Satellite-based risk assessment: Shifting from macrophyte- to phytoplankton-dominated states in lakes of Yangtze Plain

• A 34-year dataset on algal blooms and aquatic vegetation across Yangtze Plain lakes was generated. • A novel satellite-based framework for ecological risk assessment was proposed. • 85% of lakes face medium-to-high ecological risk, characterized by submerged macrophyte loss or algal proliferation. • Human activities, primarily eutrophication, contributed to 97% of ecological risks. Catastrophic shifts from a macrophyte-dominated state to a phytoplankton-dominated state in shallow lakes have been increasingly observed. Change detection in state variables supports identification or early warnings of such shifts, which can inform restoration efforts or avert a negative transition. However, spatially explicit assessment of lake ecosystem states and shift risks remains methodologically limited. In this study, we proposed an ecological risk assessment framework through monitoring of submerged aquatic vegetation (SAV) and algal blooms (AB) based on remote sensing. We estimated ecosystem resilience on 107 lakes in the Yangtze Plain employing the assessment framework and a long-term dataset of aquatic vegetation (AV) and AB derived from Landsat imagery. The majority of lakes were identified as being at high (25.2 %) and medium (59.8 %) ecological risk of catastrophic shifts, primarily due to anthropogenic drivers (94.4 %). Notably, 33.6 % of lakes (N = 36) exhibited significant SAV decrease over three decades, with AB frequency increasing from affecting 2 lakes (Lakes Taihu and Chaohu) in 1989 to 20 lakes in 2023. Whereas natural factors contributed minimally, human activities not only drove eutrophication and water quality deterioration but also enabled targeted restoration in specific cases. Our framework provides a spatially scalable solution for lake ecological assessment, offering science-informed support for the “Yangtze River’s Great Protection Strategy”.