Abstract
The current study employed diverse statistical and machine learning techniques to investigate the biodiversity and spatial distribution of phytoplankton cysts in the Black Sea. The MaxEnt distribution modeling technique was used to forecast the habitat suitability for the cysts of three potentially toxic microalgal taxa (Lingulodinium polyedra, Polykrikos hartmannii, and Alexandrium spp.). The key variables controlling the habitat suitability of Alexandrium spp. and L. polyedra were nitrates and temperature, while for the P. hartmannii cysts, nitrates and salinity. The region with the highest likelihood of L. polyedra cyst occurrence appears to be in the western coastal and shelf waters, which coincides with the areas where L. polyedra red tides have been documented. The projected habitat suitability of the examined species partially overlapped, perhaps as a result of their cohabitation within the phytoplankton community and shared preferences for specific environmental conditions, demonstrating similar survival strategies. The north-western region of the Black Sea was found to be the most suitable environment for the studied potentially toxic species, presumably posing a greater risk for the onset of blooming events. Two distinct aspects of cysts’ ecology and settlement were observed: the dispersal of cysts concerns their movement within the water column from one place to another prior to settling, while habitat suitability pertains to the particular environment required for their survival, growth, and germination. Therefore, it is crucial to validate the model in order to accurately determine a suitable habitat as well as understand the transportation patterns linked to the particular hydrodynamic properties of the water column and the distinct features of the local environment.