Estimating trends for greater sage-grouse populations within highly stochastic environments Active
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. A key component of this framework was the production of reliable estimates of sage-grouse population trends. To do this, we implemented techniques that accounted for imperfect detection of birds on leks (sage-grouse breeding sites), incomplete timeseries data for most leks, and environmental factors that can lead to regular fluctuations in abundance. Improvements over past modeling techniques allowed for a greater number of populations to be included in analyses, which resulted in trend estimates of higher spatial and temporal resolution.
Background
A substantial challenge facing estimation of sage-grouse population trends are the incomplete count data associated with many leks. Previous studies addressed this by excluding populations with irregular data, but doing so restricts the ability to estimate trends across time and space. Sage-grouse populations fluctuate over time, a phenomenon that thus far is best explained by cyclic climatic conditions that influence food and habitat availability. This relationship results in a pattern that repeats every 6-12 years and consists of relatively short increases and decreases in population size that can confound long-term trends and can lead to false interpretations of population performance. As such, studies of sage-grouse population trends are more robust when they consider datasets spanning multiple decades as well as start and stop years that represent one or more complete oscillations.
Research Objective
Our objective was to estimate trends of sage-grouse populations across their distribution in the United States in a manner that addressed multiple obstacles: (1) birds are imperfectly detected at leks, (2) lek counts represent an incomplete record of true abundance, and (3) most populations exhibit regular fluctuations in abundance.
Methods
We implemented a modeling approach that allowed for information to be shared across groups of similar leks, such that population abundance was estimated for every lek and year. Our approach accounted for variable sampling effort over time and issues with imperfect detection by fitting key parameters within the state and observation components of a state-space model.
We restricted inferences to complete oscillations, and we examined population trends using multiple time periods, each containing a different number of complete oscillations over the past 60 years (1960–2023). We used population abundance nadirs (low points), versus apexes (high points), to define start-stop temporal scales of inference. Population nadirs produced more consistent estimates of population trends and were considered more relevant for managers since populations are at greater risk of local extirpation when abundance is low.
Results and Implications
Our model estimated a 2.9% annual rate of decline for sage-grouse populations range-wide over the past six decades. Cumulative declines across short (19 years), medium (35 years), and long (55 years) temporal periods were approximately 40.9, 65.0, and 79.6% respectively (Figure 1). Most populations range-wide experienced above-average abundance between the 1960s and early-1980s. A period that began in the late-1980s and ended around approximately 2016 was marked by a substantial decline in sage-grouse numbers and coincided with widespread drought and increased development of land for energy and agriculture use (Figure 2). Sage-grouse populations across the range were reduced to smaller sizes by 2016, and have yet to recover to pre-1980s numbers. The greatest declines were observed within the western portion of the species’ range where populations have been hardest hit by wildfire and type conversion of sagebrush to invasive grasslands. Conversely, the eastern portion of the range, and western Wyoming in particular, continues to harbor the largest population sizes based on the average number of males per lek. Maintaining high-quality habitats within those areas may ensure the viability and resiliency of populations to the effects of climate in the future.
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 hierarchical population modeling framework to produce results for use in annual decision making. Because sage-grouse populations oscillate at 6–12-year intervals, population trends will change more slowly depending on the timing of the interval.
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.
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. A key component of this framework was the production of reliable estimates of sage-grouse population trends. To do this, we implemented techniques that accounted for imperfect detection of birds on leks (sage-grouse breeding sites), incomplete timeseries data for most leks, and environmental factors that can lead to regular fluctuations in abundance. Improvements over past modeling techniques allowed for a greater number of populations to be included in analyses, which resulted in trend estimates of higher spatial and temporal resolution.
Background
A substantial challenge facing estimation of sage-grouse population trends are the incomplete count data associated with many leks. Previous studies addressed this by excluding populations with irregular data, but doing so restricts the ability to estimate trends across time and space. Sage-grouse populations fluctuate over time, a phenomenon that thus far is best explained by cyclic climatic conditions that influence food and habitat availability. This relationship results in a pattern that repeats every 6-12 years and consists of relatively short increases and decreases in population size that can confound long-term trends and can lead to false interpretations of population performance. As such, studies of sage-grouse population trends are more robust when they consider datasets spanning multiple decades as well as start and stop years that represent one or more complete oscillations.
Research Objective
Our objective was to estimate trends of sage-grouse populations across their distribution in the United States in a manner that addressed multiple obstacles: (1) birds are imperfectly detected at leks, (2) lek counts represent an incomplete record of true abundance, and (3) most populations exhibit regular fluctuations in abundance.
Methods
We implemented a modeling approach that allowed for information to be shared across groups of similar leks, such that population abundance was estimated for every lek and year. Our approach accounted for variable sampling effort over time and issues with imperfect detection by fitting key parameters within the state and observation components of a state-space model.
We restricted inferences to complete oscillations, and we examined population trends using multiple time periods, each containing a different number of complete oscillations over the past 60 years (1960–2023). We used population abundance nadirs (low points), versus apexes (high points), to define start-stop temporal scales of inference. Population nadirs produced more consistent estimates of population trends and were considered more relevant for managers since populations are at greater risk of local extirpation when abundance is low.
Results and Implications
Our model estimated a 2.9% annual rate of decline for sage-grouse populations range-wide over the past six decades. Cumulative declines across short (19 years), medium (35 years), and long (55 years) temporal periods were approximately 40.9, 65.0, and 79.6% respectively (Figure 1). Most populations range-wide experienced above-average abundance between the 1960s and early-1980s. A period that began in the late-1980s and ended around approximately 2016 was marked by a substantial decline in sage-grouse numbers and coincided with widespread drought and increased development of land for energy and agriculture use (Figure 2). Sage-grouse populations across the range were reduced to smaller sizes by 2016, and have yet to recover to pre-1980s numbers. The greatest declines were observed within the western portion of the species’ range where populations have been hardest hit by wildfire and type conversion of sagebrush to invasive grasslands. Conversely, the eastern portion of the range, and western Wyoming in particular, continues to harbor the largest population sizes based on the average number of males per lek. Maintaining high-quality habitats within those areas may ensure the viability and resiliency of populations to the effects of climate in the future.
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 hierarchical population modeling framework to produce results for use in annual decision making. Because sage-grouse populations oscillate at 6–12-year intervals, population trends will change more slowly depending on the timing of the interval.
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.