Landscape genetics is a rapidly growing field of study that compares patterns of gene flow among populations with habitat heterogeneity across a landscape to infer the interaction between dispersal of individuals and their physical environment. Empirical data generated from a landscape genetics study can inform conservation and management strategies, making the field increasing popular. However, concerns have arisen in the literature that the field is expanding faster than the analytic framework that supports it. Multiple methods for generating estimates of the association among habitat types and dispersal (i.e., least-cost paths and resistance surfaces) have been proposed, and there is a debate as to which statistical methods are best for examining the genetic structure on a landscape. We use an integrated empirical- and expert-opinion-based strategy to generate a landscape resistance surface for the California tiger salamander, Ambystoma californiense, which is a species of conservation concern. We utilize several alternative analysis methods (e.g., CCA, MRDM, ResistanceGA, GESTE, and partial Mantel tests) to look for agreement among methods describing the relationship of landscape features and genetic variation. Our analysis revealed variation among methods for describing genetic structure in this A. californiense metapopulation, but all methods indicated the presence of genetic structure, to some extent, across the landscape. This empirical data set provides both a perspective on habitat management for A. californiense and on the suitability of several novel analysis strategies for landscape genetics.