Modeling carbon uptake by vegetation of grassland ecosystems and its associated factors in China based on remote sensing

Abstract

In order to reveal the spatial variation characteristics and influencing factors of grassland net primary productivity (NPP) in China, this paper uses remote sensing data, land use data and meteorological data to simulate and estimate China’s grassland net primary productivity from 2001 to 2019 using the Carnegie-Ames-Stanford Approach (CASA). The trend analysis and complex correlation analysis were used to analyze the relationship with the temporal and spatial changes of grassland NPP from the perspectives of climate factors, topography, longitude and latitude. The results show that: 1) In the past 19 years, the China’s grassland NPP has generally shown a fluctuating upward trend, the spatial distribution of NPP variation shows a characteristic of low in the west and high in the east, with the increased area accounting for 70.39% of the total grassland area, and the low NPP values are mainly distributed in the northwestern part of Tibet and Qinghai and the central part of Inner Mongolia, the average annual NPP is 257.13 g C·m−2·a−1. 2) The change of mean NPP value of grassland in China is more dependent on precipitation (p) than air temperature (T). 3) Grassland NPP showed a decreasing trend with the increase of altitude, and the NPP on the gradient with DEM between 200 m and 500 m was the highest (483.86 g·C·m−2·a−1); The maximum annual mean value (448.42 g C·m−2·a−1) is fallen over the sharp slope of 35°–45°; the NPP of grassland increases with the slope (from shade to sunny), and the NPP of grassland on the semi-sunny slope increases. The annual average NPP is the highest (270.87 g C·m−2·a−1). 4) The mean value of grassland NPP was negatively correlated with the change of latitude, and showed a “wave-like” downward trend from south to north; the mean value of grassland NPP was positively related to the change of longitude. The correlation relationship shows a “stepped” upward trend from west to east.