United States Department of Agriculture

Forest Rocky Mountain General Technical Report April 2017

Service Research Station RMRS-GTR-360

Science Framework for Conservation 

and Restoration of the Sagebrush Biome: 

Linking the Department of the Interior’s 

Integrated Rangeland Fire Management 

Strategy to Long-Term Strategic 

Conservation Actions 

Part 1. Science Basis and Applications

Jeanne C. Chambers, Jeffrey L. Beck, John B. Bradford, Jared Bybee, Steve 

Campbell, John Carlson, Thomas J. Christiansen, Karen J. Clause, Gail Collins, 

Michele R. Crist, Jonathan B. Dinkins, Kevin E. Doherty, Fred Edwards, Shawn 

Espinosa, Kathleen A. Griffin, Paul Griffin, Jessica R. Haas, Steven E. Hanser, 

Douglas W. Havlina, Kenneth F. Henke, Jacob D. Hennig, Linda A. Joyce, Francis 

F. Kilkenny, Sarah M. Kulpa, Laurie L. Kurth, Jeremy D. Maestas, Mary Manning, 

Kenneth E. Mayer, Brian A. Mealor, Clinton McCarthy, Mike Pellant, Marco A. Perea, 

Karen L. Prentice, David A. Pyke, Lief A. Wiechman, and Amarina Wuenschel
Chambers, J.C.; Beck, J.L.; Bradford, J.B.; Bybee, J.; Campbell, S.; Carlson, J.; Christiansen, 

T.J.; Clause, K.J.; Collins, G.; Crist, M.R.; Dinkins, J.B.; Doherty, K.E.; Edwards, F.; 

Espinosa, S.; Griffin, K.A.; Griffin, P.; Haas, J.R.; Hanser, S.E.; Havlina, D.W.; Henke, 

K.F.; Hennig, J.D.; Joyce, L.A.; Kilkenny, F.M.; Kulpa, S.M.; Kurth, L.L.; Maestas, J.D.; 

Manning, M.; Mayer, K.E.; Mealor, B.A.; McCarthy, C.; Pellant, M.; Perea, M.A.; Prentice, 

K.L.; Pyke, D.A.; Wiechman, L.A.; Wuenschel, A. 2017. Science framework for conservation and restoration of the sagebrush biome: Linking the Department of the Interior’s 

Integrated Rangeland Fire Management Strategy to long-term strategic conservation 

actions. Part 1. Science basis and applications. Gen. Tech. Rep. RMRS-GTR-360. Fort 

Collins, CO: U.S Department of Agriculture, Forest Service, Rocky Mountain Research 

Station. 213 p.

Abstract

The Science Framework is intended to link the Department of the Interior’s Integrated 

Rangeland Fire Management Strategy with long-term strategic conservation actions in the 

sagebrush biome. The Science Framework provides a multiscale approach for prioritizing areas for management and determining effective management strategies within the sagebrush 

biome. The emphasis is on sagebrush (Artemisia spp.) ecosystems and Greater sage-grouse 

(Centrocercus urophasianus). The approach provided in the Science Framework links 

sagebrush ecosystem resilience to disturbance and resistance to nonnative, invasive plant 

species to species habitat information based on the distribution and abundance of focal species. A geospatial process is presented that overlays information on ecosystem resilience and 

resistance, species habitats, and predominant threats and that can be used at the mid-scale 

to prioritize areas for management. A resilience and resistance habitat matrix is provided that 

can help decisionmakers evaluate risks and determine appropriate management strategies. 

Prioritized areas and management strategies can be refined by managers and stakeholders 

at the local scale based on higher resolution data and local knowledge. Decision tools are 

discussed for determining appropriate management actions for areas that are prioritized for 

management. Geospatial data, maps, and models are provided through the U.S. Geological 

Survey (USGS) ScienceBase and Bureau of Land Management (BLM) Landscape Approach 

Data Portal. The Science Framework is intended to be adaptive and will be updated as 

additional data become available on other values and species at risk. It is anticipated that 

the Science Framework will be widely used to: (1) inform emerging strategies to conserve 

sagebrush ecosystems, sagebrush dependent species, and human uses of the sagebrush 

system, and (2) assist managers in prioritizing and planning on-the-ground restoration and 

mitigation actions across the sagebrush biome. 

Keywords: sagebrush habitat, Greater sage-grouse, persistent ecosystem threats, land use 

and development threats, climate change, management prioritization, resilience, resistance, 

conservation, protection, restoration 

Front cover photo. Spring bloom in sagebrush country in the Bodie Hills overlooking Mono 

Lake near the Nevada-California State line. Photo by Bob Wick.

Inside cover photos. Natural recovery of native forbs and grasses in the Soda Fire rehabilitation area in southwestern Idaho with native lupine in the upper right (photos by Francis 

Kilkenny) and a mature mountain big sagebrush and bluebunch wheatgrass community in the 

upper left (photo by Kirk Davies).

Rear cover photo. Spring bloom in a Wyoming big sagebrush community near Pilot Butte in 

southwestern Wyoming. Photo by Corey Kallstrom.
i

Authors

Jeanne C. Chambers, Research Ecologist, USDA Forest Service, Rocky Mountain Research 

Station, Reno, Nevada.

Jeffrey L. Beck, Associate Professor, Department of Ecosystem Science and Management, 

University of Wyoming, Laramie, Wyoming.

John B. Bradford, Research Ecologist, USDOI U.S. Geological Survey, Southwest 

Biological Science Center, Flagstaff, Arizona.

Jared Bybee, Acting On-Range Branch Chief, Wild Horse and Burro Program, USDOI 

Bureau of Land Management, Washington, DC.

Steve Campbell, Soil Scientist, USDA Natural Resources Conservation Service, Portland, 

Oregon.

John Carlson, Management Zone I Greater Sage-Grouse Lead, USDOI Bureau of Land 

Management, Billings, Montana.

Thomas J. Christiansen, Sage-Grouse Program Coordinator, Wyoming Game & Fish 

Department, Green River, Wyoming.

Karen J. Clause, Rangeland Management Specialist, USDA Natural Resources 

Conservation Service, Pinedale, Wyoming.

Gail Collins, Supervisory Wildlife Biologist, USDOI U.S. Fish and Wildlife Service, SheldonHart National Wildlife Refuge Complex, Nevada.

Michele R. Crist, Landscape Ecologist, USDOI Bureau of Land Management, National 

Interagency Fire Center, Boise, Idaho.

Jonathan B. Dinkins, Postdoctoral Research Associate, Department of Ecosystem Science 

and Management, University of Wyoming, Laramie, Wyoming. 

Kevin E. Doherty, Wildlife Biologist, USDOI U.S. Fish and Wildlife Service, Lakewood, 

Colorado.

Fred Edwards, Great Basin Ecoregional Coordinator, USDOI Bureau of Land Management, 

Reno, Nevada.

Shawn Espinosa, Wildlife Staff Specialist, Nevada Department of Wildlife, Nevada 

Department of Wildlife, Reno, Nevada.

Kathleen A. Griffin, Grouse Conservation Coordinator, Colorado Parks and Wildlife, Grand 

Junction, Colorado.

Paul Griffin, Research Coordinator, Wild Horse and Burro Program, USDOI Bureau of Land 

Management, Fort Collins, Colorado. 

Jessica R. Haas, Ecologist, USDA Forest Service, Rocky Mountain Research Station, 

Missoula, Montana.

Steven E. Hanser, Sagebrush Ecosystem Specialist, USDOI U.S. Geological Survey, 

Reston, Virginia.

Douglas W. Havlina, Fire Ecologist, USDOI Bureau of Land Management, National 

Interagency Fire Center, Boise, Idaho.

Kenneth F. Henke, Natural Resource Specialist, Bureau of Land Management, Cheyenne, 

Wyoming.

Jacob D. Hennig, Spatial and Data Technician, Department of Ecosystem Science and 

Management, University of Wyoming, Laramie, Wyoming.

Linda A. Joyce, Supervisory Research Rangeland Scientist, USDA Forest Service, Rocky 

Mountain Research Station, Fort Collins, Colorado.
ii

Francis F. Kilkenny, Research Biologist/Great Basin Native Plant Project Lead, USDA 

Forest Service, Rocky Mountain Research Station, Boise, Idaho.

Sarah M. Kulpa, Restoration Ecologist/Botanist, USDOI Fish and Wildlife Service, Reno Fish 

and Wildlife Office, Reno, Nevada.

Laurie L. Kurth, Assistant Director, Landscapes and Partnerships, USDA Forest Service, 

Fire and Aviation Management, Washington, DC.

Jeremy D. Maestas, Sagebrush Ecosystem Specialist, USDA Natural Resources 

Conservation Service, Redmond, Oregon.

Mary Manning, Regional Vegetation Ecologist, USDA Forest Service, Northern Region, 

Missoula, Montana.

Kenneth E. Mayer, Wildlife Ecologist, Western Association of Fish and Wildlife Agencies, 

Sparks, Nevada.

Brian A. Mealor, Director, Research and Extension Center, University of Wyoming, Sheridan, 

Wyoming.

Clinton McCarthy, Retired Wildlife Biologist, Intermountain Region, USDA Forest Service, 

Ogden, Utah.

Mike Pellant, Rangeland Ecologist, USDOI Bureau of Land Management, Boise, Idaho.

Marco A. Perea, Fire Management Specialist, USDOI Bureau of Land Management, 

Lakewood, Colorado.

Karen L. Prentice, National Healthy Lands Coordinator, USDOI Bureau of Land 

Management, Washington, DC.

David A. Pyke, Research Ecologist, USDOI U.S. Geological Survey, Forest & Rangeland 

Ecosystem Science Center, Corvallis, Oregon.

Lief A. Wiechman, Wildlife Biologist, USDOI U.S. Fish and Wildlife Service, Fort Collins, 

Colorado.

Amarina Wuenschel, Ecologist, USDA Forest Service, Pacific Southwest Region, North 

Fork, California.

Acknowledgments

We thank the Western Association of Fish and Wildlife Agencies, Great Basin Landscape 

Conservation Cooperative, and Bureau of Land Management for financial assistance and the 

numerous other agencies that provided in-kind support of this effort. We received comments 

from over 50 reviewers from State and Federal Agencies, non-governmental organizations (NGOs), and private individuals during two review periods that helped to improve the 

manuscript. Technical reviews provided by Michael J. Wisdom, Peter J. Weisberg, Michael J. 

Haske, Terry A. Messmer, Stanley G. Kitchen, Matt C. Reeves, Peter S. Coates, and David 

Tart also helped to improve the manuscript. 

All Rocky Mountain Research Station publications are published by U.S. Forest Service 

employees and are in the public domain and available at no cost. Even though U.S. Forest 

Service publications are not copyrighted, they are formatted according to U.S. Department of 

Agriculture standards and research findings and formatting cannot be altered in reprints. Altering 

content or formatting, including the cover and title page, is strictly prohibited.

Any use of trade, product, or firm names is for descriptive purposes 

only and does not imply endorsement by the U.S. Government.
iii

Contents

1. Executive Summary...............................................................................................1

2. Use of This Document ...........................................................................................4

3. Overview of The Science Framework ....................................................................4

3.1 Background ....................................................................................................4

3.2 Approach ........................................................................................................6

3.3 Scope and Scales ..........................................................................................6

4. Climatic Regimes and Vegetation Types in the Sagebrush Biome ...................... 10

4.1 West-Central Semiarid Prairies Ecoregions ................................................. 14

4.2 Cold Deserts Ecoregions in the Eastern Part of the Sagebrush Biome ....... 16

4.3 Cold Deserts Ecoregions in the Western Part of the Sagebrush Biome ...... 17

4.4 Western Cordillera Ecoregions in the Eastern Part of the Sagebrush 

Biome ......................................................................................................18

4.5 Western Cordillera Ecoregions in the Western Part of the Sagebrush 

Biome ......................................................................................................19

5. Threats to Sagebrush Ecosystems and 

Greater Sage-Grouse ......................................................................................19

5.1 Persistent Ecosystem Threats: Invasive Plant Species, Conifer 

Expansion, and Altered Fire Regimes .....................................................20

5.2 Persistent Ecosystem Threats: Climate Change .......................................... 30

5.3 Land Use and Development Threats ............................................................35

6. Resilience to Disturbance and Resistance to Invasive Annual Grasses in 

Sagebrush Ecosystems ..................................................................................47

7. Integrating Resilience and Resistance With Species Habitat Requirements to 

Prioritize Areas For Management and Inform Management Strategies .......... 51

7.1 Soil Temperature and Moisture Regimes as Indicators of Ecosystem 

Resilience to Disturbance and Resistance to Invasive Annual 

Grasses at Biome to Mid-Scales .............................................................51

7.2 Greater Sage-Grouse Breeding Habitat Probabilities and Population 

Indices .....................................................................................................57

7.3 Landscape Cover of Sagebrush as an Indicator of Habitat .......................... 60

7.4 Sage-Grouse Habitat Resilience and Resistance Matrix: A Key 

Prioritization Tool .....................................................................................64

7.5 Adapting the Sage-Grouse Resilience and Resistance Matrix and 

Management Strategies to Other Sagebrush Obligate Species.............. 73

8. Delineating Habitats For Targeted Management Intervention at the 

Biome and Ecoregion or Management Zone Scale ........................................ 75

8.1 Assessing Priority Areas for Habitat Management: Key Data Layers and 

Their Use .................................................................................................75

8.2 Assessing Priority Areas for Habitat Management: Overlaying Data 

Layers......................................................................................................81

9. Determining Appropriate Management Treatments at Local Scales ................... 89

9.1 Steps in the Process ....................................................................................89
iv

9.2 Examples of How to Apply the Concepts and Tools ..................................... 92

9.3 Sources of Management Information .........................................................106

References ............................................................................................................107

Appendix 1—Definitions of Terms Used in This Document ................................... 135

Appendix 2—Explanation of Soil Temperature and Moisture Regimes 

Data and the Resilience and Resistance Categories.................................... 138

Appendix 3—Climate Change Projections for the Sagebrush Biome: Data, 

Methods, and Maps .......................................................................................141

Appendix 4—Methods for Determining the Predominant Ecological Types ......... 168

Appendix 5—Generalized State-and-Transition Models for Predominant 

Sagebrush Ecological Types in the West-Central Semiarid 

Prairies (MZ I), and Western Cordillera and Cold Desert (MZ II, VII) 

in the Eastern Portion of the Range ..............................................................171

Appendix 6—Generalized State-and-Transition Models for Predominant 

Sagebrush Ecological Types in the Cold Deserts (MZ III, IV, V) in 

the Western Portion of the Range ...............................................................183

Appendix 7—Explanation of the Use of Landscape Measures to Describe 

Sagebrush Habitat ........................................................................................189

Appendix 8—Data Sources and Websites for the Maps in This Report ................ 190

Appendix 9—Connectivity Between Priority Areas for Conservation of 

Greater Sage-Grouse ....................................................................................196

Appendix 10—Fire Risk Assessment for Greater Sage-Grouse Breeding 

Habitat ...........................................................................................................199

Appendix 11—Explanation of Seed Transfer Guidance ....................................... 202

Appendix 12—Tables and Figures Summarizing the Relative Resilience 

and Resistance, Greater Sage-Grouse Breeding Habitat Probabilities, 

and Greater Sage-Grouse Breeding Populations for the Sagebrush 

Biome ............................................................................................................206

Appendix 13—Tables Summarizing Fire Area by Resilience and Resistance 

Category .......................................................................................................212
v
USDA Forest Service RMRS-GTR-360. 2017. 1

1. Executive Summary

In May 2015 the Department of the Interior released “An Integrated Rangeland 

Fire Management Strategy: Final Report to the Secretary of the Interior,” (IRFMS; 

USDOI 2015b). The IRFMS outlined longer-term actions needed to implement 

policies and strategies for preventing and suppressing rangeland fire and restoring 

rangeland landscapes affected by fire in the Western United States (USDOI 2015a). 

Priority was placed on protecting, conserving, and restoring Great Basin sagebrush 

(Artemisia spp.) ecosystems and, in particular, Greater sage-grouse (Centrocercus 

urophasianus; hereafter, GRSG) habitat. Eighty-three individual actions were identified and a provision was included for developing a multi-scale Conservation and 

Restoration Strategy (C and R Strategy) for sagebrush ecosystems. 

Part 1 of the “Science Framework for Conservation and Restoration of the 

Sagebrush Biome: Linking the Department of the Interior’s Integrated Rangeland 

Fire Management Strategy to Long-Term Strategic Conservation Actions” (Science 

Framework) focuses on the science basis and applications for the C and R Strategy. 

Scientific information and decision-support tools are provided that are intended to: 

(1) facilitate prioritization of areas for conservation and restoration management 

actions, (2) inform budget prioritization of management actions, and 3) inform management strategies across scales and ownerships. 

Part 2 of the Science Framework focuses on management considerations for the C 

and R Strategy and will be available in 2017. The following topics are planned for 

inclusion in Part 2: (1) nonnative invasive plant species management, (2) wildfire 

and fuels management, (3) livestock grazing management, (4) wild horse and burro 

considerations, (5) seed zone considerations, (6) monitoring to inform adaptive 

management, and (7) integration of the Science Framework with other actions initiated in response to the IRFMS. 

The Science Framework builds on a strategic, multi-scale approach developed by 

two regional Western Association of Fish and Wildlife Agencies (WAFWA) working 

groups to address persistent ecosystem threats, including invasive plant species, uncharacteristic wildfire, conifer expansion, climate change, and land use and development threats. The approach developed by these groups has been published in two 

U.S. Department of Agriculture (USDA), Forest Service, Rocky Mountain Research 

Station, General Technical Reports (Chambers et al. 2014b, 2016a), and was used 

by the Bureau of Land Management to develop a multi-year program of work for 

the Great Basin (BLM 2014). The Science Framework provides a unifying approach 

that includes and updates the two previous efforts and incorporates areas that were 

not addressed earlier, such as the Columbia Plateau.

The Science Framework focuses on the sagebrush biome and GRSG, but provides 

information and tools to allow managers to address other resource values and at-risk 

species as geospatial data for those values and species become available. A crosswalk is provided between Environmental Protection Agency ecoregions (EPA 2016) 

and sage-grouse Management Zones (Stiver et al. 2006). This approach aligns with 

the Sage-grouse Habitat Assessment Framework (Johnson 1980; Stiver et al. 2015). 

Three scales are included to inform different aspects of the planning process: (1) the 

sagebrush biome scale where consistent, rangewide data can inform budget prioritization; (2) the mid-scale (individual or multiple ecoregions/Management Zones) 
2 USDA Forest Service RMRS-GTR-360. 2017.

where assessments are typically conducted to inform budget prioritization and develop priority planning areas; and (3) the local scale where local data and expertise 

are used to select project sites and determine appropriate management strategies and 

treatments within priority planning areas.

An overview of the dominant threats to sagebrush ecosystems and GRSG is 

provided and spatially explicit data and maps are presented for the threats. The 

threats included are those identified in the Sage-Grouse Conservation Objectives 

Team Final Report (COT Report; FWS 2013). These threats are consistent with 

those included in the Greater Sage-Grouse Monitoring Framework developed by the 

Interagency Greater Sage-Grouse Disturbance and Monitoring Subteam (IGSDMS 

2014) and the State Wildlife Action Plans, which were prepared for the purpose 

of maintaining the health and diversity of wildlife within the States and reducing 

the need for future listings under the Endangered Species Act. In addition to these 

previously identified threats, climate change is addressed in the Science Framework 

and climate projections are included for key climate variables (e.g., mean annual 

temperature and mean annual precipitation) (Appendix 3) and for the most common 

sagebrush species, Wyoming big sagebrush (Still and Richardson 2015).

The Science Framework uses an approach for prioritizing areas for management 

and determining effective management strategies that is based on ecosystem resilience to disturbance and resistance to invasive species. Resilient ecosystems have 

the capacity to reorganize and regain their basic characteristics when altered by 

stressors such as invasive plant species and disturbances such as improper livestock 

grazing and altered fire regimes (Holling 1973). Ecosystems that are resistant to 

invasion by nonnative plants have attributes that limit the establishment and expansion of the invader (D’Antonio and Thomsen 2004). Management focused on 

ecosystem resilience and resistance can help sustain local communities by ensuring 

that ecosystem services, such as water for consumer and agricultural use, forage for 

livestock, and recreational opportunities are maintained or improved over time. The 

resilience of socio-economic systems, threats to those systems, and current capacities to implement management actions to address those threats is a separate aspect 

of developing an approach for conservation and restoration of the sagebrush biome 

that will be addressed in other venues.

The approach used in the Science Framework is intended to help prioritize areas 

for management and determine the most appropriate management strategies. The 

Science Framework is based on: (1) the likely response of an area to disturbance or 

stress due to threats and/or management actions (i.e., resilience to disturbance and 

resistance to invasion by nonnative plants), (2) the capacity of an area to support 

target species and/or resources, and (3) the predominant threats. It uses a mid-scale 

approach and has six steps.

 1. Identify focal species or resources and key habitat indicators for the 

assessment area, and then delineate their distribution or area using the best 

information available. For GRSG, this currently includes the recently modeled 

breeding habitat probabilities and the population index (Doherty et al. 2016). 

Information and tools are provided to allow managers to address other resource 

values and at-risk species as geospatial data for those values and species 

become available.

 2. Develop an understanding of ecosystem resilience and resistance for the 

assessment area. At landscape scales, the resilience and resistance of sagebrush 
USDA Forest Service RMRS-GTR-360. 2017. 3

ecological types are closely linked to soil temperature and moisture regimes 

(Chambers et al. 2014a,b), and soil temperature and moisture regimes are 

used to quantify and map resilience and resistance (Appendix 2; Maestas et al. 

2016a). More detailed information on soil characteristics and ecological site 

descriptions assist managers to step-down generalized vegetation dynamics, 

including resilience and resistance concepts, to local scales.

3. Integrate ecosystem resilience and resistance with species or resource habitat 

requirements and develop a decision matrix that can be used to spatially link 

ecosystem resilience and resistance, habitat requirements, and management 

strategies.

4. Assess the key threats in the assessment area using geospatial data and maps.

5. Prioritize areas for management in the assessment area using geospatial data 

and maps of species or resource habitat requirements, such as the breeding 

habitat probabilities for GRSG, resilience and resistance, and the key threats.

6. Determine the most appropriate management strategies for areas prioritized 

for management based on its habitat characteristics, relative resilience and 

resistance, and predominant threats. The management strategies are developed 

in collaboration with stakeholders and are reconciled with socio-economic and 

budgetary considerations.

These six steps help identify priority areas for management and overarching management strategies for the assessment area. To step down ecoregion/Management 

Zone priorities to the local scale, managers and stakeholders are engaged to: 

(1) refine priorities and management strategies based on higher resolution geospatial 

products, additional species information, and local knowledge (including traditional 

ecological knowledge), (2) select specific project areas, and (3) identify opportunities to leverage partner resources. The Science Framework provides methods and 

decision tools for determining the suitability of an area for management actions 

as well as the most appropriate action. Examples of the approach in the Science 

Framework are provided for three areas that support GRSG populations but differ 

in relative resilience and resistance and the dominant habitat threat: (1) east-central 

Montana, which is exhibiting cropland conversion, (2) southwestern Wyoming, 

which has wide-spread oil and gas development, and (3) northeastern Nevada, 

which is exhibiting cheatgrass (Bromus tectorum) invasion and spread at low- to 

mid-elevations, localized conifer expansion, and large wildfires.

The Science Framework—both Part 1, science basis and applications, and Part 2, 

management considerations—is intended to be adaptive and will be updated to 

highlight potential management considerations as new science and information on 

resources and focal species become available. The Western Association of Fish and 

Wildlife Agencies and U.S. Fish and Wildlife Service (FWS) have developed the 

Sagebrush Science Initiative, which has identified and prioritized science needs for 

conservation of sagebrush dependent species and allocated funding to address them. 

As information and data are compiled for these species, they will be used to inform 

the Science Framework. Future updates to the Science Framework can be further informed by the outcomes of the research conducted as part of implementation of the 

Actionable Science Plan (ASPT 2016). The State Wildlife Action Plan provides a 

resource for more detailed information for the Science Framework at the State level, 

while the Science Framework provides a resource for the State plan revisions.
4 USDA Forest Service RMRS-GTR-360. 2017.

The Sagebrush Science Initiative, with additional support from the Department of 

the Interior and the Bureau of Land Management (BLM), is developing a collaborative strategy to conserve sagebrush, sagebrush dependent species, and human uses 

of the sagebrush system that adopts the use of resistance and resilience concepts, 

threat assessments, and habitat prioritization methods described in the Science 

Framework. This strategy will identify sagebrush dependent species and associated 

habitat and vegetation types for the sagebrush biome as a whole.

To support use of the Science Framework, geospatial data, maps, and models are 

provided through the U.S. Geological Survey (USGS) ScienceBase (https://www.

sciencebase.gov/catalog/item/576bf69ce4b07657d1a26ea2) and BLM Landscape 

Approach Data Portal (https://landscape.blm.gov/geoportal/catalog/main/home.

page).

2. Use of This Document

This document is divided into four topic areas that can be used by the reader 

to gain an understanding of: (1) the background and structure of the Science 

Framework, (2) the biophysical characteristics of sagebrush ecosystems and the 

threats to sagebrush ecosystems and GRSG, (3) the key concepts and approach used 

in the Science Framework to prioritize areas for management and develop effective 

management strategies, and (4) the information used for determining appropriate 

management treatments.

Users of the document will find the background for the Science Framework as 

well as the approach, scope, and scales in Section 3. Individuals who are unfamiliar 

with the biophysical characteristics of sagebrush ecosystems and threats to sagebrush ecosystems and GRSG can access that information in Sections 4 and 5, respectively. Those who are familiar with sagebrush ecosystems and their threats, but 

lack an understanding of resilience to disturbance and resistance to invasive annual 

grasses can obtain that information in Section 6. The key elements of the approach 

used in the Science Framework are in Sections 7 and 8 and will be of interest to 

all users. Section 7 combines information on resilience and resistance with species 

habitat requirements to develop a spatially explicit sage-grouse habitat matrix that 

can be linked directly to management strategies for maintaining or increasing sagebrush habitat. Section 8 provides the data sources and geospatial process for delineating priority areas for management at the biome, ecoregional/Management Zone, 

and local scale. Section 9, the final section, provides information and examples for 

determining appropriate management treatments at the local scale and will be of 

general interest.

In addition to this technical document, geospatial tools and training are being developed to assist managers in implementing the resilience-based approach described 

here. Also, handbooks and guides for implementing this approach are available for 

the western portion of the sagebrush biome and may be adapted to the eastern portion of the sagebrush biome (Miller et al. 2014, 2015; Pyke et al. 2015a,b).

3. Overview of The Science Framework

3.1 Background

Sagebrush ecosystems are among the largest and most imperiled ecosystems in 

North America (Noss et al. 1995). Sage-grouse and more than 350 other vertebrate 
USDA Forest Service RMRS-GTR-360. 2017. 5

species rely on sagebrush ecosystems (Suring et al. 2005a). These ecosystems now 

comprise only about 59 percent of their historical area and the primary patterns, 

processes, and many components of these systems have been significantly altered 

since Euro-American settlement in the mid-1800s (Knick et al. 2011; Miller et al. 

2011a). In 2010, the FWS determined that GRSG, a sagebrush obligate species, was 

warranted for listing under the Endangered Species Act, but listing was precluded 

by higher priority actions (FWS 2010). The concern over sagebrush habitats and the 

potential for listing resulted in major changes to Federal and State land management 

plans and new management direction and actions to address current threats to sagebrush ecosystems and GRSG (FWS 2015). In September 2015, the FWS determined 

that GRSG did not warrant protection under the Endangered Species Act due to 

ongoing conservation and restoration efforts, but that its status would be reevaluated 

in 2020 (FWS 2015).

Two types of threats impact sagebrush ecosystems and sagebrush obligate species. 

Persistent ecosystem threats include the spread of nonnative invasive plant species, 

altered fire regimes, conifer expansion, and climate change (Knick et al. 2011; 

Miller et al. 2011a). (See Appendix 1 for definitions used in this report.) These types 

of threats are difficult to regulate and are managed using ecologically based approaches (Boyd et al. 2014a; Evans et al. 2013). In contrast, threats due to land uses 

and development include cropland conversion, energy development, mining, roads 

and other infrastructure, urban and exurban development, recreation, wild horse and 

wild burro use, and improper livestock grazing (FWS 2013). These types of threats 

can be regulated but because of human population growth and increasing resource 

demands will likely continue to affect sagebrush ecosystems.

The two types of threats often interact with each other. For example, oil and gas 

development can increase the spread of invasive annual grasses and potential for 

wildfire, and invasive annual grasses can increase the difficulty of restoring sites 

impacted by oil and gas development (Mealor et al. 2013). Many of the threats 

from land uses and development have been the subject of detailed assessments or 

reviews in recent years (see Hanser et al. 2011; Knick and Connelly 2011; Knick et 

al. 2011; Manier et al. 2011; Wisdom et al. 2005). The Science Framework focuses 

on persistent ecosystem threats and the secondary effects of land use and development threats on ecosystems such as reduced ecosystem functioning and landscape 

connectivity. Importantly, the same types of ecologically based approaches used 

to manage the detrimental effects of persistent ecosystem threats can be used to 

promote avoidance, minimize impacts, guide mitigation, and increase restoration 

effectiveness of habitats affected by land use and development.

