Abstract

The dynamic changes between toxic and non-toxic strains of Microcystis blooms have always been a hot topic. Previous studies have found that low CO2 favors toxic strains, but how changing dissolved CO2 (CO2 [aq]) in water body influences the succession of toxic and non-toxic strains in Microcystis blooms remains uncertain. Here, we combined laboratory competition experiments, field observations, and a machine learning model to reveal the links between CO2 changes and the succession. Laboratory experiments showed that under low CO2 conditions (100–150 ppm), the toxic strains could make better use of CO2 (aq) and be dominant. The non-toxic strains demonstrated a growth advantage as CO2 concentration increased (400–1000 ppm). Field observations from June to November in Lake Taihu showed that the percentage of toxic strains increased as CO2 (aq) decreased. Machine learning highlighted links between the inorganic carbon concentration and the proportion of advantageous strains. Our findings provide new insights for cyanoHABs prediction and prevention.

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