Linking the soil carbon pool management index to ecoenzymatic stoichiometry and organic carbon functional groups in abandoned land under climate change

土壤碳 降水 总有机碳 环境化学 环境科学 高原(数学) 化学 碳纤维 生物量(生态学) 黄土高原 土壤水分 土壤科学 生态学 数学分析 材料科学 复合材料 气象学 物理 复合数 生物 数学
作者
Xing Wang,Fang Chen,Jianjian Liu,Zhengchen Wang,Zhenjiao Zhang,Xiangyang Li,Qi Zhang,Weichao Liu,Hanyu Liu,Jia Zeng,Chengjie Ren,Gaihe Yang,Zekun Zhong,Xinhui Han
出处
期刊:Catena [Elsevier BV]
卷期号:235: 107676-107676 被引量:25
标识
DOI:10.1016/j.catena.2023.107676
摘要

Ongoing, multifaceted climate change impacts soil carbon (C) dynamics, with serious possible consequences on terrestrial C cycling. Using a three-year manipulative experiment in abandoned land on the Loess Plateau of China, we examined the effects of in situ warming and altered precipitation (ranging from 50% reduction to 50% increases in precipitation) on different fractions of the soil organic C (SOC), the C pool management index (CPMI), ecoenzymatic stoichiometry, and SOC functional groups. Our results showed that SOC, readily oxidizable organic C, dissolved organic C, particulate organic C, and microbial biomass C exhibited an increasing trend with increasing precipitation, whereas warming had no significant effect. This response pattern also led to an increase in the CPMI with increasing precipitation. The ecoenzymatic vector model indicated that microbial C limitation decreased with increasing precipitation. In addition, the proportion of labile poly-alcoholic C and aliphatic C increased with precipitation gradient, while recalcitrant aromatic C and carboxylic C decreased. The CPMI correlated negatively with microbial C limitation and positively with labile SOC functional groups. Structural equation modeling and relative importance analyses further indicated that microbial C-limitation and labile SOC functional groups are important factors mediating the CPMI but have opposite effects. Overall, these findings considerably advance our understanding of the links between the soil CPMI and both microbial elemental limitations and SOC chemical composition, providing new insight for the accurate prediction of soil C dynamics under changing environments.
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