Centrocercus urophasianus

Common Name: 
SAGE GROUSE
Taxonomic Key: 
Birds
Legacy ID: 
524
Species Name: 
urophasianus

Evaluation of Genetic, Behavioral and Morphological Distinctness of Greater Sage-grouse in the Bi-State Planning Area

Code: 
RB00CNJ
A sage brush habitat. USGS photo.
A sage brush habitat. USGS photo.
Abstract: 

The goal of this study was to obtain a more comprehensive understanding of the boundaries of this genetically unique population (where the Bi-State population begins) and to examine the genetic structure within the Bi-State, which is needed to help guide effective management decisions. Our genetic data supports the idea that the Bi-State population represents a genetically unique population and identified the Pine Nut Mountains to be the northern boundary of the Bi-State population.  We also found three distinct subpopulations (southern Pine Nut Mountains, mid Bi-State, and White Mountains) within the Bi-State that would benefit from conservation and management actions.

Landscape Genetic Analysis of Greater Sage-grouse in Wyoming

Code: 
RB00CNJ
Flying Greater Sage-grouse. Photo by T. Gettleman, USGS.
Flying Greater Sage-grouse. Photo by T. Gettleman, USGS.
Abstract: 

This study compared the genetic differences between Greater Sage-grouse breeding areas with seasonal habitat distributions or combinations of landscape factors – such as amount of sagebrush habitat, agriculture fields or roads – to understand how each factor or combination of factors influence effective dispersal of sage-grouse across the state. The study revealed that the juxtaposition and quality of nesting and winter seasonal habitats were the greatest predictors of gene flow for Greater Sage-grouse in Wyoming. Furthermore, the combinations of high levels of forest cover and highly rugged (steep and uneven) terrain or low levels of sagebrush cover and highly rugged terrain were correlated with low levels of gene flow among sage-grouse populations. This research is in collaboration with the University of Waterloo, supported by Wyoming Game and Fish Department and BLM.

Z Chromosome Divergence, Polymorphism, and Relative Effective Population Size in a Genus of Lekking Birds

Code: 
RB00CNJ
A male sage-grouse. BLM photo.
A male sage-grouse. BLM photo.
Abstract: 

The goal of this project was to map genetic markers (Single Nucleotide Polymorphisms or SNPs) that were identified in comparisons of Greater and Gunnison Sage-grouse to the chicken genome and determine the chromosomal location of each SNP. We wanted to determine where in the genome (which chromosome or chromosomes) housed SNPs with the greatest divergence between Greater and Gunnison Sage-grouse. When we found that the divergence SNPs were on the Z chromosome we evaluated the role of the lek mating system on this phenomenon. Species with more skewed mating systems (such as lekking sage-grouse) had smaller effective population sizes on the Z chromosome which may contribute to the increased divergence on the Z. This research was in collaboration with the University of Colorado, Denver.

Product: Z chromosome divergence, polymorphism and relative effective population size in a genus of lekking birds

Re-examining Patterns of Genetic Variation in Sage-grouse Using Genomic Techniques

Code: 
RB00CNJ
A Gunnison Sage-grouse. Photo by Doug Ouren, USGS.
A Gunnison Sage-grouse. Photo by Doug Ouren, USGS.
Abstract: 

The goal of this study was to use new comprehensive genomic markers to re-examine patterns of genetic variation in sage-grouse focusing on differences between Gunnison Sage-grouse, the Bi-State population of Greater Sage-grouse, and the rest of the range of Greater Sage-grouse. We found that by using genomic methods we were able to reveal that Gunnison Sage-grouse are much more diverged from Greater Sage-grouse than the Bi-State population of Greater Sage-grouse is from Greater Sage-grouse. This study confirms definitively that Gunnison Sage-grouse represent a distinct species and that the Bi-State is a distinct population of Greater Sage-grouse.  This study also confirms that Gunnison Sage-grouse have much lower genomic diversity than Greater Sage-grouse. This research was in collaboration with the University of Colorado, Denver.

Publication: Genomic single-nucleotide polymorphisms confirm that Gunnison and Greater sage-grouse are genetically well differentiated and that the Bi-State population is distinct

Rangewide Connectivity and Landscape Genetic Assessment for Greater Sage-grouse

Code: 
RB00CNJ.22.3
Greater Sage-grouse chicks. USGS photo.
Greater Sage-grouse chicks. USGS photo.
Abstract: 

Greater Sage-grouse consist primarily of a few large core populations surrounded by numerous small populations. The viability of these small populations is sustained by dispersing individuals from neighboring populations.  Development that causes habitat loss or creates barriers to dispersal between core areas restricts movements important to maintain genetic diversity, augment small populations, or recolonize extirpated populations. The goal of this study is to assess connectivity among core areas, and to identify features that may act as barriers to movement.  In addition to defining populations and assessing connectivity, this study uses genetic approaches to address many other relevant questions including the conservation of genetic diversity, the impacts of inbreeding, and the association among landscape and geographic characteristics, habitats, and genetics. This research is in collaboration with USGS, USFS, and the University of Montana and is supported by Natural Resources Conservation Service, USFWS, and 11 US state fish and wildlife agencies.

