Genes in Streams: Using DNA to Understand the Movement of Freshwater Fauna and Their Riverine Habitat

Abstract

Today, decisions regarding the management and conservation of populations are often informed to some degree by population genetics. A fundamental measure sought by decisionmakers is the degree of connectivity between populations, which, when approached from a genetic perspective, may be influenced by many factors, making it difficult to generalize across taxa, habitats, or life histories. In the case of freshwaterlimited fauna, the shared constraint of habitat structure (e.g., a dendritic stream network) imposed on all species in the system simplifies the task. A number of models have been proposed that predict how populations of taxa with different life-history traits and dispersal capabilities interact within structured freshwater habitats of this kind. In this article, we summarize these models and illustrate the general patterns of phylogeographic structure expected to occur under different scenarios of freshwater population connectivity. Additionally, we describe how the genetic structure of stream inhabitants can reflect historical changes in the physical structure of streams and thus open a window on past patterns of connectivity. A greater understanding of these concepts will contribute to an improved multidisciplinary approach to managing freshwater ecosystems.

Landscape genetics informs mesohabitat preference and conservation priorities for a surrogate indicator species in a highly fragmented river system

“…The inferred overall pattern led us to reject the stream hierarchy model for G. marmoratus in the MDB and to propose either the Death Valley model or a nonequilibrium model of population structure (Meffe and Vrijenhoek, 1988;Hughes et al, 2009). The Death Valley model predicts that remnant populations across the MBD landscape have a high level of between-population structure, but no significant basin or catchment structure, no IBD, no gene flow and small local population size, perhaps driven by naturally chaotic and variable patterns of stream connectivity exacerbated by human-driven change (Walker et al, 1995).…”

“…One such model is the stream hierarchy model that predicts that dispersal of riverine organisms is influenced by riverine distances between populations, and is therefore hierarchically constrained by the dendritic nature of the river basins (Meffe and Vrijenhoek, 1988;Fausch et al, 2002;Hughes et al, 2009). Being able to test predictions from spatial models of population structure can greatly improve our knowledge of the movements and habitat preferences of a species.…”

Fish movement in an Atlantic Forest stream

“…There are also some intra-population behaviour differences in which some individuals are sedentary, some are mobile, and others alternate between both behaviours (Knaepkens et al, 2005). Such variability contributes to colonization and maintenance of the gene flow (Hughes et al, 2009). Previous studies in tropical streams (e.g.…”

Human effects on ecological connectivity in aquatic ecosystems: Integrating scientific approaches to support management and mitigation

“…Freshwater systems, conversely, cover only ~0.8% of the earth's surface and are typically organised into networks of hierarchically branching streams and rivers, occasionally punctuated by lakes and wetlands (Grant et al 2007). The complex structure of freshwater ecosystems can create isolation among populations at 110 much smaller spatial scales than would be expected in marine systems; for example, when nearby populations occupy habitats that are not connected via the river network (Hughes et al 2009). Four general models of ecological connectivity have been proposed to describe the unique constraints imposed by hierarchical network structure in freshwater ecosystems (Text box 1).…”