A targeted annual warning system (TAWS) for identifying aberrant declines in greater sage-grouse populations
Land and wildlife managers require accurate estimates of sensitive species’ trends to help guide conservation decisions that maintain biodiversity and promote healthy ecosystems. Researchers within the U.S. Geological Survey (USGS) and Colorado State University (CSU) worked with the Bureau of Land Management (BLM) and State Wildlife Agencies to develop a hierarchical population monitoring framework for managing greater sage-grouse (Centrocercus urophasianus; sage-grouse) populations and the sagebrush ecosystems that they depend upon for survival and reproduction. Part of the hierarchical population monitoring strategy is a targeted annual warning system (TAWS) that identifies where and when sage-grouse populations may benefit from management intervention.
Background
Resource managers and conservation practitioners have limited time and resources to put towards monitoring and managing sage-grouse populations. Given the widespread declines in sage-grouse populations, managers need tools that can aid them in identifying populations that are likely to respond to management intervention.
Research Objective
We aimed to develop a method of monitoring sage-grouse populations across their range within the United States that would specifically help managers identify when and where populations were declining in response to local disturbances (Figure 1). By accounting for broad-scale factors responsible for changes in population size, the framework could effectively focus on localized threats that fall within the purview of land and wildlife management agencies. To do this, we designed the framework to monitor populations at multiple spatial scales, to capture disturbances ranging in size from point sources (for example, mines) to large wildfires. We evaluated populations within a 2–4-year moving window, a timeframe in which managers can reasonably respond to population declines while avoiding false positives. We identified thresholds for initiating management intervention based on a simulation analysis that accounted for variation in ecosystem responses to conservation actions and imperfect rates of management efficacy.
Methods
Scientists from the U.S. Geological Survey (USGS) and Colorado State University (CSU) worked closely with state and federal agencies to develop a unified lek database, define hierarchically nested population clusters, and model population trends at three key spatial scales: (1) leks, (2) ‘neighborhoods’ of leks clustered together, and (3) clusters of neighborhoods, termed ‘climate’ clusters. The TAWS utilizes the collective output from these products to evaluate changes in population size and identify which populations could benefit most from monitoring and management.
A key feature of the framework is its ability to differentiate population changes, particularly declines, according to mechanisms that can or cannot be addressed by land and wildlife management agencies. With this goal in mind, we designed population clusters to capture a unique suite of factors at each spatial scale:
- Population change at the climate cluster scale was driven by abiotic factors that often exhibit cyclic patterns.
- Population change at the neighborhood and lek scales was driven by abiotic factors, as well as local-level factors such as migration, predator composition, land management practices, and disease.
From these clusters, we compared annual estimates of population change between management (that is, neighborhood or lek) and climate scales to determine if population declines are the result of local or broader factors. We then defined signals for when populations are declining in a way that warrants additional monitoring (“watch”) or management intervention (“warning”). Watches and warnings serve as the foundation of the TAWS framework and are intended to help guide management actions in a more targeted and localized manner.
Results and Implications
We applied the TAWS framework to over 4,400 leks distributed across the western United States, with estimates of population change spanning more than 30 years (1990–Present; Figure 3). Results revealed 58-68% population declines immediately preceding watches or warnings (2–4-year period). Population trends unassociated with signals showed little-to-no sign of decline. Furthermore, we found an average annual rate of 1.7% of leks or 1.3% of neighborhood clusters (lek aggregations) would have required management intervention to reverse range-wide declines and stabilize the entire sage-grouse range.
Future Co-production
We continue working with all collaborators to improve sage-grouse management tools. Each year, a new standardized database is developed to include newly digitized historical data and improve data quality using critical quality control methods. These data are incorporated into the TAWS framework to produce results that are delivered in time for annual agency decision making.
Data Restrictions
State wildlife agencies collect and manage lek databases. Because sage-grouse are a species of conservation concern and sensitive to activities during breeding, these data are available only after acquiring data-sharing agreements with individual states.
Funders
U.S. Geological Survey (Ecosystem Mission Area, Land Management Research Program and Species Management Research Program; Wyoming Landscape Conservation Initiative) and Bureau of Land Management.
Partners
State Wildlife Agencies (California Department of Fish and Wildlife; Colorado Parks and Wildlife; Idaho Department of Fish and Game; Montana Fish, Wildlife & Parks; Nevada Department of Wildlife; North Dakota Game and Fish Department; Oregon Department of Fish and Wildlife; South Dakota Department of Game, Fish and Parks; Utah Division of Wildlife Resources; Wyoming Game and Fish Department; Washington Department of Fish and Wildlife), Colorado State University, BLM, US Fish and Wildlife Service, US Forest Service, researchers who provided field data to evaluate results.
