Investigating Fourteen Years of Net Primary Productivity Based on Remote Sensing Data for China

Abstract

Net primary productivity (NPP) is an important environmental indicator that provides information about vegetation productivity and carbon fluxes. Analyses of NPP time-series allow for understanding temporal patterns and changes in vegetation productivity. These are especially important in rapidly changing environments, such as China, the world’s third largest country. In this study, we use the model BETHY/DLR (Biosphere Energy Transfer Hydrology Model) for derivation of NPP time-series for China for 14 years from 1999–2012. We analyse spatial and temporal NPP distributions. These include mean annual NPP distribution and mean productivities for different land cover classes. Monthly data provide information about temporal patterns of vegetation productivity for different regions in China and different vegetation types. Analyses of interannual NPP variability revealed considerable differences in the development of annual vegetation productivity within the analysed time period for different provinces. The decrease in NPP for the district Shanghai shows the strong influence of one of Asia’s fastest growing megacities on the environment. The NPP time-series was additionally analysed for a forest region in North China, which has been affected by forest disturbances. Our results show that the NPP data are suitable for monitoring of forest disturbance and regrowth. The analyses and results presented in this study provide valuable information about spatial and temporal variation of vegetation productivity in the various regions within China.