• 研究报告 •

### 中国潜在植被NPP的空间分布模拟

1. (西北师范大学地理与环境科学学院， 兰州 730070)
• 出版日期:2020-03-10 发布日期:2020-03-10

### Modeling spatial distribution of potential vegetation NPP in China.

PAN Jing-hu*, XU Bai-cui

1. (College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China).
• Online:2020-03-10 Published:2020-03-10

Abstract: Potential NPP refers to the NPP that is generated in the natural state when the impacts of human beings on the ecological environment are excluded. The study of spatial pattern of potential vegetation productivity has become basic work toward the ecological environment rehabilitation and reconstruction in China. Data from 592 meteorological stations were used to build climate models, while regression trees were applied to estimate potential NDVI based on climate variables and training data of actual NDVI. Then, potential NPP of China was simulated using CASA model and potential NDVI data. The results showed that China’s potential NDVI and potential NPP show a pattern of high in the south and low in the north and high in the east and low in the west. The lower potential NPP occurred at desert, Gobi and other arid areas, and the higher potential NPP are mostly distributed in low and middle plain. In particular, the spatial pattern can be divided into relatively higher and lower parts in 400 mm equivalent precipitation line. The average potential NDVI and potential NPP of China were 0.396 and 319.31 g C·m-2 respectively. The mean value of potential NPP in summer was the highest, followed by spring and the lowest in winter. According to the difference between potential NPP and actual NPP in 2015, the national vegetation restoration area can be divided into three parts: high potential area in the west, low potential area in the north, and non-potential area in the south. Spatial simulation of potential NDVI and potential NPP can separate the direct impact of human activities on natural ecosystems from the impact of climate change and quantify the differences between real and potential ecological conditions under external pressures, and thus could provide scientific basis for formulating differentiated ecological restoration strategies.