Spatially explicit knowledge of how ecosystem resilience and resistance vary 

across large landscapes can provide the basis for managing threats (Chambers et 

al. 2014b, 2016a, 2017; Wisdom and Chambers 2009). Resilient ecosystems have 

the capacity to reorganize and regain their fundamental structure, processes, and 

functioning when altered by stressors such as invasive plant species and disturbances such as improper livestock grazing and altered fire regimes (Holling 1973). 

Resistant ecosystems have the capacity to retain their fundamental structure, processes, and functioning when exposed to stressors or disturbances (Folke 2004).

Resistance to invasion by nonnative plants is increasingly important in sagebrush 

ecosystems. It is a function of the abiotic and biotic attributes and ecological 

processes of an ecosystem that limits the population growth of an invading species (D’Antonio and Thomsen 2004). By identifying key indicators of the capacity 
6 USDA Forest Service RMRS-GTR-360. 2017.

of ecosystems and species to recover from disturbance and resist stressors, like 

nonnative invasive plant species, it is possible to assess and predict how native 

ecosystems and species will respond to management actions designed to mitigate 

persistent threats.

3.2 Approach

The Science Framework uses a strategic, multi-step approach (see table 1) that 

builds on those developed by two WAFWA working groups (Chambers et al. 

2014b, 2016a). The first group focused on persistent ecosystem threats, specifically invasive annual grasses, uncharacteristic wildfire, and conifer expansion in 

the western range of sagebrush and GRSG (MZs III, IV and V; Chambers et al. 

2014b). The second addressed both persistent ecosystem threats and land use and 

development threats to sagebrush ecosystems, Gunnison sage-grouse (C. minimus; 

GUSG), and GRSG in the eastern portion of its range (MZs I, II, and VII; Chambers 

et al. 2016a). The approach developed for the western portion of the range was 

subsequently incorporated into the “Greater Sage-Grouse Wildfire, Invasive Annual 

Grasses, and Conifer Expansion Assessment” (BLM 2014), which served as the 

basis for a multi-year program of work by the BLM in the Great Basin. The Science 

Framework updates the two previous efforts and incorporates areas that were not 

previously addressed, such as the Columbia Plateau (MZ VI). To support future 

assessments related to the Science Framework, geospatial data, maps, and models 

are provided through the USGS ScienceBase (https://www.sciencebase.gov/catalog/

item/576bf69ce4b07657d1a26ea2) and BLM Landscape Approach Data Portal 

(https://landscape.blm.gov/geoportal/catalog/main/home.page).

3.3 Scope and Scales

The Science Framework focuses on sagebrush ecosystems and GRSG. Updates 

to the Science Framework will include additional species and values as biome-wide 

and other data become more available. For example, the WAFWA-coordinated 

Sagebrush Science Initiative will identify sagebrush dependent species and associated habitat or vegetation types for the sagebrush biome as a whole. Information and 

data compiled for these species will be used to inform the Science Framework.

The Science Framework provides a cross-walk between EPA ecoregions (EPA 

2016) and sage-grouse Management Zones (Stiver et al. 2006) (fig. 1). The sagebrush biome encompasses four Level II and thirteen Level III ecoregions (fig. 1; 

EPA 2016). The seven Management Zones are based largely on ecoregional differences and provide a common basis for GRSG management within the sagebrush 

biome (fig. 1). Distinct differences in the type and extent of sagebrush habitat, 

persistent ecosystem threats, resilience to disturbance, and resistance to invasive 

plant species exist across the sagebrush biome and are reflected in the different 

ecoregions. These differences influence management strategies both within and 

among ecoregions.

This Science Framework uses a multi-scale approach that includes the sagebrush 

biome, ecoregions and Management Zones, and local land planning areas (table 2). 
USDA Forest Service RMRS-GTR-360. 2017. 7

Table 1—Components of a strategic, multi-scale approach for managing threats to sagebrush ecosystems, sagegrouse, and other sagebrush obligate species.

Process steps Description

1.0 Identify focal species and key habitat indicators

1.1 Identify focal species Native species whose spatial, compositional, and 

functional requirements are representative of the needs of 

a larger set of species

1.2 Determine the habitat characteristics needed 

to support persistent populations 

Landscape-scale indicators of habitat suitability such as 

climate, landform, vegetation, and degree of disturbance

2.0 Develop an understanding of ecosystem resilience and resistance for the planning area

2.1 Determine biophysical indicators of 

ecosystem processes

Landscape-scale indicators of potential ecosystem 

response to stress and disturbance and to invasive plants 

such as temperature and moisture regimes and 

ecosystem productivity 

3.0 Integrate resilience and resistance with species habitat requirements

3.1 Develop a habitat matrix that links resilience 

and resistance with species habitat 

characteristics

A matrix that can be used to spatially link ecosystem 

response to stress and disturbance, species habitats, and 

management actions

3.2. Determine appropriate management 

strategies and link the strategies to matrix 

cells

Management strategies that are related to different levels 

of ecosystem resilience and resistance and habitat 

probabilities

3.3. Evaluate the spatial relationships between 

resilience and resistance and species habitat 

characteristics

Maps and geospatial data that illustrate and quantify the 

relationships between resilience and resistance indicators 

and species habitat characteristics

4.0 Assess dominant threats

4.1 Incorporate dominant stressors and 

disturbances

Maps and data that illustrate and quantify stressors and 

disturbances such as land use and development, invasive 

species, wildfire, and conifer expansion

5.0 Prioritize areas for management 

5.1 Use available species data or models to help 

identify habitats for targeted management 

within ecoregions/ management zones

Information on focal species, such as distribution and 

abundance, that can be used to identify stronghold or 

connectivity areas needed to support persistent 

populations

5.2 Prioritize areas for targeted management 

based on species information, relative 

resilience and resistance, and threats

Maps and data that overlay species information with 

information on resilience and resistance to dominant 

threats to assess risks and target efforts

6.0 Determine the most appropriate management strategies and treatments

6.1. Managers and stakeholders select 

appropriate management strategies for 

priority areas at mid- to local scales based 

on species information and resilience to 

threats

Management strategies that consist of coordinated 

management activities conducted at mid- to local scales 

to achieve landscape-scale vegetation and habitat 

objectives, such as strategically locating firefighting 

resources

6.2. Managers and stakeholders select project 

areas and treatments at the local scale for 

priority areas based on species information, 

resilience and resistance, and threats

Treatments or management actions conducted at local 

scales that directly manipulate vegetation to achieve a 

vegetation or habitat objective

6.3. Implement monitoring to evaluate and adapt 

management actions

Monitoring data for both ecosystem and species 

responses to threats and management actions that can 

be used in an adaptive management framework
8 USDA Forest Service RMRS-GTR-360. 2017.

This approach aligns with the Sage-Grouse Habitat Assessment Framework (Stiver 

et al. 2015) and Johnson’s (1980) orders of habitat selection. The sagebrush biome 

approximates GRSG species range (1st order), ecoregions and Management Zones 

provide population relevant information (2nd order), and local planning areas inform 

decisions regarding seasonal habitats (3rd and 4th order). Data, models, and tools 

from a variety of partners (e.g., U.S. Forest Service [USFS], Natural Resources 

Conservation Service [NRCS], WAFWA, non-governmental organizations [NGOs], 

States, and USDOI bureaus including USGS, BLM, and FWS) are available for use 

at each scale. The data, models, and tools are specific to the different scales, but are additive from the sagebrush biome scale to the local land planning area scale. For example, 

habitat data available at the biome scale, such as landscape cover of sagebrush, is 

also relevant at the ecoregion and Management Zone scale, but higher resolution or 

more detailed data may further inform ecoregional assessments. Similarly, data from 

ecoregional scales are relevant at local planning area scales, but higher resolution or 

more detailed data may be available from planning area assessments or monitoring.

Figure 1—A cross-walk between Level II and Level III Ecoregions (EPA 2016) 

and sage-grouse Management Zones (MZs; Stiver et al. 2006). 
USDA Forest Service RMRS-GTR-360. 2017. 9

The three scales inform different aspects of the planning process (table 2). 

Prioritizations of areas for management actions are typically conducted at the 

mid-scale (individual or multiple ecoregions and Management Zones) because 

of similarities in environmental characteristics, ecosystem threats, and management strategies. At the sagebrush biome scale, such ecoregional and Management 

Zone assessments are used to inform budget prioritization within USDOI and help 

ensure rangewide consistency in allocating funds. At the local scale, local data and 

expertise are used to select project sites and determine appropriate management 

strategies and treatments within areas prioritized for management. In this document, 

management strategies are coordinated management activities conducted at mid- to 

local scales to achieve vegetation and habitat objectives (e.g., strategically locating 

firefighting resources to protect habitat, coordinating Early Detection and Rapid 

Response (EDRR) activities for invasive plant species, or positioning treatments to 

increase habitat connectivity). Treatments are local scale management actions that 

directly manipulate vegetation to achieve a vegetation or habitat objective (e.g., 

conifer removal, invasive annual grass control, fuel treatment, or seeding efforts).

Table 2—Scales and areas included in the strategic approach for managing threats to sagebrush ecosystems, sagegrouse, and other sagebrush obligate species and the data, tools, models, and processes considered at each scale

or area.

Area Geographic 

scale

Map extent Data, Tools, Models Process

Sagebrush biome and 

multiple Management 

Zones

Broad West-wide

Habitat 

Soils 

Population data and models 

Priority resource data 

Fire and other threat data 

Climate change projections 

 

Budget prioritization 

within DOI 

for rangewide consistency

Sage-grouse 

Management Zones 

and ecoregions

Mid State or 

National 

Forest

Above, plus

Assessments and planning 

docs 

Regional data and models 

Regional tools

Assessments at 

ecoregion/MZ scales

for

prioritization of 

management actions

Local planning areas Local District, Field

Office, 

or Project Area 

Above, plus

Local data and information

Selection of treatment types 

within prioritized project 

areas

Assessments at

coregion/MZ 

for

rioritization of 

anagement 
10 USDA Forest Service RMRS-GTR-360. 2017.

4. Climatic Regimes and Vegetation Types in the 

Sagebrush Biome

In the Science Framework, level II and level III EPA ecoregions are used as the 

basis for describing the differences in climatic regimes, dominant landforms and 

elevation ranges, and soil temperature and moisture regimes among ecoregions and 

Management zones (fig. 1; table 3). An understanding of these differences can help 

inform biome to mid-scale prioritizations and management strategies.

The ecoregions are characterized by distinct temperature and precipitation regimes (fig. 2) and differ in the amount of precipitation received in winter versus 

summer (fig. 3). In the western portion of the sagebrush biome most precipitation 

arrives as winter snow and rain. In contrast, in the eastern portion of the biome 

as much as 30 to 50 percent of the annual precipitation arrives during the summer months of July, August, and September (fig. 3). These differences, especially 

when coupled with total amount of precipitation, influence both plant functional 

type dominance (Lauenroth et al. 2014; Sala et al. 1997) and competitive interactions with invasive species such as cheatgrass (Bromus tectorum) and field brome 

(B. arvensis, formerly B. japonicus) (Bradford and Lauenroth 2006).

The amount of precipitation that is received during the period when temperature, 

and thus potential evapotranspiration, is low influences the amount of water stored 

in deep soil layers and therefore the balance between woody and herbaceous species (Lauenroth et al. 2014; Sala et al. 1997). Areas that receive more winter and 

spring precipitation typically have greater deep soil water storage and are dominated 

by woody species, such as sagebrush, which are more effective at using deep soil 

water (figs. 4a,b). In contrast, areas that receive predominantly summer precipitation are typically dominated by grasses. Also, seasonality of precipitation during 

the period when temperatures are favorable for plant growth is an important control 

on the balance between C3 and C4 species (cool and warm season with different 

photosynthetic pathways). C3 species such as wheatgrasses (e.g., Pascopyrum, 

Pseudoroegnaria, and Elymus spp.) dominate in areas with cool, wet springs and 

C4 species such as grama grasses (Bouteloua spp.) dominate in areas with warm, 

wet summers (Paruelo and Lauenroth 1996; Sala et al. 1997). These differences 

are reflected in the landscape cover of sagebrush. Most of the western portion of 

the sagebrush biome is characterized by sagebrush-dominated systems, while the 

West-central Semiarid Prairies are characterized by grass-dominated systems with 

sagebrush components (fig. 5).

Resistance to Bromus species and many other cool-season invaders generally 

increases as summer precipitation and amount of precipitation increase (fig. 4c) as 

a function of higher perennial grass productivity and dominance. This appears to be 

due to less favorable conditions for establishment of annual species like cheatgrass 

and strong competition from perennial native grass species that dominate under this 

precipitation regime (Bradford and Lauenroth 2006; Bradley 2009). However, even 

in this competitive environment, disturbances that remove perennial native grass 

cover often facilitate establishment of invasive annual grasses and other invasive 

plant species, especially when productivity is low (fig. 4c; Bradford and Lauenroth 

2006; Knight et al. 2014; Lauenroth et al. 2014).
USDA Forest Service RMRS-GTR-360. 2017. 111	 Table 3—Environmental characteristics of the Level III Ecoregions based on Griffith (2010). Temperature range (°F) Frost-free days Precipitation range (in) Dominant landforms Elevation range (ft) Soil temperature regime Soil moisture regime Cold Deserts Columbia Plateau 45 to 54 70 to 190 6 to 24 Tableland, plateaus, hills 197 to 4,921 – – Northern Basin and Range 41 to 48 30 to 140 6 to 39 Tableland, mountains, basins, valleys 2,625 to 9,845 Frigid, Mesic Xeric, Aridic Snake River Plain 42 to 50 50 to 170 4 to 26 Mountains, basins, valleys 2,100 to 6,450 Mesic Xeric, Aridic Central Basin and Range 36 to 57 15 to 200 4 to 39 Mountains, basins, valleys 3,346 to 13,120 Frigid, Mesic Xeric, Aridic Wyoming Basins 32 to 46 30 to 130 5 to 20 Intermontane basins 4,000 to 9,450 Frigid, Mesic Aridic-ustic Colorado Plateau 41 to 59 50 to 220 5 to 32 Tableland 2,950 to 9,840 Frigid, Mesic Aridic-ustic Western Cordillera E. Cascades Slopes and Foothills 36 to 52 10 to 140 20 to 138 Mountains, plateaus 984 to 8,202 Cryic to Mesic Mostly Xeric Idaho Batholith 28 to 46 30 to 140 8 to 60 Mountainous plateau – Cryic, Frigid Udic, Xeric Blue Mountains 30 to 50 30 to 160 9 to 80 Mountains and foothills 1,000 to 9,843 Cryic to Mesic Udic, Xeric Wasatch and Uintah Mtns 28 to 46 40 to 200 6 to 55 Mountains, plateaus 4,790 to 13,527 Cryic to Mesic Udic, Xeric, Aridic Middle Rockies 23 to 46 25 to 140 12 to 98 High mountains and foothills – Cryic, Frigid Udic, Ustic Southern Rockies 25 to 52 25 to 150 10 to 69 High mountains and foothills 5,085 to 14,403 Cryic, Frigid Udic, Ustic Northwestern Great Plains West-Central Semiarid Prairies 37 to 47 – 10 to 21 Plains – Frigid Ustic Northwestern Glaciated Plains 37 to 45 95 to 170 10 to 22 Plains – Frigid, Mesic Ustic, Aridic
12 USDA Forest Service RMRS-GTR-360. 2017.

Figure 2—The 30-year normal annual values for (A) precipitation and (B) temperature 

(PRISM 2016) across ecoregions and management zones.
USDA Forest Service RMRS-GTR-360. 2017. 13

Figure 3—Percentage of annual precipitation occurring during the months of 

July, August, and September (PRISM 2016). The amount and timing of precipitation affects plant dominance (shrubs vs. grasses) and interactions between 

native and invasive plants.

Soil climate regimes (temperature and moisture) integrate several different climate variables including mean annual temperature and precipitation and seasonality 

of precipitation, thus providing a means of assessing climatic differences among 

ecoregions and effects on vegetation. These regimes are mapped as part of the 

National Cooperative Soil Survey (NRCS 2013) and can be used in large-scale analyses (Maestas et al. 2016a). See Appendix 2 for an explanation of soil temperature 

and moisture regimes. The soil temperature and moisture regimes that characterize 

sagebrush ecosystems vary due to the large latitudinal differences and elevation 

gradients that the area encompasses as well as the variation in seasonality of precipitation (fig. 6). As with most large-scale mapping products, there are limitations 

in using the NRCS soil survey information including incongruities in soil regime 

classifications, especially along mapping boundaries, and variations in the level 

of survey detail available. However, areas with incongruities represent a relatively 

minor component of the data set and have been taken into account in this report. 
14 USDA Forest Service RMRS-GTR-360. 2017.

Figure 4—Changes in soil water storage, life form dominance, and resistance to annual 

Bromus as seasonality of precipitation transitions from primarily summer to winter. (A) Soil 

water storage increases as winter/spring precipitation and snow water equivalent increase 

and these changes are relatively greater for areas with relatively high precipitation and low 

temperature. (B) Landscape dominance of grasses is highest with primarily summer precipitation; shrub dominance is greatest with primarily winter/spring precipitation. (C) Resistance 

to Bromus is higher in areas where soil water storage is low and grasses dominate largely 

due to strong resource competition. Decreases in effective precipitation can increase resource fluctuations and lower resistance to Bromus. At more local scales, resistance also is 

influenced by nutrient availability and disturbance (figure from Chambers et al. 2016b).

Until improved products are developed, the Web Soil Survey (http://websoilsurvey.

nrcs.usda.gov/app/WebSoilSurvey.aspx) provides access to the most complete data 

set across the biome for understanding ecosystem response to both disturbances and 

management treatments. Project level planning based on resilience and resistance 

concepts can be further informed by local climate and soils data.

4.1 West-Central Semiarid Prairies Ecoregions

West-Central Semiarid Prairies include the Northwestern Glaciated Plains in 

northern Montana and the Northwestern Great Plains in the west and central 

Dakotas, southeast Montana, and northeast Wyoming (fig. 1; Griffith 2010). The 

Northwestern Glaciated Plains are comprised of rolling hills and gentle plains mantled by glacial till, outwash, and glaciolacustrine sediments. The Northwestern Great 

Plains were not glaciated and have rolling plains of shale and sandstone punctuated 

by occasional buttes. The West-Central Semiarid Prairie Ecoregion has a mostly dry, 

mid-latitude climate and is characterized by warm to hot summers and cold winters 

(Griffith 2010; table 3). In the Northwestern Glaciated Plains soil temperature and 

moisture regimes are predominantly cool (frigid) and summer-moist (ustic), respectively, but in the Northwestern Great Plains both cool (frigid) and warm (mesic) soil 

temperature regimes and summer-moist bordering on dry (ustic bordering on aridic) 

soil moisture regimes are typical (fig. 6).
USDA Forest Service RMRS-GTR-360. 2017. 15

Figure 5—Landscape cover of sagebrush-dominated ecological systems and grassdominated ecological systems with sagebrush components (USGS 2014). The western 

portion is characterized by sagebrush-dominated systems, and the eastern portion is 

characterized by grass-dominated systems with sagebrush components. 

Climate patterns in the eastern portion of the Northwestern Great Plains favor 

grassland communities. Sagebrush species include silver sagebrush (A. cana

spp. cana), Wyoming big sagebrush (A. tridentata ssp. wyomingensis), fringed 

sagewort (A. frigida), and basin big sagebrush (A. t. ssp. tridentata) (Miller et al. 

2011a; USGS 2013). Dominant grasses include wheatgrasses (Pascopyrum smithii,

Pseudoroegnaria spicata, and Elymus spp.), grama grasses (Bouteloua spp.), bluestem species (Andropogon gerardii, Schizachyrium scoparium), and needlegrasses 

(Hesperostipa spp., Nasella spp., and Achnatherum spp.). These grasses vary widely 

in relative abundance in response to climate, drought conditions, and grazing pressure (Barker and Whitman 1988).
16 USDA Forest Service RMRS-GTR-360. 2017.

4.2 Cold Deserts Ecoregions in the Eastern Part of the 

Sagebrush Biome

The Cold Deserts in the eastern part of the sagebrush biome and GRSG range 

include the Wyoming Basin in the western and central portions of Wyoming, and 

the Colorado Plateau in eastern and southern Utah and western Colorado (fig. 1). 

The Wyoming Basin is a broad, intermontane basin that ranges in elevation from 

about 4,000 ft to 9,450 ft (1,220 m to 2,850 m) and is characterized by sedimentary 

landforms and variable topography, while the Colorado Plateau is deeply dissected 

tableland comprised of sedimentary rock that ranges from about 2,950 ft to over 

9,840 ft (900 m to over 3,000 m) (Griffith 2010; table 3). The Cold Deserts ecoregion in general has a continental climate with warm to hot and dry summers and 

cool to cold and wet winters. The large topographic gradients in the Wyoming Basin 

Figure 6—Soil temperature and moisture regimes by soil moisture subclass. 

See Appendix 2 for an explanation of the soil temperature and moisture regime data used in this report. The area near the border between southeastern 

Montana and northeastern Wyoming is in a transition zone between the frigid 

and mesic soil temperature regimes, which resulted in an apparent abrupt 

change in temperature regime at the State border. Future updates to soil 

survey information will resolve these boundary issues along State lines, using 

current climate datasets and additional field data.
USDA Forest Service RMRS-GTR-360. 2017. 17

and Colorado Plateau result in considerable variation in mean annual temperature 

and precipitation but the Colorado Plateau is generally warmer (table 3). Cool and warm 

(frigid and mesic) soil temperature regimes and dry and summer moist (aridic and ustic) 

soil moisture regimes occur in the Cold Deserts ecoregion (fig. 6; table 3).

Vegetation is characterized largely by arid to semiarid shrublands that transition 

from zero to a few warm season grass species west of the Continental Divide, to 

warm season grasses as a major component east of the Continental Divide (Griffith 

2010). Sagebrush types vary along soil temperature and moisture gradients; lower 

elevation sagebrush types are dominated by Wyoming big sagebrush. Black 

sagebrush (A. nova) occurs on windswept ridges and in areas with shallow soils 

while early sagebrush (A. arbuscula ssp. longiloba) occurs on sites with higher 

clay content. Basin big sagebrush is found in areas with deeper soils and higher 

available soil moisture across the region, as is silver sagebrush in eastern portions 

of the Wyoming Basin. In ecotones between Cold Deserts and Western Cordillera 

Ecoregions at mid-elevations, Wyoming big sagebrush transitions into mountain big 

sagebrush (A. t. ssp. vaseyana), and at higher elevations mountain big sagebrush cooccurs with mountain shrubs (e.g., Saskatoon serviceberry [Amelanchier alnifolia], 

chokecherry (Prunus virginiana), currant (Ribes spp.), antelope bitterbrush [Purshia 

tridentata], and snowberry [Symphoricarpos spp.]). In these zones in Colorado, 

extensive areas of hybridization occur between black sagebrush and mountain 

big sagebrush, and between Wyoming big sagebrush and mountain big sagebrush 

(Monsen 2005; Winward 2004). Bunchgrasses are common and include wheatgrasses, needlegrasses, fescues (Festuca spp.), and bluegrasses (Poa spp.). Utah juniper (Juniperus osteosperma) occurs in the more arid basins in the western part of 

the ecoregion, while Rocky Mountain juniper (J. scopulorum) is common at higher 

elevations and in the east where summer precipitation is higher. In the Colorado 

Plateau two-needle piñon (Pinus edulis) codominates with Utah juniper.

4.3 Cold Deserts Ecoregions in the Western Part of the 

Sagebrush Biome

The western Cold Deserts include the Columbia Plateau in east central 

Washington and Oregon; Snake River Plain in central Idaho; Northern Basin and 

Range in southern Idaho, northern Nevada, and eastern Oregon; and the Central 

Basin and Range largely in central Nevada and western Utah (fig. 1). These ecoregions are generally characterized by mid-latitude steppe and desert climates, marked 

by warm to hot summers and cold winters (table 3; Griffith 2010). Topography 

tends to be characterized by tablelands and hills in the Columbia Plateau and by 

mountains, basins, and valleys in the other ecoregions. The variable topography 

results in large ranges in mean annual temperature and number of frost-free days 

and in mean annual precipitation (table 3; Griffith 2010). Soil temperature regimes 

range from cold (cryic) to warm (mesic) and soil moisture regimes from winter 

moist (xeric) to dry (aridic) (fig. 6; table 3).

Vegetation in the Columbia Plateau is largely arid sagebrush steppe and grassland due to the relatively high mean annual precipitation coupled with loess soils 

(Griffith 2010). Deeper soils occur in the periphery of the Columbia Plateau, but 

channeled scablands with shallow to very shallow soils that greatly influence soil 

water availability occur in different parts of the Plateau. Much of the vegetation in 

the Northern Basin and Range and Snake River Plain is typically classified as sagebrush steppe due to relatively cooler temperatures and more effective precipitation 
18 USDA Forest Service RMRS-GTR-360. 2017.

(West 1983a,b). In contrast, the Central Basin and Range is typically characterized 

by warmer and/or drier conditions and is classified as sagebrush desert (West 

1983a,b). The species of sagebrush are generally similar across these ecoregions, 

but differ along soil temperature and moisture gradients with mountain big sagebrush dominating on cool to cold sites, Wyoming big sagebrush on warm sites, and 

basin big sagebrush on warm to cool sites with deep soils (Appendix 2; Miller et al. 

2011a). Dwarf species of sagebrush that dominate on warm, gravelly soils are black 

sagebrush (A. nova); dominate species on warm, shallow soils are low sagebrush 

(A. a. spp. arbuscula) (Appendix 2; Miller et al. 2011a). Broadly distributed shrubs 

across the gradient are rabbit brushes (Chrysothamnus and Ericameria species) 

and bitterbrush. These ecoregions are dominated largely by bunchgrasses such as 

Idaho fescue (F. idahoensis), bluebunch wheatgrass (Pseudoroegneria spicata), 

needle grasses, and bluegrasses (Poa spp.). However, warm season, rhizomatous 

grasses such as James’ galleta (Pleuraphis jamesii) and sand dropseed (Sporobolus 

cryptandrus) are also relatively common in the southern part of the Central Basin 

and Range. Western juniper (J. occidentalis) occurs largely in the Columbia Plateau, 

western Snake River Plain, and western part of the Northern Basin and Range. 

Utah juniper occurs primarily in the eastern part of the Northern Basin and Range 

and in the Central Basin and Range where it co-occurs with single-leaf piñon 

(P. monophylla).

4.4 Western Cordillera Ecoregions in the Eastern Part of the 

Sagebrush Biome

The Western Cordillera includes the Middle Rockies that occur in southwestern Montana, eastern Idaho, western Wyoming, the Black Hills of western South 

Dakota and northeastern Wyoming, and the Southern Rockies which extend from 

southern Wyoming through Colorado (fig. 1; Griffith 2010). The Western Cordillera 

Ecoregion is characterized by high elevation mountains and foothills that range 

from 5,085 ft to over 14,400 ft (1,550 m to over 4,390 m), and by cool to warm 

short summers and cold winters. Mean annual temperature and precipitation vary 

greatly with elevation, but precipitation tends to be higher and temperature lower in 

the Middle Rockies than in the Southern Rockies (table 3). Soil temperature regimes 

range from cool to cold (frigid to cryic), and moisture regimes are summer moist, 

and wet and humid (ustic, udic) (fig. 6; table 3).

In the Middle and Southern Rockies, coniferous forests cover much of the 

region, with a pattern of elevational banding. The foothills are partly wooded or 

shrub dominated, and intermontane valleys are grass- and/or shrub-covered. In the 

Southern Rockies, the lowest elevations are generally grass- or shrub-covered, with 

sagebrush, mountain mahogany (Cercocarpus spp.), two-needle piñon, Utah juniper, 

or scattered Gambel oak (Quercus gambelii) woodlands (Griffith 2010). Dominant 

sagebrush species at higher elevations are mountain big sagebrush, low sagebrush, 

silver sagebrush, three-tip sage (A. tripartita) and spiked big sagebrush (A. t. ssp. 

spiciformis), and at lower elevations are Wyoming big sagebrush and black sagebrush (Knight et al. 2014; Miller et al. 2011a). Utah juniper and two-needle piñon 

occur in the lower and more arid areas in the western and southern part of the ecoregion, while Rocky Mountain juniper is common at higher elevations and latitudes. 