A user-friendly decision support tool for monitoring and managing greater sage-grouse populations
Hierarchical Population Monitoring Framework for Greater Sage-Grouse
Estimating trends for greater sage-grouse populations within highly stochastic environments
Data Harmonization for Greater Sage-Grouse Populations
Hierarchical Units of Greater Sage-Grouse Populations Informing Wildlife Management
Land and wildlife managers require accurate estimates of sensitive species’ trends to help guide conservation decisions that maintain biodiversity and promote healthy ecosystems. Researchers within the U.S. Geological Survey (USGS) and Colorado State University (CSU) worked with the Bureau of Land Management (BLM) and State Wildlife Agencies to develop a hierarchical population monitoring framework for managing greater sage-grouse (Centrocercus urophasianus; sage-grouse) populations and the sagebrush ecosystems that they depend upon for survival and reproduction. Part of the hierarchical population monitoring strategy is a targeted annual warning system (TAWS) that identifies where and when sage-grouse populations may benefit from management intervention.
Background
Resource managers and conservation practitioners have limited time and resources to put towards monitoring and managing sage-grouse populations. Given the widespread declines in sage-grouse populations, managers need tools that can aid them in identifying populations that are likely to respond to management intervention.
Research Objective
We aimed to develop a method of monitoring sage-grouse populations across their range within the United States that would specifically help managers identify when and where populations were declining in response to local disturbances (Figure 1). By accounting for broad-scale factors responsible for changes in population size, the framework could effectively focus on localized threats that fall within the purview of land and wildlife management agencies. To do this, we designed the framework to monitor populations at multiple spatial scales, to capture disturbances ranging in size from point sources (for example, mines) to large wildfires. We evaluated populations within a 2–4-year moving window, a timeframe in which managers can reasonably respond to population declines while avoiding false positives. We identified thresholds for initiating management intervention based on a simulation analysis that accounted for variation in ecosystem responses to conservation actions and imperfect rates of management efficacy.
Methods
Scientists from the U.S. Geological Survey (USGS) and Colorado State University (CSU) worked closely with state and federal agencies to develop a unified lek database, define hierarchically nested population clusters, and model population trends at three key spatial scales: (1) leks, (2) ‘neighborhoods’ of leks clustered together, and (3) clusters of neighborhoods, termed ‘climate’ clusters. The TAWS utilizes the collective output from these products to evaluate changes in population size and identify which populations could benefit most from monitoring and management.
A key feature of the framework is its ability to differentiate population changes, particularly declines, according to mechanisms that can or cannot be addressed by land and wildlife management agencies. With this goal in mind, we designed population clusters to capture a unique suite of factors at each spatial scale:
- Population change at the climate cluster scale was driven by abiotic factors that often exhibit cyclic patterns.
- Population change at the neighborhood and lek scales was driven by abiotic factors, as well as local-level factors such as migration, predator composition, land management practices, and disease.
From these clusters, we compared annual estimates of population change between management (that is, neighborhood or lek) and climate scales to determine if population declines are the result of local or broader factors. We then defined signals for when populations are declining in a way that warrants additional monitoring (“watch”) or management intervention (“warning”). Watches and warnings serve as the foundation of the TAWS framework and are intended to help guide management actions in a more targeted and localized manner.
Results and Implications
We applied the TAWS framework to over 4,400 leks distributed across the western United States, with estimates of population change spanning more than 30 years (1990–Present; Figure 3). Results revealed 58-68% population declines immediately preceding watches or warnings (2–4-year period). Population trends unassociated with signals showed little-to-no sign of decline. Furthermore, we found an average annual rate of 1.7% of leks or 1.3% of neighborhood clusters (lek aggregations) would have required management intervention to reverse range-wide declines and stabilize the entire sage-grouse range.
Future Co-production
We continue working with all collaborators to improve sage-grouse management tools. Each year, a new standardized database is developed to include newly digitized historical data and improve data quality using critical quality control methods. These data are incorporated into the TAWS framework to produce results that are delivered in time for annual agency decision making.
Data Restrictions
State wildlife agencies collect and manage lek databases. Because sage-grouse are a species of conservation concern and sensitive to activities during breeding, these data are available only after acquiring data-sharing agreements with individual states.
Funders
U.S. Geological Survey (Ecosystem Mission Area, Land Management Research Program and Species Management Research Program; Wyoming Landscape Conservation Initiative) and Bureau of Land Management.
Partners
State Wildlife Agencies (California Department of Fish and Wildlife; Colorado Parks and Wildlife; Idaho Department of Fish and Game; Montana Fish, Wildlife & Parks; Nevada Department of Wildlife; North Dakota Game and Fish Department; Oregon Department of Fish and Wildlife; South Dakota Department of Game, Fish and Parks; Utah Division of Wildlife Resources; Wyoming Game and Fish Department; Washington Department of Fish and Wildlife), Colorado State University, BLM, US Fish and Wildlife Service, US Forest Service, researchers who provided field data to evaluate results.