Interactive effects of warming and managements on carbon fluxes in grasslands: A global meta-analysis

文献类型： 外文期刊

第一作者： Shi, Lina

作者： Shi, Lina;Lin, Zhenrong;Peng, Cuoji;Yao, Zeying;Xiao, Qing;Liu, Kesi;Shao, Xinqing;Tang, Shiming;Yao, Zeying;Zhou, Huakun

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关键词： Carbon fluxes; Climatic warming; Grassland management; Interaction; Meta-analysis

期刊名称：AGRICULTURE ECOSYSTEMS & ENVIRONMENT （ 影响因子：6.576； 五年影响因子：7.088 ）

ISSN： 0167-8809

年卷期： 2022 年 340 卷

页码：

收录情况： SCI

摘要： The prediction of future carbon(C) dynamics of grassland ecosystems requires knowledge of how warming and management practices (e.g., fertilization, grazing, and mowing) interact to affect C fluxes. In this study, we synthesized experimental data extracted from 350 observations from 64 publications to quantify the direction and magnitude of individual and interactive effects between climatic warming and grassland management practices on seven variables related to C fluxes. Warming significantly enhanced gross primary productivity (GPP) and ecosystem respiration (ER) by 9.81% and 16.43%, respectively. Similarly, fertilization significantly increased GPP, net primary productivity (NPP), aboveground net primary productivity (ANPP), ER, and net ecosystem exchange (NEE) by 29.51%, 24.79%, 33.52%, 21.81%, and 33.89%, respectively. In contrast, grazing and mowing reduced ANPP by 19.95% and 22.83%, respectively. Furthermore, the combination of warming and fertilization significantly increased GPP and ANPP by 38.09% and 22.89%, respectively. More importantly, the results showed that additive interactions dominated the response of most of the studied variables, while synergistic interactions were found only for ANPP and ER to warming and fertilization. The responses of C fluxes to warming and management were strongly dependent on the environmental factors, experimental duration, and grassland types. Our meta-analysis highlights the importance of the interactions between warming and management on ecosystem C exchange. Therefore, incorporating these key interactions into future prediction models should enhance the accuracy of prediction of future climate change impacts on grassland ecosystems and inform the development of sustainable grassland management strategies.

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