Morpho-functional groups as an efficient tool for monitoring and management of the Billings reservoir (São Paulo, Brazil)

This research applied the Morphology-Based Functional Groups (MBFGs) combined with classical approaches, such as community descriptor species and phytoplankton classes in the Billings reservoir. This local is the largest freshwater reservoir in the metropolitan region of São Paulo that has around 22 million inhabitants. Two sampling stations differing in predominant uses were studied: Rio Grande, classified as mesotrophic, and Central Body, as super and hypereutrophic. The phytoplankton and limnological variables were collected over six months (n=12). The trophic state index was calculated using phosphorus concentrations. Three canonical correspondence analyses were calculated aiming to examine the effect of environmental variables on the phytoplankton structure from each classification method (descriptor species, classes, and MBFGs), identifying the influence of environmental variables (independent variables) on the abundance patterns of the phytoplankton community (dependent variables). The highest concentrations of chlorophyll a and phytoplankton density were recorded at the site with the highest concentrations of total phosphorous (average of 99.86 μg/L in Central Body). This site was also associated with the highest electrical conductivity, total dissolved solids, turbidity, and concentrations of total nitrogen and chlorophyll a. The main factors associated with phytoplankton distribution were the trophic state and the operational system. It was concluded that the phytoplankton approach through MBFG efficiently responds to fluctuations in the ecological attributes of phytoplankton, and because they are based on morphological features, MBFG reduces the complexity of identifying and classifying organisms at a specific level.