USGS and Colorado State University scientists are using data and hierarchical community models to create predictive surfaces of bird use by habitat type and comparing these predictions to habitat prioritization derived from sage-grouse locations.
Given the diverse habitat types used for their life history in the sagebrush biome, greater sage-grouse are often proposed as an umbrella species for communities of other sagebrush-obligate species. Data gaps remain throughout the sage-grouse range, however, including in northeastern Wyoming. Concurrently, an ambitious effort is underway to monitor bird communities across the West following the IMBCR program, and the distribution of these species can be characterized by specific habitat components that overlap sage-grouse seasonal habitats. USGS and Colorado State University scientists are using IMBCR data and hierarchical community models to create predictive surfaces of bird use by habitat type and comparing these predictions to habitat prioritization derived from sage-grouse locations. With the extent of IMBCR sampling across the West (nine states that overlap sage-grouse range), this approach has the potential to be extended to other areas with low-density sage-grouse populations where direct identification of seasonal habitats is difficult.
A neutral landscape approach to evaluating the umbrella species concept for greater sage-grouse in northeast Wyoming, USA
Using neutral landscape models to evaluate the umbrella species concept in an ecotone
Prioritizing landscapes for grassland bird conservation with hierarchical community models
Wyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools
Habitat prioritization across large landscapes, multiple seasons, and novel areas: an example using greater sage-grouse in Wyoming
- Overview
USGS and Colorado State University scientists are using data and hierarchical community models to create predictive surfaces of bird use by habitat type and comparing these predictions to habitat prioritization derived from sage-grouse locations.
Given the diverse habitat types used for their life history in the sagebrush biome, greater sage-grouse are often proposed as an umbrella species for communities of other sagebrush-obligate species. Data gaps remain throughout the sage-grouse range, however, including in northeastern Wyoming. Concurrently, an ambitious effort is underway to monitor bird communities across the West following the IMBCR program, and the distribution of these species can be characterized by specific habitat components that overlap sage-grouse seasonal habitats. USGS and Colorado State University scientists are using IMBCR data and hierarchical community models to create predictive surfaces of bird use by habitat type and comparing these predictions to habitat prioritization derived from sage-grouse locations. With the extent of IMBCR sampling across the West (nine states that overlap sage-grouse range), this approach has the potential to be extended to other areas with low-density sage-grouse populations where direct identification of seasonal habitats is difficult.
- Data
A neutral landscape approach to evaluating the umbrella species concept for greater sage-grouse in northeast Wyoming, USA
Greater sage-grouse (Centrocercus urophasianus) has been identified as a potential umbrella species with the assumption that conservation of their habitats in sagebrush ecosystems may benefit multiple other wildlife species, but co-occurrence with an umbrella species does not necessarily guarantee species will respond positively to management for sage-grouse. This may be particularly true for ecot - Publications
Using neutral landscape models to evaluate the umbrella species concept in an ecotone
ContextSteep declines in North American rangeland biodiversity have prompted researchers and managers to use umbrella species as a tool to manage diverse suites of co-occurring wildlife, but efficacy of this method has been variable. Evaluation of prairie and shrubland grouse as umbrellas is typically restricted to observed overlap between umbrella and background species, but this approach does noAuthorsCourtney Duchardt, Adrian P. Monroe, David R. Edmunds, Matthew James Holloran, Alison G. Holloran, Cameron L. AldridgePrioritizing landscapes for grassland bird conservation with hierarchical community models
ContextGiven widespread population declines of birds breeding in North American grasslands, management that sustains wildlife while supporting rancher livelihoods is needed. However, management effects vary across landscapes, and identifying areas with the greatest potential bird response to conservation is a pressing research need.ObjectivesWe developed a hierarchical modeling approach to study gAuthorsAdrian Pierre-Frederic Monroe, David R. Edmunds, Cameron L. Aldridge, Matthew J Holloran, Timothy J Assal, Alison G HolloranWyoming greater sage-grouse habitat prioritization: A collection of multi-scale seasonal models and geographic information systems land management tools
With rapidly changing landscape conditions within Wyoming and the potential effects of landscape changes on sage-grouse habitat, land managers and conservation planners, among others, need procedures to assess the location and juxtaposition of important habitats, land-cover, and land-use patterns to balance wildlife requirements with multiple human land uses. Biologists frequently develop habitat-AuthorsMichael S. O'Donnell, Cameron L. Aldridge, Kevin E. Doherty, Bradley C. FedyHabitat prioritization across large landscapes, multiple seasons, and novel areas: an example using greater sage-grouse in Wyoming
Animal habitat selection is an important and expansive area of research in ecology. In particular, the study of habitat selection is critical in habitat prioritization efforts for species of conservation concern. Landscape planning for species is happening at ever-increasing extents because of the appreciation for the role of landscape-scale patterns in species persistence coupled to improved dataAuthorsBradley C. Fedy, Kevin E. Doherty, Cameron L. Aldridge, Michael S. O'Donnell, Jeffrey L. Beck, Bryan Bedrosian, David Gummer, Matthew J. Holloran, Gregory D. Johnson, Nicholas W. Kaczor, Christopher P. Kirol, Cheryl A. Mandich, David Marshall, Gwyn McKee, Chad Olson, Aaron C. Pratt, Christopher C. Swanson, Brett L. Walker