Greater sage-grouse genetic warning system, western United States (ver 1.1, January 2023)
Dates
Publication Date
2022-12-12
Start Date
1991
End Date
2019
Revision
2023-01-11
Citation
Zimmerman, S.J., O'Donnell, M.S., Aldridge, C.L., Edmunds, D.R., Coates, P.S., Prochazka, B.G., Fike, J.A., Cross, T.B., Fedy, B.C., and Oyler-McCance, S.J., 2022, Greater sage-grouse genetic warning system, western United States (ver 1.1, January 2023): U.S. Geological Survey data release, https://doi.org/10.5066/P9FATNI9.
Summary
Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species’ conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse (Centrocercus urophasianus) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., fine-scale) with low genetic diversity relative to regional units [...]
Summary
Genetic variation is a well-known indicator of population fitness yet is not typically included in monitoring programs for sensitive species. Additionally, most programs monitor populations at one scale, which can lead to potential mismatches with ecological processes critical to species’ conservation. Recently developed methods generating hierarchically nested population units (i.e., clusters of varying scales) for greater sage-grouse (Centrocercus urophasianus) have identified population trend declines across spatiotemporal scales to help managers target areas for conservation. The same clusters used as a proxy for spatial scale can alert managers to local units (i.e., fine-scale) with low genetic diversity relative to regional units (i.e., coarse-scale), further facilitating identification of management targets. We developed a genetic warning system utilizing previously developed hierarchical population units to identify management-relevant areas with low genetic diversity within the greater sage-grouse range. Within this warning system we characterized conservation concern thresholds based on values of genetic diversity for hierarchically nested populations. We developed a spatial data set to display genetic diversity values and conservation concern information from a Genetic Warning System (GWS) for population monitoring of greater sage-grouse, as described in Zimmerman et al. (2022). Here we added the genetic diversity estimates (allelic richness and expected heterozygosity) and GWS information as attributes to the relevant fine-scale (level 2) and coarse-scale (level 13) previously developed hierarchically nested population clusters (O’Donnell et al. 2019, O’Donnell et al. 2022). The GWS incorporates population trend decline watches and warnings from the Targeted Annual Warning System (TAWS) for greater sage-grouse as reported in Coates et al. (2021) to further refine degree of conservation concern.
When considering range-wide declines in sage-grouse populations, genetic variation is an essential consideration in addition to population sizes, temporal, and spatial scale. Further, targeted management actions are needed at spatial scales that align with factors causing population change. There is a need to understand mechanisms driving population changes, allowing targeted management actions to conserve populations. Incorporation of genetic information into a multi-scaled and biologically-informed population monitoring system for greater sage-grouse has yet to be accomplished. The combination of population trend data and genetic diversity, evaluated within this hierarchical monitoring framework can be used 1) as a long-term population monitoring framework for greater sage-grouse, 2) to track the outcomes of local and regional populations by comparing population changes across scales (hierarchical levels), and 3) to inform where to best spatially target studies that identify the processes and mechanisms causing population trends to change among spatial and temporal scales. These data are for query of the Genetic Warning System (GWS) information.
