The Great Lakes and the St. Lawrence River are imposing barriers for wildlife and the additive effect of urban and agricultural development that dominates the lower Great Lakes region likely further reduces functional connectivity for many terrestrial species. As the climate warms species will need to track climate across these barriers. It is important, therefore, to investigate land cover and bioclimatic hypotheses that may explain the northward expansion of species through the Great Lakes. We investigated the functional connectivity of a vagile generalist, the bobcat, as a representative generalist forest species common to the region. We genotyped tissue samples collected across the region at 14 microsatellite loci and compared different landscape hypotheses that might explain the observed gene flow or functional connectivity. We found that the Great Lakes and the additive influence of forest stands with either low or high canopy cover and deep lake-effect snow have disrupted gene flow, whereas intermediate forest cover has facilitated gene flow. Functional connectivity in southern Ontario is relatively low and was limited in part by the low amount of forest cover. Pathways across the Great Lakes were through the Niagara region and through the Lower Peninsula of Michigan over the Straits of Mackinac and the St. Mary’s River. These pathways are important routes for bobcat range expansion north of the Great Lakes and are also likely pathways that many other mobile habitat generalists must navigate to track the changing climate. The extent to which species can navigate these routes will be important for determining the future biodiversity of areas north of the Great Lakes.

From 2012 to the end of 2017, we collected bobcat pelts samples from the North American Fur Auction (NAFA), Ontario Ministry of Natural Resources and Forestry (MNRF), researchers, and trappers. We followed the lab protocols and scoring methodology of Koen et al. (2014) and Row et al. (2012) and genotyped bobcat samples at 14 microsatellite loci (Fca031, Fca035, Fca043, Fca077, Fca090, Fca096, Fca441, Fca391, Fca559, Lc106, Lc109, Lc110, Lc111, Lc118). We removed individuals that had any missing loci and individuals that were not correctly georeferenced.

Koen, E. L., Bowman, J., Murray, D. L., & Wilson, P. J. (2014a). Climate change reduces genetic diversity of Canada lynx at the trailing range edge. Ecography, 37(8), 754–762. https://doi.org/10.1111/j.1600-0587.2013.00629.x

Row, J. R., Gomez, C., Koen, E. L., Bowman, J., Murray, D. L., & Wilson, P. J. (2012). Dispersal promotes high gene flow among Canada lynx populations across mainland North America. Conservation Genetics, 13(5), 1259–1268. https://doi.org/10.1007/s10592-012-0369-3

sample: Sample code.    

Long, Lat: Geographic coordinates in NAD83.     

X, Y: Geographic coordinates in North America Lambert Conformal Conic.    

Year.of.Auction: Year the sample was taken at an auction house or from a trapper. 

Microsatellite markers: Fca31, Fca35, Fca391, Fca43, Fca441, Fca559, Fca77, Fca90, Fca96, Lc106, Lc109, Lc110, LC111, Lc118.