Ecosystem-level warming reduces microbial necromass in the topsoil but not in deeper soil of a subtropical forest

Rising temperatures in subtropical regions pose a significant challenge to soil carbon (C) storage. Microbial necromass is an important contributor to the persistent soil C pool, yet little is known about its responses to warming in subtropical forest ecosystems. Here, we executed an 8-year continuo...

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Main Authors: Xujun Liu, Peter B. Reich, Chao Liang, Meijuan Xiao, Gangsheng Wang, Guoyi Zhou, Kristiina Karhu, Zhiyang Lie, Ting Wu, Shuyidan Zhou, Zuzheng Li, Junhua Yan, Xuli Tang, Guowei Chu, Shizhong Liu, Ze Meng, PingPing Xu, Qianmei Zhang, Zhanfeng Liu, Juxiu Liu
Format: Article
Language:English
Published: Elsevier 2025-06-01
Series:Geoderma
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Online Access:http://www.sciencedirect.com/science/article/pii/S0016706125001740
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Summary:Rising temperatures in subtropical regions pose a significant challenge to soil carbon (C) storage. Microbial necromass is an important contributor to the persistent soil C pool, yet little is known about its responses to warming in subtropical forest ecosystems. Here, we executed an 8-year continuous sampling campaign in a subtropical forest ecosystem-level passive warming experiment (+0 °C, +1.0 °C and +2.1 °C). We observed a decline in soil microbial necromass C under higher temperatures. +2 °C warming significantly reduced the topsoil (0–10 cm) microbial necromass C by 23 %, partially due to the decreased soil nitrogen caused by the elevated nitrogen requirements of plant growth, as well as the soil drying and decrease in microbial biomass. However, we found that the subsoil (10–40 cm) microbial necromass C was unchanged under warming. Random forest analysis and structural equation models suggested that this attenuated effect with soil depth was primarily attributed to the enhanced mineral protection in deeper soil and more stable microbial composition in deeper soil. The depth-dependent temperature response of microbial necromass should be considered in Earth system models to obtain accurate predictions of climate change impacts on subtropical forests.
ISSN:1872-6259