The goal of this model was to determine regions within Blue Earth County, Minnesota that were at high-risk for Emerald ash borer infestation. High-risk regions were determined by gradually reducing the region being observed until the remaining sections fit all of our criteria. These regions are within the Minnesota Department of Agriculture’s Forest Inventory, categorized as containing primarily Ash trees, are within 500 meters of a publicly accessible roadway, and contain at least 2 cords/acre of possible firewood. These high-risk regions would be ideal locations for new Emerald ash borer monitoring systems.

About 27.2 percent of Blue Earth County land is already considered a “generally infested area” by the Minnesota Department of Agriculture. This model narrowed down the remaining portion of Blue Earth County into qualifying areas of high-risk. In total, we find that there are 5 distinct sections of forest within Blue Earth County that qualify as high-risk for future infestation, totaling 24.34 acres of land. This area is roughly 2 percent of the forest area outside our existing generally infested area.

This model identified two species of Ash tree, Black ash (Fraxinus nigra) and Green ash (Fracinus pennsilvanica). Another species, White ash (Fraxinus americana) is also impacted by the Emerald ash borer but is not recognized in Blue Earth County within the Minnesota Department of Agriculture’s Forest Inventory. Three of the high-risk areas are mainly Black ash trees, making up 12.68 acres, while the other two areas are mainly Green ash trees, making up 11.66 acres. Both Ash species are affected equally by the Emerald ash borer and thus receive equal risk for future infestation.

Overall, this geospatial model combined various datasets from the Minnesota Department of Agriculture and Department of Transportation to understand locations in Blue Earth County that are highly susceptible to Emerald ash borer infestation. Without monitoring for Emerald ash borer, this model determined 24.34 acres of forest that may be lost. This model also set a priority for these sites, setting a path forward for potential private and public monitoring.