“…Landscape genetic clustering and assignment methods have largely built upon classical methods from population genetics (e.g., principal components analysis, STRUCTURE, Pritchard, Stephens, & Donnelly, ) by incorporating spatial information (e.g., GENELAND, Guillot, Mortier, & Estoup, ; sPCA, Jombart, Devillard, Dufour, & Pontier, ) and environmental heterogeneity (e.g., constrained ordination, Anderson & Willis, ; POPS, Jay, ) into estimates of population structure and providing quantitative estimates of ancestry for each individual (François & Waits, ). Clustering methods have been relatively popular in studying pathogens and implemented for the inference of landscape barriers affecting both host (Addis, Lowe, Hossack, & Allendorf, ; Cote, Garant, Robert, Mainguy, & Pelletier, ; Cullingham, Kyle, Pond, Rees, & White, ; Frantz, Cellina, Krier, Schley, & Burke, ) and microparasite (Brar et al., ; Rieux et al., ) spatial genetic variation. Edge detection methods, such as Monmonier's maximum difference algorithm, (Monmonier, ) have also been used to detect landscape barriers to transmission in pathogen studies (Carrel et al., ; Joannon et al., ).…”