Modelling the spatial pattern of net primary productivity in Chinese forests

Abstract

The spatial patterns of biomass and net primary productivity in China’s forests were estimated using empirical data sets, remote sensing methods, and climate–vegetation models, and were analysed within a spatial analysis system. Differences between spatial modelling methods for estimating net primary production (NPP) were also examined and compared. The results indicate that the present spatial pattern of NPP in Chinese forest types is a result of both natural environmental factors and human land use patterns. Estimates of NPP for the tropical zone — seasonal rainforests and rainforests — were highest, ranging from 20 to 24 Mg ha −1 year −1. NPP was lowest in boreal zone forests comprised primarily of Scotch pine and Siberian pine, averaging only 6.7 Mg ha −1 year −1. The results reported here demonstrate the usefulness of spatial analyses techniques for improving the accuracy of NPP estimates and our understanding of NPP spatial patterns and dynamics in forest ecosystems.