Water quality benefit assessment of Lake Erie coastal wetlands
Justin Saarinen, University of Michigan‐Dearborn
Kurt Kowalski, USGS‐Great Lakes Science Center
Rachael Franks‐Taylor, The Nature Conservancy in Michigan
James Cole, The Nature Conservancy in Ohio
Fundamental questions about how humans affect Great Lakes water quality have been well‐studied and are summarized in the accumulation of stressors. More recently, cumulative stress on the Great Lakes was assessed spatially to correlate with locations of landscape features , e.g. urbanization, shoreline hardening, and ecosystem services directly beneficial to humans, e.g. fishing. Following ecosystem‐based management strategies, restoration efforts should be directed toward multiple stressors to maximize ecological benefits.
Currently, the National Oceanic and Atmospheric Administration, US Geological Survey, The Nature Conservancy, and the University of Michigan‐Dearborn (UM‐ D) are assessing western Lake Erie’s coastal and diked wetlands that are and could potentially be connected to the lake between the Detroit River outlet and the Black River in Ohio. These wetlands can provide ecosystem services that are directly beneficial to humans and the water quality of Lake Erie. In an attempt to balance cumulative stress models, this project is a synthesis that utilizes existing restoration data and project outcomes to identify alternative restoration scenarios for western Lake Erie.
Models in the InVEST spatial planning toolset will be combined with in situ observations to assess whether these wetlands supply a significant water quality service benefit to western Lake Erie both in their current state and with alternative future restoration scenarios. This analysis will characterize water quality benefits associated with ongoing Great Lakes Restoration Initiative habitat restoration projects and be useful in the planning and prioritization of future projects, especially those in the EPA‐designated Areas of Concern, such as River Raisin, Maumee River and Black River.