View Abstract


Cyanobacterial blooms pose serious threats to the health of aquatic ecosystems, local economies, and humans. Understanding patterns in the distribution, intensity, and frequency, as well as the effects, of cyanobacterial blooms requires consistent water-quality monitoring. Although fundamentally important, such projects are difficult to implement because of the high costs for travel and staff needed to collect and process samples. Using a cost-effective water-quality monitoring program that leveraged expertise and resources among academics, state and federal scientists, and industry researchers with complementary needs and capabilities, we collected and analyzed >1500 samples from freshwater lakes, reservoirs, ponds, and rivers in fourteen states in the southeastern U.S. Data generated from this project were used to develop water-quality models based on transparency (i.e., Secchi depth) or nutrients (e.g., total nitrogen, total phosphorus, nitrogen-to-phosphorus ratio) to predict blooms of freshwater phytoplankton, cyanobacteria, and cyanobacterial toxins for this region. Such models will allow water resource managers to identify important drivers of algal blooms as well as to predict the future likelihood of such events in systems that they manage.


Wilson, A. E., Auburn University, USA,

Chislock, M. F., Purdue University, USA,

Olsen, B. K., Auburn University, USA,

Wright, R. A., Auburn University, USA,

Schrader, K. K., USDA-ARS, USA, Kevin.Schrader@ARS.USDA.GOV


Oral presentation

Session #:021
Date: 03/02/2017
Time: 16:30
Location: 323 B

Presentation is given by student: No