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PREDICTING THE POTENTIAL DISTRIBUTION OF THE NONNATIVE RED SWAMP CRAYFISH PROCAMBARUS CLARKII IN THE LAURENTIAN GREAT LAKES

The ongoing threat of introduction of nonnative species, including crayfish, to the Laurentian Great Lakes has motivated the development of predictive models to inform where nonnative populations are likely to establish. Our study is one of the first to apply regional freshwater-specific GIS layers to species occurrence data to predict ecosystem vulnerability to invasions, specifically of the red swamp crayfish Procambarus clarkii into the Great Lakes. We combined a database of crayfish species occurrences with the Great Lakes Aquatic Habitat Framework (GLAHF) spatial database to model habitats vulnerable to invasion by P. clarkii using a machine-learning algorithm (boosted regression trees). We developed a series of taxonomically nested models of habitat suitability, ranging from one identifying all suitable crayfish habitat across the Great Lakes to one narrowly identifying potentially suitable habitat for P. clarkii based on its current, limited distribution in this system. Our models give scenarios of uncertainty for where P. clarkii might be able to establish in this important freshwater ecosystem, which can be used to inform management efforts to slow spread or detect new invasions.

Rachel Egly (Primary Presenter/Author), University of Illinois at Urbana-Champaign, egly2@illinois.edu;


Gust Annis ( Co-Presenter/Co-Author), The Nature Conservancy, gannis@tnc.org;


W. Lindsay Chadderton ( Co-Presenter/Co-Author), The Nature Conservancy, lchadderton@tnc.org;


Jody A. Peters ( Co-Presenter/Co-Author), University of Notre Dame, peters.63@nd.edu;


Eric Larson ( Co-Presenter/Co-Author), University of Illinois, erlarson@illinois.edu;