Characterizing the environmental drivers of range-wide gene flow for greater sage-grouse
Widespread anthropogenic development in the sagebrush steppe and shifting climatic patterns have contributed to the observed dramatic declines of the greater sage-grouse since the 1960s. Alteration of the sagebrush habitat can affect many aspects of the species life history, including survival and local resource use. Over many years, the combined effects of landscape composition on these traits can lead to shifts or limitations to the flow of genetic variation between populations (“gene flow”) that may lead to reduced fitness and evolutionary capacity for the species in the long-term. In this project, we will use range-wide genetic data to understand the relationship between landscape composition and gene flow for greater sage-grouse with a focus on how gene flow patterns can inform conservation and management actions.
Background
The greater sage-grouse is a species threatened by climate and land use associated environmental change. Understanding the relationship between species and their environment is crucial to effective management, particularly as alteration of the environment is expected to continue. Much of this understanding is currently based on the relationship between directly observable traits (such as, survival, use, occupancy, for example) and the landscape, but the relationship between landscape composition and gene flow is not frequently studied at large scales. Gene flow is a distinct biological process that is the total result of multigenerational changes to those observable traits with direct links to population fitness and evolutionary capacity, where more gene flow corresponds to higher evolutionary capacity and fitness (that is, less inbreeding). As large-scale genetic datasets, new statistical modeling approaches, and access to high-throughput computing resources has become more accessible, our ability to understand these relationships through landscape genetic connectivity modeling has also improved.
Research Objectives
We aim to use existing range-wide genetic and environmental data and recently developed statistical tools to better understand the relationship between landscape composition and gene flow for the greater sage-grouse. We will create a range-wide predicted gene flow surface describing areas likely to have relatively high or low gene flow and thus areas that might be targeted for different conservation and management strategies.
Management Implications
Our analyses will provide managers with an understanding of the main drivers of gene flow and a spatial data set that can be used to prioritize conservation and management actions. More specifically, areas of high gene flow may be good targets for protection, while areas of low gene flow may be good for management actions. These data could be used to support multiple sage-grouse conservation strategies and frameworks. For example, these data could inform where management actions to ‘Defend and Grow the Core’ within the Sagebrush Conservation Design could also provide benefits for gene flow (Doherty and others 2022) or incorporated into the Genetic Warning System (Zimmerman and others 2023), potentially providing mechanistic explanations for genetic watches and warnings. The predicted gene flow surface also lends itself to simulating the predicted effect of landscape alterations mimicking management actions (refer to Zimmerman and others 2022). If conifer removal or sagebrush restoration are proposed actions, spatial variables can be altered to reflect suggested changes and incorporated into the modeled gene flow surface and subsequently used to predict the resulting change in gene flow.
Widespread anthropogenic development in the sagebrush steppe and shifting climatic patterns have contributed to the observed dramatic declines of the greater sage-grouse since the 1960s. Alteration of the sagebrush habitat can affect many aspects of the species life history, including survival and local resource use. Over many years, the combined effects of landscape composition on these traits can lead to shifts or limitations to the flow of genetic variation between populations (“gene flow”) that may lead to reduced fitness and evolutionary capacity for the species in the long-term. In this project, we will use range-wide genetic data to understand the relationship between landscape composition and gene flow for greater sage-grouse with a focus on how gene flow patterns can inform conservation and management actions.
Background
The greater sage-grouse is a species threatened by climate and land use associated environmental change. Understanding the relationship between species and their environment is crucial to effective management, particularly as alteration of the environment is expected to continue. Much of this understanding is currently based on the relationship between directly observable traits (such as, survival, use, occupancy, for example) and the landscape, but the relationship between landscape composition and gene flow is not frequently studied at large scales. Gene flow is a distinct biological process that is the total result of multigenerational changes to those observable traits with direct links to population fitness and evolutionary capacity, where more gene flow corresponds to higher evolutionary capacity and fitness (that is, less inbreeding). As large-scale genetic datasets, new statistical modeling approaches, and access to high-throughput computing resources has become more accessible, our ability to understand these relationships through landscape genetic connectivity modeling has also improved.
Research Objectives
We aim to use existing range-wide genetic and environmental data and recently developed statistical tools to better understand the relationship between landscape composition and gene flow for the greater sage-grouse. We will create a range-wide predicted gene flow surface describing areas likely to have relatively high or low gene flow and thus areas that might be targeted for different conservation and management strategies.
Management Implications
Our analyses will provide managers with an understanding of the main drivers of gene flow and a spatial data set that can be used to prioritize conservation and management actions. More specifically, areas of high gene flow may be good targets for protection, while areas of low gene flow may be good for management actions. These data could be used to support multiple sage-grouse conservation strategies and frameworks. For example, these data could inform where management actions to ‘Defend and Grow the Core’ within the Sagebrush Conservation Design could also provide benefits for gene flow (Doherty and others 2022) or incorporated into the Genetic Warning System (Zimmerman and others 2023), potentially providing mechanistic explanations for genetic watches and warnings. The predicted gene flow surface also lends itself to simulating the predicted effect of landscape alterations mimicking management actions (refer to Zimmerman and others 2022). If conifer removal or sagebrush restoration are proposed actions, spatial variables can be altered to reflect suggested changes and incorporated into the modeled gene flow surface and subsequently used to predict the resulting change in gene flow.