Natural selection may result in local adaptation to different environmental conditions across the range of a species. Understanding local adaptation, in turn, informs management decisions such as translocation to restore locally-extinct populations. We used a landscape genomics approach to detect genetic signatures of selection related to climatic variation among desert bighorn sheep populations across their indigenous range in the western United States. This approach allowed us to investigate broad patterns of both neutral and adaptive genetic variation across very different environments. Analyses suggested that ancestry and isolation by distance were the most significant forces driving genetic variation in desert bighorn sheep, but that climate was associated with at least 1 locus (i.e., location on the genome) under directional selection. The alternate allele (i.e., variant) at this locus was associated with biologically significant increases in elevation and precipitation, decreases in temperature, and was nearly private to herds occupying the Great Basin ecosystem. Our results suggest climate conditions at higher latitudes may have resulted in a distinct ecotype of desert bighorn sheep whose adaptations are still apparent among the few remaining indigenous populations in the Great Basin. We also found 2 highly supported candidate genes in the genomic region linked to this outlier. How the molecular function of these candidate genes may affect physiological response of desert bighorn sheep to climate is unclear, although their identification provides new insight into the genetic mechanisms potentially underlying environmental adaptation. We identified several other loci under strong directional selection not related to climate and described a previously unknown pattern of strong genetic divergence of bighorn sheep within the White Mountains compared to other populations. Overall, these findings suggest selection from environmental factors may influence genomic variation at the ecosystem-scale in desert bighorn sheep and these results extend our understanding of how this subspecies may respond to different environmental conditions.

Natural selection may result in local adaptation to different environmental conditions across the range of a species. Understanding local adaptation, in turn, informs management decisions such as translocation to restore locally-extinct populations. We used a landscape genomics approach to detect genetic signatures of selection related to climatic variation among desert bighorn sheep populations across their indigenous range in the western United States. This approach allowed us to investigate broad patterns of both neutral and adaptive genetic variation across very different environments. Analyses suggested that ancestry and isolation by distance were the most significant forces driving genetic variation in desert bighorn sheep, but that climate was associated with at least 1 locus (i.e., location on the genome) under directional selection. The alternate allele (i.e., variant) at this locus was associated with biologically significant increases in elevation and precipitation, decreases in temperature, and was nearly private to herds occupying the Great Basin ecosystem. Our results suggest climate conditions at higher latitudes may have resulted in a distinct ecotype of desert bighorn sheep whose adaptations are still apparent among the few remaining indigenous populations in the Great Basin. We also found 2 highly supported candidate genes in the genomic region linked to this outlier. How the molecular function of these candidate genes may affect physiological response of desert bighorn sheep to climate is unclear, although their identification provides new insight into the genetic mechanisms potentially underlying environmental adaptation. We identified several other loci under strong directional selection not related to climate and described a previously unknown pattern of strong genetic divergence of bighorn sheep within the White Mountains compared to other populations. Overall, these findings suggest selection from environmental factors may influence genomic variation at the ecosystem-scale in desert bighorn sheep and these results extend our understanding of how this subspecies may respond to different environmental conditions.

Natural selection may result in local adaptation to different environmental conditions across the range of a species. Understanding local adaptation, in turn, informs management decisions such as translocation to restore locally-extinct populations. We used a landscape genomics approach to detect genetic signatures of selection related to climatic variation among desert bighorn sheep populations across their indigenous range in the western United States. This approach allowed us to investigate broad patterns of both neutral and adaptive genetic variation across very different environments. Analyses suggested that ancestry and isolation by distance were the most significant forces driving genetic variation in desert bighorn sheep, but that climate was associated with at least 1 locus (i.e., location on the genome) under directional selection. The alternate allele (i.e., variant) at this locus was associated with biologically significant increases in elevation and precipitation, decreases in temperature, and was nearly private to herds occupying the Great Basin ecosystem. Our results suggest climate conditions at higher latitudes may have resulted in a distinct ecotype of desert bighorn sheep whose adaptations are still apparent among the few remaining indigenous populations in the Great Basin. We also found 2 highly supported candidate genes in the genomic region linked to this outlier. How the molecular function of these candidate genes may affect physiological response of desert bighorn sheep to climate is unclear, although their identification provides new insight into the genetic mechanisms potentially underlying environmental adaptation. We identified several other loci under strong directional selection not related to climate and described a previously unknown pattern of strong genetic divergence of bighorn sheep within the White Mountains compared to other populations. Overall, these findings suggest selection from environmental factors may influence genomic variation at the ecosystem-scale in desert bighorn sheep and these results extend our understanding of how this subspecies may respond to different environmental conditions.

