New strategies for characterizing genetic structure in wide-ranging, continuously distributed species: A Greater Sage-grouse case study

Abstract

Characterizing genetic structure across a species’ range is relevant for management and conservation as it can be used to define population boundaries and quantify connectivity. Wide-ranging species residing in continuously distributed habitat pose substantial challenges for the characterization of genetic structure as many analytical methods used are less effective when isolation by distance is an underlying biological pattern. Here, we illustrate strategies for overcoming these challenges using a species of significant conservation concern, the Greater Sage-grouse (Centrocercus urophasianus), providing a new method to identify centers of genetic differentiation and combining multiple methods to help inform management and conservation strategies for this and other such species. Our objectives were to (1) describe large-scale patterns of population genetic structure and gene flow and (2) to characterize genetic subpopulation centers across the range of Greater Sage-grouse. Samples from 2,134 individuals were genotyped at 15 microsatellite loci. Using standard STRUCTURE and spatial principal components analyses, we found evidence for four or six areas of large-scale genetic differentiation and, following our novel method, 12 subpopulation centers of differentiation. Gene flow was greater, and differentiation reduced in areas of contiguous habitat (eastern Montana, most of Wyoming, much of Oregon, Nevada, and parts of Idaho). As expected, areas of fragmented habitat such as in Utah (with 6 subpopulation centers) exhibited the greatest genetic differentiation and lowest effective migration. The subpopulation centers defined here could be monitored to maintain genetic diversity and connectivity with other subpopulation centers. Many areas outside subpopulation centers are contact zones where different genetic groups converge and could be priorities for maintaining overall connectivity. Our novel method and process of leveraging multiple different analyses to find common genetic patterns provides a path forward to characterizing genetic structure in wide-ranging, continuously distributed species.

A genetic warning system for a hierarchically structured wildlife monitoring framework

“…This is consistent with previous genetic analyses for all three regions. The Bi‐State is a distinct though regionally relatively diverse population (Oh et al, 2019; Oyler‐McCance, Taylor, & Quinn, 2005; Oyler‐McCance et al, 2015) while Utah (Oyler‐McCance, Taylor, & Quinn, 2005; Oyler‐McCance et al, 2022) and Jackson (Oyler‐McCance et al, 2022; Schulwitz et al, 2014) have some evidence of being locally distinct and having relatively low genetic diversity. These findings are also consistent with previous reports of extensive habitat fragmentation (Schroeder et al, 2004; Schulwitz et al, 2014), and limited movement (Dahlgren et al, 2016) in all three regions when compared to the rest of the range.…”

Corridor‐based approach with spatial cross‐validation reveals scale‐dependent effects of geographic distance, human footprint and canopy cover on grizzly bear genetic connectivity

“…Isolation by distance occurs within a continuously distributed population when movement of genes is spatially restricted (Hardy & Vekemans, 1999) and is an underlying pattern that likely challenged our ability to detect strong relationships between landscape variables and genetic differentiation (Oyler‐McCance et al, 2022). Our results were consistent with other landscape genetics studies that showed only incremental improvement in the amount of variation explained by final models when compared to a null expectation of isolation by distance (e.g.…”

“…Resistant kernels from models with paved roads as the only retained landscape variable (40,80,120,200 Isolation by distance occurs within a continuously distributed population when movement of genes is spatially restricted (Hardy & Vekemans, 1999) and is an underlying pattern that likely challenged our ability to detect strong relationships between landscape variables and genetic differentiation (Oyler-McCance et al, 2022).…”

The ties that bind the sagebrush biome: integrating genetic connectivity into range-wide conservation of greater sage-grouse

“…The greater sage-grouse (Centrocercus urophasianus; hereafter, sage-grouse) is a species of conservation concern ranging across eleven western US states and two Canadian provinces. Sage-grouse populations are poised to benefit from the collection of greater than 16 000 genetic samples across their range [8,[10][11][12]. Sage-grouse populations vary substantially in population density and dispersal [13]; these two parameters are fundamentally influenced by connectivity, and both influence the genetic diversity of populations.…”

“…Data products and metadata are publicly available as follows. (i) FCM microsatellite and spatial data: https://doi.org/10.5066/F7RB73V0 [74]. (ii) NCM microsatellite, spatial and network attribute data: https://doi.org/ 10.5066/F73N22PN [75].…”