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Tree mortality in response to climate change induced drought has emerged as a global concern. Small changes of tree mortality rates can profoundly affect forest structure, composition, dynamics and ecosystem services such as carbon sequestration. Our analyses of longitudinal data from natural stands (82 plots) in Beijing showed that tree mortality rates have increased significantly over the two decades from 1986 to 2006. In contrast, recruitment rates decreased significantly over this period. The increase in overall mortality rates resulted from an increase in tree deaths dominantly attributed to changes in temperature and precipitation resulting in drier conditions across latitudes, elevations, tree species, and tree sizes. In addition, the results showed that mortality rates of Chinese pine ( Pinus tabuliformis) ( β = 0.0874) as a result of climate change induce drought were much smaller than oak ( Quercus) ( β = 0.1583). [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]