Use of regression tree to investigate the effective parameters on algal bloom in the southeastern coasts of Iran

In recent years, the incidence of many cases of algal blooms have been reported in the southeastern coasts of Iran, which led to the loss of mass mortality of marine fish in this area. The aim of this study was to use regression trees to investigate the effects of physicochemical parameters and nutrient concentration on algal blooms. During the one-year study period, sampling was done in 6 stations along 2 transects in the coastal waters of Pasabandar and Beris. The trend of changes in pH, salinity, temperature, dissolved oxygen, nitrate concentration, nitrite, phosphate, and silicate with the community of dominant phytoplankton genera was recorded. Overall, 40 phytoplankton genera were identified and more than 95% of the total number of observed cells belonged to 14 genera of phytoplankton. Results showed that increase in the pH, temperature, salinity, phosphate, nitrate and silicate were the effective parameters to bloom of Gonyaulax, Leptocylindrus, Mesodinium, Chaetocerus, Prorocentrum, Rhizosolenia and Nitzschia, respectively.