Stream hierarchy defines riverscape genetics of a North American desert fish

Abstract

Global climate change is apparent within the Arctic and the south-western deserts of North America, with record drought in the latter reflected within 640,000 km(2) of the Colorado River Basin. To discern the manner by which natural and anthropogenic drivers have compressed Basin-wide fish biodiversity, and to establish a baseline for future climate effects, the Stream Hierarchy Model (SHM) was employed to juxtapose fluvial topography against molecular diversities of 1092 Bluehead Sucker (Catostomus discobolus). MtDNA revealed three geomorphically defined evolutionarily significant units (ESUs): Bonneville Basin, upper Little Colorado River and the remaining Colorado River Basin. Microsatellite analyses (16 loci) reinforced distinctiveness of the Bonneville Basin and upper Little Colorado River, but subdivided the Colorado River Basin into seven management units (MUs). One represents a cline of three admixed gene pools comprising the mainstem and its lower-gradient tributaries. Six others are not only distinct genetically but also demographically (i.e. migrants/generation <9.7%). Two of these (i.e. Grand Canyon and Canyon de Chelly) are defined by geomorphology, two others (i.e. Fremont-Muddy and San Raphael rivers) are isolated by sharp declivities as they drop precipitously from the west slope into the mainstem Colorado/Green rivers, another represents an isolated impoundment (i.e. Ringdahl Reservoir), while the last corresponds to a recognized subspecies (i.e. Zuni River, NM). Historical legacies of endemic fishes (ESUs) and their evolutionary potential (MUs) are clearly represented in our data, yet their arbiter will be the unrelenting natural and anthropogenic water depletions that will precipitate yet another conservation conflict within this unique but arid region.

Gene flow and genetic structure of a mountain riparian tree species, Euptelea pleiospermum (Eupteleaceae): how important is the stream dendritic network?

“…This method differs from IBD in two aspects: (1) it allows shorter sections of streams to be assigned larger genetic distances, and (2) it does not involve geographic distance but rather stream network topology (Hopken et al 2013). STREAMTREE, an extension of the least-squares method for constructing evolutionary trees, is a new statistical approach to map genetic distance among populations to the sections of streams that connect those populations (Kalinowski et al 2008).…”

“…Clearly, the preferential dispersal pathways of species in study influence if and how the effects of dendritic network occur. Species with low dispersal ability, whose dispersal is always restricted to the river corridor, is more likely to show hierarchical genetic structure, e.g., Mimulus caespitosus (Ritland 1989), Dicamptodon aterrimus (Mullen et al 2010), Abedus herberti (Phillipsen and Lytle 2013), and Catostomus discobolus (Hopken et al 2013). On the contrary, species with high dispersal ability, which can move extensively across the river system, always did not present hierarchical genetic structure, e.g., E. pleiospermum, Nuphar lutea (Fér and Hroudová 2008), and P. australis (Fér and Hroudová 2009).…”

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

“…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. This allows us to better direct conservation initiatives, predict metapopulation scenarios and plan for future threats (see, for example, Hopken et al, 2013).…”

“…Very few studies have been conducted on benthic, low dispersal species that display traits that make them more susceptible to habitat fragmentation (McCraney et al, 2010;Hopken et al, 2013;Roberts et al, 2013). In addition, most studies have predominantly focused on the impact that barriers or landscapes variables have on population connectivity, or gene flow, with only a few assessing the impact of the local environment on population genetic diversity (Cena et al, 2006;Faulks et al, 2010Faulks et al, , 2011).…”

Applying landscape genetics to evaluate threats affecting endangered Atlantic salmon populations

“…an agricultural field adjacent to a particular stream reach) using resistance surfaces developed for a dendritic landscape (i.e. one in which animals are constrained to move along the stream network ;Fagan 2002;Hopken et al 2013).…”