Next-generation models to predict cyanobacteria harmful algal blooms

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This project aims to address the need for improved predictions of cyanobacteria (blue-green algae) harmful algal blooms. Accurate predictions of blooms with computer models are important to support management strategies to prevent their occurrence. This project is expected to generate new knowledge of strain-level variation in cyanobacteria that leads to toxic blooms. This project will lead to new knowledge of the significance of strain-level variation in cyanobacteria harmful algal blooms, how strains influence toxin production and models for prediction of bloom and toxins. The project will generate significant benefits for water security for the purposes human consumption and recreation, and ecosystem health.