Forecasting the Causes, Consequences, and Potential Solutions for Hypoxia in Lake Erie
Project Status: This project began in January 2006 and was completed in December 2012
In recent years, the central basin of Lake Erie has experienced low-oxygen conditions, despite measures taken by surrounding states and provinces to reduce nutrient inputs. This project studies the conditions that have led to the present low-oxygen state and forecasts future oxygen conditions and their impacts. Key factors addressed include phosphorus loading, zebra mussel (dreissenid) populations, and climate variability.
Why We Care
Lake Erie is the southernmost and shallowest of the Laurentian Great Lakes and is used extensively for drinking water, recreation, and the fishing industry. It receives runoff from watersheds in Indiana, Michigan, New York, Ohio, Pennsylvania, and Ontario. Excessive phosphorus inputs in the mid-1900s may have contributed to the decline of important commercial fish species by the 1960s. Measures taken to reduce the phosphorus load enhanced oxygen levels, and, by the mid-1990s, several species began to recover. More recently, however, large-scale low-oxygen (hypoxic) events have returned conditions to levels comparable to those experienced in mid-1900s. Phosphorus target levels are also being reconsidered across states and between the US and Canadian governments. To improve water quality and fish production, we need a fuller understanding of the complex relationships leading to hypoxia before effective phosphorus target levels can be safely established.
What We’re Doing
Field data from the International Field Years on Lake Erie (IFYLE) and other extensive historical ecological data sets from Lake Erie are being used to develop multiple forecast models for the watershed to evaluate the consequences of seasonal hypoxia on the Lake Erie ecosystem structure and fishery production. Models are developed for nutrient loads (nitrogen and phosphorus), hypoxia (climate, phosphorous loading, invasive mussels) and ecological effects (phytoplankton, zooplankton, fish). Model outputs are used to predict the impacts of hypoxia (e.g. timing of onset, intensity, duration, and extent) on fish biomass and potential harvest rates. Models can also be run to see how fisheries’ harvest rates respond to hypoxia under different climate or management scenarios. Our objectives are to develop forecasts that can be used by Lake Erie fisheries managers to guide fisheries policies in response to anticipated hypoxia impacts and to supply information in support of phosphorus control measures. A suite of modeling approaches is used to enable nutrient-load hindcasts (past) and forecasts, including statistical modeling approaches and a detailed hydrologic model (SWAT, the Soil and Water Assessment Tool) developed and tested extensively for Great Lakes tributaries.
This work is part of the Ecological Forecasting Program (EcoFore). The project team is led by Dr. Don Scavia of the University of Michigan with co-investigators from the University of Michigan, the NOAA Great Lakes Environmental Research Laboratory, Heidelberg College, Ohio Department of Natural Resources, Western Michigan University, University of Wisconsin at Green Bay, Limno-Tech, Inc., Oregon Sea Grant, and E2 Consulting Engineers, Inc.
What We’re Finding
Thus far, we have found that low-oxygen conditions typically occurred from mid-July to mid-October. These hypoxic conditions reduced the habitat quality for all fish studied, but the degree of effect varied with species and life stage based on differences in low-oxygen and warm-water tolerances.
Across years, trends in habitat quality mirrored trends in phosphorus concentration and water column oxygen demand in central Lake Erie. The percent reduction in habitat quality owing to hypoxia was greatest for adult rainbow smelt and round goby (mean: −35%), followed by adult emerald shiner (mean: −12%), young-of-year (YOY) rainbow smelt (mean: −10%), and YOY and adult yellow perch (mean: −8.5%).
These findings are examples of the type of data used in the hypoxia models. This ensemble-modeling approach is improving the reliability of forecasts by integrating output from different models, each with different strengths and weaknesses. In addition, assessments of the variations in model output are helping to identify key uncertainties in the forecasted scenarios. Our objectives fit the needs of end-users (primarily fishery managers) by developing forecasts focused on appropriate time scales and relevant fish species.
We will continue to refine our model forecasts so they can be used by Lake Erie fisheries managers to guide policies in response to anticipated hypoxia impacts
Related Regions of Study: Great Lakes, Michigan, New York, Ohio, Pennsylvania
Primary Contact: Elizabeth Turner
Related NCCOS Center: CSCOR