Landscape features, such as land use, vegetation cover, roads, and topography, strongly influence genetic connectivity yet these relationships can vary across spatial scales which therefore requires multi-scale approaches for evaluating landscape genetics relationships. We used the federally threatened eastern indigo snake (Drymarchon couperi), a terrestrial habitat generalist endemic to the southeastern United States, as a case study with which to evaluate the consequences of different approaches for accounting for spatial scale when optimizing genetics resistance surfaces using the software ResistanceGA. Resistance surfaces with scale selected using a true optimization approach simultaneously comparing all possible combinations of scale across each set of covariates performed better than resistance surfaces where scale was selected individually for each covariate. Truly optimized resistance surfaces also outperformed resistance surfaces based on habitat selection models and categorical land cover maps. Optimal scales were usually larger than average indigo snake home range sizes suggesting that gene flow was mediated mostly by extra-home range dispersal. Large tracts of undeveloped upland habitat with intermediate habitat heterogeneity most promoted indigo snake gene flow while roads did not appear to restrict gene flow. Our results show the importance of testing a wide range of spatial scales in landscape genetics studies. 

Article: Bauder JM, Peterman WE, Spear SF, Jenkins CL, Whiteley AR, McGarigal K. 2021. Multiscale assessment of functional connectivity: Landscape genetics of eastern indigo snakes in an anthropogenically fragmented landscape in central Florida. Molecular Ecology https://doi.org/10.1111/mec.15979.