Enhanced Ulva prolifera blooms induced by moderate salinity and a multi-variable integrated risk assessment in...

Over the past decades, coastal regions worldwide have experienced increasing eutrophication driven by persistent terrestrial nutrient influx, leading to widespread macroalgal blooms. Among these, Ulva prolifera green tides in the Yellow Sea have emerged as the largest recorded events globally, posing severe ecological and environmental challenges. While nutrient enrichment has been extensively studied as a key driver, the role of moderate salinity conditions, particularly influenced by winter Yangtze River runoff, remains underexplored. This study investigated the relationship between salinity levels and U. prolifera growth, with a focus on cross-seasonal hydrological dynamics that promote bloom risks. Through controlled indoor experiments, we demonstrated a significant negative correlation between salinity and U. prolifera growth rate within a refined moderate salinity range. Numerical simulations and observational data revealed that over 80 % of winter freshwater input to the Subei coastal region originated from the Yangtze River, where early winter runoff strongly correlated with the Maximum Distribution Area (MDA) of U. prolifera in the subsequent summer. Sensitivity experiments confirmed that the combination of increased Yangtze River discharge and weakened winter northerly wind stress fosters persistent moderate salinity environments, creating favorable conditions for green tide proliferation. A linear least-squares regression model, incorporating winter runoff and wind stress predictors, achieved a high correlation (R² = 0.89) with observed MDA values, providing a novel tool for bloom risk assessment. Our findings emphasize that winter Yangtze River runoff played a critical role in maintaining moderate salinity conditions that drive U. prolifera blooms in the Yellow Sea. By advancing the understanding of cross-seasonal hydrological processes, this study offers dynamic insights and innovative approaches for predicting and mitigating marine environmental disasters in eutrophic coastal waters.