Net Primary Productivity （NPP） is an important parameter, which is closely connected with global climate change, the global carbon balance and cycle. The study of climate- vegetation interaction is the basis for res...Net Primary Productivity （NPP） is an important parameter, which is closely connected with global climate change, the global carbon balance and cycle. The study of climate- vegetation interaction is the basis for research on the responses of terrestrial ecosystemto global change and mainly comprises two important components： climate vegetation classification and the NPP of the natural vegetation. Comparing NPP estimated from the classification indices-based model with NPP derived from measurements at 3767 sites in China indicated that the classification indices-based model was capable of estimating large scale NPP. Annual cumulative temperature above 0~C and a moisture index, two main factors affecting NPP, were spatially plotted with the ArcGIS grid tool based on measured data in 2348 meteorological stations from 1961 to 2006. The distribution of NPP for potential vegetation classes under present climate conditions was simulated by the classification indices-based model. The model estimated the total NPP of potential terrestrial vegetation of China to fluctuate between 1.93 and 4.54 Pg C year-1. It pro- vides a reliable means for scaling-up from site to regional scales, and the findings could potentially favor China＇s position in reducing global warming gases as outlined in the Kyoto Protocol in order to fulfill China＇s commitment of reducing greenhouse gases.展开更多
文摘Net Primary Productivity （NPP） is an important parameter, which is closely connected with global climate change, the global carbon balance and cycle. The study of climate- vegetation interaction is the basis for research on the responses of terrestrial ecosystemto global change and mainly comprises two important components： climate vegetation classification and the NPP of the natural vegetation. Comparing NPP estimated from the classification indices-based model with NPP derived from measurements at 3767 sites in China indicated that the classification indices-based model was capable of estimating large scale NPP. Annual cumulative temperature above 0~C and a moisture index, two main factors affecting NPP, were spatially plotted with the ArcGIS grid tool based on measured data in 2348 meteorological stations from 1961 to 2006. The distribution of NPP for potential vegetation classes under present climate conditions was simulated by the classification indices-based model. The model estimated the total NPP of potential terrestrial vegetation of China to fluctuate between 1.93 and 4.54 Pg C year-1. It pro- vides a reliable means for scaling-up from site to regional scales, and the findings could potentially favor China＇s position in reducing global warming gases as outlined in the Kyoto Protocol in order to fulfill China＇s commitment of reducing greenhouse gases.
