Data from: Scale-dependent genetic structure of the Idaho giant salamander (Dicamptodon aterrimus) in stream networks

The network architecture of streams and rivers constrains evolutionary, demographic, and ecological processes of freshwater organisms. This consistent architecture also makes stream networks useful for testing general models of population genetic structure and the scaling of gene flow. We examined genetic structure and gene flow in the facultatively paedomorphic Idaho giant salamander, Dicamptodon aterrimus, in stream networks of Idaho and Montana, USA. We used microsatellite data to test population structure models by (1) examining hierarchical partitioning of genetic variation in stream networks and (2) testing for genetic isolation by distance along stream corridors versus overland pathways. Replicated sampling of streams within catchments within three river basins revealed that hierarchical scale had strong effects on genetic structure and gene flow. AMOVA identified significant structure at all hierarchical scales (among streams, among catchments, among basins), but divergence among catchments had the greatest structural influence. Isolation by distance was detected within catchments, and in-stream distance was a strong predictor of genetic divergence. Patterns of genetic divergence suggest that differentiation among streams within catchments was driven by limited migration, consistent with a stream hierarchy model of population structure. However, there was no evidence of migration among catchments within basins, or among basins, indicating that gene flow only counters the effects of genetic drift at smaller scales (within rather than among catchments). These results show the strong influence of stream networks on population structure and genetic divergence of a salamander, with contrasting effects at different hierarchical scales.

河溪与河流的网络架构会制约淡水生物的演化、种群统计与生态过程。这种统一的网络架构也使得河溪网络成为检验种群遗传结构通用模型以及基因流尺度效应的理想研究体系。我们以美国爱达荷州与蒙大拿州河溪网络中的兼性幼态型爱达荷巨螈（*Dicamptodon aterrimus*）为研究对象，探究其种群遗传结构与基因流模式。我们利用微卫星数据检验种群遗传结构模型，具体通过两个途径：一是分析河溪网络中遗传变异的层级分区模式；二是检验沿溪流水道与陆上通路的遗传距离隔离效应差异。我们对三个流域内各集水区的河溪进行重复采样，结果显示层级尺度对种群遗传结构与基因流具有显著影响。分子方差分析（AMOVA）结果显示，所有层级尺度（河溪间、集水区间、流域间）均存在显著的遗传结构，但集水区间的遗传分化对种群结构的影响最为显著。在集水区内部检测到了距离隔离效应，且河溪内距离是遗传分化的强预测因子。遗传分化模式表明，集水区内部河溪间的遗传分化由有限的迁移所驱动，这与种群结构的河溪层级模型相符。然而，流域内集水区之间以及不同流域之间均未检测到迁移信号，这表明基因流仅能在更小的尺度（集水区内部而非集水区之间）抵消遗传漂变的影响。上述结果证实了河溪网络对该爱达荷巨螈种群结构与遗传分化的强烈影响，且不同层级尺度下的影响模式存在显著差异。