The Middle Rockies and Southern Rockies are characterized by many of the same 

grass species as the Cold Deserts ecoregions including wheatgrasses, needlegrasses, 

fescues, and bluegrasses.
USDA Forest Service RMRS-GTR-360. 2017. 19

4.5 Western Cordillera Ecoregions in the Western Part of the 

Sagebrush Biome

The Western Cordillera in the western sagebrush biome includes the Eastern 

Cascade Slopes and Foothills in northern California and eastern Oregon and 

Washington, North Cascades in Washington, Northern Rockies in Washington 

and Idaho, Blue Mountains in Washington, Oregon, and Idaho, Idaho Batholith 

largely in Idaho, and Wasatch and Uintah Mountains in Utah. These ecoregions are 

characterized by mountains and plateaus and mountains and foothills with midlatitude, continental climates (Griffith 2010; table 3). The Eastern Cascade Slopes 

and Foothills in northern Oregon and southern Washington, northern Rockies north 

of the Salmon River, and the Blue Mountains have a notable maritime influence 

in winter due to the presence of the Columbia River gorge and broad, low passes 

in northern Oregon and southern Washington. Precipitation and temperature are 

relatively high in the Eastern Cascade Slopes and Foothills but are lower and similar 

among the other ecoregions (table 3). Soil temperatures are generally cold (cryic) to 

warm (mesic) or cold (cryic) to cool (frigid), while soil moisture regimes are moist 

(udic) or winter moist (xeric) (fig. 6; table 3).

Coniferous forests cover much of these ecoregions, with the lower foothills and 

valleys characterized by sagebrush and grasses. The sagebrush and grass species are 

largely the same as those that occur in cold to cool soil temperatures and moist soil 

moisture regimes in the adjacent Cold Deserts of the western part of the sagebrush 

biome.

5. Threats to Sagebrush Ecosystems and 

Greater Sage-Grouse

Assessing the persistent ecosystem and land use and development threats to sagebrush ecosystems and GRSG populations (table 4) is a primary component of the 

strategic approach for the Science Framework (see table 1). The threats included in 

the Science Framework were identified in the COT Report (FWS 2013), which was 

a State and Federal interagency product. These threats are largely consistent with 

those included in: (1) the State Wildlife Action Plans, and (2) the BLM and USFS 

rangewide planning effort to address the threats identified in both the 2010 FWS 

finding of “warranted but precluded” from listing and the COT Report (FWS 2013). 

It is noteworthy that the BLM and USFS planning effort resulted in publication of 

four separate Records of Decision covering 98 separate land use plans across 11 

western States in September 2015.

 In this section, an overview of these threats is provided for sagebrush ecosystems 

and GRSG. We first focus on the interacting effects of persistent ecosystem threats 

on sagebrush ecosystems and on GRSG. Threats to the West-Central Semiarid 

Prairies ecoregion and the Cold Deserts and Western Cordillera ecoregions are discussed separately because of the differences in climatic regimes, vegetation types, 

and responses to disturbance and management treatments. The effects of climate 

change are also discussed separately to highlight new information developed for the 

sagebrush biome in the Science Framework. We later focus on the effects of land 

use and development threats on sagebrush ecosystems and GRSG. Effects of the 

different threats are discussed separately. A section is included that discusses the 

interacting effects of persistent ecosystem and development threats.
20 USDA Forest Service RMRS-GTR-360. 2017.

5.1 Persistent Ecosystem Threats: Invasive Plant Species, 

Conifer Expansion, and Altered Fire Regimes

5.1.1 Threats to the West-Central Semiarid Prairies Ecoregion (MZ I)

Herbivory, in conjunction with fire, strongly influenced historical plant community composition, structure, and productivity of the West-Central Semiarid Prairies 

(Samson and Knopf 1996). Prior to Euro-American settlement, large numbers of 

bison (Bos bison) moved nomadically through the area in response to changes in 

vegetation associated with drought, past herbivory, and fire (Bragg and Steuter 

1996). The interval between grazing episodes may have ranged from 1 to 8 years 

(Malainey and Sherriff 1996), but the impacts of these herds on the vegetation, 

soils, and riparian areas were probably extensive. Also, the mixed and short-grass 

prairies comprising the West-Central Semiarid Prairies may have supported the 

Table 4—List of persistent ecosystem threats and land use and development threats to 

sagebrush ecosystems and Greater sage-grouse and associated management objectives. 

The threats are based on the Greater Sage-Grouse Conservation Objectives: Final Report 

(FWS 2013) and the Greater Sage-Grouse Monitoring Framework (IGSDMS 2014).

Threats Management objective

Isolated or small population size of 

Greater sage-grouse

Landscape connectivity and resilient populations 

Weeds and invasive grasses Minimal weeds

Conifer expansion Conifer reduction where appropriate to support 

sagebrush dependent species

Altered fire regimes Fire regimes/sizes in historic range of variability

Sagebrush elimination Sagebrush land cover sufficient to support 

sagebrush dependent species

Climate change Effective adaptation

Cropland conversion Low fragmentation

Energy development Low fragmentation 

Mining Low fragmentation 

Urban and exurban development Low fragmentation 

Recreation Little to no impact

Infrastructure Low impact disturbance

Livestock grazing Meets identified vegetation standards

Wild horses and burros Managed within established appropriate 

management levels (AML)
USDA Forest Service RMRS-GTR-360. 2017. 21

highest densities of black-tailed prairie dogs (Cynomys ludovicianus) in the prairie 

ecoregions (Knopf 1996). Rocky Mountain locusts (Melanoplus spretus), which 

became functionally extinct by 1900, often erupted in swarms numbering in the billions and their impact on vegetation was presumed to be extensive (Lockwood and 

DeBrey 1990).

Climate extremes also played an important role in structuring the composition of 

plant communities in this ecoregion, and resulted in temporal changes in the dominant graminoid species (e.g., shifts from western wheatgrass [Pascopyrum smithii] 

to blue grama [Bouteloua gracilis]; Bragg and Steuter 1996). Large fires often 

occurred, but fire regimes were probably highly variable depending on rainfall and 

subsequent grass growth (Bukowski and Baker 2013; Umbanhowar 1996). Because 

fire temporarily removed much of the above-ground vegetation, continual shifts in 

the abundance and distribution of herbivores across large areas occurred with the direction and extent of vegetation response mediated by drought and grazing by bison 

and/or locusts (Umbanhowar 1996).

Euro-American settlement had profound impacts on the West-Central Semiarid 

Prairies. Prior to settlement, fire coupled with herbivory was an integral component 

of natural landscape dynamics and likely limited expansion of shrub communities, including sagebrush. Following Euro-American settlement, land use and 

development resulted in changes in vegetation patterns on the landscape. The 

extent and distribution of fires was reduced and shrub abundance likely increased 

(Umbanhowar 1996). Although numerous fires burned in this ecoregion in the past 

15 years (fig. 7), most large fires were within conifer dominated areas and outside 

of GRSG Priority Areas for Conservation (PACs) (Marco Perea, BLM, personal 

communication).

After Euro-American settlement, managed domestic livestock (mostly cattle) 

largely replaced the native herbivores and their effects on grassland habitats are 

different in both scale and duration (Umbanhowar 1996). A high proportion of the 

area was converted from native prairie to cropland (tilled agriculture). Much of this 

development occurred on sites with more productive (resilient) soils and temperature regimes. However, a number of homesteads were filed on lands not suitable for 

non-irrigated agricultural development. Following the severe drought (“dust bowl”) 

years of the 1930s, portions of the area were reacquired by the Federal government under The Bankhead Jones Farm Tenant Act (Public Law 75-210, 1937, as 

amended). The Bankhead Jones Act included provisions for developing a land conservation and utilization program, through purchase of land considered submarginal 

for cropland, and using this land for purposes to which it was better suited (Maddox 

1937). Under management of USDA, conservation measures were taken to restore 

water and soil resources that included planting nonnative grass species. Several 

introduced seeded species became widely naturalized including crested wheatgrass (A. cristatum) (Lesica and Deluca 1996). More recently, other introduced 

seeded species such as sweet clover (Melilotus officinalis), Kentucky bluegrass 

(P. pratensis), smooth brome (B. inermis), and timothy (Phleum pratense), as well 

as nonnative invasive plants such as annual bromes and leafy spurge (Euphorbia

esula), have altered native communities. Climate change and land use and development in the ecoregion may further exacerbate effects of these species on sagebrush 

communities.
22 USDA Forest Service RMRS-GTR-360. 2017.

5.1.2 Threats to the Cold Deserts and Western Cordillera Ecoregions 

(MZs II to VII)

Euro-American arrival in the mid-1800s initiated a series of changes in vegetation composition and structure in the Cold Deserts that had cumulative effects on 

sagebrush habitats. Native American land use practices, including burning, were 

curtailed and new land uses and management activities were introduced such as 

livestock grazing, sagebrush removal, mining and road building, and fire suppression (Morris and Rowe 2014; Romme et al. 2009).

Improper grazing by livestock led to a decrease in native perennial grasses and 

forbs across much of the area (Miller and Eddleman 2001; Miller et al. 2011a). 

Decreased competition from perennial herbaceous species coupled with fire suppression resulted in increases in shrub abundance (primarily Artemisia species) in 

many areas (Miller and Eddleman 2001). These factors as well as favorable conditions for juniper and piñon pine establishment at the beginning of the twentieth 

century also resulted in increases in juniper and piñon pine at mid-elevations (Baker 

2011; Miller et al. 2008, 2011a, 2013; Romme et al. 2009).

Figure 7—Perimeters of fires that have occurred since 2000. Data for fires 

larger than 1,000 acres are from MTBS (2014) and data for fires smaller than 

1,000 acres are from GeoMAC (2015). 
USDA Forest Service RMRS-GTR-360. 2017. 23

Invasive annual grasses (e.g., cheatgrass and field brome) were introduced from 

Eurasia in the late 1800s and spread into low- to mid-elevation ecosystems that had 

depleted understories due to improper grazing or were disturbed by anthropogenic 

development (Knapp 1996; Knight et al. 2014; Mealor et al. 2013; Pyke et al. 2016). 

The invasive annual grasses increased the amount and continuity of fine fuels in 

lower elevation sagebrush habitats and initiated annual grass/fire cycles characterized by shortened fire return intervals and larger, more contiguous fires (fig. 8; 

Brooks et al. 2004; D’Antonio and Vitousek 1992). A reduction in fire-free intervals 

prevented establishment and persistence of fire intolerant species like sagebrush in 

many of these lower elevation habitats (Miller et al. 2013).

Annual grass/fire cycles are most problematic in the western part of the sagebrush 

biome (Brooks et al. 2015). Cheatgrass and other invasive annuals now dominate 

at least 6 percent (650,000 km2

) of the central Great Basin (Balch et al. 2013) and 

have the potential to spread across many of the remaining low- to mid-elevation 

sagebrush ecosystems in the western part of the sagebrush biome. For example, 

Suring et al. (2005b) determined that approximately 58 percent of the combined 

sagebrush cover types in the Great Basin were at moderate to high risk of displacement by cheatgrass.

In the eastern part of the sagebrush biome, conversion to invasive annual grasses 

is a rapidly emerging problem (Baker 2011; Brooks et al. 2015; Mealor et al. 

2012). These grasses increase with wildfire in both the Wyoming Basin (Knight 

et al. 2014) and Colorado Plateau, particularly in the eastern portion (Floyd et al. 

2006; Shinneman and Baker 2009a). On sites with oil and gas drilling and mining 

A

Figure 8—(A) A wildfire that burned through a Wyoming big 

sagebrush ecosystem with an invasive annual grass understory in southern Idaho (photo by Douglas J. Shinneman). 

(B) A wildfire that started in invasive annual grass adjacent 

to a railroad track and burned upslope into a mountain 

big sagebrush and Jeffrey pine ecosystem in northeast 

Nevada. (C) A big sagebrush ecosystem that has converted 

to invasive annual grass in north central Nevada (photos B 

and C by Nolan E. Preece). 

B

C
24 USDA Forest Service RMRS-GTR-360. 2017.

disturbances, invasive annual grasses and a host of other annual invaders typically increase at the expense of native species diversity and cover (fig. 9; Allen 

and Knight 1984; Bergquist et al. 2007). Also, vegetation management treatments 

designed to reduce Wyoming big sagebrush density and increase understory grasses 

and forbs often result in increases in invasive annuals grasses if these species are 

already present (Beck et al. 2012; Chambers et al. 2014c) and slow recovery of 

sagebrush canopy cover (Hess and Beck 2012a).

Localized expansion of juniper and piñon pine trees into sagebrush types at mid to 

high elevations is reducing the grass, forb, and shrub species associated with these 

types (figs. 10, 11; Miller et al. 2008, 2011, 2013; Romme et al. 2009). Over the 

past 150 years, juniper and piñon have exhibited range expansions and stand infilling due to factors such as favorable climate periods for tree establishment, increases 

in atmospheric CO2, fire suppression, and livestock grazing (Miller et al. 2011a; 

Miller et al. 2013; Romme et al. 2009). Also, in areas where Euro-American settlers 

heavily used juniper and piñon for mining, home structures, fuel, and fencing, natural regeneration has occurred (Miller et al. 2013; Morris and Rowe 2014). Ongoing 

infill of trees is increasing woody fuels, but is also reducing fine fuels (grasses and 

Figure 9—Annual invasive species established on disturbed sites 

in Wyoming: (A) cheatgrass (Bromus tectorum) and (B) saltlover 

(Halogeton glomeratatus) (photos by Kenneth F. Henke).

B

A
USDA Forest Service RMRS-GTR-360. 2017. 25

Figure 10—Landscape cover of conifer-dominated ecological systems (USGS 2014). 

Conifer-dominated systems with little or no sagebrush are differentiated from those with 

the potential to expand into sagebrush-dominated systems (IGSDMS 2014).

forbs), and resulting in less frequent fires in many mid- to high-elevation sagebrush 

communities (Miller et al. 2013). Extreme burning conditions (high winds, high 

temperatures, and low relative humidity) in high density (Phase III) stands are 

resulting in large and severe fires that result in significant losses of above- and 

below-ground organic matter (sensu Keeley 2009) and may have detrimental ecosystem effects (fig. 12; Miller et al. 2013). Based on tree-ring analyses at sites in 

the Northern Basin and Range, Snake River Plain and Central Basin and Range, it 

is estimated that the extent of juniper and/or piñon woodland increased two- to sixfold since Anglo-American settlement (Miller et al. 2008). Areas with substantial 

increases may exhibit canopy closure within the next 50 years (Miller et al. 2008). 

In the eastern part of the biome, juniper and piñon expansion is a more localized issue. For example, infill of persistent woodlands and wooded shrublands and expansion of juniper and piñon into shrublands have been documented for portions of the 

Uncompahgre Plateau and Mesa Verde in southwestern Colorado (Eisenhart 2004; 

Floyd et al. 2004, 2006; Shinneman and Baker 2009b).
26 USDA Forest Service RMRS-GTR-360. 2017.

Figure 11—(A) Expansion of Utah juniper trees into a mountain big 

sagebrush ecosystem in east central Utah. (B) Progressive infilling of 

the trees is resulting in exclusion of native understory species such as 

sagebrush (photos by Bruce A. Roundy). 

B

A

Warmer temperatures may be increasing the risk of invasive annual grasses and 

wildfire in both the western and eastern part of the biome (fig. 7; Bradley et al. 

2016; Brooks et al. 2015; Littell et al. 2009). Shorter fire rotations caused by interactions with cheatgrass and other fire prone invasives in portions of the Colorado 

Plateau are leading to a net decline of juniper and piñon cover compared to their 

historical extent (Arendt and Baker 2013). For example, in southwestern Colorado 

in Mesa Verde National Park, a greater proportion of the juniper and piñon woodland burned in the decade between 1995 and 2005 than had burned throughout the 

previous 200 years (Floyd et al. 2006). Those stands that had sparse understories 

prior to burning are now dominated largely by cheatgrass and other annual invaders 

(Floyd et al. 2006). Also, severe drought-induced dieback has resulted in up to 90 

percent mortality of piñon in portions of the Southwest (e.g., Breshears et al. 2005), 

perhaps reversing expansion trends in some areas.
USDA Forest Service RMRS-GTR-360. 2017. 27

5.1.3 Effects of Persistent Ecosystem Threats on Greater Sage-Grouse

The COT Report (FWS 2013) provides a ranking of threats to sagebrush habitats 

and GRSG for each Management Zone by GRSG population that helps illustrate 

differences across the sagebrush biome in persistent ecosystem threats and identify 

management priorities and strategies. In general, persistent ecosystem threats 

are ranked more highly in the western than the eastern part of the range, and fire, 

weeds, and invasive annual grasses are ranked more highly than conifer expansion. 

In the eastern part of the range (MZs I, II, VII), which includes15 GRSG populations, persistent and widespread threats are altered fire regimes in 9 populations, 

weeds and annual grasses in 10 populations, and conifers in 5 populations. In the 

western part of the range (MZs III, IV, V, VI), which includes 29 GRSG populations, persistent and widespread threats are fire in 23 populations, weeds and annual 

grasses in 26 populations, and conifers in 16 populations.

Doherty et al. (2016) developed a model that provides additional information 

on both the environmental factors and threats affecting GRSG breeding habitat. 

The model evaluates GRSG breeding habitat probabilities within a 4 mile (6.4 

km) radius of leks, which is where most nests occur (Coates et al. 2013; Doherty 

et al. 2010; Holloran and Anderson 2005). It is based on a multivariate analysis 

that couples vegetation (i.e., land cover), climate, landform, and disturbance data 

with densities of male GRSG attending leks from 2010 to 2014. Variables showing 

the highest importance for predicting breeding habitat within Management Zones 

are: cover of all sagebrush species (positively associated; MZs II, III, V, and VII), 

tree canopy cover (negatively associated; MZs I and IV), and elevation (positive 

quadratic relationship; MZ VI) (Doherty et al. 2016; table 5). Landscape cover 

of sagebrush is an important predictor variable in all Management Zones; other 

common predictors are annual drought index (negative quadratic relationship), low 

sagebrush (positive relationship), and degree days greater than 5 °C (positive quadratic 

relationship) (table 5). These results clearly illustrate the importance of sagebrush cover 

and other environmental variables in predicting distribution of GRSG breeding habitats.

Figure 12—A postburn, Phase III, singleleaf piñon and Utah juniper 

dominated sagebrush ecosystem. The bare soils are highly erosive 

and few understory plants remain (photo by Jeanne C. Chambers). 
28 USDA Forest Service RMRS-GTR-360. 2017.

Reductions in sagebrush cover due to persistent ecosystem threats, uncharacteristic wildfires, invasive annual grasses, and conifer expansion, are affecting the 

ability of land managers to achieve the range-wide goal of stable-to-increasing 

population trends. Sage-grouse are true sagebrush obligate species that require large 

and intact sagebrush landscapes and that respond negatively when wildfires occur 

at the extremes of the natural range of variability and remove sagebrush over large 

areas (Coates et al. 2016c; Knick and Connelly 201l). For example, Coates et al. 

(2016c) found that wildfire has long-lasting adverse effects and negates increases in 

sage-grouse population growth that typically occur after years of higher precipitation. Reduction of sagebrush cover is most critical in low- to mid-elevations with 

moderate to low resilience and resistance where natural recovery of sagebrush can 

be very limited within timeframes important to GRSG population dynamics (Davies 

et al. 2011).

1	

Table 5—Top predictor variables and relative importance values from Random Forest models for GRSG (2010–

2014) in each management zone from Doherty et al. (2016). 

Management 

zone 1st Variable 2nd Variable 3rd Variable 4th Variable 5th Variable

I Conifer cover (–) All sagebrush (+) Roughness 

(negative

quadratic)

Topographic 

wetness 

(positive

quadratic)

Gross primary 

production 

(positive

quadratic)

Importance 1.00 0.63 0.57 0.55 0.45

II All sagebrush (+) Conifer cover 

(–) 

Annual drought 

index (negative

quadratic)

Degree days 

>5 oC (positive

quadratic)

Mean annual 

precipitation 

(positive

quadratic)

Importance 1.00 0.73 0.68 0.59 0.49

III

Importance

All Sagebrush 

(+)

1.00

Degree Days 

>5 oC (positive

quadratic)

0.79

Elevation 

(positive

quadratic)

0.70

Annual Drought 

Index (negative

quadratic)

0.54

Conifer Cover 

(–) 

0.48

IV

Importance

Conifer cover 

(–) 

1.00

Annual drought 

index (negative

quadratic)

0.60

All sagebrush 

(+)

0.59

Degree days 

>5 oC (positive

quadratic)

0.51

Gross primary 

production 

(positive

quadratic)

0.50

V 

Importance

All sagebrush (+)

1.00

Annual drought 

index (negative

quadratic)

0.96

Low sagebrush 

(+)

0.91

Mean annual 

precipitation 

(positive

quadratic)

0.79

Degree days 

>5 oC (positive

quadratic)

0.65

VI

Importance

Elevation 

(positive

quadratic) 

1.00

Degree Days 

>5 oC (positive

quadratic) 

0.42

Grassland/

Herbaceous

(+)

0.41

Annual Drought 

Index (negative

quadratic) 

0.27

All Sagebrush 

(+)

0.22

VII (GRSG) All sagebrush (+) Low sagebrush 

(+)

Human 

disturbance index 

(–) 

Oil and gas 

wells 

(–) 

Importance 1.00 0.67 0.48 0.4
USDA Forest Service RMRS-GTR-360. 2017. 29

Nonnative annual grasses and forbs have invaded large areas of the sagebrush 

biome, reducing both habitat quantity and quality (Balch et al. 2013; Miller et al. 

2011a; Rowland et al. 2006). Due to repeated fires in the western part of the range, 

some low- to mid-elevation native sagebrush communities are shifting to novel annual grassland states resulting in habitat loss that may be irreversible with current 

ecological understanding and technical ability (Chambers et al. 2014a; Davies et al. 

2011; Miller et al. 2011a). Studies in the western Cold Deserts ecoregions indicate 

that the presence of nonnative annual grasslands on the landscape may be influencing GRSG distribution and abundance. Recent models indicate that the negative 

impacts of wildfire on sage-grouse population numbers are largely a function of 

slow or no postfire recovery of burned areas near leks and increasing abundance of 

invasive annual grasses (Coates et al. 2016c). In an analysis of active leks, Knick 

et al. (2013) found that most active leks had very little annual grassland cover 

(2.2%) within a 3.1-mile (5 km) radius of the leks; leks that were no longer used had 

almost five times as much nonnative annual grassland cover as active leks. Johnson 

et al. (2011) found that lek use became progressively less as the cover of invasive 

annual species increased at both the 3.1-mile (5 km) and 11.2-mile (18 km) scales. 

Also, few active leks had more than 8 percent invasive annual vegetation cover 

within both buffer distances.

Patterns of nest site selection also suggest local impacts of invasive annual grasses 

on birds. In western Nevada, Lockyer et al. (2015) found that GRSG selected large 

expanses of sagebrush-dominated areas and, within those areas, GRSG selected 

microsites with higher shrub canopy cover and lower cheatgrass cover. Average 

cheatgrass cover at selected locations was 7.1 percent compared to 13.3 percent at 

available locations. Sage-grouse females essentially avoided nesting in areas with 

higher cheatgrass cover. Kirol et al. (2012) also found nest site selection was negatively correlated with the presence of cheatgrass in south-central Wyoming.

Sage-grouse population demographic studies in northern Nevada show that recruitment and annual survival also are affected by the presence of annual grasslands 

at larger scales. Blomberg et al. (2012) analyzed land cover within a 3.1-mile (5 km) 

radius of leks and found that leks impacted by annual grasslands experienced lower 

recruitment than non-impacted leks, even following years of high precipitation. 

Leks that were not affected by invasive annual grasslands exhibited recruitment 

rates nearly twice as high as the population average and nearly six times greater 

than affected leks during years of high precipitation.

Piñon and juniper expansion at mid- to upper-elevations into sagebrush ecosystems also has altered fire regimes and reduced GRSG habitat availability and suitability over large areas with population-level consequences (Baruch-Mordo et al. 

2013; Knick et al. 2013; Miller et al. 2011a). Conifer expansion results in nonlinear 

declines in sagebrush cover and reductions in perennial native grasses and forbs as 

conifer canopy cover increases (Miller et al. 2000), and this has direct effects on the 

amount of available habitat for sagebrush obligate species. Sites in the late stage 

of juniper and piñon expansion and infill (Phase III from Miller et al. 2005) have 

reduced fire frequency (due to decreased fine fuels), but are prone to higher severity fires (due to increased woody fuels), which significantly reduces the likelihood 

of sagebrush habitat recovery (figs. 11, 12; Bates et al. 2013). Even before direct 

habitat loss occurs, GRSG avoid or are negatively associated with conifer cover 

during all life stages (i.e., nesting, brood-rearing, and wintering) in both the western 

and eastern portions of the range (Atamian et al. 2010; Casazza et al. 2011; Dinkins 
30 USDA Forest Service RMRS-GTR-360. 2017.

et al. 2014b; Doherty et al. 2008, 2010; Fedy et al. 2014; Walker et al. 2016; 

Severson et al. 2016).

Population-level impacts are incurred with low amounts of conifer present. No 

leks remained active when conifer canopy exceeded 4 percent in the immediate 

vicinity (within 1,000 m) of the lek in an Oregon study (Baruch-Mordo et al. 2013). 

Also, most active leks averaged less than 1 percent conifer cover at landscape scales 

in the western part of the range (5 km; Knick et al. 2013). Sage-grouse movement 

across conifer-expansion areas may be more rapid than across areas without coniferexpansion resulting in lower survival (Prochazka et al. 2017). Also, more productive 

sites at higher elevations that provide desirable food sources but are exhibiting early 

phase woodland expansion (>2% conifer cover) may function as ecological traps, 

likely due to increased predation from raptors (Coates et al. 2017).

Targeted conifer removal can effectively increase habitat availability for nesting 

and brooding sage-grouse (Sandford et al. 2017; Severson et al. 2017) and can 

have positive effects on other ecosystem attributes like perennial grass and forb 

cover (Miller et al. 2017). Consequently, conifer removal is increasingly used 

to help restore sagebrush habitats (Miller et al. 2017). Since 2010, the Natural 

Resources Conservation Service (NRCS), through its Sage Grouse Initiative, 

has worked with private landowners and partners to implement 457,145 acres 

(185,000 ha) of conifer removal focused in-and-around sage-grouse strongholds 

(www.sagegrouseinitiative.com). Similar projects have been implemented rangewide on BLM and USFS administered lands. In Utah alone, conifers have been removed from over 494,211 acres (200,000 ha) of sagebrush landscapes since 2006 by 

Federal, State, and local partners through the Utah Watershed Restoration Initiative 

(UDNR 2014). Information on the effects of conifer removal on species other than 

GRSG that use juniper and piñon habitat has been identified as a science need in the 

Actionable Science Plan (ASPT 2016).

5.2 Persistent Ecosystem Threats: Climate Change

5.2.1 Recent Climate Trends in the Sagebrush Biome

In the last few decades, temperatures have increased across the sagebrush biome, 

but precipitation has been highly variable (Kunkel et al. 2013a,b). In the Western 

Great Plains as a whole, the largest increases in average temperatures occurred 

during the winter months and the number of frost-free days increased (Kunkel et al. 

2013a). There were no significant trends in precipitation, but there was a significant upward trend in extreme precipitation events over the last 100 years. In the 

Southwest part of the sagebrush biome, annual temperature generally increased over 

the past 115 years and in the southern portion of the area the recent 10 year averages 

surpassed any previous decadal value (Kunkel et al. 2013b). Nighttime temperatures 

showed the greatest increase and the recent period of elevated temperatures was 

most prominent in spring and summer. The frost-free season length increased by 

about 2 weeks relative to the 1960s and 1970s and by a month relative to the early 

1900s. Recent precipitation was highly variable and showed no long-term trend. In 

the 20th century, two prolonged dry periods occurred. A drought near the turn of the 

century followed the wet periods of the 1980s and 1990s and set up conditions for 

record-setting wildfires in several Southwest States. In the Pacific Northwest part 

of the biome, all but 2 years since 1986 had above average temperatures (relative to 

1901−1960), and the frost-free days increased by 11 days in 1991−2010 (relative to 
USDA Forest Service RMRS-GTR-360. 2017. 31

1961−1990) (Kunkel et al. 2013c). Precipitation variability since 1976 has increased 

with most recent years below the 1901−1960 annual mean.

5.2.2 Climate Change Projections for the Sagebrush Biome

Climate change projections are being used to explore the risk of future changes in 

temperature and precipitation patterns. Future scenarios of likely carbon dioxide (CO2) 

and other trace gases emissions, along with information on the earth’s surfaces 

and oceans, are used as input to climate models (IPCC 2014). To develop climate 

projections for the sagebrush biome, two scenarios were chosen. One scenario, 

representative concentration pathway (RCP) 4.5, assumes moderate warming. 

The second scenario, RCP 8.5, assumes high warming of the earth’s atmosphere. 

Climate was projected for each of these scenarios from eleven general circulation 

models (GCMs) from the most recent Intergovernmental Panel on Climate Change 

(IPCC) report (IPCC 2014) for two future time periods: near-term (2020−2050) and 

longer-term (2070−2100) (Appendix 3). These projections of future climate were 

compared to the climate of the recent past (1980−2010) to forecast climate change 

for the sagebrush biome. To examine differences across the sagebrush biome, 

climate projections were evaluated for the biome as a whole and for different groupings of ecoregions with similar climate and topography.

