Abstract:With climate change, the increasing frequency and intensity of extreme climate events have intensified the outbreak and expansion of cyanobacterial blooms in shallow eutrophic lakes, posing severe threats to the security and water supply safety of lake ecosystems. However, how extreme climate events drive the long-term dynamics of cyanobacterial blooms, as well as the dominant factors and underlying mechanisms, remain unclear. Taking Lake Hongze as a case study, Mann-Kendall trend analysis based on 64 years of meteorological observations revealed a significant warming trend in extreme temperature indices. Since 1991, the total duration and frequency of extreme heat events has increased by approximately 5.33 days and 2 events per decade, respectively. Meanwhile, the Simple Daily Intensity Index (SDII) and the annual total precipitation from very wet days (R95p) have increased by 0.38 mm d-1and 15.18 mm per decade, respectively. Based on remote-sensing observations from 2003 to 2020, the bloom occurrence rate in Lake Hongze has increased by 1.15%, while the maximum bloom extent has expanded by 154.69 km². The bloom onset has advanced by 24.56 days, and the potential bloom duration has extended by an average of 27.20 days. Further attribution analysis using the SHAP method indicated that the bloom occurrence rate and the maximum bloom extent are the cyanobacterial bloom metrics most sensitive to extreme climate events, with the mean intensity of extreme heat events playing a dominant role. The continued intensification of extreme heat events is expected to further advance the bloom onset and expand the bloom extent. Notably, when temperatures exceed a certain threshold, algal growth may be inhibited due to thermal stress, suggesting a dual “promoting-inhibiting” effect of extreme heat events on cyanobacterial bloom dynamics. This study elucidates the response mechanisms and threshold behaviors of cyanobacterial blooms under extreme climate forcing, providing a theoretical basis and scientific support for the early warning of bloom risks and adaptive watershed management.