Does greater molecular diversity in soil organic matter imply greater persistence: Insights from molecular and multi-property analyses in Western China

Chemodiversity of soil organic matter (SOM) is vital for its formation and eco-functions. However, the link between SOM molecular diversity and its persistence across various ecosystems remains unclear. This study investigates the correlation between SOM molecular diversity and persistence in cropland, grassland, and forest ecosystems in western China. We analyzed soil samples and identified 42 parameters related to SOM persistence, which were grouped into six property categories: SOM carbon pools, carbon and nitrogen element properties, optical properties of dissolved organic matter (DOM), DOM molecular size, soil iron oxides, and soil amino acid properties. The persistence index (PI) based on multi-property was calculated using the Hill-number multifunctionality method to describe SOM persistence within each property category. The SOM molecular diversity (i.e., richness index, Shannon index, and evenness index) and complexity derived from topological metrics of molecular network analysis were assessed through pyrolysis products from pyrolysis–gas chromatography–mass spectrometry (Py–GC–MS) and thermally assisted hydrolysis and methylation gas chromatography–mass spectrometry (THM–GC–MS) using tetramethylammonium hydroxide (TMAH) as the methylating agent. The correlations between the PI for each SOM property category, SOM molecular diversity, and network complexity were evaluated. Results demonstrated that forest soils had the highest levels of SOM persistence, chemodiversity, and complexity, with positive correlations between SOM molecular diversity/complexity and its persistence across all ecosystems, most pronounced in forests. This research emphasizes the ecosystem-specific interplay between SOM molecular diversity and persistence, enhancing our understanding of the role of SOM in carbon sequestration and informing strategies for carbon storage and soil health management. In addition, the combined use of Py–GC–MS and THM–GC–MS allowed for a more comprehensive picture of SOM molecular characteristics.