Using Uncertainty of Bayesian Theorem to Predict Mortality of Tree in Forest Growth Simulation System

Abstract

Researchers have done a lot of methods to link between growth rate and mortality. However, very little information about the uncertainty involve in tree mortality process. In this study, we presented the mortality prediction in forest simulation system by using uncertainty technique of Bayesian approach based on individual tree. The prediction will take account the overlapping of tree crowns, whether the species are shade tolerance or intolerance and the number of years the tree is under shade of suppression. The system will display the end status of the tree. The decision of the end status of the tree for dead tree is based on the ranking of the tree. The tree has higher potential to be dead if it is under suppression for several cycles. This new approach appears practicable particularly on its ability to project the mortality trees in their respective location. In addition, this approach will improve the decision-making process of the sustainable management of tropical forest as well as to improve its information database system.