The Role of Turbulence in Regulating Quagga Mussel Effects
Since their arrival at the turn of this century, invasive quagga mussels have dramatically altered the food web in Lake Michigan. Quagga mussels now cover the bottom of much of Lake Michigan, particularly deeper waters, with densities exceeding 10,000 mussels per square meter in certain locations. As prolific filter-feeders, quagga mussels can filter up to several liters of water per day. The increased water clarity of Lake Michigan may seem like a good thing (Lake Michigan’s water clarity now rivals Lake Tahoe), but these hardy “ecosystem engineers” have had a dramatic effect on Lake Michigan’s ecosystem, causing species extinction, alterations to nutrient cycling, and benthic substrate changes. Quagga mussels have invaded all of the Great Lakes except for Lake Superior, and are currently colonizing deeper reservoirs in the Western U.S. as well as lakes in Western Europe (among other places).
The ability of quagga mussels to clear the water column depends strongly on the turbulent mixing characteristics of the overlying water, Our ability to model the effects of mussels on aquatic systems depends then in turn on our abilities to model turbulent mixing in large lakes and oceans. When mixing is weak, mussels can only filter a small volume of water around them; when turbulence is energetic, new water is continually delivered to the lake bed, and mussels effectively have access to the entire water column. Our role in this collaborative project, which focuses on quagga mussel dynamics in the deeper waters of Lake Michigan, is to quantify deep water mixing rates and to link these rates to mussel effects on the food web. To address these objectives, we are carrying out and analyzing a set of Lake Michigan field experiments, in a range of locations and conditions, where we measure water column temperatures, currents, and turbulence using a range of instrumentation and analysis techniques. The mixing prescriptions elucidated from these observations will then serve as the basis for a mixing model onto which we layer nutrient, plankton, and zooplankton models (NPZD).
National Science Foundation, Division of Ocean Sciences
Project home page – NSF BCO-DMO
Harvey Bootsma and Qian Liao, University of Wisconsin-Milwaukee
David Cannon, University of Michigan