Establishing connections among natural landscapes is the most frequently recommended strategy for adapting management of natural resources in response to climate change. The U.S. Northern Rockies still support a full suite of native wildlife, and survival of these populations depends on connected landscapes. Connected landscapes support current migration and dispersal as well as future shifts in species ranges that will be necessary for species to adapt to our changing climate. Working in partnership with state and federal resource managers and private land trusts, we sought to: 1) understand how future climate change may alter habitat composition of landscapes expected to serve as important connections for wildlife, 2) estimate how wildlife species of concern are expected to respond to these changes, 3) develop climate-smart strategies to help stakeholders manage public and private lands in ways that allow wildlife to continue to move in response to changing conditions, and 4) explore how well existing management plans and conservation efforts are expected to support crucial connections for wildlife under climate change. We assessed vulnerability of eight wildlife species and four biomes to climate change, with a focus on potential impacts to connectivity. Our assessment provides some insights about where these species and biomes may be most vulnerable or most resilient to loss of connectivity and how this information could support climate-smart management action. We also encountered high levels of uncertainty in how climate change is expected to alter vegetation and how wildlife are expected to respond to these changes. This uncertainty limits the value of our assessment for informing proactive management of climate change impacts on both species-specific and biome-level connectivity (although biome-level assessments were subject to fewer sources of uncertainty). We offer suggestions for improving the management relevance of future studies based on our own insights and those of managers and biologists who participated in this assessment and provided critical review of this report.

Establishing connections among natural landscapes is the most frequently recommended strategy for adapting management of natural resources in response to climate change. The U.S. Northern Rockies still support a full suite of native wildlife, and survival of these populations depends on connected landscapes. Connected landscapes support current migration and dispersal as well as future shifts in species ranges that will be necessary for species to adapt to our changing climate. Working in partnership with state and federal resource managers and private land trusts, we sought to: 1) understand how future climate change may alter habitat composition of landscapes expected to serve as important connections for wildlife, 2) estimate how wildlife species of concern are expected to respond to these changes, 3) develop climate-smart strategies to help stakeholders manage public and private lands in ways that allow wildlife to continue to move in response to changing conditions, and 4) explore how well existing management plans and conservation efforts are expected to support crucial connections for wildlife under climate change. We assessed vulnerability of eight wildlife species and four biomes to climate change, with a focus on potential impacts to connectivity. Our assessment provides some insights about where these species and biomes may be most vulnerable or most resilient to loss of connectivity and how this information could support climate-smart management action. We also encountered high levels of uncertainty in how climate change is expected to alter vegetation and how wildlife are expected to respond to these changes. This uncertainty limits the value of our assessment for informing proactive management of climate change impacts on both species-specific and biome-level connectivity (although biome-level assessments were subject to fewer sources of uncertainty). We offer suggestions for improving the management relevance of future studies based on our own insights and those of managers and biologists who participated in this assessment and provided critical review of this report.

Establishing connections among natural landscapes is the most frequently recommended strategy for adapting management of natural resources in response to climate change. The U.S. Northern Rockies still support a full suite of native wildlife, and survival of these populations depends on connected landscapes. Connected landscapes support current migration and dispersal as well as future shifts in species ranges that will be necessary for species to adapt to our changing climate. Working in partnership with state and federal resource managers and private land trusts, we sought to: 1) understand how future climate change may alter habitat composition of landscapes expected to serve as important connections for wildlife, 2) estimate how wildlife species of concern are expected to respond to these changes, 3) develop climate-smart strategies to help stakeholders manage public and private lands in ways that allow wildlife to continue to move in response to changing conditions, and 4) explore how well existing management plans and conservation efforts are expected to support crucial connections for wildlife under climate change. We assessed vulnerability of eight wildlife species and four biomes to climate change, with a focus on potential impacts to connectivity. Our assessment provides some insights about where these species and biomes may be most vulnerable or most resilient to loss of connectivity and how this information could support climate-smart management action. We also encountered high levels of uncertainty in how climate change is expected to alter vegetation and how wildlife are expected to respond to these changes. This uncertainty limits the value of our assessment for informing proactive management of climate change impacts on both species-specific and biome-level connectivity (although biome-level assessments were subject to fewer sources of uncertainty). We offer suggestions for improving the management relevance of future studies based on our own insights and those of managers and biologists who participated in this assessment and provided critical review of this report.

Areas of desert bighorn sheep home ranges from southern Nevada. Home ranges are attributed with average slope, average vector ruggedness measure (VRM), median distance to water, average NDVI, NDVI coefficient of variation, and Palmer's drought severity index (PDSI).

Areas of desert bighorn sheep home ranges from southern Nevada. Home ranges are attributed with average slope, average vector ruggedness measure (VRM), median distance to water, average NDVI, NDVI coefficient of variation, and Palmer's drought severity index (PDSI).

Tabular and raster data containing spatial capture recapture records for male and female bighorn sheep (Ovis canadensis nelsoni) in Grand Canyon National Park and surrounding landscape collected from 2010 to 2018 and associated tabular data files required for analysis of data with spatial capture connectivity models and raster data describing the ouput from SCR models. Associated tables and rasters include details for traps and genetic captures, and the state space for required modeling and associated spatial covariates in models, as well as rasters describing population density and habitat use.

Tabular and raster data containing spatial capture recapture records for male and female bighorn sheep (Ovis canadensis nelsoni) in Grand Canyon National Park and surrounding landscape collected from 2010 to 2018 and associated tabular data files required for analysis of data with spatial capture connectivity models and raster data describing the ouput from SCR models. Associated tables and rasters include details for traps and genetic captures, and the state space for required modeling and associated spatial covariates in models, as well as rasters describing population density and habitat use.