Greater Sage-Grouse Population Monitoring Framework: Glossary of Terms
The Greater Sage-grouse Population Monitoring Framework fills a prominent information gap to aid current assessments of sage-grouse population trends across spatial and temporal scales. It centers on four objectives: 1) create a standardized database of lek counts; 2) cluster leks to develop spatial population structures; 3) estimate spatial trends across temporal extents; and 4) develop a system to estimate where and when management action is likely to benefit declining populations of sage-grouse at the appropriate spatial scale on an annual basis.
The framework is comprised of three lines of evidence to help managers estimate past, present, and future population performance:
The trends analysis provides evidence of past population performance. It addresses the question: How have sage-grouse populations performed historically?
The Targeted Annual Warning System (TAWS) provides evidence of present population performance. It addresses the question: How are sage-grouse populations performing right now?
The extirpation probabilities provide evidence of future population performance. They address the question: How are sage-grouse populations expected to perform in the future?
Inputs |
Cluster | Nested management units that are defined by sage-grouse biology. There are 13 nested scales, or levels, to support management at regional (coarse) to local (fine) scales. |
---|---|---|
Lek Cluster (Lek) | A lek cluster represents a single lek and is level 1 of the spatial clusters. Leks used in the population monitoring framework must meet the criteria for inclusion in the range-wide lek database. These rules are described in the associated handout, “Range-wide Lek Database Rules”. | |
Neighborhood Cluster (NC) | Polygons that group leks based on their connectivity (https://doi.org/10.1111/2041-210X.13949) and represent closed population units. Connectivity is upheld as long as 1) leks are <30 km apart; and 2) lek connections do not cross high traffic volumes on interstates, highways, and major roads (≥4000 annual average daily traffic). Neighborhood clusters contain approximately 20-30 leks. Less than 20 leks occur because there are too few leks to merge with a connected neighboring cluster or because a rule prevents the connection. Neighborhood clusters are level 2 of the spatial clusters. | |
Climate Cluster (CC) | Large regions of the landscape that group leks with similar climate conditions ( https://doi.org/10.3133/ofr20201154). Neighborhood clusters are nested within climate clusters. Climate clusters are level 13 of the spatial clusters. | |
Trends |
Trends Analysis (Trends) | The trends analysis estimates population performance at different scales and time periods. Population performance is defined as estimated abundance. Trends are estimated at local (lek, neighborhood cluster) and regional (climate cluster) scales. This informs management at several spatial scales. The trends analysis also predicts performance over six different timeframes, or population cycles. This can help managers identify if recent population performance deviates from historical population performance. Importantly, the trends analysis accounts for natural fluctuations in sage-grouse populations that can otherwise obscure accurate assessments of population performance. |
Oscillation | A phenomenon where populations experience natural, regular fluctuations in abundance. In sage-grouse, these oscillations are driven by climatic factors such as precipitation that mediate vegetation used for food, nesting, and brood rearing. | |
Nadir | The time period within an oscillation that has the lowest abundance. | |
Cycle | The temporal range that is repeating a pattern. It represents a single oscillation and is measured nadir to nadir. | |
Trend | The estimated change in population performance, or abundance, over some time period. In this analysis, time periods are defined as one, two, three, four, five, or six cycles. Estimates within and across cycles are made nadir-to-nadir to avoid overestimating population performance. | |
Extirpation probability | The probability that, given current population trends, a population will be reduced to less than two males, which aligns with state wildlife agencies definition of lek inactivity. Extirpation probabilities are calculated at three different temporal scales: two, four, and six cycles into the future. | |
Targeted Annual Warning System |
Targeted Annual Warning System (TAWS) | A system that identifies sustained, aberrant population declines across nested spatial scales on an annual basis. To determine if a decline is aberrant, the TAWS compares the rate of population change at a local scale (leks or neighborhood clusters) to the rate of population change at a regional scale (climate cluster). In this way, the TAWS helps managers differentiate between broad-scale, natural population declines driven by climatic factors that are difficult to manage, and unexpected population declines driven by local factors that may be mitigated through management. The TAWS also identifies when aberrant declines are sustained over at least 2 consecutive years. This helps managers avoid allocating resources to populations that experience a chance year of poor performance. |
Signal | A signal is assigned to a population that is 1) declining at a local scale (lek or neighborhood cluster); 2) is decoupled from the trend at the regional scale (climate cluster); 3) the decline is sustained over multiple years. | |
Slow Signal | A slow signal indicates a population is declining and the rate of decline is slightly decoupled from the regional trend. | |
Fast Signal | A fast signal indicates a population is declining and the rate of decline is steeply decoupled from the regional trend. | |
Watch | Assigned to populations that had slow signals over 2 consecutive years | |
Warning | Assigned to populations that had slow signals in 3 out of 4 consecutive years or fast signals in 2 out of 3 consecutive years. |
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 U.S. 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.
