Nonlinear responses of ecosystem carbon fluxes to precipitation change in a semiarid grassland

文献类型： 外文期刊

第一作者： Chai, Hua

作者： Chai, Hua;Li, Jie;Zhou, Xuhui;Chai, Hua;Li, Junqin;Meng, Bo;Wang, Chengliang;Sun, Wei;Ma, Jianying;Zhang, Jinwei;Pan, Duofeng

作者机构：

关键词： ecosystem carbon fluxes; altered precipitation; nonlinear responses; precipitation gradient; semiarid grasslands

期刊名称：FRONTIERS IN PLANT SCIENCE （ 影响因子：4.8； 五年影响因子：5.7 ）

ISSN： 1664-462X

年卷期： 2025 年 16 卷

页码：

收录情况： SCI

摘要： Carbon (C) fluxes in semiarid grasslands subject to precipitation variability play a critical role in the terrestrial C cycle. However, how ecosystem C fluxes respond to variability in precipitation (both decreases and increases precipitation along a gradient) remains unclear. In this study, we conducted a three-year field experiment in a semiarid grassland, with six precipitation treatments (precipitation decreased by 70%, 50%, and 30% [P-70%, P-50%, and P-30%], natural precipitation [P+0%], and precipitation increased by 30% and 50% [P+30% and P+50%]) to examine how variations in precipitation influence ecosystem C fluxes, specifically focusing on gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem CO2 exchange (NEE). We found that both decreased and increased precipitation significantly altered the GEP (from -26% to 14%), but only decreased precipitation significantly reduced the ER and NEE (from 1% to 31%), relative to their values during natural precipitation. This suggests that ecosystem C fluxes are more sensitive to decreased precipitation, and respond nonlinearly to the precipitation gradient. Furthermore, structural equation modeling indicated that the soil water content was the primary controlling factor driving changes in ecosystem C fluxes. Our research underscores the nonlinear response of ecosystem C fluxes to changes in precipitation within semiarid ecosystems, particularly their sensitivity to extreme drought. Considering this nonlinear response, it is crucial to improve dynamic models of the C cycle and predict ecosystem responses to precipitation variability.

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