Using geographic information system (GIS) mapping, the scientists looked at road density, farm size, availability of deer and other factors to develop statewide maps for Wisconsin and Minnesota. Despite dramatic differences in the two states' wolf populations, hunting policies, and farm sizes, the maps revealed several similarities among the sites where wolves had preyed on cattle in the past.
Each town in the two states was assigned a color-code ranging from red (highest risk) to blue (lowest risk). Low risk townships included those with lots of cropland, wetlands and open water. Overall, just 0.3 percent of Wisconsin's towns were classified as highest risk and none occurred in Minnesota. The two higher risk classes of townships (red and orange) were clustered in two areas that had not previously been identified as problematic.
The map revealed that southwest Wisconsin faced moderate to high risk, an area where breeding packs of wolves have not yet recolonized. The map also revealed that highest risk townships were clustered along the edge of the wolf population--areas with the lowest habitat suitability for wolves and where newly formed wolf packs encounter landowners with little, recent experience of conflict with wolves. Among farms, the authors found that those with large land holdings and large herds were more likely to suffer losses from wolves. In Minnesota, risk was particularly high for farms sharing the land with dense deer populations.