Jing Wang, Lingli Liu, Xin Wang, Sen Yang, Beibei Zhang, Ping Li, Chunlian Qiao, Meifeng Deng, Weixing Liu
The decomposition of dead plant material, such as leaf litter, plays an important role in global carbon and nutrient cycles. Litter in semi-arid ecosystems usually undergoes a prolonged standing dead phase after senescence. Although standing litter constitutes a large fraction of aboveground litter in arid and semi-arid ecosystems, our knowledge of litter decomposition in grasslands is almost exclusively derived from studies on litter that has fallen on the soil surface. We know little about the ways in which abiotic and microbial processes affect standing litter decomposition.
Here, we conducted a 26-month in situ decomposition experiment in a semi-arid grassland in Inner Mongolia, China and a 192-day laboratory incubation experiment. We want to know the potential mechanisms governing the decomposition of standing litter. We also interested in whether the standing stage will affect subsequent litter decomposition and soil organic carbon formation after falling to the soil surface.
We found that standing litter decomposed significantly faster than soil surface litter. This was because standing litter experienced higher night-time humidity than surface litter, which increased litter moisture content and stimulated microbial activity. Standing litter also has higher dissolved organic carbon concentration. The higher dissolved organic carbon concentration, combined with the greater night-time moisture content increased microbial decomposition of standing litter. Moreover, the standing phase conditioned the litter and increased its microbial biodegradability, leading to a more rapid decomposition after the litter fell to the soil surface and increasing the efficiency with which the litter formed soil organic carbon.
We conclude that the long-neglected standing phase greatly determines litter decomposition and soil carbon storage in semi-arid grasslands. Accounting for standing litter decomposition is critical for accurately simulating carbon turnover in these regions.