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Chinese Journal of Ecology ›› 2023, Vol. 42 ›› Issue (3): 561-568.doi: 10.13292/j.1000-4890.202303.032

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Variations of mean residence time of organic carbon pools in red paddy soil in a typical area in recent 10 years.

WANG Xiyang1,2, LI Xiaohui1,2, XIN Zaijun1,2, HE Shifu1,2, SUN Xiaoyan1,2, LI Liang1,2*   

  1. (1Institute of Microbiology, Jiangxi Academy of Sciences, Nanchang 330096, China; 2Jiangxi Institute of Watershed Ecology, Nanchang 330096, China).
  • Online:2023-03-10 Published:2023-03-06

Abstract: It is crucial to understand the spatiotemporal variations of mean residence time (MRT) of soil organic carbon (SOC) pool for taking effective measures to enhance carbon sink of agricultural ecosystems. In this study, a new round of soil sample collection was carried out based on historical sampling information, and a 100 d incubation experiment was carried out. Then, the data were fitted to a three-pool first-order kinetics model to estimate the MRT of active SOC pool (MRTa) and slow SOC pool (MRTs). We analyzed the spatiotemporal variations and the influencing factors of MRTa and MRTs in surface paddy soil in Dongxiang of Jiangxi Province from 2009 to 2019. The results showed that the MRTa and MRTs of paddy soil in Dongxiang in 2019 were 26.5 days and 14.1 years, respectively, both of which showed no significant changes compared with that in 2009. The active and slow SOC pools in the southern Dongxiang were generally more stable than the other areas. There were obvious spatiotemporal variations both in MRTa and MRTs in red paddy soil in Dongxiang, with the variation ranges of -1.3%-544.5% and -6.7%-1375.5%, respectively. Such variations were partly due to the spatial differences in the proportion of active and slow SOC pools in the total SOC. Compared with other rice-growing areas in southern China, the SOC pool of red paddy soil in Dongxiang was more stable in recent 10 years, despite substantial spatial variation.


Key words: red paddy soil, active soil organic carbon pool, slow organic carbon pool, mean residence time, spatiotemporal variation.