Séminaire NANCY – Stéphane Couture (MIAT INRAE)

Détails de l'événement :

“How can ambiguity influence the optimal management of a forest? An approach with Multi-Model Markov Decision Processes” avec Marie-Josée Cros et Régis Sabbadin

Abstract: In a context of climate change, it becomes difficult for private forest owners to project themselves into the future and to optimize their decisions in order to meet the objectives they have set for the management of their forest. Indeed, climate change is not predictable in a perfect way, and the risks of fire threats on forests, strongly linked to climate change, will also evolve. Forest owners must therefore act in a situation of ambiguity. In addition, private forest owners are very heterogeneous in terms of objectives, attitudes and behaviors in their forest management, but also in terms of perception and defiance to ambiguity. It is therefore essential, in any given framework, to take this heterogeneity into consideration. In such an environment, providing recommendations to private forest owners that take into account their preferences regarding ambiguity is a fundamental societal challenge in the face of climate change. This study aims to provide some answers in this context of ambiguity in order to optimize forest owners’ decisions and find optimal policies. We define a maximization approach to obtain optimal forest management policies considering ambiguity and ambiguity aversion in order to explicitly consider climate change and the various possible fire risks. We adopt an infinite-horizon stationary Multi-Model Markov Decision Processes (MMDP) framework to model this problem. The main contribution of this work is to design a MMDP model to evaluate forest management policies in an ambiguous context due to climate change, and to generate the forest management policies evaluated under several parameters of forest owner’s ambiguity preferences, according to two decision criteria, the -MEU model or the smooth ambiguity model.This enables the forest owners to develop insights into the economic forest management under climate change. The MMDP framework is applied to a non-industrial private forest owner located in southwestern France facing a fire risk. In some cases, ambiguity and ambiguity aversion amplifie the effects of risk aversion and further reduces the optimal cutting age.