Snow-tracking and GIS: using multiple species-environment models to determine optimal wildlife crossing sites and evaluate highway mitigation plans on the Trans-Canada Highway

Snow-tracking data were collected for cougars (  Felis concolor ), lynx (  Lynx canadensis ), martens ( Martes americana ) and wolves ( Canis lupus ) and combined with remotely sensed imagery in a geographic information system (GIS) to identify wildlife crossing sites on the Trans-Canada Highway in Banff National Park, Alberta. We used logistic regression to assess the dependent (species presence/absence) relative to measures of topography and vegetation. The exponent form of each logistic regression equation was used to predict crossing sites in a GIS, which were then contrasted with mitigation sites proposed by Parks Canada. We found that: (1) cougars were influenced positively by normalized difference vegetation index (NDVI); negatively by northness and distance to ruggedness, (2) lynx were influenced positively by wetness, greenness, rugged terrain, eastness and distance to rugged terrain; negatively by slope, (3) martens were related positively to wetness, elevation, eastness, and distance to rugged terrain; negatively to northness, (4) wolves were influenced positively by distance to ruggedness; negatively by brightness, elevation, eastness and terrain ruggedness. There were few sympatric crossing sites for all species, supporting the use of species-specific mitigation or wide structures that capture multiple species needs. Inconsistencies were observed between the crossing sites predicted in this study and the Parks Canada proposal. The usefulness of GIS and track data to enhance mitigation projects is illustrated.