Multi-scale resistant kernel surfaces derived from inferred gene flow: An application with vernal pool breeding salamanders

The importance of assessing spatial layers at multiple spatial-scales when modeling species environmental relationships has been highlighted by several empirical studies. However, no landscape genetics studies have optimized landscape resistance surfaces by evaluating relevant spatial predictors at multiple spatial-scales. Here, we model multi-scale/layer landscape resistance surfaces to estimate resistance to inferred gene flow for two vernal pool breeding salamander species, spotted (A. maculatum) and marbled (A. opacum) salamanders. Multi-scale resistance surface models outperformed spatial layers modeled at their original spatial scale. A resistance surface with forest land cover at a 500m Gaussian kernel bandwith, and normalized vegetation index at a 100m Gaussian kernel bandwidth was the top optimized resistance surface for A. maculatum. A resistance surface with traffic rate and topographic curvature, both at a 500m Gaussian kernel bandwidth was the top optimized resistance surf...