Across the sagebrush biome, average temperatures were projected to increase by 

about 1.8 to 5.4 °F (1 to 3 °C; ensemble minimum and maximum, respectively) in 

the near-term (2020−2050) compared to 1980−2010 under RCP 4.5 and RCP 8.5 

(Appendix 3). Variability in these near-term temperature changes was primarily a 

result of different climate models rather than different assumptions about emissions 

of greenhouse gases. Longer-term (2070−2100) forecasts of average temperature 

change showed the magnitude of change associated with different assumptions 

about future emissions. In the moderate warming scenario (RCP 4.5) temperatures 

increased about 3.6 to 9 °F (2 to 5 °C), whereas under the higher warming scenario (RCP 8.5), temperatures increased about 5.4 to 12.6 °F (3 to 7 °C) (fig. 13). 

Temperature increases were projected to be slightly greater in the summer than 

other seasons; winter, spring, and summer increases for the mean ensemble for 

2070−2100 under RCP 8.5 were projected to be approximately 9, 8.5, and 10.8 °F 

(5, 4.7, and 6 °C), respectively.

Precipitation was projected to increase slightly across most of the sagebrush 

biome (Appendix 3). However, precipitation is more difficult for climate models 

to simulate accurately than temperature. In the near term (2020−2050) biome-wide 

precipitation change varied from a small decrease (<10%) for the ensemble minimum, to an increase of roughly 20 percent for the ensemble maximum. Longer-term 

(2070−2100) projections showed biome-wide precipitation changes ranging from 

a 10 percent decrease (about 1.0 in yr-1 [25 mm yr-1]) to increases of almost 50 

percent (about 5.9 in yr-1 [150 mm yr-1]) in RCP 8.5 (fig. 13). The variation in all 

precipitation projections was high and the differences in the RCP scenarios were not 

observable. Seasonal precipitation projections for 2070 under RCP 8.5 (ensemble 

mean) suggest 20 to 40 percent increases in winter (except for the southern edge), 0 

to 20 percent decreases in spring (except for the northeast and north central part of 

the region, where 10 to 20 percent increases are projected), and 0 to 100 percent increases during summer, with the greatest increase in the Sierra Nevada and Central 

Basin and Range ecoregions.
32 USDA Forest Service RMRS-GTR-360. 2017.

Generally, the scientific community has more confidence in temperature projections, than precipitation projections. These changes in temperature, even if precipitation does not change, can influence water cycling and alter the timing and depth 

of soil water available to plants. If slightly wetter winters promote greater moisture 

availability during winter and early spring, higher winter and spring temperatures 

coupled with longer and drier warm seasons indicate that soils are likely to dry out 

earlier in the year, further stressing these ecosystems (Palmquist et al. 2016a).

Figure 13— Projected changes in mean annual precipitation and mean annual temperature 

for 2070–2100 over the distribution of big sagebrush ecosystems. Changes are presented 

on a 10 km by 10 km cell and show the value from the median climate model within each cell 

(from a set of 11 models examined). Top panels show temperature change in degrees C and 

bottom panels show precipitation change in percent of current precipitation for RCP 4.5 on 

the left and RCP8.5 on the right.
USDA Forest Service RMRS-GTR-360. 2017. 33

5.2.3 Geographic Patterns in Forecasted Change

Spatial patterns in temperature change suggested that the greatest increases will 

occur in the center of the range and the far northeastern edge, where temperatures 

were projected to rise more than 10.8 °F (6 °C) in the high warming scenario 

(RCP 8.5) by the end of the century (fig. 13). Temperature increases were forecast 

to be most pronounced in the Wyoming Basin, Idaho Batholith, and Middle Rockies 

ecoregions (see Appendix 3 for ecoregional differences). Temperature increases in 

winter were projected to be especially large in the northeastern part of sagebrush 

range, specifically the Northwestern Glaciated Plains and Northwestern Great Plains 

ecoregions, where average winter (December−February) temperature were projected 

to increase by almost 0.9 °F (0.5 °C) by the end of the century. By contrast, temperature increases in spring were projected to be greatest in the central and southern 

areas, particularly the Wasatch and Uinta Mountains, Wyoming Basin, and Colorado 

and Arizona-New Mexico Plateau ecoregions. Average January daily minimum 

temperatures were projected to increase between 0.9 and 5.4 °F (0.5 and 3 °C) in the 

near-term, and between 5.4 and 14.4 °F (3 and 8 °C) by the end of the 21st century, 

with the largest increases in the central and northeastern part of the range. Average 

July daily maximum temperatures were anticipated to increase between 5.4 and 

16.2 °F (3 to 9 °C) by the end of the 21st century, with average increases ranging 

between 9 and 14.4 °F (5 and 8 °C) and generally increasing from south to north.

Absolute increases in annual and winter precipitation were projected to be largest in higher elevation, cooler, and wetter areas throughout the range (fig. 13). 

However, spring (April−June) precipitation was projected to increase most in 

the northeastern part of the range, notably the Idaho Batholith, Middle Rockies, 

Northwestern Glaciated Plains and Northwestern Great Plains ecoregions (see 

Appendix 3 for ecoregional differences). Furthermore, summer precipitation (July−

September) was projected to increase most in the south and western part of the 

region, specifically the Central Basin and Range, Sierra Nevada, and Arizona-New 

Mexico Plateau ecoregions. Relative change in precipitation was projected to be 

greatest in the Central Basin and Range, Northern Basin and Range, Snake River 

Plain, and Columbia Plateau ecoregions, where annual precipitation was projected 

to increase by about 20 percent. By contrast, the Colorado and Arizona-New 

Mexico Plateaus were projected to experience only a 10 percent increase in annual 

precipitation. Projections indicated a decreasing proportion of precipitation falling 

between May and October, with the greatest decreases in summer precipitation projected in the northern part of the biome.

Geographic patterns identified in projections of climate change illustrated important variations among big sagebrush ecological types and, thus, sage-grouse habitat 

types. In particular, the largest increases in spring soil water availability were 

projected to occur in the high-elevation, big sagebrush and mountain brush areas 

in the eastern and central portion of the sagebrush biome (Palmquist et al. 2016b). 

By contrast, the most dramatic decreases in summer soil moisture were projected 

in the west-central part of the sagebrush biome. Furthermore, days with wet soil 

were projected to decrease throughout the range of big sagebrush ecosystems due to 

temperature related increases in evapotranspiration. These decreases were projected 

to be especially large in the mid- to high-elevation areas in the northern portion of 

the biome (Palmquist et al. 2016b).
34 USDA Forest Service RMRS-GTR-360. 2017.

5.2.4 Implications for Species and Ecosystems

The changes in precipitation and temperature regimes described above are projected to have large consequences for species distributions, and because individual 

species differ in their climatic requirements, for community composition. Warmer 

temperatures are leading to species distribution shifts to the north and upward in 

elevation—a trend that has been observed for thousands of species globally (e.g., 

Chen et al. 2011; Parmesan and Yohe 2003; Root et al. 2003). Bioclimate envelope 

models for big sagebrush and other sagebrush species project large decreases in 

climate suitability in southern latitudes and lower elevations, but relatively small 

increases in northern latitudes and higher elevations (Bradley 2010; Homer et al. 

2015; Schlaepfer et al. 2012; Still and Richardson 2015). For Wyoming big sagebrush, which occupies the warmest and driest portions of the species range, a 39 

percent reduction (163 million ac; 66 million ha) in suitable climate is projected by 

mid-century (Still and Richardson 2015). Areas in these regions that retain or gain 

climate suitability include higher elevations in the Cold Deserts and the entirety of 

the Northern Great Plains. For juniper and piñon woodlands, habitat with suitable 

climate is projected to move north and upslope with principal gains in Colorado and 

southwest Wyoming and losses in the Southwest (Rehfeldt et al. 2006, 2012).

Climate change is also projected to have significant effects on invasive annual grasses. 

Cheatgrass will likely spread upwards in elevation and red brome (B. rubens) might 

either expand northward, increase its abundance in the Cold Deserts and Colorado 

Plateau, or both (Bradley et al. 2016). Decreases in average summer precipitation 

or prolonged summer droughts could enable cheatgrass invasion into sagebrush 

ecosystems that are currently resistant to invasion and resilient to fire disturbance 

(Bradley et al. 2016; Mealor et al. 2012). If average summer plant available water 

declines, the land area susceptible to cheatgrass invasion may increase by up to 45 

percent, particularly in mountain big sagebrush steppe in Montana and higher elevation areas of the Colorado Plateau (Bradley et al. 2016). Warming temperatures and 

a decreasing proportion of precipitation during summer (Appendix 3) may facilitate 

the expansion of cheatgrass in the northern mixed-grass prairie, allowing it to more 

successfully colonize what is currently considered a largely invasion-resistant grassland (Blumenthal et al. 2016).

Greater climate variability likely will favor invasion of annual invasive species 

in many areas (Bradley 2010) and negatively affect native species persistence in 

areas that remain otherwise climatically suitable. Reduced soil moisture availability 

coupled with greater climate variability can result in reduced resilience of seasonal 

habitats (i.e., nesting, brood-rearing, and wintering) and thus recovery potential of 

native ecosystems following disturbances such as improper livestock grazing and 

uncharacteristic wildfire (Chambers et al. 2014a,c). In turn, decreased resilience can 

lower resistance of these ecosystems to invasive annual grasses like cheatgrass, red 

brome, and field brome (Chambers et al. 2014a,c).

Climate-driven changes are likely to combine with both persistent ecosystem and 

land use and development induced stresses to further increase the vulnerability of 

natural ecosystems to pests, disease, invasive species, and loss of native species. 

Changes in temperature and precipitation affect the composition and diversity of 

native animals and plants by altering their breeding patterns, water and food supply, 

and habitat availability. For GRSG, there is a positive relationship between precipitation and sage-grouse population recruitment rates (Blomberg et al. 2013) and 
USDA Forest Service RMRS-GTR-360. 2017. 35

population growth (Coates et al. 2016c). However, information is largely lacking on 

effects of increased temperature, more variable precipitation, and extreme weather 

events. In a changing climate populations of some pests, such as mosquitos that are 

better adapted to a warmer climate, are projected to increase resulting in an increase 

in diseases such as West Nile virus, which is a threat to sage-grouse (FWS 2014; 

Schrag et al. 2010).

5.3 Land Use and Development Threats

The effects of land use and development on ecosystem resilience are diverse, but 

here we focus on changes in native species composition, degradation of soils, increases in exotic annual grasses and other invasive plants, and altered fire regimes. 

Recent analyses and reviews of the effects of land use and development on the sagebrush biome and GRSG are available for individual ecoregions or areas of concern 

(BLM Rapid Ecoregional Assessments, http://www.blm.gov/wo/st/en/prog/more/

Landscape_Approach/reas.html; Hanser et al. 2011, Wyoming Basins; Wisdom et 

al. 2000, Columbia Basin; Wisdom et al. 2005, Central Basin and Range) and for 

the sagebrush habitats within GRSG Management Zones (Knick et al. 2011, GRSG 

range). Information on threats to Management Zones and populations are in the 

COT Report (FWS 2013) and Doherty et al. (2016).

5.3.1 Cropland Conversion

Extensive cultivation and fragmentation of native habitats have been associated 

with GRSG population declines. Cropland conversion (changing native ecosystems 

to cropland) directly and indirectly influences up to 77 percent of the area within 

Management Zones (Knick et al. 2011). In the COT Report, cropland conversion 

was ranked a present and widespread threat on more productive soils across the 

range of GRSG (6 of 15 populations in the eastern range and 9 of 29 populations 

in the western range) (figs. 14, 15; FWS 2013). In Doherty et al.’s (2016) analysis 

(table 5), the amount of tilled cropland in the analysis was ranked a minor factor in 

predicting GRSG breeding habitat in MZ I (7th), MZ II (14th), MZ IV (13th), and 

MZ VI (13th). However, effects of cropland conversion may be underestimated in 

Doherty et al.’s (2016) analysis as many productive lands with deeper soils that supported GRSG habitat historically were among the first lands converted to cropland 

(Vander Haegen et al. 2000) and are no longer considered in analyses of GRSG 

habitat within their current range.

The West-Central Semiarid Prairies (MZ I) have the highest percentage of private 

lands and highest amount of tilled cropland, followed by the Snake River Plain, and 

Columbia Basin (Doherty et al. 2016; table 12.1 in Knick et al. 2011). Sage-grouse 

are known to use agricultural fields periodically, such as for strutting grounds and 

brood-rearing habitat, but pesticide contamination is a documented concern (Blus et 

al. 1989; Connelly et al. 2000). The amount and configuration of sagebrush habitat 

in the surrounding landscape also influences habitat use (Schroeder and Vander 

Haegen 2011). Several studies indicate that GRSG populations cannot persist in 

areas with less than 25 percent landscape cover of sagebrush (Aldridge et al. 2008; 

Knick et al. 2013; Wisdom et al. 2011). Sage-grouse extirpations have occurred in 

areas where cultivated crops exceeded 25 percent landscape cover (Aldridge et al. 

2008), and recent studies show that 96 percent of active leks are surrounded by less 

than 15 percent cropland in MZ I (SGI 2015; Smith et al. 2016).
36 USDA Forest Service RMRS-GTR-360. 2017.

Figure 14—Percent annually tilled agricultural land (cropland; NASS 2014) 

within 5.0 km of each pixel. Cropland conversion is a threat on more productive soils across the range of Greater sage-grouse.

Figure 15—Conversion of a sagebrush ecosystem in the West-Central Semiarid 

Prairies to agricultural land (photo by John Carlson, used with permission).
USDA Forest Service RMRS-GTR-360. 2017. 37

5.3.2 Energy Development and Mining

Loss of landscape cover of sagebrush associated with energy development has 

been well documented in recent analyses, especially for oil and gas. Oil and gas 

development affects 8 percent of sagebrush habitats with the highest intensities 

occurring in the eastern part of the range (Management Zones I and II); more than 

20 percent of the sagebrush land cover is indirectly influenced in the North-West 

Semiarid Prairies, Wyoming Basin, and Colorado Plateau (figs. 16, 17; table 12.16 

in Knick et al. 2011). The “Wyoming Basin Ecoregional Assessment” (Hanser et al. 

2011), which included south-central Montana, western and central Wyoming, northeastern Utah, and northern Colorado indicated that oil and gas development has removed approximately 658 mi2

 (1,703 km2) of sagebrush and other native habitats in 

this area since 1900 due to construction of well pads and supporting infrastructure 

such as roads, power lines, and pipelines (Finn and Knick 2011). 

Figure 16—Number of active oil and gas wells per square kilometer. Oil and 

gas development is a widespread threat in the eastern portion of the range 

(see Appendix 8 for data source). 
38 USDA Forest Service RMRS-GTR-360. 2017.

Geothermal and especially wind energy development are rapidly increasing due 

to the National Energy Policy (2001), which encouraged development of alternative 

energy sources. The Energy Policy Act of 2005 (Public Law 109–58, Section 211) 

directed the Department of the Interior to approve 10,000 megawatts of non-hydro 

renewable electrical generation within 10 years of the date of enactment. Area 

leased per year on BLM managed lands for wind energy has increased since 2001, 

with the highest total leased areas in the Northern Great Basin, Snake River Plain, 

and Central Great Basin (table 12.18 in Knick et al. 2011). The COT Report identifies those populations across the range where energy development is considered a 

present and widespread threat (6 of 15 populations in the eastern range and 14 of 29 

populations in the western range) (FWS 2013).

Summary data for the effects of mining across the sagebrush biome and range of 

GRSG are not readily available. However, mining is considered a persistent and 

Figure 17—(A) Deep gas drill rig outside of Pinedale, Wyoming (photo by 

Thomas J. Christiansen), and (B) well pad (photo by Kenneth F. Henke). 

B

A
USDA Forest Service RMRS-GTR-360. 2017. 39

widespread threat to 8 of 15 populations in the eastern range and 9 of 29 populations in the western range in the COT Report (FWS 2013). To address this threat, 

in September 2015, the Department of Interior published notice of the BLM and 

FS application to withdraw approximately 10 million acres of public and National 

Forest System lands in Idaho, Montana, Nevada, Oregon, Utah, and Wyoming from 

location and entry under the United States mining laws, subject to valid existing 

rights. Consideration of this proposed withdrawal, including the preparation of an 

environmental impact statement, is ongoing. This land withdrawal is to protect 

GRSG and its habitat from adverse effects of locatable mineral exploration and mining, (BLM 2015b). Processing of this proposed withdrawal, including the preparation of an environmental impact statement, is ongoing.

A number of studies indicate that energy development activities have significant 

effects on GRSG and can result in localized extirpations of GRSG populations 

(Aldridge and Boyce 2007; Duncan 2010; Gregory and Beck 2014; Harju et al. 

2010; Walker et al. 2007). Infrastructure related to energy development (e.g., roads, 

pipelines, storage facilities, mines, wind turbines, transmission lines) decreases 

the effectiveness of habitat for GRSG (Braun et al. 2002; Dinkins et al. 2014a,b; 

Doherty et al. 2008; Holloran 2005; Kirol et al. 2015; LeBeau et al. 2014; Lyon 

and Anderson 2003; Smith et al. 2014). Sage-grouse females with successful 

nests located their nests farther from roads in oil and gas fields than unsuccessful 

hens (Lyon and Anderson 2003). In addition, noise from natural gas development 

activities has been found to lead to immediate and sustained declines in lek attendance (Blickley et al. 2012), indicating the importance of the natural soundscape 

(Patricelli et al. 2013). Also, transmission towers may provide perches and nesting 

structures for raptors and ravens and result in increased densities of these predators 

(Beck et al. 2006; Borell 1939; Coates et al. 2014a,b; Howe et al. 2014; Messmer et 

al. 2013). Proximity to distribution and transmission lines was related to lower adult 

female survival for GRSG, which was most likely related to increases in raptors 

(Dinkins et al. 2014b). Also, West Nile virus and increased abundance of mesocarnivores, both of which are associated with reservoirs created to hold water produced 

from energy development, can cause declines in GRSG populations (Taylor et al. 

2013).

5.3.3 Urban and Exurban Development

Loss of sagebrush land cover due to urban and exurban (residential) development 

since Anglo-American settlement is estimated at 48.4 percent for the Columbia 

Basin (MZ VI), 29.2 percent for the Colorado Plateau and adjacent Rockies (MZ 

VII), and from 12.5 percent to 18.5 percent for the remaining ecoregions and 

Management Zones (figs. 18, 19; table 12.2 in Knick et al. 2011). In the COT 

Report, urban and exurban development was considered a present and widespread 

threat to 7 of 15 populations in the eastern range and 4 of 29 populations in the west 

(FWS 2013). The rank order of the variables in Doherty et al.’s (2016) analysis 

showed that human disturbance was a major factor in predicting GRSG breeding 

habitat in MZ VII (3rd) and a minor factor in MZ I (12th), MZ II (11th), MZ III 

(15th), MZ IV (14th), and MZ VI (7th). However, within the western portion of 

the GRSG range (MZ III, IV, and V) disturbance was an important determinate of 

GRSG occurrence and GRSG habitat suitability was significantly higher in areas 

with less than 3 percent development (Knick et al. 2013).
40 USDA Forest Service RMRS-GTR-360. 2017.

Figure 18—Percentage of developed land (NLCD 2011) within 5.0 km of each 

pixel. Loss of sagebrush land cover due to urban and exurban (residential) development since Anglo-American settlement has been extensive.

Figure 19—Rural subdivision in Sublette County, Wyoming (photo by Thomas J. 

Christiansen).
USDA Forest Service RMRS-GTR-360. 2017. 41

Most residential areas are on the edge of the current distribution of sagebrush and 

GRSG rather than within core areas, but resource use and connecting infrastructure 

can extend well beyond the boundaries of developed areas (figs. 19, 20; Knick et al. 

2011). Low-density exurban developments support lower native species abundance, 

and more human-commensal bird and mammal species and invasive plants than 

comparable unfragmented sagebrush ecosystems (Maestas et al. 2003).

5.3.4 Recreation

Recreational activities (off-highway vehicle [OHV] use, snowmobiling, mountain biking, hiking, camping, hunting, fishing) can have both direct and indirect 

impacts on sagebrush ecosystems and sage-grouse. Recreational use of OHVs is 

one of the fastest growing outdoor activities, although the effects of OHV use on 

sagebrush and GRSG have not been studied (Knick et al. 2011). In the COT Report 

(FWS 2013) recreation is considered a present and widespread threat or a localized 

threat in 9 of 15 populations in the eastern range and 19 of 29 populations in the 

western range.

Figure 20—Density of all roads (surface roads, major roads, and interstate 

highways; ESRI Street Map Premium) in kilometers per square kilometer. 

Connecting infrastructure can extend well beyond the boundaries of developed areas.
42 USDA Forest Service RMRS-GTR-360. 2017.

Recreation, including hiking, hunting, fishing, and OHV use was a major cause 

of species endangerment in the Great Basin and a primary factor endangering 12 

species in Nevada and Utah (Czech et al. 2000). Even activities perceived to have 

low impacts like hiking and mountain biking can affect sagebrush habitats and have 

negative effects on species (Gaines et al. 2003; Miller et al. 1998; Taylor and Knight 

2003).

5.3.5 Infrastructure

Although interstate and major paved highways cover an estimated 0.1 percent of 

the land cover in the Management Zones, they influence 38 percent of the sagebrush 

land cover when their effect size is considered (fig. 20; table 12.3 in Knick et al. 

2011; effect area of 4.3 mi [7 km]). Secondary roads, railroads, and especially 

power lines may have additional fragmentation effects, with the greatest overall 

influence on sagebrush area in the Columbia Basin, Wyoming Basins, and Colorado 

Plateau (table 12.3 in Knick et al. 2011; Manier et al. 2014b). The COT Report 

ranked infrastructure a present and widespread threat in 14 of 15 populations in the 

eastern range and 20 of 29 populations in the west (FWS 2013).

The connecting infrastructure of roads, motorized trails, railroads, powerlines, and 

communications corridors fragment or remove sagebrush cover (Knick et al. 2013; 

Leu and Hanser 2011). Additional ecological impacts of roads and motorized trails 

include: (1) increased mortality of wildlife from collisions with vehicles, (2) modification of animal behavior due to habitat changes or noise, (3) alteration of the 

physical and chemical environment via changes in vegetation structure, soil erosion, 

leaching, etc., (4) spread of nonnative invasive plants and wildlife, and (5) increased 

habitat alteration due to use by humans (Forman and Alexander 1998; Gelbard and 

Belnap 2003; Ouren et al. 2007; Trombulak and Frissel 2000).

5.3.6 Interactions Among Development and Persistent Ecosystem 

Threats

Removal of sagebrush vegetation as a function of development can increase soil 

resources such as available nitrogen and alter soil properties that can favor various 

invasive plant species (fig. 9; Bergquist et al. 2007; Nielson et al. 2011). When compared to sites not influenced by development activities, sites disturbed by energy 

development had higher species richness (numbers) of exotic than native plant species and cover of exotic species was similar to that of native species (Bergquist et 

al. 2007). Similar effects have been documented for croplands and populated areas 

(Nielson et al. 2011). Invasive plant species are also associated with development 

infrastructure such as roads, highways, oil and gas well pads, pipelines, and power 

lines (Manier et al. 2011; 2014a,b; Nielson et al. 2011). Although many invasive 

plant species decline at distances beyond 50 to 100 m of these structures, several 

species, including halogeton (Halogeton glomeratus) and cheatgrass, show low 

rates of decline in abundance with increasing distance from roads and reclaimed 

sites (Manier et al. 2011; Nielson et al. 2011). Once these species are established, 

restoration is much more difficult, especially in areas with warm or dry soil temperature and moisture regimes (Pyke 2011).

Effects of development on sagebrush communities interact with other disturbance 

processes such as wildfire and drought. In southwest Wyoming, 10 to 15 percent 

of sagebrush ecosystem changes in the area were directly related to anthropogenic disturbances (Xian et al. 2011). Decreases in precipitation and increases in 
USDA Forest Service RMRS-GTR-360. 2017. 43

temperature between 1996 and 2006 appeared to impact sagebrush communities 

across all canopy cover ranges by increasing the extent of bare ground and reducing 

herbaceous cover (Xian et al. 2011). Also, fires that occurred largely after 1996 accounted for approximately 12 to 23 percent of the changes in sagebrush landscape 

cover (Xian et al. 2011). These types of changes also affect GRSG populations. 

Numbers of oil and gas well pads, percent area burned by wildfire, and variability of 

shrub height within 1 km of leks were all correlated with GRSG lek abandonment in 

the Bighorn Basin of northcentral Wyoming (Hess and Beck 2012b). This indicates 

that anthropogenic development can decrease ecosystem resilience by reducing 

resistance to invasive plant species, which in turn can increase fire frequency and 

extent. In addition, anthropogenic ignitions increase in proximity to roads and other 

types of development (Narayanaraj and Wimberly 2012).

The cumulative effects of anthropogenic development and persistent ecosystem 

threats may be most evident for sites with relatively warm or dry soil temperature 

and moisture regimes with relatively low resilience and resistance, and may increase as the climate warms. Both current climate and climate change trends are 

important factors driving the negative effects of habitat loss and fragmentation on 

species density and diversity (Mantyka-Pringle et al. 2011). Current studies indicate 

that contemporary habitat loss and fragmentation may outweigh the responses of 

climate change on species and ecosystems (Franco et al. 2006; Jetz et al. 2007), but 

the impact of climate change is predicted to increase over time and exacerbate the 

effects of land use on species population trends (Lemoine et al. 2007). Populations 

in fragmented landscapes are more vulnerable to environmental drivers, such as 

climate change, than those in continuous, intact landscapes (Opdam and Wascher 

2004; Travis 2003).

5.3.7 Livestock Grazing

Livestock grazing is currently the most widespread land use in the sagebrush 

biome. Grazing has well-recognized effects on ecosystem composition, pattern, and 

function (Beck and Mitchell 2000; Boyd et al. 2014b; Cagney et al. 2010; Freilich 

et al. 2003; Fuhlendorf and Engle 2001; Knick et al. 2011). In the COT Report, improper livestock grazing was considered a present and widespread threat to GRSG 

in 8 of 15 populations in the eastern portion of the range (MZ I, II, VII), and in 19 

of 29 populations in the western part of the range (MZ III, IV, V, VI) with differences in the ranking drawn primarily along state boundaries (FWS 2013).

The potential landscape effects of livestock grazing have been difficult to evaluate 

because of a lack of area-wide spatial data (Knick et al. 2011). To address this lack 

of data, Veblen et al. (2011, 2014) compiled spatial allotment boundaries for all 

BLM grazing allotments and combined those spatial boundaries with tabular data 

from the Rangeland Administration System, including billed animal unit months 

(AUMs), type of animal, and season of use by pasture and allotment. Veblen et al. 

(2011, 2014) demonstrated that allotment spatial data can be combined with other 

allotment-related data, for example BLM’s land health data, and with additional 

spatial vegetation data to examine relationships between livestock grazing and 

vegetation. Veblen et al. (2011, 2014) suggested that these types of analyses could 

assist managers in identifying allotments where livestock were potentially the cause 

of not meeting land health standards and prioritizing allotments for further evaluation. Similar data are being used to model vegetation phenology, timing of grazing, 

and intensity of grazing by allotment to relate spatial data for the population growth 
44 USDA Forest Service RMRS-GTR-360. 2017.

rates of GRSG to the multivariate effects of livestock grazing on management units 

in Wyoming (Adrian Monroe, Colorado State University, personal communication). Currently, the BLM maintains grazing allotment boundary data in a geospatial 

format at BLM State offices. The data are compiled at the national level and include allotment numbers by State that are related to the information tracked in the 

Rangeland Administration System. Livestock effects on sagebrush ecosystems and 

GRSG habitat at mid- to local-scales are evaluated on a case-by-case basis that typically does not involve spatial data analyses.

Major differences in plant responses to herbivory exist among ecoregions due 

to evolutionary adaptations to grazing and browsing, plant phenology relative to 

the timing of grazing, and selectivity of grazers for different plant species within 

the community. Plants in the Cold Deserts evolved without large numbers of grazing animals (Mack and Thompson 1982). In contrast, plants in the West-Central 

Semiarid Prairies were grazed regularly and many have adapted to regular defoliation (Coughenour 1985). In the Western Cordillera colder and snow-covered winter 

landscapes protected low-statured plants from grazing until the growing season 

when moisture was available and plants typically evolved without large numbers of 

grazers.

Season of defoliation relative to availability of water for plant regrowth after 

defoliation is an important factor related to livestock grazing and plant tolerance of 

defoliation. Water storage and plant growth in the Cold Deserts depend on winter 

precipitation, especially in the western portion of the range (fig. 4). Cool-season 

plants (C3 photosynthesis pathway) dominate plant communities in this ecoregion. 

Generally, water becomes limiting during late spring and perennial plants become 

dormant if they are not able to extract deep-soil moisture or photosynthesize during the heat of summer. The West-Central Semiarid Prairies have more available 

moisture during summer and have a mixture of cool-season plants and warm-season 

(C4 photosynthesis) grasses that have greater water use efficiency.

The effects of livestock grazing on sagebrush ecosystems are likely more pronounced in Cold Deserts where stocking rates (Briske et al. 2011) and grazing season together affect plant responses to grazing (Briske and Richards 1995). In Cold 

Deserts, defoliation of perennial grasses during inflorescence development (late 

spring) occurs when moisture is becoming limited and plant regrowth and recovery 

can be compromised (Briske and Richards 1995). In the Western Cordillera and 

West-Central Semiarid Prairies, precipitation during the growing season may allow 

greater tolerance to grazing, but cool-season grasses can be eliminated by seasonal 

use that impacts them yet allows warm-season plants to remain ungrazed.

