Estimation of Forest Biomass and Carbon Storage in China Based on Forest Resources Inventory Data

Forests are important in the global carbon cycle and it is necessary to quickly and accurately measure forest volume to estimate forest aboveground biomass (AGB) and aboveground carbon storage (AGC). In this paper, we used data from the eighth forest resources inventory of China to establish two stand volume models based on stand density and forest basal area for 37 arbor forest types (dominant species); and performed a comparative analysis to obtain the best model. Then the AGB, AGB density, AGC, and AGC density of the different forest types and regions were estimated by conversion function methods. The results showed that: (1) The volume model of tree height and forest basal area could better fit the natural growth process of forests, and 36 of the 37 forest types had R2 greater than 0.8; (2) The average AGB density of arbor forest in China was 95.03 Mg ha−1 and the average AGC density was 48.15 Mg ha−1 (3) Among forest types, Picea asperata Mast., Quercus spp., and Populus spp. had the highest AGB and AGC, while Cinnamomum camphora (L.) Presl, Pinus taiwanensis Hayata, and Pinus densiflora Sieb. et Zucc. had the lowest. The AGB density and AGC density of Phoebe zhennan S. Lee et F. N. Wei and Pinus densata Mast. were the highest, while those of Pinus densiflora Sieb. et Zucc., Pinus elliottii Engelmann, and Eucalyptus robusta Smith were the lowest. (4) Among regions, AGB and AGC ranging from high to low, were as follows: northwest, southwest, northeast, central south, east, and north. The northwest and southwest regions accounted for more than 70% of the country’s AGB and AGC. The average AGB density and AGC density among the regions were 91.34 Mg ha−1 and 46.4 Mg ha−1, respectively. Ranging from high to low as follows: southwest, northwest, northeast, east, central south, and north. The methods used in this paper provide a basis for fast and accurate estimation of stand volume, and the estimates of AGB and AGC have important reference value for explaining the role of ecosystems in coping with global climate change in China.