Seasonal and depth-dependent dynamics of molecular properties of lake dissolved organic matter during chlorophyll-a production and depletion

• Dynamic response mechanism of lake DOM molecules to Chl-a production and depletion • FT-ICR MS with machine learning visualized the season-/depth-dependent DOM molecules • Molecules positively correlated with Chl‑a (+MFs*) accumulated in the production stage • Abundance of –MFs* negatively correlated with Chl‑a increased in the depletion stage • DOM +MFs* were characterized by high saturation, low aromaticity and small weight • Seasonal shifts and depth gradients drove the changes in lake Chl-a and DOM molecules The molecular properties of dissolved organic matter (DOM) are closely tied to diverse biogeochemical processes and are fundamental to aquatic ecosystem function. However, how changes in lake DOM molecular composition relate to chlorophyll a (Chl‑a) dynamics remains poorly understood. Here, we examine the seasonal and depth-dependent dynamics of DOM molecular properties during Chl-a production and depletion and propose a dynamic response mechanism linking DOM molecules to Chl-a variability using Fourier-transform ion cyclotron resonance mass spectrometry and machine-learning analysis. During the Chl‑a production stage (June‒August), molecular formulas positively correlated with Chl‑a (+MFs*) accumulated, and these +MFs* were characterized by high saturation, low aromaticity, low carbon content, and small molecular weight. +MFs* were most abundance in surface waters (0‒5 m) and progressively increase at shallow (10‒20 m) and deep (30‒70 m) depths as the season advanced. During the Chl-a depletion stage (October‒March), depletion of +MFs* exceeded their production rate, and the abundance of –MFs* negatively correlated with Chl‑a increased. Thermal inversion and mixing homogenized +MFs*/–MFs* while retaining depth-specific signatures and facilitating the downward redistribution of surface +MFs*. Seasonal shifts and depth gradients drove changes in Chl-a, which modulated the diversity and complexity of DOM molecules. These findings provide a process-based framework linking DOM molecular properties to Chl-a dynamics and inform predictive lake assessment and management.