The greatest potential for livestock grazing to affect GRSG habitat is by changing composition, structure, and productivity of herbaceous plants used for nesting 

and early brood-rearing (Beck and Mitchell 2000; Boyd et al. 2014b; Cagney et al. 

2010; Hockett 2002). The effects of specific grazing systems on sage-grouse likely 

depend on their longer-term effects on these plant community attributes, especially 

the relative abundance of perennial grasses and forbs versus sagebrush (Dahlgren 

et al. 2015). Empirical studies and meta-analyses have reported that GRSG nest and 

early brood micro-habitat selection and brood-rearing success are closely tied to 

areas with greater sagebrush and grass canopy cover and height than are randomly 

available in sagebrush landscapes (Dinkins et al. 2016; Doherty et al. 2011a, 2014; 

Hagen et al. 2007; Kirol et al. 2012; Thompson et al. 2006). The reported effects 

of grass-related variables on nest site selection and nest survival have been less 
USDA Forest Service RMRS-GTR-360. 2017. 45

consistent in the literature. In particular, some studies have reported grass height 

as important for GRSG (Aldridge and Brigham 2002; Doherty et al. 2011a, 2014; 

Gregg et al. 1994; Herman-Brunson et al. 2009; Kaczor et al. 2011; Sveum et al. 

1998) and GUSG (Stanley et al. 2015) nesting, whereas others have reported weak 

(Davis et al. 2014; Dinkins et al. 2016; Holloran et al. 2005) or no effects (Kolada 

et al. 2009; Lockyer et al. 2015; Popham and Gutierrez 2003). Additionally, other 

studies concluded no influential effects on GRSG nest survival with any studied 

grass-related microhabitat variable (Coates and Delehanty 2010; Gibson et al. 2016; 

Kolada et al. 2009; Lockyer et al. 2015). Recently, Gibson et al. (2016) demonstrated that reported positive effects of grass height may have been an artifact of 

timing in sampling procedures. Data on grass height were generally collected when 

nest fate was determined rather than using a predicted hatch date, which can result 

in a bias towards greater grass heights relative to the true effect. Thus, revisiting 

management prescriptions based on potential regional variation and potential confounding effects associated with plant phenology within nesting habitat is advised. 

Nevertheless, repeated heavy grazing of sagebrush bunchgrass communities in 

MZ II removes bunchgrasses and leads to a sagebrush and rhizomatous grass or 

bluegrass state, which has reduced resource value for GRSG reproduction (Cagney 

et al. 2010). Sagebrush cover is inherently lower in the West-Central Semiarid 

Prairies (MZ I) than in other portions of the species range (Herman-Brunson et al. 

2009), suggesting greater reliance by breeding GRSG on herbaceous cover than in 

other portions of the range.

Infrastructure related to domestic livestock grazing (e.g., water developments) 

can result in loss of vegetation structure and plant species diversity near these 

features (Rinehart and Zimmerman 2001). Also, fences to control livestock and 

manage grazing on western rangelands can contribute to collision related mortality, 

particularly when located on flat terrain in close proximity to leks (Stevens et al. 

2012). Coates et al. (2016d) found that the odds of raven occurrence, a pervasive 

sage-grouse nest predator, increased by approximately 46 percent in areas where 

livestock were present. The authors suggested that the increased raven predation 

may be partially due to the presence of features such as stock ponds and troughs and 

associated perching structures (e.g. windmills, tanks, and fences) that may increase 

raven presence.

5.3.8 Wild Horses and Wild Burros

Wild horses (Equus caballus) and wild burros (E. asinus), like all large-bodied 

herbivores, can alter sagebrush ecosystem structure and composition and affect 

habitat quality for sagebrush obligate species (Beever and Aldridge 2011). In the 

COT Report (FWS 2013) wild horses and wild burros were considered a present 

and widespread threat in only 1 of 15 populations in the eastern portion of the range 

(Parachute-Piceance-Roan Basin, MZ VII), but in 10 of 29 populations in the western portion of the range. Wild horses and wild burros were considered a persistent 

but localized threat in two populations in MZ II (Wyoming Basin and Northwest 

Colorado), and in one population in MZ IV (Northern Great Basin) (FWS 2013). 

BLM Herd Management Areas (HMAs) that overlap with GRSG occur in the 

Northern Basin and Range, Central Basin and Range, and Wyoming Basins (MZs II, 

III, and IV) (Beever and Aldridge 2011).

Wild horse and burro populations pose long-term challenges to habitat conservation and restoration efforts that differ in several key ways from the challenges posed 
46 USDA Forest Service RMRS-GTR-360. 2017.

by managed livestock grazing (FWS 2013). Wild horse and burro management 

is primarily limited to managing numbers of animals and their distribution. Wild 

horses and burros live on the range the entire year and roam freely, and the locations 

and timing of wild horse and burro grazing are not regulated like livestock grazing.

Wild horse populations have the potential to grow on the order of 15 to 20 percent 

per year (National Research Council 2013; Ransom et al. 2016), and wild horse 

population sizes on Federal lands have almost doubled since the COT Report (FWS 

2013) was published. It was estimated that 67,027 wild horses and burros occurred 

on BLM-administered land as of March 1, 2016. Approximately 60 percent of 

those (39,285 horses) occur within 13 million ac (5.3 million ha) of GRSG habitat. 

On USFS-administered lands, an estimated 6,000 wild horses and 900 wild burros 

occupy approximately 2 million ac (8 million ha). An estimated 3,400 of these 

animals occur within about 446,065 ac (180,516 ha) of GRSG general and priority 

habitat. In addition, an estimated 650 wild horses occur within bi-State sage-grouse 

habitat on about 70,000 ac (28,329 ha) administered by the USFS and 82,403 ac 

(33,347 ha) administered by the BLM.

Wild burros are not nearly as numerous as wild horses in the sagebrush biome. 

However, the tendency of burros to use low-elevation habitats throughout the year 

may lead to a high degree of overlap between burros and sage-grouse habitat, where 

burros and GRSG co-occur (Beever and Aldridge 2011). Also, wild burros can 

substantially affect riparian habitats (e.g., Tiller 1997) and native wildlife, and have 

grazing and trampling impacts similar to wild horses (Douglas and Hurst 1993).

The direct effects of wild horses on sagebrush ecosystems have been summarized 

by FWS (2008) and Beever and Aldridge (2011). Horse presence has broad effects 

on sagebrush ecosystem functioning. In general, wild horse presence is associated 

with lower overall plant cover, but greater relative abundance and cover of grazingtolerant, unpalatable, and invasive plant species (Smith 1986), including cheatgrass. 

In the Great Basin, areas without wild horses have greater native plant cover, shrub 

cover, species richness, and overall plant biomass compared to areas with horses 

(Beever et al. 2008; Davies et al. 2014; Ziegenfuss et al. 2014). Also, there are measurable differences in soil structure, soil penetration resistance, and erosion as well 

as in invertebrate, small mammal, and reptile communities (Beever and Aldridge 

2011; Ostermann-Kelm et al. 2009).

Many studies corroborate the general conclusion that high densities of wild horses 

can lead to biologically significant changes in sagebrush ecosystems. Although 

horses are usually considered to be grazers (Hanley and Hanley 1982), sagebrush 

can represent a large part of their diet in the Great Basin during the summer 

(Nordquist 2011). Wild horses are potential agents for the spread of nonnative plant 

species (Couvreur et al. 2004; Loydi and Zalba 2009) and may limit the effectiveness of restoration projects (Jessop and Anderson 2007). Grazing by wild horses can 

also have severe impacts on aquatic ecosystems and riparian communities (Barnett 

2002; Beever and Brussard 2000; Earnst et al. 2012; FWS 2008, 2012). Wild horses 

can degrade the quality of limited water sources and behaviorally exclude ungulates 

and other native wildlife (e.g., pronghorn) from these water sources (Gooch et al. 

2017; Hall et al. 2016; Ostermann-Kelm et al. 2008; Perry et al. 2015; FWS 2008). 

Even in areas with long histories of livestock grazing, once domestic livestock are 

removed, continued wild horse grazing may cause ongoing detrimental ecosystem 

effects (Davies et al. 2014; FWS 2008). In the sagebrush-steppe ecosystem, plant 

communities can take several decades to recover from such impacts (e.g., Anderson 

and Inouye 2001).
USDA Forest Service RMRS-GTR-360. 2017. 47

6. Resilience to Disturbance and Resistance to Invasive 

Annual Grasses in Sagebrush Ecosystems

An understanding of the factors that determine resilience to stress and disturbance 

and resistance to invasion by nonnative plants can be used to address persistent 

ecosystem and land use and development threats to sagebrush habitats (Brooks and 

Chambers 2011; Chambers et al. 2014a,b, 2017; Wisdom and Chambers 2009). In 

sagebrush ecosystems resilience to stress and disturbance changes along climatic 

and topographic gradients at both landscape and local scales (figs. 21, 22, 23, 24). 

Figure 21—Resistance to invasive annual brome grasses (A) and resilience to disturbance (B) over a typical soil moisture and temperature gradient in the West-Central 

Semiarid Prairies. Dominant ecological sites occur along a continuum from relatively 

warm and summer moist with Wyoming big sagebrush, silver sagebrush, and cool 

season grasses and a minor component of warm season grasses to cold and summer moist with a mixture of cool and warm season grasses and silver sagebrush. 

Resistance to annual brome grasses varies along the temperature and precipitation 

gradient as a function of their ecological amplitudes and is affected by disturbances and 

management treatments that alter vegetation structure and composition and increase 

resource availability. Resilience also increases along the gradient and is influenced by 

site characteristics like soils and aspect (figure adapted from Brooks et al. 2016).

Figure 22—Representative sagebrush ecological types in the eastern portion of the range. (A) Cool and 

warm season grasses with silver sage characterized by high resilience and resistance. (B) Wyoming 

big and silver sage with cool and warm season grasses characterized by low resilience and resistance 

(BLM file photos).

A B

High

LowResistance

A

B

B. tectorum

Wyoming big/silver sage

Cool season with minor

warm season grasses

Cool/warm season grasses

Wyoming big/

silver sage

Cool/warm season grasses

silver sage

Warm-Summer Moist Cold-Summer Moist

Productivity

High

LowResilience

B. arvense

Disturbance/Altered Vegetation
48 USDA Forest Service RMRS-GTR-360. 2017.

Figure 23—Resistance to invasive annual brome grasses (A) and resilience to disturbance (B) over a typical soil temperature and moisture gradient in the Cold Deserts. 

Dominant ecological sites occur along a continuum from relatively warm and dry to 

cold and wet conditions that includes salt desert shrub, Wyoming big sagebrush, 

basin big sagebrush, mountain big sagebrush, and mountain big sagebrush with rootsprouting shrubs. Resistance to annual brome grasses varies along the temperature 

and precipitation gradient as a function of their ecological amplitudes and is affected 

by disturbances and management treatments that alter vegetation structure and 

composition and increase resource availability. Resilience also increases along the 

temperature and precipitation gradient and is influenced by site characteristics like 

soils and aspect (figure adapted from Chambers et al. 2014a).

At landscape scales higher precipitation and cooler temperatures typically result 

in greater resource availability, more favorable environmental conditions for plant 

growth and reproduction, and higher ecosystem productivity (Alexander et al. 1993; 

Dahlgren et al. 1997). In contrast, lower precipitation and higher temperatures result 

in reduced resource availability for plant growth and reproduction and thus lower 

ecosystem productivity (Smith and Nowak 1990; West 1983a,b). Higher levels of 

available resources coupled with greater productivity generally result in increased 

ecosystem resilience to both disturbances and management treatments (Chambers 

et al. 2014a,c). More resilient ecosystems typically exhibit smaller changes following disturbances and recover more rapidly than less resilient ecosystems (Chambers 

et al. 2014c; Davies et al. 2012). These relationships also are observed at local 

scales where aspect, slope, and topographic position affect solar radiation, effective 

precipitation, and erosion processes, and thus soil development and vegetation composition and structure (Condon et al. 2011; Johnson and Miller 2006).
USDA Forest Service RMRS-GTR-360. 2017. 49

Figure 24—Representative sagebrush ecological types in 

the Cold Deserts: (A) Mountain big sagebrush/mountain 

brush type with relatively cold and moist soils characterized by high resilience and resistance, (B) mountain big 

sagebrush type with cool and moist soils and moderate 

resilience and resistance, and (C) Wyoming big sagebrush 

type with warm and dry soils and low resilience and resistance (photos by Jeanne C. Chambers).

A

B

C
50 USDA Forest Service RMRS-GTR-360. 2017.

Resistance to nonnative invasive plant species depends on environmental factors 

and ecosystem attributes and is a function of: (1) the invasive species’ physiological and life history requirements for establishment, growth, and reproduction; and 

(2) interactions with the native perennial plant community including interspecific 

competition and response to herbivory and pathogens. Soil temperature and moisture regimes strongly influence resistance to invasive plant species. The importance 

of soil temperature and moisture regimes in determining invasibility is well illustrated for nonnative invasive brome grasses, which are among the most widespread and problematic invasive plant species in sagebrush ecosystems (figs. 21, 

23; Brooks et al. 2016; Chambers et al. 2007, 2016b). For example, germination, 

growth, and/or reproduction of cheatgrass is physiologically limited in relatively 

warm and dry sites at lower elevations by frequent, low precipitation years, constrained by low soil temperatures at high elevations, and optimal under relatively 

moderate temperature and water availability at mid-elevations (Chambers et al. 

2007; Meyer et al. 2001). In contrast, red brome is found primarily on warm and dry 

salt desert sites (Salo 2005). Field brome (B. arvensis) is limited on warm and dry 

as well as cold sites but is relatively abundant on cool and moist sites (Baskin and 

Baskin 1981). Slope, aspect, and soil characteristics modify soil temperature and 

water availability and influence resistance to brome grasses at landscape to plant 

community scales (Chambers et al. 2007; Condon et al. 2011; Mealor et al. 2012, 

2013; Reisner et al. 2013, 2015; Salo 2005).

The occurrence and persistence of nonnative plants in sagebrush habitats are 

strongly influenced by interactions with the native perennial plant community. For 

example, cheatgrass is a facultative winter annual that can germinate from early 

fall through early spring, exhibits root elongation at low soil temperatures, and has 

higher nutrient uptake and growth rates than most perennial species (Arredondo 

et al. 1998; James et al. 2011; Mack and Pyke 1983). Seedlings of native, perennial 

plant species are generally poor competitors with cheatgrass, but mature plants, 

especially those with similar growth forms and phenology, can be highly effective 

competitors with the invasive annual (Blank and Morgan 2012; Booth et al. 2003; 

Chambers et al. 2007). Also, biological soil crusts, which are an important component of plant communities in warmer and drier sagebrush ecosystems, can reduce 

germination or establishment of cheatgrass (Eckert et al. 1986; Kaltenecker et 

al. 1999). Disturbances or management treatments that reduce abundance of native 

perennial grasses and biological soil crusts and increase the distances between these 

perennial grasses often are associated with higher resource availability and increased competitive ability of cheatgrass (Chambers et al. 2007; Reisner et al. 2013, 

2015; Roundy et al. 2014). Similarly, decreases in native perennial grasses and 

elevated resources result in increased abundances of red brome (Salo et al. 2005), 

field brome (Collins and Uno 1985), and species like spotted knapweed (Centauria 

stoebe ssp. micranthos syn. C. maculosa) (Willard et al. 1988).

The type, characteristics, and historical range of variability of stress and disturbance strongly influence both resilience and resistance. Disturbances like improper 

grazing of perennial plants by livestock or wild horses and burros and uncharacteristic fire regimes are outside of the natural range of conditions and can reduce the resilience of sagebrush ecosystems (Pyke et al. 2016). Reduced resilience is triggered 

by changes in environmental factors like temperature regimes, abiotic attributes like 

water and nutrient availability, and biotic attributes such as vegetation structure, 

composition, and productivity (Chambers et al. 2014a) and cover of biological soil 
USDA Forest Service RMRS-GTR-360. 2017. 51

crusts (Reisner et al. 2013). Changes in abiotic and biotic attributes can result in 

decreased resistance to nonnative invasive annual grasses (Chambers et al. 2007). 

Increased resource availability or altered habitat suitability can both influence an invasive species’ ability to establish and persist as well as compete with native species 

(Chambers et al. 2007, 2014c). Progressive reduction of resilience and resistance 

can result in the crossing of abiotic and biotic thresholds and an inability of the 

system to recover to the reference state (Briske et al. 2008).

7. Integrating Resilience and Resistance With 

Species Habitat Requirements to Prioritize Areas For 

Management and Inform Management Strategies

A strategic, multi-scale approach is needed to conserve sagebrush ecosystems and 

sagebrush obligate species because of the differences in the extent and magnitude of 

persistent ecosystem and land use and development threats and ecosystem resilience 

and resistance to those threats (Chambers et al. 2014b, 2016a; Meinke et al. 2009; 

Pyke 2011; Wisdom and Chambers 2009; Wisdom et al. 2005). This type of approach includes: (1) prioritizing management actions that can increase ecosystem 

resilience to stress and disturbance and resistance to nonnative invasive plants, 

(2) identifying those locations that provide current or potential sagebrush habitat 

for focal species, and (3) efficiently allocating management resources to minimize 

threats and improve habitat conditions (Pyke 2011; Wisdom and Chambers 2009). 

At biome to mid-scales, key biophysical characteristics such as soil temperature and 

moisture regimes can be used as indicators of ecosystem resilience and resistance 

and thus likely ecosystem response to disturbance and management treatments 

(Chambers et al. 2014 a,b, 2016a, 2017; Maestas et al. 2016a). Key habitat characteristics, such as land cover type, climate, landform, and type and magnitude 

of disturbance can be used as indicators of potential habitat for GRSG and other 

sagebrush obligate species. Linking information on resilience and resistance with 

species habitat characteristics provides the basis for a decision support process to 

prioritize management actions based on the likelihood of maintaining or increasing 

ecosystem and species persistence.

7.1 Soil Temperature and Moisture Regimes as Indicators of 

Ecosystem Resilience to Disturbance and Resistance to Invasive 

Annual Grasses at Biome to Mid-Scales

Soil temperature and moisture regimes are available through the Web Soil Survey 

(http://websoilsurvey.nrcs.usda.gov/app/WebSoilSurvey.aspx) and currently provide 

one of the most complete data sets for understanding ecosystem resilience and resistance in the sagebrush biome. To facilitate landscape analyses and prioritization, 

relative resilience to disturbance and resistance to invasive annual grasses were categorized as high, moderate, or low based on soil temperature regime and moisture 

regime subclasses. Resistance was categorized in terms of invasive annual grasses 

because: (1) the potential exists for widespread conversion of sagebrush ecosystems 

to annual grass dominance, and (2) substantial scientific information exists relating resistance to invasive annual grasses to soil temperature and moisture regimes 

or climatic regimes (e.g., Brooks et al. 2016; Chambers et al. 2007; Condon et al. 

2011; Davies et al. 2012; Meyer et al. 2001). 
52 USDA Forest Service RMRS-GTR-360. 2017.

An explanation of soil temperature and moisture regimes and a cross-walk between soil temperature and moisture regimes and relative resilience and resistance 

are in Appendix 2. The dominant sagebrush ecological types are characterized 

according to soil temperature and moisture regimes, major characteristics, and 

resilience to disturbance and resistance to invasive annual grass species in table 6. 

In the Science Framework, ecological type is defined in a broad sense and refers 

to ecological site/type groups. The methods used to develop the ecological types 

are described in Appendix 4. State-and-transition models based on soil temperature 

and moisture regimes, ecological type characteristics, and relative resilience and 

resistance were developed for those ecological types that represent the greatest area 

in the eastern and western portion of the range (Appendices 5 and 6, respectively). 

These state-and-transition models provide information on the alternative states, 

ranges of variability within states, and processes that cause plant community shifts 

within states as well as transitions among states.

In general, higher resilience and resistance occurs with cool to cold (frigid to 

cryic) soil temperature regimes and moist (udic), winter moist (xeric) or predominantly summer moist (ustic) soil moisture regimes, while lower resilience and 

resistance occur with warm (mesic) soil temperatures and relatively dry (aridic) or 

summer moist bordering on dry (ustic bordering on aridic) soil moisture regimes 

(figs. 6, 21, 23; Chambers et al. 2014b, 2016a; Maestas et al. 2016a). The ecoregions and Management Zones differ in soil temperature and moisture regimes and, 

consequently, in dominant ecological types and relative resilience and resistance 

(figs. 21, 23; table 6). Much of the West-Central Semiarid Prairies (MZ I) is characterized by moderate to high resilience and resistance as indicated by relatively cool 

and summer moist regimes (fig. 6; table 6a). However, the southeastern part of this 

ecoregion has low to moderate resilience and resistance as indicated by warm and 

drier regimes. The dominant ecological types are comprised of varying amounts of 

cool season and warm season grasses, Wyoming big sagebrush, and plains silver 

sagebrush (table 6a). The Western Cordillera in MZs II and VII grades into the foothills of the Wyoming Basin and Colorado Plateau and is characterized by cold and 

wet to cool and summer moist soil temperature and moisture regimes with generally 

high to moderate resilience and resistance (fig. 6; table 6b). Ecological types are 

typically comprised of mountain big sagebrush, snowberry and other shrubs, and 

cool season grasses (table 6b).

The Cold Deserts in MZs II and VII encompass a broad range of soil temperature 

and moisture regimes—cool bordering on cold and summer moist bordering on dry 

to warm and dry with generally moderate to low resilience and resistance (fig. 6; 

table 6c). The ecological types are characterized by mountain big sagebrush on the 

coolest sites, Wyoming big sagebrush and salt desert shrubs on the warmest and driest sites, and basin big sagebrush and sometimes silver sagebrush in drainages. Cool 

season grasses predominate with warm season grasses occurring in some types with 

summer moisture.
USDA Forest Service RMRS-GTR-360. 2017. 53

Table 6—Predominant sagebrush ecological types in the West-Central Semiarid Prairies (MZ I; 6a), Western 

Cordillera (MZs II, VII; 6b), Cold Deserts in the eastern portion of the range (Wyoming Basin, Colorado Plateau; 

MZ II, VII; 6c), and Cold Deserts in the western portion of the range (Snake River Plain, Northern Basin and Range, 

Central Basin and Range; MZs III, IV, V; 6d). Information for the eastern part of the range is based on a mid-scale 

analysis (ecoregions/Management Zones) that used data from the National Soil Information System (NASIS) to 

summarize the predominant ecological types occurring in the Priority Areas for Conservation (PACs). For detailed 

methodology, see Appendix 4. Information for the western part of the range is based on Chambers et al. (2014b,c). 

The ecological types are characterized by soil temperature and moisture regimes (to moisture subclass), vegetation, 

resilience to disturbance, and resistance to invasive annual grasses. Relative abundance of sagebrush species 

and composition of understory vegetation vary depending on Major Land Resource Area (MLRA) and ecological 

site. Definitions of MLRAs, ecological types, state-and-transition models, and ecological sites are in Appendix 1. 

An explanation of the soil temperature and moisture regimes is in Appendix 2. State-and-transition models for 

ecological types comprising the largest area are in Appendices 5 and 6. A detailed description of how to use this 

information is in the section on “Determining Appropriate Management Treatments at Local Scales.” 

a—West-Central Semiarid Prairies (Northwestern Glaciated Plains and Northwestern Great Plains)

Ecological type Characteristics Resilience and resistance 

Cool bordering on cold/ Summer 

moist bordering on dry

(Frigid bordering on Cryic/Ustic 

bordering on Aridic)

Representative Area:

Northwestern Glaciated Plains—

MLRA 52 in northern Montana

Precipitation: 10–14 inches

Typical vegetation: Green 

needlegrass, wheatgrasses, needleand-thread, plains silver sagebrush 

Grass dominated—cool with some 

warm season grasses

Resilience—High. High precipitation 

and high productivity result in high 

resilience. 

Resistance—High. Climate 

suitability to invasive annual bromes 

is low due to low soil temperature 

and club mosses. 

Cool/Summer moist 

(Frigid/Ustic-Typic)

Representative Area: Northwestern 

Great Plains—MLRA 60A in South 

Dakota

Precipitation: 13–18 inches

Typical vegetation: Western 

wheatgrass, green needlegrass, 

blue and sideoats grama, 

buffalograss, plains silver 

sagebrush, Wyoming big sagebrush 

on shallow clay sites

Grass dominated—mixture of cool 

and warm season grasses 

Resilience—Moderate to high.

Effective moisture and productivity 

are high, depending on soil texture. 

Resistance—Moderate to high. 

Climate suitability to invasive annual 

grasses is moderate to high 

increasing on warmer sites.

Cool/Summer moist bordering on dry

(Frigid/Ustic bordering on Aridic)

Representative Area: Northwestern 

Great Plains—MLRA 58A in Montana

and 58D in SD, 58C in North Dakota

Precipitation: 10–14 inches 

Typical vegetation:

Wyoming big sage, plains silver 

sagebrush, wheatgrasses, green 

needlegrass, needle-and-thread, 

and blue grama

Shrub dominated—cool with some 

warm season grasses

Resilience—Moderate to high.

Effective moisture and productivity 

are relatively high, depending on soil 

texture. 

Resistance—Moderate to high. 

Climate suitability to invasive annual 

grasses is low and increases on 

warmer and drier sites.

Warm/Summer moist

(Mesic/Ustic-Typic)

Representative Area:

Northwestern Great Plains—wetter 

portions of MLRA 58B in Wyoming

near Black Hills

Precipitation: 15–17 inches

Typical vegetation: Wyoming big 

sagebrush, western wheatgrass, 

green needlegrass, needle-andthread 

Ponderosa pine potential 

Shrub dominated—cool and warm 

season grasses 

Resilience—Moderate to high.

Effective precipitation and 

productivity are relatively high.

 

Resistance—Moderate. Climate 

suitability to invasive annual grasses 

is moderate to low depending on soil 

temperature and texture.

Warm/Summer moist bordering on 

dry

(Mesic/Ustic bordering on Aridic)

Representative Area:

Northwestern Great Plains—drier 

portions of MLRA 58B in Wyoming, 

and probably warmer portions of 58A, 

Land Resource Unit E in 

southeastern Montana

Precipitation: 10–14 inches

Typical vegetation: Wyoming big 

sagebrush, silver sagebrush, 

wheatgrasses, green needlegrass, 

needle-and-thread, blue grama

Shrub dominated—cool and warm 

season grasses

Resilience—Low to moderate.

Effective precipitation and 

productivity are relatively low. 

Resistance—Low to moderate. 

Climate suitability to invasive annual 

grasses is moderate to high 

depending on soil temperature and 

texture.
54 USDA Forest Service RMRS-GTR-360. 2017.

b—Western Cordillera (Middle and Southern Rockies).

Ecological Type Characteristics Resilience and resistance

Cold/Wet

(Cryic/Udic-Typic)

Representative Area:

Middle and Southern Rockies—

MLRA 43B in Wyoming and Montana; 

48A in Colorado; MLRA 47 in Utah

Precipitation: 20+ inches

Typical vegetation: mountain big 

sagebrush, spiked big sagebrush, 

snowberry, mountain silver 

sagebrush , aspen, lodgepole pine, 

slender wheatgrass, fescues, 

needlegrasses, bromes 

Shrub dominated—cool season 

bunchgrasses

Resilience—High. High precipitation 

and high productivity result in high 

resilience. 

Resistance—High. Climate 

suitability to invasive annual bromes 

is low due to low soil temperature.

Cold/Summer moist

(Cryic/Ustic-Typic)

Representative Area:

Middle and Southern Rockies—

MLRAs 46/43B Foothills in Wyoming 

and Montana; MLRA 48A in Wyoming 

and Northern Colorado; MLRA 49 in 

Wyoming

Precipitation: 15–19 inches

Typical vegetation: mountain big 

sagebrush, bitterbrush, snowberry, 

serviceberry, mahogany, aspen, 

fescues, needlegrasses, bluebunch 

wheatgrass

Shrub dominated—cool season 

bunchgrasses

Resilience—High. High precipitation 

and high productivity result in high 

resilience. 

Resistance—High. Climate 

suitability to invasive annual bromes 

is low due to low soil temperature. 

Lower resistance on south-facing 

aspects.

Cool/Summer moist

(Frigid/Ustic-Typic)

Representative Area:

Uinta Mountains (MLRA 47 Land 

Resource Unit C) in Utah and 

Wyoming; Southern Rockies in 

Colorado and Utah—MLRA 48A;

Precipitation: 16–22 inches

Typical vegetation:

mountain big sagebrush, 

serviceberry, snowberry, bitterbrush, 

western wheatgrass, needlegrasses, 

bluegrasses

Shrub dominated—cool season 

grasses with some warm season 

grasses in southern extent

Resilience—Moderate to high.

Precipitation and productivity are 

moderate. Decreases in herbaceous 

perennial species and ecological 

conditions can decrease resilience. 

Resistance—Moderate to high. 

Climate suitability to invasive annual 

grasses is relatively high. 

