Modelling harmful algal blooms in a mono- and a polydominant eutrophic lake under temperature and nutrient changes.

Cyanobacterial blooms, driven by nutrient loading and temperature, pose significant ecological and economic challenges. This study employs a combined data-driven and trait-based modelling approach to predict changes in cyanobacterial communities in a mono- and a polydominant shallow temperate lakes under varying temperature and nutrient scenarios. Results of the AQUATOX simulation model for two aquatic systems suggest that a 2 °C temperature increase, consistent with Intergovernmental Panel on Climate Change's predictions, may influence cyanobacteria species composition and dominance, with trends indicating a possible shift favouring Nostocales over Oscillatoriales and Chroococcales. Temperature increases by 4 °C clearly promoted the dominance of Nostocales. Nutrient dynamics appear to influence community structure. In a nutrient-rich monodominant lake, temperature was the primary driver, while in a nutrient-limited polydominant lake, phosphorus availability influenced cyanobacteria species dominance. Combined warming and phosphorus alterations significantly affected cyanobacteria bloom intensity and duration, particularly enhancing Nostocales growth. The study highlights the complexity of cyanobacterial responses to climate change, emphasizing the need for more analysis and comprehensive models to predict harmful algal blooms (HABs) in freshwater ecosystems. While the findings suggest that temperature and nutrient availability may be critical drivers of cyanobacterial dominance, additional research across a broader range of systems is necessary.