Causal relationships of Raphidiopsis (formerly Cylindrospermopsis) dynamics with water temperature and N:P-ratios: A...

Raphidiopsis raciborskii is a tropical toxic cyanobacterium that is rapidly expanding to diverse lake habitats in different climate zones by sophisticated adaptation mechanisms. This meta-analysis investigated correlations of R. raciborskii with water temperature and N:P (nitrogen to phosphorus)-ratios across four lakes with different climates and trophic states by means of long-term time series and the hybrid evolutionary algorithm HEA. The results have shown that in the lakes with temperate and Mediterranean climate, R. raciborskii is strongly correlated with water temperature since germination and growth rely on rising water temperatures in spring. In contrast, there was a weaker correlation with water temperature in subtropical and tropical lakes where pelagic populations of R. raciborskii are overwintering, and are present all year round. However, the highest abundances of R. raciborskii coincided with highest water temperature for the Mediterranean, subtropical and tropical lakes, whilst in the temperate Langer See the highest abundances of R. raciborskii occurred at 24.1 °C, even though temperatures of up to 27 °C were recorded in 2013 and 2014. The correlation of R. raciborskii with N:P-ratios proved to be strongest for the meso- to eutrophic Lake Kinneret (r² = 0.8) and lowest for the eutrophic Lake Paranoa (r² = 0.16). However, the assumption has been confirmed that R. raciborskii is growing fastest when waters are N-limited regardless of trophic states. In terms of phenology, the temperate and Mediterranean lakes displayed "fastest growth" in spring and early summer. In contrast, the growing season in subtropical and tropical lakes lasted from spring to autumn most likely because of overwintering populations, and growing importance of direct and indirect biotic regulating factors such as competition, grazing, remineralisation of nutrients along warming climate. In order to carry out a meta-analysis of time series across four different lakes, HEA served as powerful tool resulting in inferential models with predictive capacity for population dynamics of R. raciborskii just driven by water temperature or N:P-ratios, whilst coefficients of determination r² served as criteria for hypotheses testing.