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Nitrogen, lignin, C/N as important regulators of gross nitrogen release and immobilization during litter decomposition in a temperate forest ecosystem

Pei, Guangting, Liu, Jun, Peng, Bo, Gao, Decai, Wang, Chao, Dai, Weiwei, Jiang, Ping, Bai, Edith
Forest ecology and management 2019 v.440 pp. 61-69
biogeochemical cycles, carbon nitrogen ratio, ecological function, forest ecosystems, leaching, lignin, models, nitrogen, nitrogen content, soil, stable isotopes, temperate forests
Litter decomposition plays an important role in nutrient cycling and ecosystem functions. Although litter quality has been considered as an important factor of decomposition rate, how litter quality regulates the gross nitrogen (N) fluxes (release and immobilization) remains unclear. Here, we conducted a field study of litter decomposition using 15N-labeled litter. We found that the temporal patterns of gross N release and immobilization were best described by the one-pool model y=100-a1∗e-k1∗x and y=a2∗(1-e-k2∗x), respectively, which could help us better predict the gross N fluxes during litter decomposition. We also found that litter with higher initial N or lower initial lignin concentration had higher gross N release rate, which is consistent with their effects on litter mass loss. Initial C/N ratio was the most important factor determining gross N immobilization rate. Gross N release was mainly regulated by N concentration during the initial stage (0–0.5 years) of decomposition dominated by leaching process, but was mainly regulated by lignin concentration during the second stage (0.5–2.25 years). Gross N immobilization was positively correlated with N concentration during the initial stage of decomposition, but was positively correlated with C/N ratio during the second stage. Furthermore, litter with higher gross N release rate contributed more to soil N pools and to N losses from the litter-soil system. Our study highlights the different controlling factors of N release and immobilization at different stages of litter decomposition and helps better estimation and management of forest N fluxes and productivity.