数字农科院2.0

Impact of soil moisture regimes on greenhouse gas emissions, soil microbial biomass, and enzymatic activity in long-term fertilized paddy soil

文献类型： 外文期刊

作者： Asad Shah;Jing Huang;Tianfu Han;Muhammad Numan Khan;Kiya Adare Tadesse;Nano Alemu Daba;Sajeela Khan;Sami Ullah;Muhammad Fahad Sardar;Shah Fahad;Huimin Zhang

作者机构：

关键词： Greenhouse gas emissions;Long-term fertilization;Microbial biomass stoichiometry;Moisture content;Soil enzymes

期刊名称： Environmental Sciences Europe

ISSN： 2190-4707

年卷期： 2024 年 36 卷 1 期

页码：

收录情况： SCIE（2024版） ; ; EI（2024版）

摘要： Two potent greenhouse gases that are mostly found in agricultural soils are methane and nitrous oxide. Therefore, we investigated the effect of different moisture regimes on microbial stoichiometry, enzymatic activity, and greenhouse gas emissions in long-term paddy soils. The treatments included a control (CK; no addition), chemical fertilizer (NPK), and NPK + cattle manure (NPKM) and two moisture regimes such as 60% water-filled pore spaces (WFPS) and flooding. The results revealed that 60% water-filled pore spaces (WFPS) emit higher amounts of N2O than flooded soil, while in the case of CH4 the flooded soil emits more CH4 emission compared to 60% WFPS. At 60% WFPS higher N2O flux values were recorded for control, NPK, and NPKM which are 2.3, 3.1, and 3.5 µg kg−1, respectively. In flooded soil, the CH4 flux emission was higher, and the NPKM treatment recorded the maximum CH4 emissions (3.8 µg kg−1) followed by NPK (3.2 µg kg−1) and CK (1.7 µg kg−1). The dissolved organic carbon (DOC) was increased by 15–27% under all flooded treatments as compared to 60% WPFS treatments. The microbial biomass carbon, nitrogen, and phosphorus (MBC, MBN, and MBP) significantly increased in the flooded treatments by 8–12%, 14–21%, and 4–22%, respectively when compared to 60% WFPS. The urease enzyme was influenced by moisture conditions, and significantly increased by 42–54% in flooded soil compared with 60% WFPS while having little effect on the β-glucosidase (BG) and acid phosphatase (AcP) enzymes. Moreover DOC, MBC, and pH showed a significant positive relationship with cumulative CH4, while DOC showed a significant relationship with cumulative N2O. In the random forest model, soil moisture, MBC, DOC, pH, and enzymatic activities were the most important factors for GHG emissions. The PLS-PM analysis showed that soil properties and enzymes possessed significantly directly impacted on CH4 and N2O emissions, while SMB had indirect positive effect on CH4 and N2O emissions.

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