University of Wisconsin–Madison
aerial photo of Yahara watershed

Harmful algal blooms

In freshwater, harmful algal blooms (HABs) are outbreaks of toxic microorganisms, usually cyanobacteria or ‘blue-green algae’, in water bodies polluted by excess nutrients.  HABs in lakes and reservoirs are associated with high inputs of phosphorus. However, phosphorus explains only a fraction of the variability observed among lakes on the landscape. Thus, other characteristics of landscapes related to topography, hydrology and soils are also important. Cyanobacteria have increased in abundance in northern hemisphere temperate and subarctic lakes over the past 200 years, according to contemporary records and sediment cores. Nonetheless, cyanobacteria concentrations vary enormously from day to day, or year to year, in a given lake. This variability is related to weather, grazing, cycles of other nutrients (iron, nitrogen) and other factors. A great diversity of models has been used to understand and predict the biomass of cyanobacteria in lakes. However, no models address broad spatial extents (large landscapes with many lakes) and within-lake temporal dynamics together with sufficient precision to anticipate abrupt changes and to meet the needs of lake managers.

In this context, we are asking: how variable is cyanobacteria biomass among lakes, and how is this variability related to watershed characteristics? How variable is cyanobacteria biomass over time, and how is this variability related to climate, nutrients, grazers and other factors? Do we see regime shifts (discontinuities in abundance or cycles) of cyanobacteria across landscapes; across time, since the beginnings of European agriculture, or the intensification of agriculture in the 1950s; or among or within years in individual lakes? If such regime shifts are evident, what factors are associated with the regime shifts? To answer those questions, we are analyzing aggregated databases from the Western Great Lakes region (Iowa, Michigan, Minnesota, Ontario, Wisconsin) for analysis, and developing models for predictions of cyanobacteria blooms. Eventually, we aim to provide relevant recommendations for decision maker and lake managers.