%A Jian Sun, Shuli Niu, Jinniu Wang %T Divergent biomass partitioning to aboveground and belowground across forests in China %0 Journal Article %D 2018 %J J Plant Ecol %R 10.1093/jpe/rtx021 %P 484-492 %V 11 %N 3 %U {https://www.jpe.ac.cn/CN/abstract/article_28998.shtml} %8 2018-03-06 %X Aims Belowground to aboveground biomass (BGB/AGB) ratio is a highly valued parameter of the terrestrial carbon cycle and productivity. However, it remains far from clear whether plant biomass partitioning to aboveground and belowground is isometric (equal partitioning) or allometric (unequal partitioning) at community levels and what factors are necessary in order to regulate the partitioning. This study aimed to comprehensively find out the patterns of biomass partitioning and their regulatory factors across forests in China.
Methods The data of AGB and BGB were compiled from 1542 samples for communities across forests in China. Standardized major axis regression was conducted to examine whether AGB and BGB were allocated isometrically or allometrically at a community level. Redundancy analysis was used to analyze the relationships of BGB/AGB ratio with climatic factors and soil properties.
Important findings We found that the slopes of the relationship between logAGB and logBGB were not always comparable to 1.0 (isometric allocation) at community levels, including primary forest, secondary forest, and planted forest. Meanwhile, samples in clay, loam, and sand soil types also presented the same phenomenon. Furthermore, the radically different allocations of AGB and BGB were found in northern and southern China. Environmental factors totally explained 3.86% of the variations in the BGB/AGB ratio at the community level, which include the mean annual precipitation, mean annual temperature, potential water deficit index, soil carbon content, soil nitrogen content, soil clay, soil loam, soil sand, soil pH, and soil bulk density. In addition, the environmental factors also have effects on the BGB/AGB ratio in other categories. The patterns revealed in this study are helpful for better understanding biomass partitioning and spreading the carbon circle models.