Climate-driven redistribution of harmful cyanobacterial blooms: a global MaxEnt projection of Microcystis aeruginosa suitable habitat

Abstract

Harmful cyanobacterial blooms dominated by Microcystis aeruginosa represent an escalating threat to freshwater ecosystems and public health worldwide, driven by climate change and eutrophication. This study employs maximum entropy (MaxEnt) modeling to project the global distribution of suitable habitat for M. aeruginosa under current and future climatic conditions. We compiled 395 occurrence records from the Global Biodiversity Information Facility and field surveys, integrating them with six bioclimatic variables selected through rigorous multicollinearity filtering: Annual Mean Temperature (bio_1), Temperature Seasonality (bio_4), Maximum Temperature of Warmest Month (bio_5), Mean Temperature of Warmest Quarter (bio_10), Precipitation of Driest Month (bio_14), and Precipitation of Driest Quarter (bio_17). The MaxEnt model demonstrated excellent predictive performance (AUC = 0.91, TSS = 0.82), identifying temperate and subtropical regions across central Europe, eastern North America, East Asia, and southern Australia as current high-suitability zones. Limiting factor analysis revealed Temperature Seasonality as the dominant constraint on global distribution, emphasizing the critical role of inter-annual climatic variability in governing bloom dynamics. Projections under Representative Concentration Pathways RCP 2.6 and RCP 8.5 for 2050 and 2070 indicate substantial northward expansion of suitable habitat, particularly under high-emission scenarios. By 2070 under RCP 8.5, suitable habitat is projected to increase by 8.4% globally, with pronounced gains in high-latitude regions of Canada, northern Europe, and Russia, while some currently suitable subtropical areas experience habitat contraction due to intensified drought stress. These findings identify regions where future climatic conditions may become increasingly suitable for M. aeruginosa occurrence, providing a basis for prioritizing monitoring and precautionary water resource management strategies.