The impact of agricultural land use on the linkages between soil microbial communities and agroecosystem functioning is depth-dependent

文献类型： 外文期刊

第一作者： Cao, Wenchao

作者： Cao, Wenchao;Zou, Yukun;Shan, Ying;Wang, Jinchuang;Li, Gang;Singh, Brajesh Kumar;Singh, Brajesh Kumar

作者机构：

关键词： Deep soil; Soil organic carbon; C mineralization; Net N mineralization; Soil microorganisms; Extracellular enzyme activities

期刊名称：AGRICULTURE ECOSYSTEMS & ENVIRONMENT （ 影响因子：6.4； 五年影响因子：6.8 ）

ISSN： 0167-8809

年卷期： 2025 年 379 卷

页码：

收录情况： SCI

摘要： Soil carbon (C) and nitrogen (N) mineralization rates are critical indicators of ecosystem functioning in agricultural land. However, the effects of agricultural land use on the interactions between soil C and N mineralization at different soil depths, especially in tropical regions, are poorly understood. Here, a longan orchard (LO) was converted to a conventional tea plantation (CTP) and an organic tea plantation (OTP) in the tropical region of China, and the responses of fungal and bacterial communities to these changes were assessed. The characteristics of the microbial communities, enzyme activities, and N and C mineralization rates were evaluated in response to the changes in land use. It was found that LO and OTP had faster N and C mineralization rates than CTP in surface soil. However, in subsurface soil, LO and OTP showed a faster C mineralization rate and a slower N mineralization rate than CTP. Structural equation modeling revealed that pH and C/N were the most crucial factors affecting N and C mineralization rates in surface soil. In contrast,soil bacterial and fungal community structures were the principal drivers of both the C and N mineralization in subsurface soil. Although soil C and net N mineralization were positively correlated in surface soil, this was not seen in subsurface soil. Collectively, this study demonstrated that differential drivers and their effects on the interactions between soil C and N mineralization at different soil depths should be considered for more accurate prediction of soil C and N dynamics under land-use changes.

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