Cool/Winter moist

(Frigid/Xeric-Typic)

Described in Chambers et al. 2014b. 

Representative Area: Wasatch and 

Uinta Mountains in Utah (MLRA 47) 

Precipitation: 12–22 inches

Typical vegetation: mountain big 

sagebrush, antelope bitterbrush, 

snowberry, and/or low sagebrush, 

bluebunch wheatgrass, basin 

wildrye, Nevada bluegrass

Piñon pine and juniper potential

in some areas 

Shrub dominated—cool season 

grasses

Resilience—Moderately high. 

Precipitation and productivity are 

generally high. Decreases in site 

productivity, herbaceous perennial 

species, and ecological conditions 

decrease resilience.

Resistance—Moderate. Climate 

suitability to invasive annual grasses 

is moderate, but increases as soil 

temperatures increase. 
USDA Forest Service RMRS-GTR-360. 2017. 55

c—Cold Deserts (Wyoming Basin and Colorado Plateau).

Ecological Type Characteristics Resilience and resistance

Cool bordering on cold/ 

Summer moist bordering on dry

(Frigid bordering on Cryic/Ustic 

bordering on Aridic)

Representative Area:

Wyoming Basin—MLRA 34A in 

Wyoming west of continental divide 

into Rich Co., UT 

 

Precipitation: 9–14 inches 

Typical vegetation: Wyoming big 

sagebrush, Gosiute sagebrush, 

mountain big sagebrush, basin big 

sagebrush in drainages, Indian 

ricegrass, needle-and-thread, 

wheatgrasses

Shrub dominated—cool season 

grasses

Resilience—Moderate to low. Effective 

precipitation and cold temperatures can limit site 

productivity and plant establishment. 

Resistance—Moderately high. Climate 

suitability to invasive annual bromes is relatively 

low due to low soil temperature.

Cool/Summer moist bordering on dry

(Frigid/Ustic bordering on Aridic)

Representative Area: 

Wyoming Basin—MLRA 34A in 

Wyoming east of continental divide 

and southern extent of MLRA 34A in 

Colorado west of continental divide.

Precipitation: 10–14 inches

Typical vegetation: Wyoming big 

sagebrush; basin big sagebrush or 

silver sagebrush in drainages, 

wheatgrasses, needle-and-thread, 

Indian ricegrass

Shrub dominated—cool season 

grasses with some warm season 

grasses (blue grama)

Resilience—Moderate. Precipitation and 

productivity are moderate. Decreases in site 

productivity, herbaceous perennial species, and 

ecological conditions decrease resilience.

Resistance—Moderate. Climate suitability to 

invasive annual bromes is relatively low, but 

increases with temperature and soil sand 

content. 

Cool bordering on warm/ Summer 

moist

(Frigid bordering on Mesic/UsticTypic)

Representative Area: 

Colorado Plateau—MLRA 48A/34A 

Piceance Basin-Book Cliffs in 

Colorado and Utah 

Precipitation: 14–18 inches

Typical vegetation: Wyoming big 

sagebrush, basin big sagebrush in 

drainages, mountain big sagebrush, 

Utah juniper, twoneedle pinyon, 

Gambel oak, basin wildrye, 

rhizomatous wheatgrasses, 

Sandberg bluegrass

Pinyon-juniper potential

Shrub dominated—cool season with 

some warm season grasses 

Resilience—Moderate to high. Effective 

precipitation and productivity are high, depending 

on soil texture. Erosive soils and steep terrain 

can decrease resilience. 

Resistance—Moderate to Low. Climate 

suitability to invasive annual grasses is 

moderate. Decreases in site productivity, 

herbaceous perennial species, and ecological 

conditions decrease resistance.

Cool/dry bordering on summer moist

(Frigid/Aridic bordering on Ustic)

Representative Area: 

Wyoming Basin—MLRA 34A in 

Green River Basin (west of 

continental divide) and Great Divide 

Basin

Precipitation: 7–10 inches

Typical vegetation: Wyoming big 

sagebrush and salt desert shrubs, 

bottlebrush squirreltail, 

needleandthread, Indian ricegrass, 

wheatgrasses

Shrub dominated—cool season 

grasses 

Resilience—Moderate to Low. Effective 

precipitation limits site productivity. Decreases in 

site productivity, herbaceous perennial species, 

and ecological conditions further decrease 

resilience.

Resistance—Moderate. Climate suitability to 

invasive annual grasses is moderate, but 

depends on soil texture and temperature. 

Warm/summer moist bordering on 

dry

(Mesic/Ustic bordering on Aridic)

Representative Area: 

Wyoming Basin—MLRA 32 foothills 

in Wyoming, MLRA 34B and 36 in 

Colorado and Utah 

Precipitation: 10–14 inches in WY; 

12-16 inches in UT and CO

Typical vegetation: Wyoming big 

sagebrush, Utah juniper and two 

needle pinyon, wheatgrasses, 

needleandthread, Indian ricegrass

Shrub dominated—cool season 

grasses with warm season grasses 

increasing in south

Resilience—Moderate to low. Effective 

precipitation and productivity are moderately low, 

and vary with soil temperature and texture.

Resistance—Low. High climate suitability to 

invasive annuals. 
56 USDA Forest Service RMRS-GTR-360. 2017.

d—Cold Deserts (Snake River Plain, Northern Basin and Range, Central Basin and Range).

Ecological type Characteristics Resilience and resistance

Cold/Winter moist

(Cryic/Xeric-Typic)

Precipitation: 14 inches +

Typical vegetation: Mountain big 

sagebrush, snowfield sagebrush, 

snowberry, serviceberry, silver 

sagebrush, and/or low sagebrush, 

slender wheatgrass, Idaho fescue, 

needlegrasses, bromes

Shrub dominated—cool season 

grasses

Resilience—Moderately high. Precipitation and productivity 

are generally high. Short growing seasons can decrease 

resilience on coldest sites.

Resistance—High. Low climate suitability to invasive annual 

grasses

Cool/Winter moist

(Frigid/Xeric-Typic) 

Precipitation: 12–22 inches

Typical vegetation: mountain big 

sagebrush, antelope bitterbrush, 

snowberry, and/or low sagebrush, 

slender wheatgrass, Idaho fescue, 

June grass, needle grasses, bromes 

Piñon pine and juniper potential

Shrub dominated—cool season 

grasses

Resilience—Moderately high. Precipitation and productivity 

are generally high. Decreases in site productivity, 

herbaceous perennial species, and ecological conditions 

can decrease resilience.

Resistance—Moderate. Climate suitability to invasive 

annual grasses is moderate, but increases as soil 

temperatures increase. 

Cool bordering on 

warm/Winter moist

(Frigid bordering on 

Mesic/Xeric-Typic) 

Precipitation: 12–16 inches

Typical vegetation: mountain big 

sagebrush, antelope bitterbrush, 

and/or low sagebrush, Idaho fescue, 

bluebunch wheatgrass, needle 

grasses, bromes 

Shrub dominated—cool season 

grasses

Resilience—Moderate. Precipitation and productivity are 

generally high. Decreases in site productivity, herbaceous 

perennial species, and ecological conditions can decrease 

resilience.

Resistance—Moderate. Climate suitability to invasive 

annual grasses is moderate, but increases as soil 

temperatures increase. 

Warm bordering on 

cool/Winter moist

(Mesic bordering on 

Frigid/Xeric-Typic)

Precipitation: 12–16 inches

Typical vegetation: Basin big 

sagebrush, Bonneville big 

sagebrush, and/or low sagebrush, 

bluebunch wheatgrass, needle 

grasses, bromes

Piñon pine and juniper potential 

Shrub dominated—cool season 

grasses

Resilience—Moderate. Precipitation and productivity are 

moderately high. Decreases in site productivity, herbaceous 

perennial species, and ecological conditions decrease 

resilience.

Resistance—Moderately low. Climate suitability to invasive 

annual grasses is moderately low, but increases as soil 

temperatures increase.

Cool bordering on 

warm/Dry

(Frigid bordering on 

Mesic/Aridic-Typic)

Precipitation: 6–12 inches

Typical vegetation: Wyoming big 

sagebrush, black sagebrush, and/or 

low sagebrush, bluebunch 

wheatgrass, needle grasses, 

Sandberg’s bluegrass, bottlebrush 

squirreltail

Shrub dominated—cool season 

grasses 

Resilience—Low. Effective precipitation limits site 

productivity. Decreases in site productivity, herbaceous 

perennial species, and ecological conditions further 

decrease resilience.

Resistance—Moderately low. Climate suitability to invasive 

annual grasses is moderate, but increases as soil 

temperatures increase. 

 

Warm/Dry bordering on 

winter moist

(Mesic/Aridic bordering 

on Xeric)

Precipitation: 8–12 inches

Typical vegetation: Wyoming big 

sagebrush, black sagebrush and/or 

low sagebrushes, Sandberg’s 

bluegrass, bottlebrush squirreltail, 

needleandthread, Indian ricegrass

Shrub dominated—cool season 

grasses

Resilience—Low. Effective precipitation limits site 

productivity. Decreases in site productivity, herbaceous 

perennial species, and ecological conditions further 

decrease resilience. Cool season grasses susceptibility to 

grazing and hot, dry summer fire conditions promote 

cheatgrass establishment and persistence.

Resistance—Low. High climate suitability to cheatgrass and 

other invasive annual grasses. Resistance generally 

decreases as soil temperature increases, but establishment 

and growth are highly dependent on precipitation.
USDA Forest Service RMRS-GTR-360. 2017. 57

The Cold Deserts in MZ III, IV, V, and VI (primarily the northern and central 

Great Basin and Columbia Plateau) differ from those of the Wyoming Basin and 

Colorado Plateau largely because most precipitation is received in winter (fig. 6; 

table 6d). Soil temperature and moisture regimes vary with elevation and range 

from cool bordering on cold and winter moist to warm and dry with generally 

moderate to low resilience and resistance. The ecological types are characterized by 

mountain big sagebrush and mountain brush on the coolest sites, and Wyoming big 

sagebrush on the warmest and driest sites. Cool season grasses predominate in these 

ecoregions.

7.2 Greater Sage-Grouse Breeding Habitat Probabilities and 

Population Indices

7.2.1 The GRSG Breeding Habitat Model

Two models were recently developed for the FWS status assessment (Doherty 

et al. 2016) to quantify GRSG breeding habitat probabilities and create a population 

index to spatially identify population centers of breeding male GRSG within each 

Management Zone (MZ). The Occupied Breeding Habitat Distribution Model (hereafter, breeding habitat model) was developed to more accurately portray important 

breeding areas for GRSG (Doherty et al. 2016), because information available to the 

FWS regarding occupied GRSG range was developed at a broad scale and included 

large areas of unsuitable habitat. The breeding habitat model used GRSG lek data 

(2010−2014) as a proxy for landscapes important to breeding birds, because leks are 

central to the breeding ecology of GRSG and the majority of nests occur relatively 

close (within 4 miles; 6.3 km) to leks (Coates et al. 2013; Holloran and Anderson 

2005). The breeding habitat model evaluated characteristics such as vegetation (i.e., 

landscape cover), climate, landform, and disturbance variables around leks, i.e., 

within a radius of 4 miles (6.4 km; Doherty et al. 2016). The model provided an 

estimate of the probability of occurrence of breeding sage-grouse at a spatial resolution of 120 x 120 m based on habitat characteristics for each Management Zone 

(fig. 25). Breeding habitat for GUSG in MZ VII was recently modeled following 

the same methodology used by Doherty et al. (2016) for GRSG (see Chambers et al. 

2016a).

Breeding habitat probabilities for GRSG in Doherty et al. (2016) (table 7; 

Chambers et al. 2016a) were used to develop three categories of breeding 

habitat probability for prioritizing management actions on the landscape. The 

categories were based on the probability of areas near leks, i.e., within a radius 

of 4 miles (6.4 km; Doherty et al. 2016), providing suitable breeding habitat and 

included: low (0.25 to <0.50), moderate (0.50 to <0.75), and high (0.75 to 1.00). 

Areas with probabilities of 0.01 to less than 0.25 were considered to be unsuitable for breeding habitat. However, it is important to note that these areas may 

provide habitat during other life stages or linkages between areas of suitable breeding habitat. To obtain these categories, probability values were estimated with data 

from existing active lek locations and used to define thresholds in breeding habitat 

probabilities. Probability values were then estimated for inactive lek locations and 

used to conduct an accuracy assessment of the categorization of habitat probabilities 

(table 7). This categorization achieved the goal of clearly differentiating where management actions to improve habitat are warranted (<10% of active leks and >90% of 

inactive leks occurred in the low and moderate probability ranges; table 7).
58 USDA Forest Service RMRS-GTR-360. 2017.

Figure 25—GRSG breeding habitat probabilities based on 2010–2014 lek data 

(Doherty et al. 2016). Priority Areas for Conservation (PACs; FWS 2015) are 

overlaid. The breeding habitat probability model was developed to more accurately portray important breeding areas for GRSG.

Table 7—Percentage (and number) of active and inactive leks within four breeding habitat model probability 

classes. Breeding habitat model probabilities (Doherty et al. 2016) for all Management Zones were grouped 

into ranges relative to their probability of supporting sage-grouse leks. Habitat probabilities for GRSG were 

modeled by comparing habitat characteristics within 4 mi (6.4 km) around active and inactive lek locations 

(Doherty et al. 2016). Active and inactive GRSG lek data were provided by the Western Association of Fish 

and Wildlife Agencies. The categorization differentiates where management actions to improve habitat are 

warranted (<10% of active leks and >90% of inactive leks occurred in the low and moderate probability 

ranges). 

Breeding habitat model probability classes

Lek type Unsuitable Low Moderate High

0.01 to <0.25 0.25 to <0.50 0.50 to <0.75 0.75 to 1.0

Active 0.1% (n = 4) 1.1% (n = 38) 9.3% (n = 308) 89.5% (n = 2978)

Inactive 5.9% (n = 71) 22.5% (n = 272) 36.8% (n = 446) 34.8% (n = 422)
USDA Forest Service RMRS-GTR-360. 2017. 59

Managers can consult table 5 to identify the top predictor variables for GRSG 

breeding habitat in each Management Zone to help identify specific issues relating 

to why individual leks may be located in low, moderate, or high probability ranges. 

For example, energy development structures or wildfire may have eliminated sagebrush near inactive leks in the moderate or low probability range.

7.2.2 The GRSG Population Index Model

Doherty et al. (2016) also developed a Population Index Model (hereafter, population index) to spatially identify areas that contain population centers of breeding 

male GRSG based on a combination of breeding habitat probability and 2010−2014 

lek data (fig. 26). Past work has shown that GRSG populations are highly clumped 

(Coates et al. 2015; Doherty et al. 2016). Relatively small areas can contain a 

disproportionate number of males attending leks (Doherty et al. 2011b), and large 

differences in the density of birds can occur even within the high GRSG breeding 

habitat probability category. The population index serves as a proxy for relative 

abundance of GRSG, which allows for a spatial delineation of where threats (e.g. 

conifer expansion) can be targeted for management. This population index model is 

representative of GRSG populations between 2010 and 2014 and will need periodic 

updates.

7.2.3 Use and Limitations of the Breeding Habitat and Population Index 

Models

Partial probability plots were used to elucidate habitat relationships among the 

variables in the final breeding habitat model for GRSG (Doherty et al. 2016). These 

types of figures demonstrate how the probability of the landscape supporting a 

breeding population of GRSG changes relative to specific habitat variables (e.g., 

landscape cover of sagebrush) (fig. 27). Partial probability plots of habitat relationships can also be used to identify thresholds in which non-habitat features exceed 

the tolerance of a species. However, because the habitat characteristics of species 

are defined by multiple variables (e.g., James 1971), use of a spatially explicit 

model is preferred over using threshold values of a single habitat variable such as 

that identified in fig. 27. However, graphing the probability of lek occurrence relative to a single variable can be used to evaluate the effect of the variable of interest.

One of the primary limiting factors of these models is the focus on the breeding 

location. Although the majority of nesting occurs within a radius of 4 miles (6.4 km; 

Coates et al. 2013; Holloran and Anderson 2005) around the leks, seasonal habitat 

(e.g., winter) and areas that link seasonal habitats may be located elsewhere and 

may be a limiting factor in some populations. Identification of seasonal habitats 

for Greater sage-grouse across their entire range is a priority science need (ASPT 

2016).

The metrics used to develop these models are very broad in scale and the modeled 

response is not specific to any particular life stage. Lek based models do not account for habitat selection or demographic responses. For those populations where 

data regarding the needs of each life stage and spatially explicit maps are available 

at finer resolution, this information may be more useful for management purposes.
60 USDA Forest Service RMRS-GTR-360. 2017.

7.3 Landscape Cover of Sagebrush as an Indicator of Habitat

In the absence of spatially explicit habitat models such as those developed by 

Doherty et al. (2016), habitat variables such as type and extent of landscape cover 

and type and magnitude of predominant disturbances can provide a viable alternative for assessing the probability of suitable habitat and informing management decisions. Landscape cover of sagebrush has been shown to be an important predictor 

of persistence of GRSG and other sagebrush obligate species (Aldridge et al. 2008; 

Donnelly et al. 2016; Hanser et al. 2011; Knick et al. 2013; Rowland et al. 2006; 

Wisdom et al. 2011). Sagebrush landscape cover is typically derived from remotely 

sensed land cover data such as LANDFIRE (USGS 2013) using a moving window 

Figure 26—Cumulative percent of the GRSG population based on breeding 

bird abundance during 2010–2014 (Doherty et al. 2016). The 10 percent bin 

includes 10 percent of the GRSG population; the blue and green colors include 60 percent of the GRSG population; all colors include 100 percent of the 

population. This population index was developed to spatially identify areas that 

contain population centers of breeding male Greater sage-grouse.
USDA Forest Service RMRS-GTR-360. 2017. 61

0.0 0.2 0.4 0.6 0.8 1.0

N. Great Plains

WY Basin

S. Great Basin

Snake River

N. Great Basin

Columbia Basin

Proportion of sagebrush cover within a 6.4-km radius

0.0 0.2 0.4 0.6 0.8 1.0

Probability of the landscape supporting a

breeding population

Figure 27— Partial probability plot depicting the effect of landscape cover of 

sagebrush on the probability of a landscape supporting a breeding population of GRSG (modified from Doherty et al. 2016). The red line shows the 

minimum level of sagebrush landscape cover needed to support a breeding 

population of GRSG based on a 4 mi (6.4 km) radius in the Northern Great 

Plains (Management Zone I). Landscape cover of sagebrush was derived 

from Landfire (USGS 2014). 

analysis (figs. 28, 29; see Appendix 7 for an explanation of landscape cover and 

moving window analyses). Analyses of the landscape cover of sagebrush around 

GRSG leks in various portions of the range (Aldridge et al. 2008; Knick et al. 2013; 

Wisdom et al. 2011) indicated that the relative probability of lek persistence can be 

estimated using percentage landscape sagebrush cover. In general, low GRSG lek 

persistence occurs with 1 to 25 percent landscape cover of sagebrush, intermediate 

persistence with 25 to 65 percent, and high persistence with less than 65 percent 

(Chambers et al. 2014b).

These three categories of landscape cover of sagebrush were used to indicate the 

potential of an area to provide GRSG habitat in the western range GTR (MZs III, 

IV, V) that was published in 2014 (Chambers et al. 2014b), prior to development of 

the multi-variate breeding habitat models by Doherty et al. (2016). This approach 

was subsequently incorporated into the “Greater Sage-Grouse Wildfire, Invasive 

Annual Grasses, and Conifer Expansion Assessment” (BLM 2014). In the analyses 

described in the General Technical Report (GTR) (Chambers et al. 2014b) and 

implemented in the assessment (BLM 2014), landscape cover of sagebrush was 

evaluated in conjunction with the GRSG breeding density data as in the Doherty et 

al. (2016) breeding habitat suitability model. In the Doherty et al. (2016) breeding 

habitat suitability model, landscape cover of sagebrush was among the top predictor variables in MZs III, IV, and V (table 5). Thus, while the Doherty et al. (2016) 

models may have provided additional information to inform the western range GTR 

and assessment, it is likely that highly similar results would have been obtained. 
62 USDA Forest Service RMRS-GTR-360. 2017.

Analyses based on landscape cover of sagebrush and species population abundance 

can be used for other sagebrush obligate species until multi-variate models are developed for these species. For example, a recent rangewide analyses of sagebrushobligate passerine birds indicates that there is a threshold of about 40 percent 

landscape cover of sagebrush for predicted counts of several species (Brewer’s sparrow, Spizella breweri; sagebrush sparrow, Artemisiospiza nevadensis; sage thrasher,

Oreoscoptes montanus) (fig. 30; Donnelly et al. 2016).

Analyses conducted for MZ I show that active leks are distributed across all of 

the above landscape sagebrush cover categories (when measured within 6.4 km of 

leks) (Chambers et al. 2016a). This is probably a function of: (1) the difficulty of 

accurately classifying sagebrush pixels in remotely sensed data for the West-central 

Figure 28—The landscape cover of sagebrush-dominated ecological systems 

(USGS 2014) displayed in 10 percent increments. Percentage of sagebrush 

within each of the categories was determined within a 3.1 mi (5 km) radius of 

each sagebrush pixel.
USDA Forest Service RMRS-GTR-360. 2017. 63

Semiarid Prairies, and (2) selection of breeding habitat by GRSG across a broader 

range of sagebrush landscape cover in MZ I than in other Management Zones. 

This finding reflects the fact that sagebrush land cover is only 14 percent in MZ I, 

compared to 45 percent in MZ II (Knick et al. 2011), where most active GRSG leks 

occur in areas of high sagebrush land cover.

Evaluating the type, extent, and magnitude of the threat(s), such as the dates and 

perimeters of past fires and locations and densities of oil and gas wells, can provide 

additional information on habitat characteristics. Coupling information on landscape 

cover of sagebrush and the predominant threats for a region provides necessary 

information for evaluating habitat characteristics.

Figure 29—The landscape cover of grass-dominated ecological systems with 

sagebrush components (USGS 2014) displayed in 10 percent increments. 

Percentage of sagebrush within each of the categories was determined within 

a 3.1 mi (5 km) radius of each sagebrush pixel.
64 USDA Forest Service RMRS-GTR-360. 2017.

7.4 Sage-Grouse Habitat Resilience and Resistance Matrix: A Key 

Prioritization Tool

Knowledge of resilience and resistance of sagebrush ecosystems can be used in 

conjunction with the probability that an area will provide GRSG breeding habitat 

to determine priority areas for management and identify effective management 

strategies (Chambers et al. 2016a). The sage-grouse habitat resilience and resistance 

matrix (table 8) illustrates an area’s relative resilience to disturbance and resistance 

to invasive annual grasses in relation to its probability of providing breeding habitat 

for GRSG. As resilience and resistance go from high to low, as indicated by the 

rows in the matrix, the amount of time required for sagebrush regeneration and 

perennial grass and forb regrowth progressively limits the capacity of sagebrush 

ecosystems to recover after disturbances without management assistance. Also, 

the risk of invasive annual grasses increases, and the ability to successfully restore 

burned or otherwise disturbed areas decreases. As the probability of GRSG breeding 

habitat goes from low to high within these same ecosystems, as indicated by the 

columns in the matrix, the capacity to sustain populations of GRSG increases. Areas 

with breeding habitat probabilities of 0.25 to less than 0.5 are unlikely to provide 

adequate breeding habitat for GRSG (table 7; Chambers et al. 2016a). Areas with 

breeding habitat probabilities of 0.5 to less than 0.75 can provide breeding habitat 

for GRSG, but are at risk if sagebrush loss occurs without regeneration or if other 

factors negatively impact the area, such as conifer expansion, development, or infrastructure (table 7; Chambers et al. 2016a). Areas with breeding habitat probabilities 

greater than or equal to 0.75 can provide the necessary breeding habitat conditions 

for GRSG to persist. Predicted count

Proportion sagebrush (AllSB120m)

0.0 0.2 0.4 0.6 0.8

0 5 10 20 25 30

Density of sagebrush within study area

15

A)

0 2 6 8 4

BRSP

SASP

SATH

Figure 30—Partial dependence plot showing the predicted relationships 

among the proportion of sagebrush within a 120-m buffer and counts of 

Brewer’s sparrow (BRSP), sagebrush sparrow (SASP), and sage thrasher 

(SATH) (Donnelly et al. 2016). There is an apparent threshold value of 40 

percent landscape cover of sagebrush above which abundance of the different species increases. The background histogram is the frequency of 

covariate values across the landscape, and shows that a large proportion 

of sampled areas had low density of sagebrush (right y-axis). 
USDA Forest Service RMRS-GTR-360. 2017. 65

Table 8—Sage-grouse habitat resilience and resistance matrix based on resilience and resistance concepts from 

Chambers et al. (2014a,b), and GRSG breeding habitat probabilities from Doherty et al. (2016). Rows show the 

ecosystem’s relative resilience to disturbance and resistance to invasive annual grasses (1 = high resilience and 

resistance; 2 = moderate resilience and resistance; 3 = low resilience and resistance). Resilience and resistance 

categories were derived from soil temperature and moisture regimes (see Appendix 2; Maestas et al. 2016a) and 

relate to the sagebrush ecological types in table 6. Columns show the landscape-scale sage-grouse breeding habitat 

probability based on table 7 (A = 0.25 to <0.5 probability; B = 0.5 to <0.75 probability; C = ≥0.75 probability). Use 

of the matrix is explained in text. Potential management strategies for persistent ecosystem threats, anthropogenic 

threats, and climate change are in table 9. 
66 USDA Forest Service RMRS-GTR-360. 2017.

 The sage-grouse habitat resilience and resistance matrix is a decision support 

tool that allows land managers to better evaluate risks at mid- to local-scales and 

decide where to focus specific activities to promote desired species and ecosystem 

conditions (table 8; Chambers et al. 2014c, 2016a). Management strategies can be 

determined by considering: (1) an area’s resilience to disturbance and resistance 

to nonnative invasive plants, (2) GRSG breeding habitat index values, and (3) the 

predominant threats to both sagebrush ecosystems and their associated GRSG 

populations.

Management strategies for sagebrush ecosystems have been organized by threat 

and are found in table 9. Management strategies often cross-cut multiple program 

areas for land management agencies and an integrated approach is typically used 

to address the predominant threats. For example, agency program areas such as 

invasive plant management, fuels management, range management, wildlife, and 

others may all contribute to vegetation management strategies designed to address 

persistent ecosystem and land use and development threats.

Areas with high GRSG breeding habitat probabilities and high concentrations 

of birds are typically comprised of intact habitats and thus are higher priorities for 

management (table 8 cells 1C, 2C, 3C). Protective management can be used in and 

adjacent to these areas to maintain habitat connectivity and ecosystem resilience and 

resistance. Protective management can include a diverse set of strategies such as 

reducing or eliminating disturbances from land uses and development, establishing 

conservation easements, utilizing an early detections and rapid response approach 

(EDRR) (USDOI 2016) for invasive plant species, and suppressing fires (table 9). 

Areas with high GRSG breeding habitat probabilities but lower resilience and resistance are slower to recover following fire and surface disturbances and are more 

susceptible to invasive plant species than areas with higher resilience and resistance 

(Chambers et al. 2014a). Consequently, these low resilience and resistance areas are 

at greater risk of habitat loss than areas with moderate to high resilience and resistance and are high priorities for protective management (table 8, cell 3C; Chambers 

et al. 2014c, 2016a). 

Areas with moderate GRSG breeding habitat probabilities are comprised of 

habitat that supported a higher proportion of leks in the past than currently (table 7) 

and that may be improved through various management strategies (table 8 cells 1B, 

2B, 3B). Management objectives may include increasing resilience and resistance 

by promoting perennial grasses and forbs and biotic soil crusts, identifying and 

correcting improper livestock management, removing conifers, reducing or eliminating new infestations of invasive plants through EDRR approaches, or restoring 

sagebrush habitat through seeding or transplanting (table 9). Management strategies 

often have synergistic effects (Chambers et al. 2017). Increasing abundance of 

native perennial grasses and forbs can decrease the probability of invasion or expansion of annual invasive grasses (Chambers et al. 2007; Reisner et al. 2013). This, in 

turn, can reduce the risk of altered fire regimes, transitions to undesired states, and 
USDA Forest Service RMRS-GTR-360. 2017. 67

decreased connectivity. Similarly, management strategies aimed at reducing the risk 

of wildfires outside of the historical range of variation, such as removing conifers in 

Phase I and Phase II expansion areas, can increase the functional capacity of plant 

communities to resist invasive annual grasses (Chambers et al. 2014c; Roundy et al. 

2014) as well as enhance habitat connectivity (Baruch-Mordo et al. 2013).

The relative resilience and resistance of an area strongly influences its response 

to management strategies such as conifer removal or postfire rehabilitation and the 

likelihood of nonnative annual grass invasion (Chambers et al. 2014a,c; Miller et 

al. 2013, 2014, 2015). Areas with lower resilience and resistance may still be high 

priorities for management in areas with moderate breeding habitat probabilities, 

but management activities such as restoring sagebrush habitat through seeding or 

transplanting may require greater investment and repeated interventions (table 8 cell 

3B; Chambers et al. 2014b; 2016a). In areas projected to exhibit large changes in 

climate, favoring or restoring native species that are expected to be better adapted 

to the future range of climatic and site conditions may help increase restoration success (Butler et al. 2012).

