Can we explain regional abundance and road‐kill patterns with variables derived from local‐scale road‐kill models? Evaluating transferability with the European polecat

Abstract

AbstractAim We evaluated the transferability of variables previously found to have a significant effect on European polecat Mustela putorius road‐kills at a local scale (i.e. 50 m around location points) when we extrapolate them to a large scale [Universal Transverse Mercator (UTM) 100 km2] in a neighbouring area.Location Andalusia, south Spain. We carried out our study in 821 of the 985 UTM 100 km2 cells included in this region.Methods The units of the different variables were adapted to the new scale. We used data from the Spanish Atlas survey to obtain the abundance of the different species and GIS data for the rest of the variables. We controlled the spatial autocorrelation by incorporating spatial filters obtained with Spatial Eigenvector Mapping into multiple regression analyses. We used AIC criteria and the best subset procedure to investigate the relationship between the selected variables and species abundance, and road‐kill occurrence.Results The best subset procedure provided two models that explained 40% of variation in polecat abundance and eleven models that explained around 25% of variation in road‐kills. The main explanatory factor for polecat abundance was the abundance of other carnivores, whereas polecat abundance was the main factor for road‐kills. In both cases, rabbit abundance was the second most important explanatory variable.Main Conclusions Our findings highlight the possibility of partially explaining the abundance and road‐kill patterns at a large scale based on significant variables from local‐scale models. Mitigation measures to reduce polecat fatalities should combine actions at different scales. Routes that cross carnivore hotspots, including those of polecats, and areas with important populations of rabbits, should be avoided during road planning. When these routes are unavoidable, local‐scale mitigation measures must be implemented.