roberto MOLOWNY-HORAS, Centre de Recerca Ecològica i Aplicacions Forestals (CREAF), Spain
Sustainable development problems inherently involve complex systems. With sustainability on their agenda, governments and decision makers are faced with decisions to intervene in social-ecological systems. In that regard, two of the challenges of governance for sustainable development are that (1) governments and decision makers often need to engage their societies in actions that are not profitable in the short term, and (2) even if their societies fully cooperate in those actions, governments and decision makers are not certain about the outcome of those actions. Complex systems modelling is a suitable approach for these problems, especially when the risk of unanticipated adverse consequences is a constraint to learning by trial and error. Building on an example case of forest disturbance, we present a coupled social-ecological model that is made up of abstract and non-abstract components, and we demonstrate how this model can be used to address the two challenges named above. Our approach involves running the model in various scenarios and hypothetical tests, and comparing the results of those tests with each other. This allows us to learn about the space of possible outcomes, which in turn allows us to perform better ‘what-if’ analyses and gain insight about the complexities of the studied system. Applying this approach in our case of study lead to the conclusion that promoting cooperation in environmentally responsible actions in possible, even without use of force or financial incentives.
Keywords: Social-ecological system|governance|Agent Based Model|Reinforcement Learning|conceptual model
A104642SH