Combining multiscale replication in network and landscape-genetic analyses to assess functional connectivity and population resilience in Parnassius clodius butterflies

Abstract Characterizing functional connectivity is an important challenge in the face of ongoing environmental change. Approaches combining landscape-genetic and network methodologies have shown promise in allowing for simultaneous identification of strong and vulnerable populations, and the landscape factors that may inhibit or facilitate population connectivity. Here we leverage these tools to assess the genetic structure and functional connectivity of Parnassius clodius butterflies in three protected regions in the United States, North Cascades National Park (WA), Grand Teton National Park (WY), and Yosemite National Park (CA), and determine whether these metrics vary with differences in sampling scale among regions. We also test the resilience of population connectivity to extirpation using graph–theoretic analyses (e.g. network analyses) and test the relative importance of isolation-by-distance, isolation-by-resistance, and isolation-by-environment in limiting population connectivity, using butterfly habitat suitability, host plant data, terrain roughness, percent forest cover, and climate variables. Both traditional genetic clustering analyses and network analyses revealed fine-scale genetic structure across all three regions. Our network analyses revealed similarity in topology across regions despite significant landscape variation, and network sensitivity analyses revealed that P. clodius subpopulations within the Grand Teton and Yosemite NP regions are more vulnerable to perturbations. Our landscape-genetic analyses suggest that environmental variation has an important impact on genetic differentiation in addition to geographical distance, but the contribution of specific variables varies across replicate landscapes.