Background Use of genomic tools to characterize wildlife populations has increased in recent years. In the past, genetic characterization has been accomplished with more traditional genetic tools (e.g., microsatellites). The explosion of genomic methods and the subsequent creation of large SNP datasets has led to the promise of increased precision in population genetic parameter estimates and identification of demographically and evolutionarily independent groups, as well as questions about the future usefulness of the more traditional genetic tools. At present, few empirical comparisons of population genetic parameters and clustering analyses performed with microsatellites and SNPs have been conducted. Results Here we used microsatellite and SNP data generated from Gunnison sage-grouse (Centrocercus minimus) samples to evaluate concordance of the results obtained from each dataset for common metrics of genetic diversity (HO, HE, FIS, AR) and differentiation (FST, GST, DJost). Additionally, we evaluated clustering of individuals using putatively neutral (SNPs and microsatellites), putatively adaptive, and a combined dataset of putatively neutral and adaptive loci. We took particular interest in the conservation implications of any differences. Generally, we found high concordance between microsatellites and SNPs for HE, FIS, AR, and all differentiation estimates. Although there was strong correlation between metrics from SNPs and microsatellites, the magnitude of the diversity and differentiation metrics were quite different in some cases. Clustering analyses also showed similar patterns, though SNP data was able to cluster individuals into more distinct groups. Importantly, clustering analyses with SNP data suggest strong demographic independence among the six distinct populations of Gunnison sage-grouse with some indication of evolutionary independence in two or three populations; a finding that was not revealed by microsatellite data. Conclusion We demonstrate that SNPs have three main advantages over microsatellites: more precise estimates of population-level diversity, higher power to identify groups in clustering methods, and the ability to consider local adaptation. This study adds to a growing body of work comparing the use of SNPs and microsatellites to evaluate genetic diversity and differentiation for a species of conservation concern with relatively high population structure and using the most common method of obtaining SNP genotypes for non-model organisms.

Population genomic analysis can be an important tool in understanding local adaptation. Identification of potential adaptive loci in such analyses is usually based on the survey of a large genomic dataset in combination with environmental variables. Phenotypic data are less commonly incorporated into such studies, although combining a genome scan analysis with a phenotypic trait analysis can greatly improve the insights obtained from each analysis individually. Here, we aimed to identify loci potentially involved in adaptation to climate in 283 Loblolly pine (Pinus taeda) samples from throughout the species' range in the southeastern United States. We analyzed associations between phenotypic, molecular, and environmental variables from datasets of 3082 single nucleotide polymorphism (SNP) loci and 3 categories of phenotypic traits (gene expression, metabolites, and whole-plant traits). We found only 6 SNP loci that displayed potential signals of local adaptation. Five of the 6 identified SNPs are linked to gene expression traits for lignin development, and 1 is linked with whole-plant traits. We subsequently compared the 6 candidate genes with environmental variables and found a high correlation in only 3 of them (R 2 > 0.2). Our study highlights the need for a combination of genotypes, phenotypes, and environmental variables, and for an appropriate sampling scheme and study design, to improve confidence in the identification of potential candidate genes.

Biological soil crusts can affect seed germination and seedling establishment. We have investigated the effect of biological soil crusts on seed water status as a potential mechanism affecting seed germination. The seed water potential of two annual grasses, one exotic Bromus tectorum L. and another native Vulpia microstachys Nutt., were analyzed after placing the seeds on bare soil, on a crust that contains various lichens and mosses (mixed crust), or on a crust dominated by the crustose lichen Diploschistes muscorum (Scop.) R. Sant. (Diploschistes crust). Seed water potential and germination were similar on the bare soil and the mixed crust, except for the initial germination of V. microstachys, which was higher on the mixed crust than on the bare soil. For the two grasses studied, seed water potential was significantly higher on the bare soil and mixed crust than on the Diploschistes crust. These differences in water potential correlated with differences in germination, which was much lower on the lichen crust. Experiments were conducted under two watering regimens. Increasing the frequency of watering amplified the differences in seed water potential and germination between the Diploschistes crust and the other two surfaces. For a particular watering regimen, the bare soil, mixed crust, and Diploschistes crust received the same amount of water, but they reached significantly different water potentials. Throughout the experiments, the water potential of the soil and mixed crust remained above −0.6 MPa, while there was a marked decline in the water potential of the Diploschistes surface to about −4 MPa. To ascertain that water was the major factor limiting germination on the Diploschistes crust, we conducted germination tests in an environment with 100% relative humidity. Under these conditions, germination on the Diploschistes crust was similar to that on the bare soil. However, the seeds that germinated on the Diploschistes crust did not penetrate this surface and approximately 60% of their root tips became necrotic. Our results indicate that the presence of D. muscorum can inhibit seedling establishment by two mechanisms: a reduction in seed water absorption and an increase in root tip mortality.

