The use of phytoplankton patterns of diversity for algal bloom management

Many biotic and abiotic processes contribute to variability in phytoplankton diversity in aquatic ecosystems. Depending on their intensity and on their frequency, these may drive non-equilibrium dynamics and enhance the species diversity. Different studies propose that biodiversity buffers ecosystem functioning against environmental fluctuations leading to more predictable aggregate community or ecosystem properties. Salto Grande reservoir is polymictic and eutrophic with recurrent summer cyanobacterial blooms. The aim of this study was to determine the key variable(s) related with phytoplankton diversity in order to predict the possible occurrence of an algal bloom at the ecosystem. A preliminary analysis of the data matrix suggested non-linear relationships between diversity and the selected variables: phytoplankton abundance and the vertical attenuation coefficient (Kd). The best function fitting of the scatter plot of phytoplankton diversity versus phytoplankton abundance was a rational function. The inflection point of phytoplankton diversity estimated by the second derivate of this function was 2.7 bit cell−1 which corresponded to an abundance of 3000 cells ml−1. The relationship of phytoplankton diversity and vertical attenuation coefficient values also show a humped distribution pattern (Gauss function). The inflection point of this function corresponded to a diversity value of 1.9 bit cell−1 and 2.5 m−1 for Kd. These inflection points were, respectively, related with the resource competition among the present species and the light limitation conditions. The showed patterns of diversity and the estimated threshold values could be integrated to construct a predictive model for the reservoir based on phytoplankton diversity and the probable ambient conditions of the reservoir.