Grazing intensity significantly affects belowground carbon and nitrogen cycling in grassland ecosystems: a meta‐analysis

放牧 环境科学 草原 生态系统 自行车 农学 土壤碳 氮气循环 生物量(生态学) 碳循环 土壤呼吸 陆地生态系统 生态学 氮气 生物 土壤水分 土壤科学 林业 地理 化学 有机化学
作者
Guiyao Zhou,Xuhui Zhou,Yanghui He,Junjiong Shao,Zhenhong Hu,Ruiqiang Liu,Huimin Zhou,Shahla Hosseini Bai
出处
期刊:Global Change Biology [Wiley]
卷期号:23 (3): 1167-1179 被引量:455
标识
DOI:10.1111/gcb.13431
摘要

Abstract Livestock grazing activities potentially alter ecosystem carbon (C) and nitrogen (N) cycles in grassland ecosystems. Despite the fact that numerous individual studies and a few meta‐analyses had been conducted, how grazing, especially its intensity, affects belowground C and N cycling in grasslands remains unclear. In this study, we performed a comprehensive meta‐analysis of 115 published studies to examine the responses of 19 variables associated with belowground C and N cycling to livestock grazing in global grasslands. Our results showed that, on average, grazing significantly decreased belowground C and N pools in grassland ecosystems, with the largest decreases in microbial biomass C and N (21.62% and 24.40%, respectively). In contrast, belowground fluxes, including soil respiration, soil net N mineralization and soil N nitrification increased by 4.25%, 34.67% and 25.87%, respectively, in grazed grasslands compared to ungrazed ones. More importantly, grazing intensity significantly affected the magnitude (even direction) of changes in the majority of the assessed belowground C and N pools and fluxes, and C : N ratio as well as soil moisture. Specifically,light grazing contributed to soil C and N sequestration whereas moderate and heavy grazing significantly increased C and N losses. In addition, soil depth, livestock type and climatic conditions influenced the responses of selected variables to livestock grazing to some degree. Our findings highlight the importance of the effects of grazing intensity on belowground C and N cycling, which may need to be incorporated into regional and global models for predicting effects of human disturbance on global grasslands and assessing the climate‐biosphere feedbacks.
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