An Integrative Approach to Study How Driving Factors Control Biomass Carbon Density for Natural Mountain Forests, in China’s Loess Plateau

Abstract

Mountain forests, accounting for 84.95% of the total forest area, are the most important part of the natural vegetation in China. An assessment of the factors affecting the carbon capture capacity of mountain forests is very crucial to realizing the nation’s goal of capping carbon-emissions growth by 2030. Based on the 9th national forest inventory data in the eastern Loess Plateau of China, which is mountainous terrain, we characterized the spatial pattern of biomass carbon density (BCD) for natural coniferous and broad-leaved forests using Local Getis-ord G* and proposed an integrative framework to evaluate the direct and indirect effects of stand, geographical and climatic factors on BCD for the two types of forests using structural equation modeling. The results showed that there was no significant difference between the mean BCDs of the natural coniferous and broad-leaved forests. Compared with broad-leaved forests, the hot spots of BCDs at the 1% significance level for coniferous forests were located in areas with higher average latitude, higher average elevation, lower mean temperature, or lower mean precipitation. Stand age and elevation were important driving factors, which had stronger effects for the coniferous forests than broad-leaved forests. Among all driving factors, age had the strongest total effect for the two forests types. No significant difference was detected in BCDs between natural coniferous and broad-leaved forests. Spatial patterns of BCDs were different between the two forests types. Stand age and elevation were important driving factors, which had stronger effects for the coniferous forests than broad-leaved forests.