Interannual variation in grassland net ecosystem productivity and its coupling relation to climatic factors in China
Grassland, as an important part of land cover, plays an important role in the global carbon cycle and carbon balance. Net ecosystem productivity (NEP) is a key indicator of the carbon cycle process and an important factor in assessing ecosystem security and maintaining ecosystem balance. In this paper, Boreal Ecosystem Productivity Simulator (BEPS) combining meteorological data, leaf area index, and land cover type data were used to simulate the grassland NEP of China from 1979 to 2008. This model was also used to analyze the responses to changes in climate factors, interannual variation in carbon conversion efficiency, drought stress coefficient, and water use efficiency of grassland in China. Results showed that from 1979 to 2008, the mean annual grassland NEP was 13.6 g C/m2 with weak carbon sinks. The grassland NEP distribution increased from northwest to southeast across China. Regions with NEP of > 0 (C sink) accounted for 73.1% of the total grassland area of China. The total C sequestration reached 26.6 Tg yearly, and grassland NEP was positive from 1979 to 2008. The annual changing characteristics were analyzed. Grassland NEP was positive with carbon sink from June to September, which was negative with carbon source in the remaining months. The carbon conversion efficiency and water use efficiency of the grassland increased significantly within 30 years. NEP showed positive correlation with precipitation (accounting for 74.2% of the total grassland area was positively correlated) but weakly positive correlation with temperature (50.2% of the case). Furthermore, significant positive correlation was found between grassland NEP and precipitation, especially in northeastern and central Inner Mongolia, northern Tianshan of Xinjiang, southwestern Tibet, and southern Qinghai Lake.
KeywordsGrassland carbon source/sink Water use efficiency Carbon conversion efficiency BEPS model Return grazing land to grassland
This work was supported by the basic science and advanced technology Fund of Chongqing Scientific Council (cstc2016jcyjA1540), the National Youth Science Fund (41501575, 41701227), Fundamental Research Program of Chongqing Municipal Education Commission (KJQN201800702, KJ1705114), and the National Key R&D Program of China (2018YFD1100301). We also thank the China Meteorological data sharing service system for granting us access to climate datasets. Finally, we would like to thank the technical support of College of Surveying and Geography, Lanzhou Jiaotong University, and Joint Innovation Center for Modern Forestry Studies, College of Biology and the Environment, Nanjing Forestry University.
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