Improving the Lake Erie HAB Tracker: A Forecasting & Decision Support Tool for Harmful Algal Blooms

Abstract

This Master’s Project sought to improve the performance, data display and utility of the Lake Erie HAB Tracker model for predicting the location and movement of harmful algal blooms (HABs) in western Lake Erie. These improvements will benefit stakeholders by allowing public water systems to prepare for HAB events and by allowing anglers and boaters to avoid affected locations. Specifically, this research addressed three topics: 1) Microcystis colony rising/sinking (buoyant) velocity, a parameter in the HAB Tracker model, was measured using an improved method. Statistical relationships were obtained between buoyant velocity and environmental variables, showing lower buoyancy associated with greater light exposure, smaller colony size and deficient nutrient levels. 2) Model skill was assessed in comparison to satellite-derived HAB distributions using a neighborhood-based spatial smoothing method. We found that model skill was improved after spatial smoothing using a 3-km neighborhood. 3) We conducted a series of focus group interviews with Lake Erie fishing charter captains and recreational anglers to evaluate perceptions of HABs and the HAB Tracker. Our results indicated that the majority of anglers seek to avoid fishing in HABs, but that beliefs vary regarding the impact of HABs on fish and human health. We determined that anglers may find the HAB Tracker to be useful, but we recommend specific changes to improve the presentation of information on the HAB Tracker web site to make it more accessible. We also recommend improved content and methods of communication to better reflect angler concerns and interests.