Improving tree survival prediction with forecast combination and disaggregation

Abstract

The tree mortality model plays an important role in simulating stand dynamic processes. Past work has shown that the disaggregation method was successful in improving tree survival prediction. This method was used in this study to forecast tree survival probability of Chinese pine (Pinus tabulaeformis Carrière) in Beijing. Outputs from the tree survival model were adjusted from either the stand-level model prediction or the combined estimator from the forecast combination method. Our results show that the disaggregation approach improved the performance of tree survival models. We also showed that stand-level prediction played a crucial role in refining outputs from a tree survival model, especially when it is a very simple model. Because the forecast combination method produced better stand-level prediction, we prefer the use of this method in conjunction with the disaggregation approach, even though the performance gain in using the forecast combination method shown for this data set was modest.