AUTHORS: Nick Sievert, Missouri Department of Conservation; Matt Combes, Missouri Department of Conservation; Steffanie Abel, Missouri Department of Conservation; Emily Sinnott, Missouri Department of Conservation; Jessica Scholz, Missouri Department of Conservation
ABSTRACT: Harmful algal blooms, caused by outbreaks of cyanobacteria, pose substantial health risks to humans, domesticated animals, and wildlife. Often, the monitoring of harmful algal blooms is conducted based on reported observations from the public or through formal monitoring programs. While this approach is effective in many ways, there are limitations to the scope of coverage and the timeliness of detection. To reduce the harm caused by these events, it is important to both quickly identify active blooms to provide notice to the public and facilitate additional data collection and to evaluate long-term patterns to better identify at risk areas and develop management strategies for reducing the frequency and severity of outbreaks. Remotely sensed data, made available by the Cyanobacteria Assessment Network (CyAN), provides daily estimates of cyanobacteria cell counts for thousands of waterbodies across the United States. With these data, we are developing methods and tools for early detection and reporting of potential harmful algal blooms, evaluating waterbody specific historical outbreaks and contextual variables such as watershed land cover and climate data, and using observational and monitoring data to validate the remotely sensed data for Missouri waterbodies. The next day delivery of this information and the broad-scale coverage of waterbodies in the CyAN dataset provides a valuable resource for both timely decision making and long-term research efforts.
