Modelling the drivers of phytoplankton in subtropical coastal waters

Temporal variability in phytoplankton is driven by a range of biotic and abiotic factors. In this study, we aimed to identify and estimate the important explanatory variables affecting the diatom species and their abundance in the coastal waters of Bangladesh.For this, species interaction and six explanatory variables were taken into consideration to develop a density dependent Bayesian regression model for quantifying the relative importance of different explanatory variables causing the variability in diatom abundance. Thus, three nutrients such as silicate, nitrate and phosphate, and zooplankton were identified as the most important predictors for 19–25 species. Moreover, the effect of three nutrients and salinity was positive for most diatoms, while temperature and zooplankton had a negative effect.Species interaction and environmental variables jointly explained 77% of the variability in diatom abundance, with the latter being the dominant factor driving the diatom community dynamics in coastal waters of Bangladesh. Specifically, six environmental variables jointly explained 57% of the variability in diatom abundance and the remaining 20% of the variability was due to species interaction. This is the first modelling study on phytoplankton community describing the dynamics of diatom species in the coastal waters of northern Bay of Bengal.