River network size-dependent chemodiversity of dissolved organic matter and its driving factors in a multi-tributary...

Understanding the spatiotemporal distribution patterns of riverine dissolved organic matter (DOM) and its longitudinal control mechanisms is crucial to global carbon cycling and aquatic ecosystem health. However, the geographical distribution patterns of DOM chemodiversity across river networks and their environmental drivers remain poorly understood. To address this gap, this study focused on the upper Hanjiang River network. We collected samples from 132 sites across two seasons and employed Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS), along with multiple environmental analyses, including geographic, climatic, hydro-geomorphic, land use, and water quality parameters. The molecular and elemental composition of DOM remained stable along the river, dominated by lignin-like compounds (76.65 %-79.01 %) and CHO compounds (65.49 %-70.51 %) in both spring and autumn. Notably, river network size significantly influenced DOM composition, with large networks showing higher CHOS/CHONS abundances and small networks exhibiting elevated CHO/CHOP levels. Increasing cumulative dendritic distance upstream significantly promoted DOM richness and diversity, particularly for functional diversity indices including C/N ratio and AI_mod. Water quality was the primary driver of DOM chemodiversity, while synergistic effects of multiple factors further explained variations in DOM molecular composition. The structural equation modeling demonstrated that geographical and hydrological factors directly and indirectly (via water quality) shaped DOM functional diversity (e.g., FD_Q(NOSC)). Eutrophic areas led to DOM homogenization, whereas small networks exhibited higher spatial heterogeneity that resulted from localized environmental forcing and anthropogenic perturbations. Additionally, forested watersheds had more aromatic, recalcitrant DOM, whereas urbanization shifted DOM toward more labile, aliphatic compounds. These findings highlight the necessity of integrating multi-factor interaction models to accurately predict DOM transformation processes in fluvial systems.