The architecture of river networks can drive the evolutionary dynamics of aquatic populations

Abstract

It is widely recognized that physical landscapes can shape genetic variation within and between populations. However, it is not well understood how riverscapes, with their complex architectures, affect patterns of neutral genetic diversity. Using a spatially explicit agent-based modeling (ABM) approach, we evaluate the genetic consequences of dendritic river shapes on local population structure. We disentangle the relative contribution of specific river properties to observed patterns of genetic variation by evaluating how different branching architectures and downstream flow regimes affect the genetic structure of populations situated within river networks. Irrespective of the river length, our results illustrate that the extent of river branching, confluence position, and levels of asymmetric downstream migration dictate patterns of genetic variation in riverine populations. Comparisons between simple and highly branched rivers show a 20-fold increase in the overall genetic diversity and a sevenfold increase in the genetic differentiation between local populations. Given that most rivers have complex architectures, these results highlight the importance of incorporating riverscape information into evolutionary models of aquatic species and could help explain why riverine fishes represent a disproportionately large amount of global vertebrate diversity per unit of habitable area.

Loss of dendritic connectivity in southern California's urban riverscape facilitates decline of an endemic freshwater fish

“…This node has numerous braids and side channels that slow flow and provide refugia, and lack of consistent surface water across the Piru Gap impedes downstream dispersal beyond this reach. These physical features may promote migration–drift equilibrium and contribute to the local accumulation of genetic variation, a finding consistent with the predictions of dendritic systems in simulation studies (Grant et al., ; Morrissey & de Kerckhove, ; Thomaz et al., ). Co‐occurring threespine stickleback Gasterosteus aculeatus show the same pattern of elevated diversity in this reach compared to upstream areas (Richmond et al., ), providing further evidence that network location influences spatial genetic variation in this drainage.…”

Distributional shifts – not geographic isolation – as a probable driver of montane species divergence

“…Although beyond the scope of these analyses, it might be worthwhile to consider additional variants of each hypothesis beyond the two used here to model population connectivity (see Bemmels et al 2016 for examples based on physiological tradeoffs and local adaptation). Lastly, despite the caveats discussed here, it is worth noting that without the spatially explicit, albeit complex, models exemplified here (Neuenschwander et al 2008, He et al 2013, Thomaz et al 2016), questions about the drivers of divergence and other evolutionary processes Knowles 2016, Papadopoulou andKnowles 2016) would continue to go unexplored. That is, the analyses here would not have to be repeated.…”

Watershed‐level brook trout genetic structuring: Evaluation and application of riverscape genetics models

“…Both were representative of contemporary brook trout population status and distribution in Connecticut; while many headwater streams (Strahler order <2) had self‐sustaining populations, most were separated by mainstem habitat that does not support yearlong brook trout occupancy. The two watersheds were chosen based on the contrasting river network complexities, which may potentially affect dispersal and genetic structuring (Thomaz et al., ). The FR system (1,573 km 2 ) consisted of a complex branching network of tributaries whereas the upper SR system (1,039 km 2 ) was made up of five parallel linear sub‐watersheds, which was evident by the difference in average drainage area of the downstream watershed (FR = 242.10 km 2 and SR = 77.03 km 2 ; Table ).…”