Midwest Fish & Wildlife Conference 2018

AUTHORS. Chad Wilsey, National Audubon Society; Bradley Pickens, National Audubon Society; Nathaniel Miller, Audubon Great Lakes; Gerald Niemi, University of Minnesota; Douglas Tozer, Bird Studies Canada


ABSTRACT. Great Lakes coastal wetlands provide habitat for a diverse suite of marsh birds, provide recreational opportunities, such as wildlife-watching and hunting, and serve the vital role of improving water quality by filtering nutrients from water before they reach the Great Lakes. Yet, coastal wetlands, and their associated marsh birds, remain under threat due to land cover change and development, fragmentation, invasive species, and altered hydrological regimes. Here, we developed a spatially-explicit conservation plan that prioritizes the U.S. Great Lakes coastal landscape for wetland conservation and restoration. Our objective was to simultaneously prioritize where wetland conservation will benefit marsh birds, bird-based tourism, and enhance water quality. We synthesized and integrated existing datasets from a variety of partner organizations: secretive marsh bird monitoring data, an index of wetland potential, nitrogen and phosphorus in surface water, Phragmites habitat suitability, a bird-watching index, and Important Bird Areas. For each wetland, we used marsh bird monitoring data to develop an index of multispecies conservation value by combining the presence of individual focal species with a ranking characterizing their conservation status. The prioritization shows both the currently important wetlands and areas that have restoration potential that would benefit bird conservation and enhance water quality. Although monitoring data and models are often developed independently, we have demonstrated a holistic approach to conservation planning by integrating marsh bird distribution, invasive species, bird-watching recreation, wetland potential, and the benefits of nutrient retention. The outcome of this conservation planning process is a prioritization that efficiently achieves multiple objectives.