Deepened snow loosens temporal coupling between plant and microbial N utilization and induces ecosystem N losses
Zhou Jia, Ping Li, Yuntao Wu, Pengfei Chang, Meifeng Deng, Lu-Yin Liang, Sen Yang, Chengzhang Wang, Bin Wang, Lu Yang, Xin Wang, Zhenhua Wang, Ziyang Peng, Lulu Guo, Jitendra Ahirwal, Weixing Liu, Lingli Liu
Abstract
Abstract Seasonal differences in plant and microbial nitrogen (N) acquisition are believed to be a major mechanism that maximizes ecosystem N retention. There is also a concern that climate change may interrupt the delicate balance in N allocation between plants and microbes. Yet, convincing experimental evidence is still lacking. Using a 15 N tracer, we assessed how deepened snow affects the temporal coupling between plant and microbial N utilization in a temperate Mongolian grassland. We found that microbial 15 N recovery peaked in winter, accounting for 22% of the total ecosystem 15 N recovery, and then rapidly declined during the spring thaw. By stimulating N loss via N 2 O emission and leaching, deepened snow reduced the total ecosystem 15 N recovery by 42% during the spring thaw. As the growing season progresses, the 15 N released from microbial biomass was taken up by plants, and the competitive advantage for N shifted from microbes to plants. Plant 15 N recovery reached its peak in August, accounting for 17% of the total ecosystem 15 N recovery. The Granger causality test showed that the temporal dynamics of plant 15 N recovery can be predicted by microbial 15 N recovery under ambient snow but not under deepened snow. In addition, plant 15 N recovery in August was positively correlated with and best explained by microbial 15 N recovery in March. The lower microbial 15 N recovery under deepened snow in March reduced plant 15 N recovery by 73% in August. Together, our results provide direct evidence of seasonal differences in plant and microbial N utilization that are conducive to ecosystem N retention; however, deepened snow disrupted the temporal coupling between plant–microbial N use and turnover. These findings suggest that changes in snowfall patterns may significantly alter ecosystem N cycling and N‐based greenhouse gas emissions under future climate change. We highlight the importance of better representing winter processes and their response to winter climate change in biogeochemical models when assessing N cycling under global change.