Greater Sage-Grouse Population Monitoring Framework
Greater sage-grouse (Centrocercus urophasianus) are at the center of state and national land use policies largely because of their unique life-history traits as an ecological indicator for health of sagebrush 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 to support decision-making processes by state wildlife agencies, U.S. Department of Interior (BLM, U.S. Fish and Wildlife Service) and U.S. Department of Agriculture resource agencies (U.S. Forest Service and Natural Resources Conservation Service) for managing sage-grouse populations and the sagebrush ecosystems that they depend upon for survival and reproduction.
Associated Information Sheets
Using the app? The following pages can help you learn the framework terminology and interpret your results.
Background
Greater sage-grouse are a sagebrush obligate bird that currently occupy most sagebrush ecosystems across 11 states in the U.S. and 2 Canadian Provinces in western North America. At the turn of the twenty-first century, sage-grouse occupied roughly half of their former historical range and over the past three to five decades have demonstrated apparent population declines in many parts of their current range.
Sage-grouse are considered an indicator of the integrity of sagebrush ecosystems, as well as an umbrella species for the protection of other sagebrush-obligate or semi-obligate species given their near complete dependence on sagebrush ecosystems throughout their life. Importantly, several federal resource management plan amendments accompanying the ‘not warranted’ 2015 ESA listing determination called for greater integration of adaptive management into land-use planning, and specifically, identifying how to implement adaptive management. Several different methods are currently being used to monitor sage-grouse populations, making it difficult to manage the species across time and administrative boundaries. The hierarchical population monitoring framework for sage-grouse provides a standardized and accurate way to track sage-grouse populations across the entire sagebrush biome.
Research Objective
The primary goal of the hierarchical population monitoring framework is to help managers identify changing sage-grouse population trends and assess the influence of landscape characteristics on those trends across multiple spatial and temporal scales. The framework serves a dual purpose: 1) it allows managers to readily and accurately calculate sage-grouse population trends at multiple spatial scales to meet best available science needs for state and federal resource agencies, and 2) it provides a method for detecting population declines at different spatial scales that may warrant management action. We developed the framework in close collaboration with several state and federal agency partners and designed it to provide annually updated results for timely management decisions and policy. It is comprised of five components, each with its own research objective and science product.
1. Lek Database
State wildlife agencies identified the need for a single comprehensive database of lek (sage-grouse breeding area) count data and locations. The first component of the framework developed automated, repeatable methods for joining disparate lek count data into a standardized database. The resulting software allows for the addition of new data to the database in a consistent manner, building the historic record of lek data and supporting timely analysis using the most up-to-date inputs. For more information on this data harmonization project, see this page.
2. Spatial Clusters
While understanding population trends within geographical boundaries such as states or management districts is necessary for practitioners, populations are responding to environmental factors that are broader than these extents, and wildlife move across jurisdictional boundaries. To address this issue, the second piece of the framework was developed with thirteen biologically relevant and hierarchically nested units of analysis that capture the drivers of population changes at different spatial scales (Figure 1). The framework analyzes population trends within three of these units: the climate cluster (regional), the neighborhood cluster (population), and the lek cluster (local). For more information on the development of the clusters, see this page.
3. Greater Sage-grouse Trends
Sage-grouse populations naturally vary both within years and in approximately 10-year oscillations. This can make estimations of sage-grouse trends across time difficult. The framework used state-of-the-art models to identify six different low points in rangewide sage-grouse abundance from 1953 – 2023. Comparing population abundance among low points provides accurate estimation of trends through time. For more information on sage-grouse trends, see this page.
4. Targeted Annual Warning System (TAWS)
Understanding when and where populations are declining and identifying if declines are due to factors that can be managed can help managers develop effective management strategies. The targeted annual warning system identifies when a population or lek is declining at a rate that differs from the larger regional trend. This “signal” allows managers to distinguish regional declines caused by unmanageable environmental factors (such as temperature and precipitation) from local declines caused by disturbances that may be improved with management intervention. The TAWS assigns a different severity (watch or warning) depending on the rate and duration of the decline. Watches may identify the need for intensive monitoring whereas warnings may identify the need for management intervention aimed at stabilizing populations. In addition, the TAWS informs managers when a population has signaled a watch or warning in the past. The TAWS’ use of population signals in this manner promotes adaptive management by identifying chronic effects on population declines and allows managers to assess the outcome of management actions. For more information on the TAWS, see this page.
5. Web Tool
The framework is operationalized through a web-based decision support tool that allows users to access trends and TAWS results for their area and period of interest. The application distills the results into relevant outputs such as maps, figures, and tables, that can be directly incorporated into management plans. The design of the framework promotes living products that are annually updated to facilitate timely management intervention and adaptive management. For more information on the web tool, see this page.
Future Co-production
We continue working with all collaborators to improve the science needed for sage-grouse management. Each year, a new standardized lek count database is developed to include newly digitized historical data and improve data quality using critical quality control methods. During this process, software is updated and released to the public. The trends and TAWS models are run with the most recent lek data provided by state partners. The results are released in a USGS Data Series report and included in the trends and TAWS decision support software. We continue to inform partners of updates and improvements to the model and facilitate the incorporation of new features and outputs within the application.
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 the 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.
