Data from: A genomic assessment of population structure and gene flow in an aquatic salamander identifies the roles of spatial scale, barriers, and river architecture

Population structure and gene flow of species in lotic environments can be
constrained by river network architecture, species life history and
heterogeneous local barriers. Identifying the factors that influence
population structure and gene flow, especially in species limited to
movement within a river network, is vital for understanding the
evolutionary and demographic history of a species. We explored population
structure and gene flow for a fully aquatic salamander, the common
mudpuppy (Necturus maculosus), in Kentucky (USA) using genomic data. We
examined population structure using both parametric and nonparametric
methods, and we tested for a history of lineage divergence among
identified genetic clusters. We quantified the partitioning of genetic
variation at different hierarchical levels, and we tested for signatures
of isolation by distance. Additionally, we used coalescent-based model
selection to identify a best-fit model of gene flow between our three
sampled basins. We found the greatest support for population structure
between the Kentucky River basin and the combined Licking and Kinniconick
basins, with further subdivision within both the Kentucky and Licking
River basins. However, we found no evidence for a history of lineage
divergence among these structured units. The movement of N. maculosus is
constrained by the lotic network architecture, which likely drives the
evolution of this hierarchical population structure, with increasing
differentiation between sites nested in river basins, and even greater
differentiation between basins. However, we also found evidence for
population structure not explained by river architecture, with an isolated
population embedded within the Kentucky River basin. This study
demonstrates the heterogeneity in population structure that can evolve in
aquatic species occupying lotic systems and illustrates the potential for
genomic data to disentangle these complex patterns.