Predicting the Spatial Distribution of Dreissena polymorpha (Zebra Mussel) among Inland Lakes of Wisconsin: Modeling with a GIS

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Abstract
Previously developed models and available limnological data were used to predict (i) absence or presence, (ii) categorical population density, and (iii) numerical abundance of Dreissena polymorpha (zebra mussel) for 194 inland Wisconsin lakes. A geographical information system (GIS) was used to test for associations between predicted lake population density classes and three landscape-scale characteristics (surficial deposits, bedrock type, U.S. Environmental Protection Agency developed ecoregions) that may affect limnological parameters. Although the models used differed in their predictions of specific lakes that would support Dreissena, the overall spatial distribution of lakes within a given density class was similar among the models. A significant association was found between each landscape-scale characteristic and Dreissena density classes. This study suggests that (1) available lake monitoring data can be used to predict Dreissena density for groups of inland lakes, (2) more information on North American lakes with zebra mussel is required to reduce the uncertainty of the models, and (3) spatial analysis using GIS methods can provide valuable insight into the overall patterns of the potential spatial distribution of Dreissena.