Aboveground net primary productivity and carbon balance remain stable under extreme precipitation events in a semiarid steppe ecosystem

Autor: Wenjie Liu, Xiaoyong Cui, Xiaoqi Zhou, Linyuan Li, Lili Jiang, Yanfen Wang, Cheng-Yuan Xu, Yanbin Hao, X.M. Kang, C.T. Zhou
Rok vydání: 2017
Předmět:
Zdroj: Agricultural and Forest Meteorology. :1-9
ISSN: 0168-1923
DOI: 10.1016/j.agrformet.2017.03.006
Popis: Global climate change is projected to increase both the intensity and frequency of extreme precipitation events (EPEs), which are considered to have stronger impacts on ecosystem functions than gradual changes in mean precipitation conditions. In this study, a consecutive 20-day extreme precipitation event (282 mm) was applied during the mid- and late-growing season periods in a semiarid steppe for three years to investigate the effects of extreme large precipitation events on aboveground net primary productivity (ANPP) and ecosystem carbon dioxide (CO 2 ) fluxes, including net ecosystem carbon absorption (NEE), gross primary productivity (GPP) and ecosystem respiration (Re). Although soil moisture was significantly increased by extreme precipitation, and even exceeded field capacity during the treatment periods, ANPP remained stable across all the treatments. There was also little change in mean growing season ecosystem CO 2 fluxes under the two precipitation treatments, despite GPP rates decreased by 34.4 and 26.3%, and NEE rates were suppressed by 77 and 68% during the mid- and late-season treatment periods, respectively. The stable CO 2 fluxes could be attributed to the recovery of GPP and NEE in 7 and 12 days after the end of EPEs. Our study demonstrated that both ANPP and CO 2 fluxes in this semiarid steppe were very stable in the face of extreme large precipitation events, regardless of the timing of events occur. Nevertheless, future, long-term studies need to investigate the potential tipping points or thresholds for ecosystem function shifts, as an increasing occurrence of EPEs has been forecasted in future climate change scenarios.
Databáze: OpenAIRE