Areas with low GRSG breeding habitat probabilities are characterized by habitat 

that supported active GRSG leks in the past, but that currently support few leks 

(table 8 cells 1A, 2A, 3A). If land use and development threats such as oil and gas 

development or cropland conversion are causing low GRSG breeding habitat probabilities, then habitat improvement may not be feasible. However, if the area has the 

capacity to respond to management treatments and if breeding populations are close 

enough for recolonization, improvement of these areas to increase breeding habitat 

probabilities may still be possible. Managers may decide to restore critical habitat in 

these types of areas, but the degree of difficulty and time frame required for habitat 

restoration increase as resilience and resistance decrease (Chambers et al. 2014b, 

2016a). In those areas where interactions between climate change and stressors are 

projected to be severe, management actions may be needed that help ecosystems 

transition to new climatic regimes (e.g., Millar et al. 2007, 2012).

Careful assessment of the area of concern will always be necessary to determine 

the relevance of a particular strategy or treatment because sagebrush ecosystems 

occur over continuums of environmental conditions, such as soil temperature and 

moisture, have differing land use histories and species composition (Miller et al. 

2014, 2015; Pyke et al. 2015a,b), and are projected to experience different climate 

change effects (Appendix 3). Also, areas with low GRSG breeding habitat probabilities may support other resource values or at-risk species (Rowland et al. 2006) that 

could benefit from management strategies designed to improve habitat. Knowledge 

of the locations of other priority resources and at-risk species and their response to 

management treatments can help ensure that treatments are located and strategies 

are implemented in a manner that will not harm and ideally benefit these other 

resources and species.
68 USDA Forest Service RMRS-GTR-360. 2017.

Table 9—Management strategies for persistent ecosystem threats, climate change, and land 

use and development threats. Recommendations are provided for prioritizing and targeting 

strategies based on cells in the sage-grouse habitat resilience and resistance matrix (table 

8). Threats and strategies are cross-cutting and affect multiple program areas. While 

many of these fall under the broad umbrella of vegetation management, a coordinated and 

integrated approach will likely be used in addressing threats. For example, it is expected 

that multiple agency program areas such as nonnative invasive plant management, fuels 

management, range management, wildlife, and others will contribute to strategies that use 

vegetation manipulation to address persistent ecosystem and anthropogenic threats.

Threat—Nonnative Plant Invasive Species

Management strategies

•	 Apply integrated vegetation management practices to manage nonnative invasive plant 

species, using an interdisciplinary and coordinated approach in designing and implementing projects and treatments.

o Prioritize areas where management resources are likely available to ensure successful management in the long-term.

•	 Use resilience and resistance categories and knowledge of invasive plant distributions to 

select appropriate management approaches.

o Protect high quality (relatively weed-free) sagebrush communities with moderateto-high sage-grouse habitat probabilities (cells 1B, 1C, 2B, 2C, 3B, 3C):

§	 Focus on preventing introduction and establishment of invasive plant species, 

especially in low resistance areas with high susceptibility to annual grass 

invasion (in and adjacent to cells 3B, 3C); 

§	 Avoid seeding introduced forage species (crested wheatgrass, smooth 

brome, etc.) in postfire rehabilitation or restoration in moderate to high resilience and resistance areas because these species can dominate sagebrush 

communities; and

§	 Practice Early Detection-Rapid Response (EDRR) approaches for emerging 

invasive species of concern (in and adjacent to cells 1B, 1C, 2B, 2C, 3B, 3C). 

o Where weed populations already exist, seek opportunities to maximize treatment 

effectiveness by prioritizing restoration within relatively intact sagebrush communities (cells 1B, 1C, 2B, 2C, 3B, 3C). Restoration will likely be easier at locations in 

cooler and moister ecological types with higher resilience and resistance.

§	 Prioritize sites with sufficient native perennial herbaceous species to respond 

to release from invasive plant competition; 

§	 Manage grazing to reduce invasive species and promote native perennial 

grasses. In the West-Central Semiarid Prairies and other cool and moist 

areas, manage grazing to reduce crested wheatgrass, Kentucky bluegrass, 

smooth brome, and other introduced forage species and to promote native 

cool season perennial grasses (see grazing strategies).

o Restrict spread of large weed infestations located in lower breeding habitat probability areas (cells 1A, 2A, 3A) to prevent compromising adjacent higher quality 

habitats (cells 1B, 1C, 2B, 2C, 3B, 3C).

Threat—Conifer Expansion

Management strategies

•	 Addressing localized conifer expansion requires an interdisciplinary approach and necessarily involves multiple program areas. 

o Apply integrated vegetation management practices to treat conifer expansion, using an interdisciplinary approach in designing projects and treatments.

o Focus tree removal on early to mid-phase (e.g., Phases I, II) conifer expansion into 

sagebrush ecological sites to maintain shrub/herbaceous cover.

o Use prescribed burning cautiously and selectively in moderate to high resilience/

resistance (cells 1A, 1B, 2A, 2B) to control conifer expansion.

o Prioritize for treatment:

§	 Areas with habitat characteristics that can support sage-grouse with moderate to high resilience and resistance (cells 1B, 1C, 2B, 2C), especially near 

leks. (Note: cells 3B and 3C are generally too warm and dry to support 

conifers.)
USDA Forest Service RMRS-GTR-360. 2017. 69

§	 Areas where conifer removal will provide connectivity between sagebrush 

habitats.

§	 Areas where sufficient native perennial grasses and forbs exist to promote 

recovery and limit increases in invasive plant species.

Threat—Wildfire

Management strategies

The wildfire threat is generally addressed through fire operations, fuels management (mechanical treatments, prescribed burning, chemical and seeding treatments), and postfire 

rehabilitation. 

Fire Operations: Protection of areas supporting sagebrush is important for maintaining 

sagebrush habitat. The types and locations of GRSG habitats have been incorporated into 

decision support, dispatch, and initial attack procedures, and represent key considerations for 

fire managers. 

If resources become limiting, consider the following prioritization: 

•	 Fire suppression—typically shifts from low to moderate priority when resilience and resistance categories shift from high to moderate, but varies with large fire risk and landscape 

condition (cells 1B, 1C, 2B, 2C). In low resilience and resistance areas, the priority shifts 

from moderate to high as sage-grouse habitat probability increases (cell 3B, 3C). Scenarios requiring high priority may include:

o Areas of sagebrush that bridge large, contiguous expanses of sagebrush and that 

are important for providing habitat connectivity;

o Areas where sagebrush communities have been successfully reestablished 

through seedings or other rehabilitation investments; and

o All areas during critical fire weather conditions, where fire growth may move into 

valued sagebrush communities. These conditions may be identified by a number of 

products including, but not limited to: Predictive Services National 7-Day Significant 

Fire Potential products; National Weather Service Fire Weather Watches and Red 

Flag Warnings; and fire behavior analyses and local fire environment observations.

Fuels Management: Fuels management is a subset of vegetation management. Fuels 

management activities include treatments that mitigate wildfire risk, modify fire behavior, 

improve resilience to disturbance and resistance to invasive annual grasses, and protect and 

restore habitat. Mechanical treatments are typically applied to reduce fuel loading, modify 

fire behavior, augment fire suppression efforts, or alter species composition consistent with 

land use plan objectives. Roadside fuel breaks are applied most commonly in MZ III, IV, and 

V. Prescribed burning is one form of fuels management that may be used to improve habitat 

conditions or create fuel conditions that limit future fire spread in areas with moderate to high 

resilience and resistance, but should be considered only after consultation with local biologists and land managers. Chemical and seeding treatments are conducted to reduce invasive 

plants and change species composition to native and/or more fire resistant species where native perennial grasses and forbs are depleted. When setting priorities for fuels management, 

consider the following.

Mechanical Treatments—Conifer Removal

•	 Conifer removal conducted to decrease woody fuels and reduce the loss of large, 

contiguous sagebrush stands are high priority in areas with high GRSG breeding habitat 

probabilities and moderate to high resilience and resistance (cells 1B, 1C, 2B, 2C), and 

shift to low in areas with low breeding habitat probabilities (cells 1A and 2A). In these 

areas, the focus is primarily on conifer expansion areas with sufficient native perennial 

understory species for recovery.

•	 Management activities may include:

o Tree removal in early to mid-phase (Phases I, II) post-settlement conifer stands to 

maintain shrub/herbaceous cover and reduce fuel loads;

o Tree removal in later phase (Phase III) post-settlement conifer stands to reduce 

risks of large or high severity fires; and 

o Herbicide and/or seeding associated with mechanical treatments to reduce invasive 

species and restore native perennial herbaceous species where native perennial 

species are depleted.
70 USDA Forest Service RMRS-GTR-360. 2017.

Mechanical Treatments—Conifer Removal

Fuel breaks are strategically placed treatments where vegetation is modified in order to 

change fire behavior, making fire control efforts safer or more effective. Common types of fuel 

breaks include road maintenance/roadside disking (brown strips), mowed fuel breaks, and 

vegetative fuel breaks (greenstrips). 

•	 In areas of low resilience and resistance, fuel breaks may increase in priority as sagegrouse habitat probability increases (cells 3B, 3C). Repeated treatments may be necessary to maintain functional fuel breaks.

•	 Key management considerations for the design and placement of fuel breaks are:

o Implemented where fire managers believe they will benefit suppression efforts;

o Designed at large landscape scales, providing multiple options for fire managers;

o Designed collaboratively with interdisciplinary specialists, private landowners, fire 

response partners, and other agencies;

o Include plans for long-term monitoring and maintenance;

o Designed to minimize habitat impacts, including nonnative invasive species introduction and spread, while maximizing potential fire management benefits.

•	 Key ecological considerations for the design and placement of fuel breaks:

o Design fuel breaks in an interdisciplinary setting which addresses the need, cumulative effects, alternative treatments, and possible undesired results;

o Consider ecosystem resilience and resistance and place fuel breaks to minimize 

catastrophic ecological state changes;

o Includes conservation buffers around sagebrush leks, habitat fragmentation thresholds and minimum habitat patch sizes;

o Includes the influence on habitat connectivity between seasonal sage-grouse 

habitats;

o Follow technical guidance related to recommended design features (see Maestas 

et al. 2016b).

Prescribed Fire 

Prescribed fire to address the threat of wildfire includes burning to reduce woody biomass 

resulting from treatments, to control conifer expansion, to reduce hazardous fuels, and to create fuel breaks which augment fire suppression efforts. When setting priorities for prescribed 

fire, consider the following:

•	 Consider alternatives to prescribed burning where other treatment alternatives may meet 

management objectives.

•	 In low resilience and resistance areas, consider prescribed fire only after consultation 

with local biologists and land managers and when:

o Site information, such as state-and-transition models, affirm that the postburn 

trajectory will lead to functioning sagebrush communities. Most low resilience and 

resistance areas that receive <12 in/yr (30.5 cm/yr) of precipitation do not respond 

favorably to burning (see Miller et al. 2014).

o Burning is part of multi-stage restoration projects where burning is required to 

remove biomass following chemical treatments for site preparation or for improved 

chemical applications.

o Monitoring data validates that the preburn composition will lead to successful, native plant dominance postburn

•	 Use prescribed fire cautiously and selectively in moderate to high resilience and resistance areas, after consultation with local biologists and land managers and assessing 

site recovery potential and other management options based on the following: 

o Preburn community composition;

o Probability of invasive species establishment or spread;

o Historic fire regime, and patch size/pattern to be created by burning;

o Wildfire risk and desired fuel loading to protect intact sagebrush; and

o Alternative treatments that may meet objectives.

Chemical Treatment of Nonnative Invasive Plant Species and Seeding

Chemical treatments and seedings are used to decrease invasive species composition and 

increase native species dominance in areas where native perennial grasses and forbs are 

insufficient for site recovery. Chemical and seeding treatments may be selectively applied in 

conjunction with prescribed fire or mechanical treatments. Typically, these treatments are in 
USDA Forest Service RMRS-GTR-360. 2017. 71

response to clear evidence of a nonnative invasive species threat. Areas of higher priority for 

chemical and seeding treatments:

•	 Lower resistance and resilience cells (2A, 2B, 3A, 3B) lacking the ability for natural 

recovery;

•	 Recently disturbed areas where recovery will not occur without chemical or seeding 

treatments;

•	 Areas where investments have been made and objectives cannot be attained without 

chemical or seeding treatments.

Postfire Rehabilitation: General considerations for prioritization of postfire rehabilitation 

efforts are:

•	 Priority generally increases as resilience and resistance decrease and habitat probability 

for sage-grouse increases. High priorities include areas of low to moderate resilience 

and resistance that (1) lack sufficient native perennial grasses and forbs to recover on 

their own and (2) have nearby areas still supporting sage-grouse habitat (cells 2B, 2C, 

3B, 3C). Areas of low habitat probability for sage-grouse (cells 2A, 3A) are generally 

lower priority but may become higher priority in areas that support other resource values 

or that increase connectivity for GRSG populations. 

•	 Areas of higher priority across all cells include:

o Areas where prefire perennial herbaceous cover, density, and species composition 

is inadequate for recovery (see Miller et al. 2015);

o Areas where seeding or transplanting sagebrush is needed to maintain habitat connectivity for sage-grouse;

o Areas threatened by nonnative invasive plants; and

o Steep slopes and soils with erosion potential.

Threat—Sagebrush Reduction

Management strategies

•	 Avoid intentional sagebrush removal (either prescribed fire or mechanical removal) 

across all areas in the West-Central Semiarid Prairies due to relatively limited sagebrush 

availability and extended periods of recovery in the region. Many areas are characterized 

by moderate to moderately low resilience and resistance, and many sagebrush species 

lack the capacity to resprout.

•	 Use caution when attempting to increase herbaceous perennials by reducing sagebrush 

dominance through mechanical or chemical treatments in general. 

o Lower resistance and resilience areas are prone to annual grass increases and 

potential dominance if invasive annual grasses exist in the area before treatment. 

o Pretreatment densities of 2 to 3 native perennial bunch grasses per square meter 

are often necessary for successful increases in perennial herbaceous plants and 

for suppression of invasive annual grasses after treatment in lower resistance and 

resilience areas (Miller et al. 2014, 2015).

Threat—Climate Change

Management strategies

•	 Continue to use best management practices where effects of climate change and its interactions with stressors are expected to be relatively small and knowledge and management capacity are high.

•	 Consider proactive management actions to help ecosystems transition to new climatic 

regimes where climate change and stressor interactions are expected to be severe.

•	 Practice drought adaptation measures such as reduced grazing during droughts, conservation actions to facilitate species persistence, and seeding and transplanting techniques 

more likely to work during drought. Consider developing formal drought management 

plans for livestock grazing. 

•	 Anticipate and respond to species declines such as may occur on the southern or 

warmer edges of their geographic range. 

•	 Favor genotypes for seeding and out-planting that are better adapted to future conditions 

because of pest resistance, broad tolerances, or other characteristics.

•	 Increase diversity of plant materials for restoration activities to provide those species or 

genotypes likely to succeed.
72 USDA Forest Service RMRS-GTR-360. 2017.

•	 Protect future-adapted regeneration from inappropriate livestock grazing.

•	 Monitor transition zones between climatic regimes (the edges) to provide advanced 

warning of range shifts. Plant community shifts that affect management decisions often 

occur between Major Land Resource Areas or Level III Ecoregions.

Threat—Cropland Conversion

Management strategies

•	 Secure Conservation Easements to maintain existing sagebrush grasslands and sagegrouse habitat and prevent conversion to tillage agriculture. Prioritize all areas supporting moderate-to-high sage-grouse habitat probability (cells 1B, 1C, 2B, 2C, 3B, 3C) in locations where tillage risk is elevated (see Sage Grouse Initiative, Cultivation Risk layer).

•	 Secure term leases (e.g., 30 years) to maintain existing sagebrush grasslands and sagegrouse habitat and prevent conversion to tillage agriculture as a secondary strategy to 

Conservation Easements. Prioritize all areas supporting moderate-to-high sage-grouse 

habitat probability (cells 1B, 1C, 2B, 2C, 3B, 3C) especially in locations where tillage risk 

is elevated (see SGI Cultivation Risk layer).

•	 Offer alternatives to farming on expired USDA Conservation Reserve Program (CRP) 

lands through Federal and State programs. Prioritize lands in and around intact habitats 

(cells 1B, 1C, 2B, 2C, 3B, 3C).

•	 Encourage enrollment in the USDA CRP or similar programs to return tilled lands to 

perennial plant communities supporting mixtures of grasses, forbs, and sagebrush where 

there are benefits to sage-grouse. Prioritize lands in and around intact habitats (cells 1B, 

1C, 2B, 2C, 3B, 3C).

Threat—Energy Development

Management strategies

•	 Avoid development, if feasible, in areas with high breeding habitat probability for sagegrouse and high sagebrush cover (cells 1C, 2C, 3C) and steer development in nonhabitat areas (1A, 2A, 3A).

•	 Minimize habitat fragmentation in areas with moderate and high breeding habitat probabilities for sage-grouse (cells 1B, 2B, 3B, 1C, 2C, 3C).

•	 For disturbances that remove vegetation and cause soil disturbance, minimize and mitigate impacts (top soil banking, certified weed-free [including annual bromes] seed mixes, 

appropriate seeding technologies, and monitoring). Plan for multiple restoration interventions in areas with low resilience and resistance (cells 3B, 3C). 

•	 Minimize or co-locate energy transport corridors (e.g., roads, pipelines, transmission 

lines) and limit vehicle access, where feasible. 

•	 Maintain resilience and resistance of existing patches of sagebrush habitat by aggressively managing weeds that may require the following management practices (especially 

important in low resilience and resistant areas—cells 3A, 3B, 3C):

o A weed management plan that addresses management actions specific to a project 

area;

o Use certified weed-free (including annual bromes) gravel and fill material;

o Assess and treat weed populations, if necessary, prior to surface disturbing 

 activities;

o Remove mud, dirt, and plant parts from construction equipment;

o Address weed risk and spread factors in travel management plans;

o Ensure timely establishment of desired native plant species on reclamation sites;

o Use locally adapted native seed, whenever possible;

o Intensively monitor reclamation sites to ensure seeding success, determine presence of weeds, and implement corrective actions as necessary;

o Use mulch, soil amendments, or other practices to expedite reclamation success 

when necessary; and

o Ensure weeds are controlled on stockpiled topsoil.

Threat—Urban and Exurban Development

Management Strategies

•	 Secure conservation easements to maintain existing sagebrush stands and sage-grouse 

habitat. Prioritize areas with high habitat probability for sage-grouse and high sagebrush 

cover (cells 1C, 2C, 3C).
USDA Forest Service RMRS-GTR-360. 2017. 73

7.5 Adapting the Sage-Grouse Resilience and Resistance Matrix 

and Management Strategies to Other Sagebrush Obligate 

Species

Management strategies associated with the sage-grouse habitat matrix are designed to maintain or restore large contiguous areas of sagebrush habitat and to 

recover species distributions and population abundance. Consequently, the priorities 

and strategies are applicable to all sagebrush obligate species that benefit from large 

extents of intact sagebrush habitat at landscape scales. Adapting the habitat matrix 

for species other than GRSG first requires accurately delineating the occupied 

range of the species to ensure that management strategies and treatments target the 

right locations. It then requires identifying the probability of suitable habitat for 

the focal species. Ideally, this would be based on the suite of land cover, climate, 

landform and disturbance variables that characterize species habitat. However, 

rangewide habitat probability models that incorporate these variables have only 

been developed for GRSG and GUSG (Chambers et al. 2016a; Doherty et al. 2016). 

The majority of other sagebrush-associated species have poorly defined range maps. 

Until range-wide models are developed for other species, models developed at the 

ecoregion scale can help guide habitat management strategies for individual species 

or species groups.

For example, in the Wyoming Basins Ecoregion, models for three sagebrush obligate passerines (Brewer’s sparrow, sagebrush sparrow, and sage thrasher) have been 

developed (fig. 31; Aldridge et al. 2011). Both the scale and strength of the relationship between density and landscape cover of sagebrush differ among these species, 

and these models highlight the challenge of utilizing a single metric to characterize 

the landscape for multiple species within the sagebrush biome (fig. 31). However, 

all three species were more likely to occur, and increase in abundance, in areas 

•	 Encourage the protection of existing sage grouse habitat through appropriate land use 

planning and Federal land sale policies. Steer development towards non-habitat (cells 

1A, 2A, 3A) where habitat is unlikely to become suitable through management.

Threat—Livestock Grazing

Management strategies

•	 Manage livestock grazing to maintain a balance of native perennial grasses (warm and/

or cool season species as described in Ecological Site Descriptions for that area), forbs, 

and biological soil crusts to allow natural regeneration and to maintain resilience and 

resistance to invasive plants. Ensure strategies prevent degradation and loss of native 

cool-season grasses in particular. Areas with low to moderate resilience and resistance 

may be particularly vulnerable (cells 2A, 2B, 2C, 3A, 3B, 3C).

•	 Implement grazing strategies that incorporate periodic deferment from use during the 

critical growth period, especially for cool season grasses, to ensure maintenance of 

a mixture of native perennial grasses. This strategy is important across all sites, but 

particularly essential on areas with low to moderate resilience and resistance supporting 

sage-grouse habitat (cells 2B, 2C, 3B, 3C).

•	 Ensure grazing strategies are designed to promote native plant communities and decrease nonnative invasive plants. In ephemeral drainages and higher precipitation areas 

in the West-Central Semiarid Prairies that receive more summer moisture and have 

populations of nonnative invasive plant species, too much rest may inadvertently favor 

species such as field brome, Kentucky bluegrass, and smooth brome. Adjustments in 

timing, duration, and intensity of grazing may be needed to reduce these species.
74 USDA Forest Service RMRS-GTR-360. 2017.

with higher landscape cover of sagebrush. Thus, improving the overall extent 

and condition of sagebrush land cover will likely benefit all three species. 

Development of range-wide models for these species using Breeding Bird Survey 

data (Pardieck et al. 2015) is underway (Donnelly et al. 2016). Preliminary results 

indicate that thresholds for occurrence exist at finer spatial scales (250 m radius) 

and that three occurrence probability categories could be developed at this scale: 

low = 0 to 40 percent, moderate = 40 to 70 percent, and high = 70 to 100 percent 

(fig. 30).

For other sagebrush-associated species that do not currently have these types of 

models, developing habitat requirements will likely involve deriving categories 

of landscape cover of sagebrush for the species of interest (see Chambers et al. 

2014b). If data are available, an evaluation of the appropriate scale for measuring 

sagebrush land cover and the strength of the species’ relationship to sagebrush land 

cover could help ensure that the spatial scale and habitat management strategies 

represent landscapes appropriate for the species. Also, depending on the species 

habitat requirements, other landscape and local factors, such as soil characteristics 

or water availability, may be needed to support other sagebrush dependent species. 

The WAFWA coordinated Sagebrush Science Initiative hopes to facilitate the development of habitat suitability models for additional sagebrush-obligate species in the 

near future.

Figure 31—Maps at the top of the figure depict model output of relative bird density for three sagebrush obligate passerine species (Brewer’s sparrow, sagebrush sparrow, and sage thrasher) in the Wyoming Basins 

Ecoregional Assessment area (Aldridge et al. 2011). Relationship between bird density and landscape 

cover of sagebrush for each species and the availability of sagebrush in the landscape are shown in the 

graphs below the map for each species. The scale and strength of the relationship between bird density and 

landscape cover of sagebrush differ among species highlighting the challenge of utilizing a single metric to 

characterize the landscape for multiple species within the sagebrush biome.
USDA Forest Service RMRS-GTR-360. 2017. 75

8. Delineating Habitats For Targeted Management 

Intervention at the Biome and Ecoregion or 

Management Zone Scale

Effective conservation of sagebrush habitat and sagebrush obligate species 

benefits from an approach that prioritizes the best management practices in the 

most appropriate places. This section describes an approach for targeting areas for 

management based on four types of data: (1) species distribution and population 

abundance, (2) species habitat requirements, (3) ecosystem resilience and resistance, 

and (4) persistent ecosystem threats and land use and development threats. The 

approach involves a geospatial analysis in which the four types of data are overlaid 

and mapped. Here, key data layers are identified, the steps used to overlay and 

analyze the various data layers are discussed, and interpretations of the maps and 

analyses are provided. The geospatial data, maps, and models used to support these 

analyses are listed in Appendix 8 and provided through the USGS ScienceBase 

(https://www.sciencebase.gov/catalog/item/576bf69ce4b07657d1a26ea2) and 

BLM Landscape Approach Data Portal (http://www.blm.gov/wo/st/en/prog/more/

Landscape_Approach/dataportal.html).

8.1 Assessing Priority Areas for Habitat Management: Key Data 

Layers and Their Use

8.1.1 Priority Areas for Conservation of GRSG

Priority Areas for Conservation (PACs) have been delineated using available habitat and population data to identify areas critical for conserving GRSG populations 

(FWS 2013). These areas can be used as a first filter in prioritizing management actions for GRSG. Habitats outside of PACs are also important to consider where they 

capture important seasonal habitats and provide genetic and habitat linkages (FWS 

2013). The PACs were generally created using coarse scale approaches and do not 

always capture entire populations.

Many new products and habitat models have been developed since the PACs were 

delineated that can be used to help target conservation actions. Crist et al. (2017) 

recently evaluated habitat connectivity among PACs. Targeting conservation actions 

in the areas of high movement potential identified in Crist et al. (2017) may help 

maintain connected populations across PACs. See Appendix 9 for a detailed description. Without maintaining corridors to larger priority areas or a clustered group, 

isolation of small priority areas could lead to regional loss of GRSG.

8.1.2 Breeding Habitat Probabilities and Population Indices for GRSG

Mapping areas with high breeding habitat probabilities and population indices 

is a key aspect of prioritizing areas for management. The breeding habitat models 

provide information on habitat characteristics (fig. 25; table 5; Doherty et al. 2016), 

and the breeding habitat model probability classes show the proportion of active 

and inactive leks in each Management Zone for GRSG (table 7). These areas can be 

used to prioritize areas for management based on the probability of an area providing breeding habitat.

The population index model combines information from the breeding habitat 

model with lek count data to provide indices and spatial depictions of GRSG relative abundance (fig. 26; Doherty et al. 2016). Because the output of the population 

index model is a continuous surface or map, it can be used to focus conservation 
76 USDA Forest Service RMRS-GTR-360. 2017.

efforts on specified portions of GRSG populations identified by stakeholders (e.g., 

highest 25 percent or 85 percent of the population). Because of the large area currently occupied by GRSG, the population index model can be used to better focus 

management actions on areas that: (1) currently support viable populations, (2) 

provide connectivity between population centers, and (3) ensure that habitat restorations outside of breeding concentration areas occur in close enough proximity to 

allow successful recolonization of reclaimed habitat (Coates et al. 2016a).

The breeding habitat probability and population index models provide key elements in prioritizing target areas for management. However, because the habitat and 

population index models are based on lek data, other important seasonal habitats 

such as late brood-rearing and winter habitat may not be included. Models of 

seasonal habitat selection have been developed for Wyoming (Fedy et al. 2014), 

Nevada and northeastern California (Coates et al. 2016b), and Utah (Dahlgren et al. 

2016), which can be used to inform management actions in these areas. Also, efforts 

are underway to develop rangewide GRSG seasonal habitat information (Cameron 

Aldridge, USGS, personal communication). Until this product is available, managers can rely on local knowledge or existing local-scale information (e.g., telemetry 

locations and genetic data) about seasonal movements, linkages among areas of 

sage-grouse use, and relative habitat quality.

8.1.3 Distribution and Species Population Data for Other Sagebrush 

Obligate Species

For most sagebrush obligate species, less information is available on species distributions and populations than for GRSG. An exception is sagebrush obligate passerines, but analyses of habitat requirements for these birds have focused on local 

populations and smaller scales (Donnelly et al. 2016; Hanser et al. 2011). For other 

species of interest, such as mule deer (Odocoileus hemionus), analyses are generally 

focused on specific ecoregions or are State-based (e.g., Copeland et al. 2014). For 

most invertebrates, reptiles, amphibians, and small mammals, only coarse habitat 

distribution data and little population data are available. The Sagebrush Science 

Initiative coordinated by WAFWA is working to identify focal species, compile 

available data for these species, and determine information gaps on these species 

for the sagebrush biome. Regional analyses may also help identify resources and 

species of concern (BLM Rapid Ecoregional Assessments); http://www.blm.gov/

wo/st/en/prog/more/Landscape_Approach/reas.html; Hanser et al. 2011, Wyoming 

Basin; Wisdom et al. 2000, Columbia Basin; Wisdom et al. 2005, central Great Basin).

