Predict potential risk of bark beetle disturbance applying Bayesian Belief Networks

In recent years, due to climate and environmental change, most forest areas suffer from land degradation, mainly caused by the bark beetle disturbance which damaged many tree species. The complex multiple interactions between climate and influence factors have highlighted the need for an efficiency integrated model based on decision support system, determining important implications and support for forest management planning. Based on expert perceptions, the Bayesian Belief Networks (BBN) approach provides a more consistent method of handling uncertainties, aiming to facilitate the interpretation of interdependencies between factors considered against risk. In this research, we have developed a BBN algorithm and program to estimate the potential risk in national scale, this technique was compared to the fuzzy logic model. Both models propose rapid solution for solving complex decision problems, they could be reused in other worldwide similar study areas.