Statewide modeling of bobcat, Lynx rufus, habitat in Illinois, USA

We used sighting location and remotely sensed habitat data, multivariate statistical techniques, and a geographic information system to model bobcat (Lynx rufus) habitat in Illinois, thereby providing state wildlife managers with information to review the listing of bobcats as a state-threatened species and contribute to the development of a statewide management plan. We used canonical discriminant function analysis to model presence/absence and relative abundance of bobcats statewide. These models suggested that bobcats occurred in moderate to high abundance in 23 of 98 counties statewide (23%). We used stepwise logistic regression (SLR) analysis to model statewide habitat suitability. Spatial modeling of the SLR equation predicted that 29% of Illinois contained suitable habitat classified as P>0.50. Models were accurate when validated with an independent data set and indicated the importance of woods-related habitat variables to bobcats. In conclusion, these models provided tools to rapidly assess status that contributed to delisting bobcats as a threatened species in Illinois and provided further information to guide conservation efforts.