PW08 Aquatic Ecotoxicology II
Exhibit Hall
8:00 AM - Wednesday
(PW103) Nonlinear modeling for growth and toxin-production limits of Microcystis aeruginosa as functions of nitrogen, phosphorus.
Lian, M1, Yu, S2, Dixon, K1, 1 Department of Environmental Toxicology, Texas Tech University, Lubbock, TX 794092 School of Public Health, Fudan University, Shanghai 200032, PR China
ABSTRACT- Water bloom of toxic freshwater cyanobacteria worldwide has been becoming the critical issue in the field of environmental protection and public health. Environmental eutrophication (mainly resulted from the release of waste nitrogen and phosphorus components) is being realized as the main reason. We used the nonlinear modeling method to analyze a group of data about the effects of nitrogen and phosphorus on cell growth of the non-toxic NIES-101 strain and toxic NIES-90 strain of Microcystis aeruginosa, and toxin production of NIES-90 strain. A series of nonlinear functions of cell growth and toxin production, over the different nitrogen or phosphorus concentrations and cultured time, were set up and plotted. Predicted data and parameters for the nonlinear equation models and corresponding diagrams were determined with SAS System written in SAS/STAT and SAS/GRAPH. All fitted nonlinear functions were highly significant (all p values are less than 0.0001). The results showed that high nitrogen concentration favored growth of NIES-101 strain, and both growth of and toxin production by NIES-90 strain. In addition, growth of NIES-101 strain depended on phosphorus concentration at low levels of phosphorus, and higher concentrations had no additional effects. And, relatively lower level of phosphorus was needed for growth and toxin production of NIES-90 strain. In sum, much lower level of phosphorus contributed to the cell growth and toxin production of Microcystis aeruginosa than that of nitrogen. This suggests that phosphorus is the critical environmental stressor leading to the water bloom of freshwater cyanobacteria.
Key words: microcystis aeruginosa, nonlinear modeling, cyanobacteria