Analysis reveals the impact of land use types on soil dissolved organic matter transformations, suggesting key influencing factors including total phosphorus and ecological diversity.
Soil dissolved organic matter (SDOM), as the largest active carbon pool in terrestrial ecosystems, understanding its chemical composition and molecular transformation is of great significance for the global carbon cycle. However, due to the inherent complexity and dynamic nature of DOM in different ecosystems, the differences in molecular transformations under different land use types and the main factors affecting the transformations remain unclear. To address this issue, we employed ultrahigh‐resolution Fourier transform ion cyclotron resonance mass spectrometry (FT‐ICR MS) to analyze molecular transformation differences and their influencing factors in SDOM from five land use types: farmland (FL), forest (FR), grassland (GL), urban area (UA), and wetland (WL). The results showed that in human‐affected land use types, the transformations of aliphatic/peptide‐like compounds in FL and condensed aromatic compounds in UA were more abundant than in natural soil systems (FR, GL, and WL); the proportions accounted for 3–5 times and 1.5–100 times those of other land types, respectively. Random forest analysis identified two key factors influencing the intensity of transformation‐related molecules: Total phosphorus (TP) and Shannon index. Increased TP led to a decrease in intensity for unstable molecules involved in transformation, and enhanced Shannon index resulted in increased intensity of stable molecules (lignin compounds and condensed aromatic compounds) but decreased intensity of unstable molecules (aliphatic/peptide compounds). Compared to molecular intrinsic characteristics, the influence of external environmental factors on SDOM molecular transformation cannot be overlooked. Our findings highlight the importance of external environmental factors and chemodiversity in influencing molecular transformations, providing new insights for understanding the dynamic changes in soil carbon pools.
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Mao et al. (2025) studied this question.
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