Latent Spatial Models and Sampling Design for Landscape Genetics

Code: 
RB00CNJ.22.2
A male Greater Sage-grouse. USGS photo.
A male Sage-grouse. USGS photo.
Abstract: 

The goal of this study is to develop a spatially-explicit approach for modeling genetic variation across space and to illustrate how this approach can be used to optimize spatial prediction and sampling design for landscape genetic data. We are using a multinomial data model for categorical microsatellite allele data and introduced a latent spatial random effect to allow for spatial correlation between genetic observations. We illustrate how modern dimension reduction approaches to spatial statistics can allow for efficient computation in landscape genetic statistical models covering large spatial domains. We apply our approach to propose a retrospective spatial sampling design for Greater Sage-grouse. This research is in collaboration with Pennsylvania State University, USGS, Colorado State University, USFS, and the University of Montana.

Developing Best Practices for Linear Mixed Modelling in Landscape Genetics Through Landscape-directed Dispersal Simulations

Code: 
RB00CNJ.21
Flying Sage-grouse in Wyoming. USGS photo.
Flying Sage-grouse in Wyoming. USGS photo.
Abstract: 

Mixed models that account for the error structure of pairwise datasets are being utilized to compare models relating genetic differentiation with pairwise measures of landscape resistance.  A model selection framework based on information criteria metrics or explained variance may help disentangle the ecological and landscape factors influencing spatial genetic structure, yet there are currently no tests of the error rates of this approach, or a consensus for the best protocols for minimizing them. The goal of this project is to develop and test a landscape-directed dispersal model to simulate a series of replicates that emulate independent empirical datasets of two species with vastly different life history and habitat use characteristics (Greater Sage-grouse and eastern fox snakes). This study develops best practices for using linear mixed models to identify the features underlying patterns of dispersal across a variety of landscapes. This research is in collaboration with University of Waterloo and is supported by Wyoming Game and Fish Department and BLM.

Contrasting Evolutionary Histories of MHC Class I and Class II Loci in Grouse - Effects of Selection and Gene Conversion

Code: 
RB00CNJ.22.1
A sage-grouse chick wearing a GPS locator "backpack." USGS photo.
A sage-grouse chick wearing a GPS locator "backpack." USGS photo.
Abstract: 

This project examines the evolutionary history of two different classes of MHC genes in five closely related species of grouse.  We are investigating the roles of selection and gene conversion on class I and class II MHC genes and are comparing diversity among the five different prairie grouse. We are finding differences in the strength of balancing selection acting on MHC class I and class II genes. We are also identifying much stronger gene conversion shaping the evolution of MHC class II genes than class I genes. Overall, the combination of strong positive (balancing) selection and frequent gene conversion may be maintaining higher diversity of MHC class II than class I in prairie grouse. This research is in collaboration with University of Łódź, University of Wisconsin-Milwaukee, University of North Texas.

Assembling a High Quality Reference Genome for Sage-grouse to Serve as a Resource for Future Studies

Code: 
RB00CNJ.27.1
A male Gunnison Sage-grouse. Photo by Doug Ouren, USGS.
A male Gunnison Sage-grouse. Photo by Doug Ouren, USGS.
Abstract: 

Conservation genomics is a new field of science that applies novel whole-genome sequencing technology to problems in conservation biology. Rapidly advancing molecular technologies are revolutionizing wildlife ecology, greatly expanding our understanding of wildlife and their interactions with the environment. In the same way that molecular tools such as microsatellites revolutionized wildlife management in the past, evolving genomic-level data collection techniques are beginning to offer powerful ways to assess biodiversity, taxonomy, hybridization, diets, demography, disease resistance and outbreaks, and even local adaptation. 

This goal of this project is to sequence and assemble a high-quality reference genome for Gunnison Sage-grouse. Assembling such a reference genome can benefit several types of analyses common to conservation genetics. As Gunnison and Greater Sage-grouse are closely related, this reference genome will serve as a resource for future studies in both species, and will inform management and conservation decisions.

Genetic Adaptations to Local Sagebrush Diets in Sage-grouse

Code: 
RB00CNJ.27.4
Young mountain big sagebrush shown in the foreground. Photo by Dave Pyke, USGS photo gallery.
Young mountain big sagebrush shown in the foreground. Photo by Dave Pyke, USGS photo gallery.
Abstract: 

In this project we are evaluating the degree to which different Sage-grouse populations might be uniquely adapted to the local sagebrush plants, which make up the bulk of Sage-grouse diets during the fall and winter. Using target resequencing of several candidate genes, we are examining the evidence for functional genetic variation in genes that might allow Sage-grouse to specialize on locally available sagebrush varieties. This research is in collaboration with Boise State University.

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