Comparative landscape genetic analysis of three Pacific salmon species from subarctic North America

Abstract

We examined the assumption that landscape heterogeneity similarly influences the spatial distribution of genetic diversity in closely related and geographically overlapping species. Accordingly, we evaluated the influence of watershed affiliation and nine habitat variables from four categories (spatial isolation, habitat size, climate, and ecology) on population divergence in three species of Pacific salmon (Oncorhynchus tshawytscha, O. kisutch, and O. keta) from three contiguous watersheds in subarctic North America. By incorporating spatial data we found that the three watersheds did not form the first level of hierarchical population structure as predicted. Instead, each species exhibited a broadly similar spatial pattern: a single coastal group with populations from all watersheds and one or more inland groups primarily in the largest watershed. These results imply that the spatial scale of conservation should extend across watersheds rather than at the watershed level which is the scale for fishery management. Three independent methods of multivariate analysis identified two variables as having influence on population divergence across all watersheds: precipitation in all species and subbasin area (SBA) in Chinook. Although we found general broad-scale congruence in the spatial patterns of population divergence and evidence that precipitation may influence population divergence in each species, we also found differences in the level of population divergence (coho [ Chinook and chum) and evidence that SBA may influence population divergence only in Chinook. These differences among species support a species-specific approach to evaluating and planning for the influence of broad-scale impacts such as climate change.

Landscape heterogeneity and local adaptation define the spatial genetic structure of Pacific salmon in a pristine environment

“…Second, we predict that an inland-to-coastal transition of within-population diversity (allelic richness) will occur that coincides with the transition in environments between the upper and middle/ lower Copper River. Olsen et al (2011) hypothesized, tested, and confirmed a similar pattern for Pacific salmon in neighboring regions. Third, we predict that sockeye and Chinook salmon will exhibit largely congruent patterns of hierarchical genetic structure, highlighting the importance that landscape heterogeneity and historical geologic processes play in determining the genetic structure in multiple species.…”

“…Following, analyses were re-run incorporating outlier SNPs to determine if putative adaptive variation among populations changed population groups suggesting signals of adaptive divergence among geographically proximate populations. Because latitude and longitude data do not reflect the true spatial relationships in a fluvial system (Olsen et al 2011), we calculated proxy x and y coordinates using a pairwise matrix of waterway distances between collections to project the populations on a multidimensional scale (MDS) using the program NTSYS (Rohlf 1994). The populations were spatially referenced using the first and second MDS values (Manni et al 2004).…”

“…The middle and lower Copper River and its main tributaries, the Tazlina, Klutina, Tonsina, and Chitina rivers, drain a more forested, mountainous landscape, are largely fed by glacial meltwater, and are characterized by higher gradient, glacially turbid reaches. Based on environmental differences between the upper and middle/lower Copper River and similar research conducted on Pacific salmon in subarctic North America (Olsen et al 2011), we hypothesize that sockeye salmon will exhibit an inland-coastal transition in the distribution of genetic variation, and that abrupt differences in allele frequencies (i.e. barriers) may occur between the two environments.…”

“…Landscape genetics methods facilitate our understanding of the role that landscape heterogeneity plays in shaping genetic structure in natural populations (Manel et al 2003;Storfer et al 2007). Comparison of closely related and geographically overlapping species can be particularly useful in cases where the landscape may similarly (or differentially) influence the genetic structure of multiple species (Marten et al 2006;Olsen et al 2011). Congruent patterns among species may highlight the importance that landscape, including historical processes, plays in determining spatial genetic structure through demographic processes such as gene flow and genetic drift (Waples 1987;Petren et al 2005;Gagnon and Angers 2006).…”

“…differential dispersal abilities; Gomez-Uchida et al 2009) or the importance of species-specific adaptation to local environments (Short and Caterino 2009). In either regard, an understanding of the interacting roles that gene flow, genetic drift, and local adaptation play in shaping genetic structure can greatly improve our knowledge of species and improve conservation efforts (Schwartz et al 2009;Olsen et al 2011).…”