Periphyton

Everglades restoration includes construction of six Stormwater Treatment Areas (STAs) totaling over 16,000 hectares. These filter marshes are designed to remove excess phosphorus from agricultural runoff and urban wastewater before it reaches the Everglades. Optimizing flow through these wetlands may be important in increasing the efficiency of nutrient removal and achieving lower outflow phosphorus concentrations. We measured periphyton growth and phosphorus uptake in two sets of replicated mesocosms in post-STA treatment water. Flow rates for the study were 1.0 cm s^-1 and 0.11 cm s^-1. Unique mesocosm design allowed for simultaneous control of loading rate, retention time and surface area, leaving flow rate as the single variable between treatments. Periphyton biomass accrual was 25% greater in the faster treatment. Measurements of dissolved oxygen were positively correlated with biomass accrual and there was no significant difference in the export of biomass between treatments.

Pigment-based chemotaxonomy uses relative amounts of photosynthetic pigments (biomarkers) within algae samples to determine the algal class composition of each sample. Chemotaxonomy has been applied successfully to phytoplankton communities, but its efficacy for periphyton has not yet been established. This study examined the ability of simultaneous linear equations (SLE), CHEMTAX, and the Bayesian Compositional Estimator (BCE) to determine algal class composition in Florida Everglades periphyton. The methods were applied to artificial datasets, mixed lab cultures of known composition, and Everglades periphyton samples for which microscopic biovolume data was available. All methods were able to return accurate sample compositions for artificial data and mixed lab cultures. Correlation between pigment methods and microscopic results for natural periphyton samples was poor. SLE and CHEMTAX returned similar results for all samples while BCE performed less well.