Spatial distribution of road-kills and factors influencing road mortality for mammals in Northern New York State

Abstract

One of the most obvious impacts of roads on wildlife is vehicle-induced mortality. The aims of this study were to examine the spatial pattern of mammal-vehicle collisions (MVCs), identify and examine factors that contribute to MVCs, and determine whether the factors that increase the odds of MVCs are similar between species. On 103 road surveys that covered 7,094 total km I recorded the location of each MVC along the survey route. I measured landscape and roadway features associated with each MVC and used kernel density and network analysis tools to identify road mortality hotspots and measure spatial clustering of MVCs. I used logistic regression to model the likelihood of MVCs for all mammal data and separately for Porcupine (Erethizon dorsatum), Raccoon (Procyon lotor), Skunk (Mephitis mephitis), Muskrat (Ondatra zibethicus) and Cottontail (Sylvilagus floridanus) data sets. I identified 51 MVC hotspots and found spatial clustering of MVCs for Porcupines, Raccoons and Skunks. Two landscape variables, distance to cover and the presence of an ecotone, as well as one road variable, road width, appeared as broadly important predictors of mammalian road mortality, though there was also species- specific variation in factors that increased the risk of MVCs. Field-measured variables were more important than remotely-measured variables in predicting the odds of MVCs. Con- servation implications are that mitigation of landscape features associated with higher risk of vehicle-collisions may reduce the number of MVCs in general, but species-specific research is required to more carefully tailor mitigation efforts for particular species.