Accurate estimation of forest biomass C stock is essential to understand carbon cycles. However, current estimates of Chinese forest biomass are mostly based on inventory-based timber volumes and empirical conversion factors at the provincial scale, which could introduce large uncertainties in forest biomass estimation. Here we provide a data-driven estimate of Chinese forest aboveground biomass from 2001 to 2013 at a spatial resolution of 1 km by integrating a recently reviewed plot-level ground-measured forest aboveground biomass database with geospatial information from 1-km Moderate-Resolution Imaging Spectroradiometer (MODIS) dataset in a machine learning algorithm (the model tree ensemble, MTE). We show that Chinese forest aboveground biomass is 8.56 Pg C, which is mainly contributed by evergreen needle-leaf forests and deciduous broadleaf forests. The mean forest aboveground biomass density is 56.1 Mg C ha−1, with high values observed in temperate humid regions. The responses of forest aboveground biomass density to mean annual temperature are closely tied to water conditions; that is, negative responses dominate regions with mean annual precipitation less than 1300 mm y−1 and positive responses prevail in regions with mean annual precipitation higher than 2800 mm y−1. During the 2000s, the forests in China sequestered C by 61.9 Tg C y−1, and this C sink is mainly distributed in north China and may be attributed to warming climate, rising CO2 concentration, N deposition, and growth of young forests.
College of Urban and Environmental Sciences, Peking University, Beijing, China;College of Urban and Environmental Sciences, Peking University, Beijing, China;College of Urban and Environmental Sciences, Peking University, Beijing, China;Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China;College of Urban and Environmental Sciences, Peking University, Beijing, China;College of Urban and Environmental Sciences, Peking University, Beijing, China;Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
Recommended Citation:
Guodong Yin,Yuan Zhang,Yan Sun,et al. MODIS Based Estimation of Forest Aboveground Biomass in China[J]. PLOS ONE,2015-01-01,10(6)