饱和(图论)
土壤水分
土壤碳
土壤科学
总有机碳
环境科学
碳纤维
矿物
地质学
环境化学
地球科学
化学
材料科学
数学
组合数学
复合数
复合材料
有机化学
作者
Yuedong Liu,Yanan Huang,Batande Sinovuyo Ndzelu,Ruixing Hou
出处
期刊:Catena
[Elsevier BV]
日期:2025-08-25
卷期号:259: 109391-109391
被引量:3
标识
DOI:10.1016/j.catena.2025.109391
摘要
• MAOC comprised 40.84–86.93% of SOC, varying spatially with illite and SSA. • Oxidation depleted hydroxyl-C, enriching 13 C and polysaccharide-C in remaining MAOC. • The chemical stability of MAOC was predominantly governed by carbon saturation level. The stability of mineral-associated organic carbon (MAOC) serves as a critical determinant of long-term soil organic carbon (SOC) preservation, predominantly governed by mineral-organic binding interactions. However, the regulatory mechanisms of mineral composition and initial carbon saturation level (CSL) on MAOC stability remain poorly understood. In this study, we selected six forest soils from three climatic zones in China, and simulated microbial oxidative degradation using hydrogen peroxide (H 2 O 2 ) to investigate MAOC chemical stability. The results showed that MAOC contributed 40.84–86.93% of SOC, with spatial variation influenced by the illite content and specific surface area. The remaining MAOC (r-MAOC) after treatment accounted for 25.32–86.66% of MAOC and the oxidation-resistant efficiency was significantly correlated with CSL and clay content. During oxidation MAOC preferentially lost a high proportion of plant-derived organic carbon with relatively weak binding to the mineral surfaces like hydroxyl carbon (1.43–22.10%), while microbial-derived polysaccharide carbon significantly increased by 0.48–19.64%. Under unsaturated conditions, higher CSL levels corresponds with increased MAOC stability, implying that organic matter preferentially binds to and stabilizes on vacant mineral sites. The partial least squares path model (PLS-PM) and random forest model (RFM) analysis indicated that CSL and mineral composition were key determinants of MAOC stability (0.79 and 0.41). This study provides theoretical insights into predicting forest soil carbon stability and contributes to improving global carbon cycle modeling by refining MAOC dynamics.
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