Substantial but highly variable diffusive methane emissions from eutrophic shallow lakes

Lakes are critical natural methane (CH₄) emitters, yet their emissions magnitude remains highly uncertain due to complex regulatory factors in human-dominated regions. To address this knowledge gap, the diffusive CH₄ emissions and their drivers in heavily human-impacted shallow eutrophic lakes of China's eastern plain were investigated via integrating long-term field measurements and laboratory incubations with isotopic trajectories. Results showed that diffusive CH₄ emissions were significant but exhibited substantial variability. The emissions were 2.1 times higher in the wet period (0.21 ± 0.13 mmol m^-2 d^-1) than in the dry period (0.10 ± 0.06 mmol m^-2 d^-1), consistent with greater sediment CH₄ production rates, elevated water temperatures, higher chlorophyll-a (a proxy for algal biomass), and increased dissolved organic carbon. CH₄ emissions span one order of magnitude (0.04 ± 0.01 to 0.40 ± 0.39 mmol m^-2 d^-1) across lakes, driven by strong gradients in autochthonous (algal-derived) and allochthonous (soil-derived) organic carbon inputs, and likely associated with highly variable sediment CH₄ production modulated by eutrophication status. Further analysis revealed a seasonal shift in dominant drivers, chlorophyll-a (representing algal-derived carbon) dominated dry-period emissions, while dissolved organic carbon (primarily allochthonous such as soil-derived) regulated emissions in wet period. These observations were supported by incubations showing both algal- and soil-derived organic matter produced large CH₄ via degradation. Random forest modeling identified chlorophyll-a as the top predictors of diffusive emissions, and the carbon isotope fractionation factor derived from incubations and field measurements suggested the dominant role of acetoclastic methanogenic pathway in CH₄ production of algal-dominated lakes. Our findings likely provide a mechanistic framework for estimating CH₄ emissions and predicting their future variability in human-impacted shallow lakes.