Abstract

AbstractAnalyses of the factors shaping genetic variation in widespread plant species are important for understanding the evolutionary history and local adaptation and have applied significance for guiding conservation and restoration decisions. Thurber's needlegrass (Achnatherum thurberianum) is a widespread, locally abundant grass that inhabits heterogeneous arid environments of western North America and is of restoration significance. It is a common component of shrubland steppe communities in the Great Basin Desert, where drought, fire, and invasive grasses have degraded natural communities. Using a reduced representation sequencing approach, we generated SNP data at 5677 loci across 246 individuals from 17 A. thurberianum populations spanning five previously delineated seed zones from the western Great Basin. Analyses revealed a pronounced population genetic structure, with individuals forming consistent geographical clusters across a variety of population genetic analyses and spatial scales. Low levels of genetic diversity within populations, as well as high population estimates of linkage disequilibrium and relatedness, were consistent with self‐fertilization as a contributor to population differentiation. Variance partitioning and partial redundancy analysis (pRDA) indicated local adaptation to environment as additionally influencing the spatial distribution of genetic variation. The environmental variables driving these results were similar to those implicated in recent genecological work which inferred local adaptation for seed zone delineation. Our analyses also revealed a complex evolutionary history of A. thurberianum in the Great Basin, where previously delineated seed zones contain distantly related populations. Our results indicate evolutionary history, mating system, and differentiation across distinct geographic and environmental scales have shaped genetic variation in A. thurberianum and illustrate how numerous aspects of population genetic variation might require consideration for restoration planning.

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