Climate change influences on algal bloom intensity in lakes in the Yangtze River Basin, China from 1985 to 2022

Abstract

This study investigates the long-term influence of climate change on the spatiotemporal dynamics of harmful algal blooms in lakes larger than 10 km² across the Yangtze River Basin from 1985 to 2022. Using Landsat satellite imagery, we quantified bloom activity using three indices: annual average bloom area, maximum annual bloom area, and annual bloom frequency percentage, and assessed their relationships with climate drivers using a boosted regression tree model. Among the 90 lakes analysed, 40.00% showed significant decadal decreases in annual average bloom area (p < 0.05), 55.56% exhibited no significant change, and 4.44% showed significant increases. While most small and medium-sized lakes (10–100 km²) displayed stable or decreasing trends, a subset of super-large lakes (>500 km²), including Lakes Taihu and Chaohu, exhibited increasing maximum bloom area trends under warmer and wetter conditions. Temperature emerged as the primary climatic driver, explaining 45.5% of the variance in bloom proportion. Smaller lakes were more sensitive to temperature fluctuations, whereas larger lakes exhibited more persistent blooms, likely due to their complex hydrodynamics and catchment-scale influences. Interactions among temperature, wind speed, and precipitation minus evaporation further modulated bloom patterns, with two-way interaction strengths in the model peaking at 27.41. These findings underscore the need to integrate lake-specific climate sensitivity and nutrient management into adaptive bloom mitigation strategies under future climate scenarios.