Greater Sage-Grouse Population Monitoring Framework
Data Harmonization for 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
Trends and a Targeted Annual Warning System for Greater Sage-Grouse in the Western United States (ver. 3.0, February 2024)
A targeted annual warning system developed for the conservation of a sagebrush indicator species
Range-wide greater sage-grouse hierarchical monitoring framework—Implications for defining population boundaries, trend estimation, and a targeted annual warning system
The Greater Sage-grouse Population Monitoring Framework fills a prominent information gap to aid current assessments of sage-grouse population trends across spatial and temporal scales. It centers on four objectives: 1) create a standardized database of lek counts; 2) cluster leks to develop spatial population structures; 3) estimate spatial trends across temporal extents; and 4) develop a system to estimate where and when management action is likely to benefit declining populations of sage-grouse at the appropriate spatial scale on an annual basis.
The framework is comprised of three lines of evidence to help managers estimate past, present, and future population performance:
The trends analysis provides evidence of past population performance. It addresses the question: How have sage-grouse populations performed historically?
The Targeted Annual Warning System (TAWS) provides evidence of present population performance. It addresses the question: How are sage-grouse populations performing right now?
The extirpation probabilities provide evidence of future population performance. They address the question: How are sage-grouse populations expected to perform in the future?
Inputs |
Cluster | Nested management units that are defined by sage-grouse biology. There are 13 nested scales, or levels, to support management at regional (coarse) to local (fine) scales. |
---|---|---|
Lek Cluster (Lek) | A lek cluster represents a single lek and is level 1 of the spatial clusters. Leks used in the population monitoring framework must meet the criteria for inclusion in the range-wide lek database. These rules are described in the associated handout, “Range-wide Lek Database Rules”. | |
Neighborhood Cluster (NC) | Polygons that group leks based on their connectivity (https://doi.org/10.1111/2041-210X.13949) and represent closed population units. Connectivity is upheld as long as 1) leks are <30 km apart; and 2) lek connections do not cross high traffic volumes on interstates, highways, and major roads (≥4000 annual average daily traffic). Neighborhood clusters contain approximately 20-30 leks. Less than 20 leks occur because there are too few leks to merge with a connected neighboring cluster or because a rule prevents the connection. Neighborhood clusters are level 2 of the spatial clusters. | |
Climate Cluster (CC) | Large regions of the landscape that group leks with similar climate conditions ( https://doi.org/10.3133/ofr20201154). Neighborhood clusters are nested within climate clusters. Climate clusters are level 13 of the spatial clusters. | |
Trends |
Trends Analysis (Trends) | The trends analysis estimates population performance at different scales and time periods. Population performance is defined as estimated abundance. Trends are estimated at local (lek, neighborhood cluster) and regional (climate cluster) scales. This informs management at several spatial scales. The trends analysis also predicts performance over six different timeframes, or population cycles. This can help managers identify if recent population performance deviates from historical population performance. Importantly, the trends analysis accounts for natural fluctuations in sage-grouse populations that can otherwise obscure accurate assessments of population performance. |
Oscillation | A phenomenon where populations experience natural, regular fluctuations in abundance. In sage-grouse, these oscillations are driven by climatic factors such as precipitation that mediate vegetation used for food, nesting, and brood rearing. | |
Nadir | The time period within an oscillation that has the lowest abundance. | |
Cycle | The temporal range that is repeating a pattern. It represents a single oscillation and is measured nadir to nadir. | |
Trend | The estimated change in population performance, or abundance, over some time period. In this analysis, time periods are defined as one, two, three, four, five, or six cycles. Estimates within and across cycles are made nadir-to-nadir to avoid overestimating population performance. | |
Extirpation probability | The probability that, given current population trends, a population will be reduced to less than two males, which aligns with state wildlife agencies definition of lek inactivity. Extirpation probabilities are calculated at three different temporal scales: two, four, and six cycles into the future. | |
Targeted Annual Warning System |
Targeted Annual Warning System (TAWS) | A system that identifies sustained, aberrant population declines across nested spatial scales on an annual basis. To determine if a decline is aberrant, the TAWS compares the rate of population change at a local scale (leks or neighborhood clusters) to the rate of population change at a regional scale (climate cluster). In this way, the TAWS helps managers differentiate between broad-scale, natural population declines driven by climatic factors that are difficult to manage, and unexpected population declines driven by local factors that may be mitigated through management. The TAWS also identifies when aberrant declines are sustained over at least 2 consecutive years. This helps managers avoid allocating resources to populations that experience a chance year of poor performance. |
Signal | A signal is assigned to a population that is 1) declining at a local scale (lek or neighborhood cluster); 2) is decoupled from the trend at the regional scale (climate cluster); 3) the decline is sustained over multiple years. | |
Slow Signal | A slow signal indicates a population is declining and the rate of decline is slightly decoupled from the regional trend. | |
Fast Signal | A fast signal indicates a population is declining and the rate of decline is steeply decoupled from the regional trend. | |
Watch | Assigned to populations that had slow signals over 2 consecutive years | |
Warning | Assigned to populations that had slow signals in 3 out of 4 consecutive years or fast signals in 2 out of 3 consecutive years. |
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 U.S. 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.