Explore Components of the Hierarchical Population Monitoring Framework:
Data Harmonization
Hierarchical Units of Greater Sage-grouse Populations
Targeted Annual Warning System
Estimating Population Trends
Population Monitoring Web Tool
Greater Sage-Grouse Population Monitoring Framework: Cheat Sheet
Greater Sage-Grouse Population Monitoring Framework: Targeted Annual Warning System Information Sheet
Greater Sage-Grouse Population Monitoring Framework: Frequently Asked Questions
Greater Sage-Grouse Population Monitoring Framework: Glossary of Terms
Greater Sage-Grouse Population Monitoring Framework Data Inputs Information Sheet
Greater Sage-Grouse Population Monitoring Framework: Trends Analysis Information Sheet
Data Harmonization for Greater Sage-Grouse Populations
A user-friendly decision support tool for monitoring and managing greater sage-grouse populations
Estimating trends for greater sage-grouse populations within highly stochastic environments
A targeted annual warning system (TAWS) for identifying aberrant declines in greater sage-grouse populations
Hierarchical Units of Greater Sage-Grouse Populations Informing Wildlife Management
Greater sage-grouse (Centrocercus urophasianus) are at the center of state and national land use policies largely because of their unique life-history traits as an ecological indicator for health of sagebrush 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 to support decision-making processes by state wildlife agencies, U.S. Department of Interior (BLM, U.S. Fish and Wildlife Service) and U.S. Department of Agriculture resource agencies (U.S. Forest Service and Natural Resources Conservation Service) for managing sage-grouse populations and the sagebrush ecosystems that they depend upon for survival and reproduction.
Associated Information Sheets
Using the app? The following pages can help you learn the framework terminology and interpret your results.
Background
Greater sage-grouse are a sagebrush obligate bird that currently occupy most sagebrush ecosystems across 11 states in the U.S. and 2 Canadian Provinces in western North America. At the turn of the twenty-first century, sage-grouse occupied roughly half of their former historical range and over the past three to five decades have demonstrated apparent population declines in many parts of their current range.
Sage-grouse are considered an indicator of the integrity of sagebrush ecosystems, as well as an umbrella species for the protection of other sagebrush-obligate or semi-obligate species given their near complete dependence on sagebrush ecosystems throughout their life. Importantly, several federal resource management plan amendments accompanying the ‘not warranted’ 2015 ESA listing determination called for greater integration of adaptive management into land-use planning, and specifically, identifying how to implement adaptive management. Several different methods are currently being used to monitor sage-grouse populations, making it difficult to manage the species across time and administrative boundaries. The hierarchical population monitoring framework for sage-grouse provides a standardized and accurate way to track sage-grouse populations across the entire sagebrush biome.
Research Objective
The primary goal of the hierarchical population monitoring framework is to help managers identify changing sage-grouse population trends and assess the influence of landscape characteristics on those trends across multiple spatial and temporal scales. The framework serves a dual purpose: 1) it allows managers to readily and accurately calculate sage-grouse population trends at multiple spatial scales to meet best available science needs for state and federal resource agencies, and 2) it provides a method for detecting population declines at different spatial scales that may warrant management action. We developed the framework in close collaboration with several state and federal agency partners and designed it to provide annually updated results for timely management decisions and policy. It is comprised of five components, each with its own research objective and science product.
1. Lek Database
State wildlife agencies identified the need for a single comprehensive database of lek (sage-grouse breeding area) count data and locations. The first component of the framework developed automated, repeatable methods for joining disparate lek count data into a standardized database. The resulting software allows for the addition of new data to the database in a consistent manner, building the historic record of lek data and supporting timely analysis using the most up-to-date inputs. For more information on this data harmonization project, see this page.
2. Spatial Clusters
While understanding population trends within geographical boundaries such as states or management districts is necessary for practitioners, populations are responding to environmental factors that are broader than these extents, and wildlife move across jurisdictional boundaries. To address this issue, the second piece of the framework was developed with thirteen biologically relevant and hierarchically nested units of analysis that capture the drivers of population changes at different spatial scales (Figure 1). The framework analyzes population trends within three of these units: the climate cluster (regional), the neighborhood cluster (population), and the lek cluster (local). For more information on the development of the clusters, see this page.
3. Greater Sage-grouse Trends
Sage-grouse populations naturally vary both within years and in approximately 10-year oscillations. This can make estimations of sage-grouse trends across time difficult. The framework used state-of-the-art models to identify six different low points in rangewide sage-grouse abundance from 1953 – 2023. Comparing population abundance among low points provides accurate estimation of trends through time. For more information on sage-grouse trends, see this page.
4. Targeted Annual Warning System (TAWS)
Understanding when and where populations are declining and identifying if declines are due to factors that can be managed can help managers develop effective management strategies. The targeted annual warning system identifies when a population or lek is declining at a rate that differs from the larger regional trend. This “signal” allows managers to distinguish regional declines caused by unmanageable environmental factors (such as temperature and precipitation) from local declines caused by disturbances that may be improved with management intervention. The TAWS assigns a different severity (watch or warning) depending on the rate and duration of the decline. Watches may identify the need for intensive monitoring whereas warnings may identify the need for management intervention aimed at stabilizing populations. In addition, the TAWS informs managers when a population has signaled a watch or warning in the past. The TAWS’ use of population signals in this manner promotes adaptive management by identifying chronic effects on population declines and allows managers to assess the outcome of management actions. For more information on the TAWS, see this page.
5. Web Tool
The framework is operationalized through a web-based decision support tool that allows users to access trends and TAWS results for their area and period of interest. The application distills the results into relevant outputs such as maps, figures, and tables, that can be directly incorporated into management plans. The design of the framework promotes living products that are annually updated to facilitate timely management intervention and adaptive management. For more information on the web tool, see this page.
Future Co-production
We continue working with all collaborators to improve the science needed for sage-grouse management. Each year, a new standardized lek count database is developed to include newly digitized historical data and improve data quality using critical quality control methods. During this process, software is updated and released to the public. The trends and TAWS models are run with the most recent lek data provided by state partners. The results are released in a USGS Data Series report and included in the trends and TAWS decision support software. We continue to inform partners of updates and improvements to the model and facilitate the incorporation of new features and outputs within the application.
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 the 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.