Understanding the genetic underpinning of adaptive divergence among populations is a key goal of evolutionary biology and conservation. Gunnison sage‐grouse ( Centrocercus minimus ) is a sagebrush obligate species with a constricted range consisting of seven discrete populations, each with distinctly different habitat and climatic conditions. Though geographically close, populations have low levels of natural gene flow resulting in relatively high levels of differentiation. Here, we use 15,033 SNP loci in genomic outlier analyses, genotype–environment association analyses, and gene ontology enrichment tests to examine patterns of putatively adaptive genetic differentiation in an avian species of conservation concern. We found 411 loci within 5 kbp of 289 putative genes associated with biological functions or pathways that were overrepresented in the assemblage of outlier SNPs. The identified gene set was enriched for cytochrome P450 gene family members (CYP4V2, CYP2R1, CYP2C23B, CYP4B1) and could impact metabolism of plant secondary metabolites, a critical challenge for sagebrush obligates. Additionally, the gene set was also enriched with members potentially involved in antiviral response (DEAD box helicase gene family and SETX). Our results provide a first look at local adaption for isolated populations of a single species and suggest adaptive divergence in multiple metabolic and biochemical pathways may be occurring. This information can be useful in managing this species of conservation concern, for example, to identify unique populations to conserve, avoid translocation or release of individuals that may swamp locally adapted genetic diversity, or guide habitat restoration efforts.

Maintenance of genetic diversity is important for conserving species, especially those with fragmented habitats or ranges. In the absence of natural dispersal, translocation can be used to achieve this goal, although the success of translocation can be difficult to measure. Here we evaluate genetic change following translocation in Gunnison Sage-Grouse (Centrocercus minimus), a species reduced to 7 discrete populations with low levels of gene flow and high levels of genetic differentiation. Between 2000 and 2014, 306 birds from the largest and most genetically diverse population (Gunnison Basin) were translocated to 5 much smaller satellite populations to augment local population size and increase genetic diversity. Although the magnitude of the effect varied by population, we found evidence of increased genetic variation, decreased genetic differentiation from Gunnison Basin, and reproduction between translocated individuals and resident birds. These results suggest that translocations are impacting satellite populations, with current data providing a new baseline for genetic diversity among populations of this imperiled species.

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Habitat fragmentation and degradation impacts an organism's ability to navigate the landscape, ultimately resulting in decreased gene flow and increased extinction risk.Understanding how landscape composition impacts gene flow (i.e., connectivity) and interacts with scale is essential to conservation decision-making. We used a landscape genetics approach implementing a recently developed statistical model based on the generalized Wishart probability distribution to identify the primary landscape features affecting gene flow and estimate the degree to which each component influences connectivity for Gunnison sage-grouse (Centrocercus minimus). We were interested in two spatial scales: among distinct populations rangewide and among leks (i.e., breeding grounds) within the largest population, Gunnison Basin. Populations and leks are nested within a landscape fragmented by rough terrain and anthropogenic features, although requisite sagebrush habitat is more contiguous within populations.Our best fit models for each scale confirm the importance of sagebrush habitat in connectivity, although the important sagebrush characteristics differ. For Gunnison Basin, taller shrubs and higher quality nesting habitat were the primary drivers of connectivity, while more sagebrush cover and less conifer cover facilitated connectivity rangewide. Our findings support previous assumptions that Gunnison sage-grouse range contraction is largely the result of habitat loss and degradation. Importantly, we report direct estimates of resistance for landscape components that can be used to create resistance surfaces for prioritization of specific locations for conservation or management (i.e., habitat preservation, restoration, or development) or as we demonstrated, can be combined with simulation techniques to predict impacts to connectivity from potential management actions.

Gunnison Sage-grouse are an obligate sagebrush species that has experienced significant population declines and has been proposed for listing under the U.S. Endangered Species Act. In order to examine levels of connectivity among Gunnison Sage-grouse leks, we identified 13 novel microsatellite loci though next-generation shotgun sequencing, and tested them on the closely related Greater Sage-grouse. The number of alleles per locus ranged from 2 to 12. No loci were found to be linked, although 2 loci revealed significant departures from Hardy-Weinberg equilibrium or evidence of null alleles. While these microsatellites were designed for Gunnison Sage-grouse, they also work well for Greater Sage-grouse and could be used for numerous genetic questions including landscape and population genetics.