NONLINEAR MODELING OF MUSKRAT USE OF HABITAT

Where muskrats (Ondatra zibethicus) are burrow dwellers, traditional a erial surveys of lodges to characterize the potential of different are as to sustain the species are not adequate. We present an alternative to identifying critical habitat variables on the basis of muskrat pres ence indices. We used stepwise logistic regression to create a habitat model based on muskrat presence in early fall along various wetlands of lames Bay. We built 2 models, 1 based on presence of burrows only a nd 1 using the presence of muskrat feeding signs and droppings. Collec ting the latter data required less field time than looking for burrows . The burrow model had a classification rate of 88 and 92% for 60-m sh ore sections of wetland used to build the model and other sections of streams and rivers, respectively. Classification rates for the feeding signs and droppings model were lower (79 and 71%, respectively). Logi stic regression analysis on presence/absence of burrow (P < 0.001) sel ected bank slope, percentages of floating and submerged plant cover, p resence of clay-loam soil, and width of shore herbaceous belt as impor tant habitat variables. The number of muskrat burrows in the study are a averaged 2.1 +/- 5.5/km, and lodges were not found. Slow-flowing riv ers represented the best habitats. Methodology presented here may be u sed to determine variables related to muskrat presence in riverine wet lands. These habitat variables may be used to assign values reflecting the potential of each riparian section of a given wetland to harbor b urrow-dwelling muskrats.