title: 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.
authors.affiliation: Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, 48109. thomaz@umich.edu.
authors.forename: Andréa T
authors.initials: AT
authors.lastname: Thomaz
authors.affiliation: Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, 48109.|Department of Biological Science, Purdue University, West Lafayette, Indiana, 47907.|Department of Forestry and Natural Resources, Purdue University, West Lafayette, Indiana, 47907.
authors.forename: Mark R
authors.initials: MR
authors.lastname: Christie
authors.affiliation: Department of Ecology and Evolutionary Biology, University of Michigan, Ann Arbor, Michigan, 48109.
authors.forename: L Lacey
authors.initials: LL
authors.lastname: Knowles
mesh_terms: D000818:Animals; D017753:Ecosystem; D005399:Fishes / Q000145:classification* / Q000235:genetics; D045483:Rivers
keywords: Agent-based model (ABM); confluence position; dendritic shape; downstream migration; genetic structure; riverscapes