8.1.4 Landscape Cover of Sagebrush

In the absence of spatially explicit habitat models like those developed for GRSG 

(Doherty et al. 2016) and GUSG (Chambers et al. 2016a), landscape cover of sagebrush can provide important information on species habitat requirements (figs. 5, 

28, 29). Landscape cover of sagebrush is a measure of large, contiguous patches of 

sagebrush on the landscape and is calculated from remote sensing databases such 

as LANDFIRE (see Appendices 7, 8). Categories of sagebrush landscape cover 

required to sustain species populations can be developed as illustrated for Brewer’s 

sparrow, sagebrush sparrow, and sage thrasher (fig. 30). Sagebrush landscape cover 

datasets can be created using a moving window to summarize the proportion of area 

dominated by sagebrush that surrounds each 30-m pixel (radius determined by species habitat requirements), and then assigning those areas to the different categories 
USDA Forest Service RMRS-GTR-360. 2017. 77

(figs. 28, 29; see Appendix 7). Sagebrush cover from sources such as LANDFIRE 

may not exclude recent fire perimeters, therefore it may be necessary to either 

include recent fires in the analysis of landscape cover of sagebrush or display them 

separately. The time required for a burned area to provide desired GRSG habitat 

will depend on the characteristics of the fire, resilience and resistance of the area, 

and postfire management.

8.1.5 Resilience to Disturbance and Resistance to Nonnative Invasive 

Plants

Soil temperature and moisture regimes provide one of our best available data 

sets for evaluating resilience and resistance in the sagebrush biome (Chambers et 

al. 2014b, 2016a; Maestas et al. 2016a). The available data for soil temperature 

and moisture regimes were recently compiled for the western and eastern range of 

GRSG (Maestas et al. 2016a; Appendix 2), and relative resilience and resistance 

categories were developed from soil temperature and soil moisture subclass data 

(figs. 6, 32; Appendix 2; Maestas et al. 2016a). The soil temperature and moisture 

Figure 32—The soil temperature and moisture regimes categorized according 

to high, moderate and low resilience and resistance. The soil temperature and 

moisture regime data used in this report and the soil temperature and moisture 

regime categories are explained in Appendix 2. More detailed categorizations 

can be used at finer regional and local scales. The relationships of the soil temperature and moisture regimes to the predominant ecological types are in table 6.
78 USDA Forest Service RMRS-GTR-360. 2017.

regimes have been linked to dominant ecological types (table 6) and their associated state-and-transition models (Appendices 5, 6) for sagebrush ecosystems. Soil 

temperature and moisture regimes are a key component in prioritizing areas for 

management and evaluating effective management strategies at multiple scales 

(tables 8, 9).

8.1.6 Habitat Threats

Assessing the magnitude of persistent ecosystem and land use and development 

threats provides important insights into target areas for treatment and the most appropriate management strategies. Although habitat threats are considered in GRSG 

breeding habitat and in the GRSG population index models (Doherty et al. 2016), 

depicting threats to different populations is necessary to assess the magnitude of 

the threats and determine viable management strategies. Depicting threats is also 

necessary for determining management strategies for other sagebrush obligate or 

dependent species. The threats and data sources considered in this report largely 

follow those in IGSDMS (2014) and are in Appendix 8. New data layers included in 

the Science Framework are cheatgrass occurrence and large fire probability.

8.1.6.1 Cheatgrass Occurrence

Knowledge of the current distribution and abundance of cheatgrass on the landscape is a key component in planning and executing strategies to protect sagebrush 

ecosystems. Models of cheatgrass occurrence developed using biophysical and 

climate data can identify environmental characteristics that increase invasion risk, 

and the spatial outputs can help identify invaded areas. Downs et al. (2016) recently 

used ecological models based on a suite of climatic and biophysical variables and 

remotely sensed measures of peak NDVI (normalized difference vegetation index) 

to develop a map of cheatgrass occurrence (0 to 2 percent cover and >2 percent cover) 

across the historic range of sage-grouse (fig. 33). Field measurements of cheatgrass 

cover across the study area were used to develop correlations to these variables for 

use in the models. However, limited field measurements may have resulted in an 

underestimate of cheatgrass occurrence in the eastern portion of the range where 

cheatgrass is an emerging threat (Mealor et al. 2013). Thus, although the cheatgrass 

occurrence data layer can help inform management decisions in the eastern portion 

of the range, additional ecoregional or local information may be needed.

8.1.6.2 Large Fire Probability

Large fire probability can be used by managers in fire risk assessments to identify 

where habitats may be at a higher risk from fire and where recovery from fire may 

be more challenging based on resilience and resistance (see Appendix 10). A large 

fire probability layer was developed to depict the likelihood of large fires (>300 ac) 

over a 100-year period across the conterminous United States (Short et al. 2016). 

Spatial burn probabilities were modeled using LANDFIRE ecological systems, fuel 

and terrain data, historical fire occurrence and weather data, and fire danger rating 

information. To obtain estimates of large fires, fire ignition and growth were simulated for 10,000 to 100,000 potential annual weather scenarios using a geospatial 

Fire Simulation (FSim) system developed by the U.S. Forest Service, Missoula 

Fire Sciences Laboratory (Finney et al. 2011). The large fire burn probability 

layer shown here was extracted from the national dataset to represent likelihood 
USDA Forest Service RMRS-GTR-360. 2017. 79

of wildfire in absence of suppression efforts specifically for the sagebrush biome 

(fig. 34). Large fire probability can be used by managers in the sagebrush biome for 

mid-scale fire risk assessments to identify where habitats may be at a higher risk 

from fire and where recovery from fire may be more challenging based on resilience 

and resistance (see Appendix 10).

8.1.6.3 Other Data Sources for Threats

More refined data products are often available at mid- to local-scales. For 

example, BLM Rapid Ecoregional Assessments contain a large amount of 

geospatial data that may be useful in providing regional information on vegetation types and persistent and land use and development threats across most of the 

range of GRSG (https://www.blm.gov/wo/st/en/prog/more/Landscape_Approach/

reas.html). High resolution geospatial data for cultivation risk layers are available (Smith et al. 2016), and piñon and juniper landscape cover (Falkowski et al. 

2017) is available for the western portion of the range and is being developed for 

the eastern portion of the range (http://map.sagegrouseinitiative.com/). Also, a 

Figure 33—Percent cover of cheatgrass from ecological models based on 

climate and biophysical variables, remotely sensed measures of NDVI (normalized difference vegetation index), and field measurement of cheatgrass cover 

for the historic range of sage-grouse (Downs et al. 2016).
80 USDA Forest Service RMRS-GTR-360. 2017.

cheatgrass data layer was developed for the northern Great Basin in 2015 based 

on high frequency remote sensing data https://www.sciencebase.gov/catalog/

item/55ad3a16e4b066a2492409d5 (Boyte and Wylie 2016). Land managers can 

evaluate the available land cover datasets for the targeted area and select those datasets with the highest resolution and accuracy.

8.1.7 Climate Change

Climate change projections allow managers to consider potential changes in 

climate when prioritizing areas for management and evaluating management 

strategies.

8.1.7.1 Climate Change Projections for Key Climate Variables

For the Science Framework, climate change projections were developed for climate variables important to sagebrush ecosystems (see Appendix 3). Eleven general 

circulation models (GCMs) were used to project climate changes for two future 

time periods (2020−2050 and 2070−2100) and for two representative concentration 

pathways (RCP 4.5 and RCP 8.5), which assume moderate and high greenhouse gas 

Figure 34—Large fire probability for the sagebrush biome derived by simulating fire ignition and growth using the Fire Simulation (FSim) system (Finney et 

al. 2011; Short et al. 2016).
USDA Forest Service RMRS-GTR-360. 2017. 81

emission scenarios, respectively. The climate projections for the entire sagebrush 

biome and the different geographic areas are in Section 5.2, “Persistent Ecosystem 

Threats: Climate Change.” The maps and graphs in the appendix illustrate the magnitude of change projected and can be used similarly to data layers for persistent 

ecosystem threats.

8.1.7.2 Wyoming Big Sagebrush Climate Niche Models

Climate is the predominant factor affecting plant distributions and species adaptations to their environment. Understanding how climate change could affect species 

distributions requires two data elements: (1) species and subspecies presence and 

absence locations and (2) gridded climate surfaces. Still and Richardson (2015) 

projected the contemporary and mid-century distribution of Wyoming big sagebrush 

using presence and pseudo-absence points. This data has been reanalyzed using 

two representative concentration pathways (RCP 4.5 and RCP 8.5) from the fifth 

phase of the IPCC and CMIP5 for the Science Framework. Following Crookston 

and Rehfeldt (2008), gridded climate surfaces of RCP 4.5 and 8.5 were downscaled 

(~1 km2

) for three time periods: 2025−2035, 2055−2065, and 2085−2095. The 

presence and absence model of Wyoming big sagebrush developed from climate 

variables (see Appendix 3) were mapped for these time periods and RCPs (fig. 35).

This modeling process provided a projection of areas more susceptible and more 

resilient to climate change. The model also indicated a potential major decline in the 

area suitable for Wyoming big sagebrush, which is currently the most prevalent big 

sagebrush species in the Great Basin. These projections of climate can also serve 

to overlay adaptive genetic variation to assess the impact of climate change at the 

population level and provide guidance in seed transfer for restoration (Chaney et al. 

2016; Richardson et al. 2016). See Appendix 11 for an explanation of seed transfer 

guidelines for the sagebrush biome.

8.2 Assessing Priority Areas for Habitat Management: Overlaying 

Data Layers

8.2.1 Assessing Differences in Resilience and Resistance and 

Persistent Ecosystem Threats at the Sagebrush Biome Scale

The ecoregions and Management Zones within the sagebrush biome have differences and similarities in: (1) resilience and resistance (fig. 32; table 6), (2) persistent 

ecosystem (e.g., figs. 7, 10) and land use and development threats (figs. 14, 16, 18, 

20), and (3) GRSG breeding habitat probabilities (fig. 25) and population indices 

(fig. 26). An understanding of these differences can help to inform resource needs 

and budget prioritization at the sagebrush biome scale. A summary of relative 

resilience and resistance, GRSG breeding habitat probabilities, and GRSG breeding populations is provided for each Management Zone and the PACs within each 

Management Zone in Appendix 12. In addition, a summary of wildfire area is provided as one example of a widespread persistent ecosystem threat that differs across 

Management Zones, but that significantly influences management strategies in those 

Management Zones with high wildfire areas (Appendix 13).

Overlaying breeding habitat probabilities with resilience and resistance categories 

for the PACs in each Management Zone provides information on the capacity of the 

Management Zones to support breeding populations and the relative risk of persistent ecosystem threats such as invasive annual grasses and wildfire. In the eastern 
82 USDA Forest Service RMRS-GTR-360. 2017.

part of the range (MZ I, II, VII), a large amount of the area with high to moderate 

breeding habitat probabilities has high to moderate resilience and resistance indicating that much of this area has the capacity to recover from disturbances given 

appropriate management (fig. 36; Appendix 12). In the western part of the range 

(MZ III, IV, V, VI), large areas with high to moderate breeding habitat probabilities 

are characterized by low resilience and resistance (fig. 36; Appendix 12). The implications of these differences in resilience and resistance are detailed in Sections 

6 and 7. In general, areas with low resilience and resistance are more susceptible to 

Figure 35—A climatic niche model for Wyoming big sagebrush (Artemisia tridentata ssp. 

wyomingensis) projected for three decades and two greenhouse gas emission scenarios 

(representative concentration pathways, RCP). The columns show scenarios with moderated emissions, RCP 4.5, and unabated emission, RCP 8.5. The rows reflect the decade 

surrounding 2030, 2060, and 2090. Colors represent areas of expansion, contraction, and 

stability. The climatic niche model is adapted from Still and Richardson (2015).
USDA Forest Service RMRS-GTR-360. 2017. 83

invasive annual grasses such as cheatgrass and require longer periods for recovery 

from either disturbances or management treatments (Chambers et al. 2014a,c; Miller 

et al. 2013; Pyke et al. 2015a,b). However, invasive annual grasses are an emerging 

threat in warmer and drier areas of the eastern part of the range (Baker 2011; Brooks 

et al. 2015; Knight et al. 2014; Mealor et al. 2013) and populations often increase on 

sites disturbed by development activities (Manier et al. 2011, 2014a,b; Nielson et al. 

2011).

 Overlaying wildfire area from 1984−1999 and from 2000−2014 with resilience 

and resistance categories and evaluating differences in fire numbers and size for 

the PACs in each Management Zone provides information on the differences in the 

magnitude of the threat among Management Zones. In the western part of the range 

(MZ III, IV, V, VI), total fire area, numbers of fires, and fire size have generally 

increased from 1984−1999 to 2000−2015 (Appendix 13). Fire area within the PACs 

in MZ IV, V, and VI doubled to tripled from 1984−1999 (8, 6, and 4 percent for MZ 

IV, V, and VI respectively) to 2000−2015 (19, 17, and 13 percent for MZ IV, V, and 

VI, respectively) (fig. 37; Appendix 13). The exception for the western part of the 

range was MZ III where fire area remained at about 4 percent from 1984−1999 to 

2000−2015.

Figure 36—Greater sage-grouse breeding habitat probabilities by resilience and resistance (R&R) class in thousands 

of acres for Priority Areas for Conservation (PACs; FWS 2015) within the Management Zones (MZs; Stiver et al. 2006). 

Greater sage-grouse breeding habitat probabilities were based on 2010–2014 lek data (Doherty et al. 2016). The resilience and resistance classes are explained in Appendix 2. In the eastern part of the range (MZ I, II, VII), a large amount 

of the area with high to moderate breeding habitat probabilities has high to moderate resilience and resistance indicating 

that much of this area has the capacity to recover from disturbances given appropriate management. In the western part 

of the range (MZ III, IV, V, VI), large areas with high to moderate breeding habitat probabilities are characterized by low 

resilience and resistance are more susceptible to invasive annual grasses such as cheatgrass and require longer periods 

for recovery from either disturbances or management treatments.
84 USDA Forest Service RMRS-GTR-360. 2017.

A

B

Figure 37—(A) Thousands of acres burned within the occupied range and (B) within Priority 

Areas for Conservation (PACs; FWS 2015) for Greater sage-grouse within each Management 

Zone (MZs; Stiver et al. 2006) by resilience and resistance (R&R) class. Data are for fires 

larger than 1,000 acres (MTBS 2014). The resilience and resistance classes are explained in 

Appendix 2. Fire area within the PACs in MZ IV, V, and VI doubled to tripled from 1984−1999 

(8%, 6%, and 4% for MZ IV, V, and VI respectively) to 2000−2015 (19%, 17%, and 13% for 

MZ IV, V, and VI, respectively).

In contrast, in the eastern portion of the range (MZ I, II, VII), fire area within the 

PACs is smaller and has shown little change from 1984−1999 (0.4, 1.5, and 0.3 percent for MZ I, II, VII, respectively) to 2000−2015 (1.6, 1.2, and 0.3 percent for MZ 

I, II, and VII, respectively) (fig. 37; Appendix 13). Overall, this analysis is largely 

consistent with fire areas obtained by Brooks et al. (2015) and with their recent 

analyses showing that the western part of the range is exhibiting more fire than the 

eastern part of the range.

Climate change and other human-induced factors, including more extreme fire 

weather, invasive annual grasses, and human-caused fire starts, are resulting not 

only in increases in burn area, but also in individual fires of unprecedented size 

(Brooks et al. 2015; McKenzie et al. 2004). Since 1984, 1,021 fires over 1,000 acres 
USDA Forest Service RMRS-GTR-360. 2017. 85

(405 ha) burned within PACs in the western portion of the range, but just 12 large 

fires, 100,000 acres (40,469 ha) to 500,000 acres (202,343 ha) in size, accounted 

for 27 percent of the area burned (table 10). An additional 187 fires, 10,000 acres 

(40.5 km2

) to 100,000 acres (40,469 ha) in size accounted for 47 percent of the area 

burned. The majority of the fire area was concentrated during years of large fires as 

found elsewhere (Brooks et al. 2015).

A relatively high percentage of total fire area (37 percent or more) in the western 

portion of the range was in the low resilience and resistance category (fig. 37). 

Historically, areas with low resilience and resistance typified by Wyoming big 

sagebrush burned less frequently than higher resilience and resistance areas characterized by mountain big sagebrush and mountain brush due to lower productivity 

and thus lower fuel loads (Miller et al. 2013). This summary indicates that these low 

resilience and resistance areas currently appear to be burning at least as frequently 

as the higher resilience and resistance areas. Similar, recent analyses by Brooks et 

al. (2015) provide strong evidence for increased fire area for all sagebrush types 

(based on LANDFIRE biophysical settings; Rollins 2009) combined in the Snake 

River Plain and Columbia Plateau.

8.2.2 Prioritizing Areas for Management at Ecoregion and Management 

Zone Scales

Assessments of priority areas for management are typically conducted at the scale 

of ecoregions or Management Zones (fig. 1; table 2) because of similarities in biophysical characteristics and thus management strategies and treatments. The process 

involves overlaying key data layers in a geospatial analysis to both visualize and 

quantify: (1) species locations and abundances, (2) the probability that an area has 

suitable habitat, (3) the likely response to disturbance or management treatments, 

and (4) the dominant threats. The maps and analyses that managers derive from this 

process are an essential component of prioritizing areas for management actions and 

developing management strategies. The steps in the geospatial analysis are based on 

those identified in table 1 and are described below. The maps used to illustrate the 

steps are from the GRSG range.

 1. First, determine focal species and resources and delineate their distribution 

and area using the best information available. For GRSG, this includes PACs, 

breeding habitat probabilities, the population index (Doherty et al. 2016), and 

breeding bird densities (figs. 25, 26).

Table 10—The number, area, and percentage of fires greater 

than 1,000 acres (4 km2

) (MTBS 2014) by fire size within the 

Priority Areas for Conservation (PACs; FWS 2013).

Fire size Number Fire area

(acres) of fires (acres) (%)

1,000 to 2,000 338 485,696 5 

2,000 to 5,000 325 1,022,302 10

5,000 to 10,000 159 1,117,731 11

10,000 to 100,000 187 4,621,893 47

100,000 to 500,000 12 2,576,175 27

Total 1,021 9,823,798 100
86 USDA Forest Service RMRS-GTR-360. 2017.

Second, determine the probability of suitable habitat. For GRSG, this is the 

breeding habitat probability (table 7; low = 0.25 to <0.50, moderate = 0.50 to 

<0.75, high = 0.75 to 1.0). For other species (e.g., mule deer, localized pygmy 

rabbit populations), available species distribution data and habitat selection 

modeling can be used. For many sagebrush-obligate species, the probability 

of suitable habitat will likely be based on landscape cover of sagebrush 

until models similar to the breeding habitat model for GRSG are developed 

(Doherty et al. 2016).

2. Create the resilience and resistance layer using categorized soil temperature 

and moisture regimes (figs. 6, 32; Appendix 2; Maestas et al. 2016a).

First, overlay resilience and resistance categories with the probability of 

suitable breeding habitat (Doherty et al. 2016) for the assessment area (fig. 38). 

Figure 38— Greater sage-grouse (GRSG) breeding habitat probabilities based 

on 2010–2014 lek data (Doherty et al. 2016) intersected with resilience and resistance categories developed from soil temperature and moisture regimes. The soil 

temperature and moisture regime data used in this report and the resilience and 

resistance categories are explained in Appendix 2. This map provides a spatial depiction of the sage-grouse habitat resilience and resistance matrix.
USDA Forest Service RMRS-GTR-360. 2017. 87

This layer provides information on how areas that can support focal species 

and resources will respond to both disturbance and management treatments, 

specifically, the likelihood of recovery and risk of conversion to undesirable 

states. It can be related directly to the sage-grouse habitat resilience and 

resistance matrix (fig. 38; table 8) and management strategies (table 9). 

Calculating the areas in the different categories by ecoregion, or PACs within 

Management Zones, can help identify target areas for management of GRSG. 

Weighted or scaled measures of suitable habitat probabilities for ecoregions, 

or PACs within Management Zones, can be used to help ensure range wide 

consistency in determining target areas for management.

Second, overlay resilience and resistance with species population abundance 

measures. For GRSG, this is the population index model (fig. 39). For the 

purposes of this report, the population index model was classified into two 

categories (high = 80 percent of the breeding population; low = the remaining 

20 percent of the breeding population). These categories can be based on 

assessment objectives and identified by stakeholders. This layer provides 

information on areas that currently support large populations, have potential to 

increase connectivity between populations, and are close enough to population 

centers so that the species can recolonize reclaimed habitats. It can be related 

directly to the sage-grouse habitat resilience and resistance matrix (fig. 39; 

table 8) and management strategies (table 9). Calculating the areas in the 

different categories by ecoregion, or PACs within Management Zones for 

GRSG, can further refine areas for management of GRSG habitat.

4. Assess the extent and magnitude of the predominant threat(s). This will typically 

involve overlaying the resilience and resistance layer with the areas supporting 

high breeding habitat probabilities and the predominant threat(s). Threats vary by 

ecoregion and Management Zone. Developing thresholds (ecological minimums) 

for the extent and magnitude of the threat (e.g., land cover of juniper and piñon 

and invasive annual grasses, density of oil and gas wells, active mineral claims, 

road density, etc.) above which the habitat can no longer support a focal species 

or resource and incorporating these into the geospatial analyses can further inform 

prioritization of areas for management. For example, ability of GRSG to maintain 

active leks decreases significantly when conifer canopy exceeds 2 percent and 

extirpation occurs with canopy cover above 4 percent in the immediate vicinity 

(within 1000 m) of the lek (Baruch-Mordo et al. 2013).

5. Prioritize areas for management. The maps and data derived from the prior 

steps and the sage-grouse habitat matrix (table 8) are used to determine target 

areas for management within the assessment area. Key considerations follow.

a. Does the area provide suitable habitat and support species populations? 

For GRSG, this is the breeding habitat probability and breeding bird 

density (table 8 cells 1B, 2B, 3B, 1C, 2C, 3C).

b. If the area has reduced habitat suitability, can it be improved by active 

management? These areas may be at higher risk of becoming unsuitable 

with additional disturbances that degrade habitat (table 8 cells 1B, 2B, 

3B).
88 USDA Forest Service RMRS-GTR-360. 2017.

Figure 39—Relative percent of Greater sage-grouse (GRSG) population based 

on breeding abundance during 2010–2014 (Doherty et al. 2016) intersected with 

resilience and resistance categories developed from soil temperature and moisture 

regimes. The soil temperature and moisture regime data used in this report and the 

resilience and resistance categories are explained in Appendix 2. The high value 

represents 80 percent of the GRSG breeding population; the low value represents 

the remaining 20 percent of the breeding population. This map provides information 

on areas that currently support large populations of breeding birds, have potential 

to increase connectivity between populations, and are close enough to population 

centers so that the birds can recolonize reclaimed habitats.

c. If the area is at risk due to low resilience and resistance but has high 

conservation value for the focal species, can it be maintained or improved through protective management (table 8 cells 3B, 3C)? These 

areas have the potential for rapid conversion to invasive annual grasses, 

but could be maintained or improved by aggressive weed management, 

fire suppression, and passive management activities such as improved 

livestock management.
USDA Forest Service RMRS-GTR-360. 2017. 89

6. Determine the most appropriate management strategies. The maps and data 

derived from the prior steps and the sage-grouse habitat matrix (table 8) are 

also used to determine management strategies. At the scale of the ecoregion, 

or PACs within Management Zones for GRSG, management strategies 

are developed that require interagency coordination at the mid-scale, e.g., 

State, National Forest, etc. Examples of these types of strategies include: 

(1) prepositioning firefighting resources within fire-prone areas that provide 

suitable habitat and support species populations as is being done for areas in 

the Great Basin with high fire risk (BLM 2015a); (2) coordinating efforts to 

use EDRR to prevent expansion of invasive annual grasses and other invasive 

plants; (3) assessing habitat connectivity among PACs and species populations 

to develop coordinated approaches to management strategies, such as conifer 

removal and other habitat improvements, to decrease fragmentation (e.g., 

Coates et al. 2016b); (4) refining livestock management strategies and offering 

flexibility to promote or perpetuate perennial grass and forb establishment 

and promote recovery of soil biotic crusts; and (5) evaluating climate change 

projections and developing effective adaptation strategies.

9. Determining Appropriate Management Treatments at 

Local Scales

Once priority areas and overarching strategies are identified, higher resolution 

spatial data are combined with local information and knowledge to help managers 

and stakeholders determine the most appropriate management strategies and identify 

project areas. The sage-grouse habitat matrix (table 8) and the general criteria for 

prioritizing areas for management in Step 6 of the prior section can aid in selecting 

areas for treatment that will benefit sagebrush ecosystems and species populations. 

Also, information on the resilience and resistance of the area and the predominant 

threats can help in determining appropriate management strategies and treatments 

(table 9).

9.1 Steps in the Process

Steps in the process of determining the suitability of an area for treatment and 

the most appropriate treatment(s) include: (1) identify the different ecological sites 

that occur across the area and determine their relative resilience to disturbance and 

resistance to invasive annual grasses; (2) evaluate the current ecological dynamics 

of the ecological sites and, where possible, their restoration pathways; and (3) select 

actions with the potential to increase ecosystem functioning and habitat connectivity 

(see Miller et al. 2014, 2015 and Pyke et al. 2015a,b for detailed descriptions of this 

process). Anticipating changes like climate warming and monitoring management 

outcomes can be used to adapt management over time. A general approach that uses 

questions to identify the information required in each step is described in table 11. 

These questions can be modified to include the specific information needed for each 

project area and for treating different ecological site types. This format is used in 

Miller et al. 2014, 2015.
90 USDA Forest Service RMRS-GTR-360. 2017.

9.1.1 Ecological Site Descriptions

Ecological site descriptions and their associated state-and-transition models 

provide essential information for determining treatment feasibility and type of 

treatment. Ecological site descriptions are part of a land classification system that 

describes the potential of a set of climate, topographic, and soil characteristics and 

natural disturbances to support a dynamic set of plant communities (Bestelmeyer 

et al. 2009; Stringham et al. 2003). The Natural Resource Conservation Service 

(NRCS) soil survey data (http://soils.usda.gov/survey/), including soil temperature/

moisture regimes and other soil characteristics, are integral to ecological site 

description development. Ecological site descriptions have been developed by the 

NRCS and their partners to assist land management agencies and private landowners with making resource decisions, and are often available for the Management 

Zones. For a detailed description of ecological site descriptions and access to available ecological site descriptions see http://www.nrcs.usda.gov/wps/portal/nrcs/main/

national/technical/ecoscience/desc/. Ecological site descriptions assist managers to 1

Table 11—Questions and considerations for conducting fuels management, fire rehabilitation, and restoration 

treatments (modified from Miller et al. 2014, 2015).

Steps in the process Questions and considerations

I. Assess potential treatment 

area and identify ecological 

sites

1. Where are priority areas for fuels management, fire rehabilitation or 

restoration within the focal area? Consider sage-grouse habitat needs 

and resilience and resistance.

2. What are the topographic characteristics and soils of the area? Verify 

soils mapped to the location and determine soil temperature and 

moisture regimes. Collect information on soil texture, depth, and basic 

chemistry for restoration projects.

3. How will topographic characteristics and soils affect vegetation recovery, 

plant establishment, and erosion? Evaluate erosion risk based on 

topography and soil characteristics. 

4. What are the potential native plant communities for the area? Match soil 

components to their correlated ESDs. This provides a list of potential 

species for the site(s).

II. Determine current state 

 of the site

5. Is the area still within the reference state for the ecological site(s)? 

III. Select appropriate action 6. How far do sites deviate from the reference state? How will treatment 

success be measured?

7. Do sufficient perennial shrubs and perennial grasses and forbs exist to 

facilitate recovery? 

8. Are invasive species a minor component? 

9. Do invasive species dominate the sites while native life forms are 

missing or severely under represented? If so, active restoration is 

required to restore habitat.

10. Are species from drier or warmer ecological sites present? Restoration 

with species from the drier or warmer sites should be considered. 

11. Have soils or other aspects of the physical environment been altered? 

Sites may have crossed a threshold and represent a new ecological site 

type requiring new site-specific treatment/restoration approaches.

IV. Determine post-treatment 

management 

12. How long should the sites be protected before land uses begin? In 

general, sites with lower resilience and resistance should be protected 

for longer periods. 

13. How will monitoring be performed? Treatment effectiveness monitoring 

includes a complete set of measurements, analyses, and a report.

14. Are adjustments to the approach needed? Adaptive management is 

applied to future projects based on consistent findings from multiple 

locations.
USDA Forest Service RMRS-GTR-360. 2017. 91

step-down generalized vegetation dynamics, including the concepts of resilience 

and resistance, to local scales. For example, variability in soil characteristics and the 

local environment (e.g., average annual precipitation as indicated by soil moisture 

regime) can strongly influence plant community resilience to disturbance and resistance to nonnative invasive species (table 6). The relative resilience and resistance 

of an ecological site can be used to help determine the most appropriate management actions.

A tool has recently been developed through the Web Soil Survey that produces a 

“Sagebrush Ecosystem Resilience and Resistance Soils Report” based on the approach developed in Miller et al. (2014, 2015) (http://websoilsurvey.nrcs.usda.gov/

app/). It provides managers with necessary information to assess the soil characteristics of a project area and determine the area’s relative resilience to disturbance and 

management treatments and resistance to nonnative invasive annual grasses.

9.1.2 State-and-Transition Models

State-and-transition models are a central component of ecological site descriptions 

that are widely used by managers to illustrate changes in plant communities and 

associated soil properties, causes of change, and effects of management interventions (Briske et al. 2005; NRCS 2015; Stringham et al. 2003) including in sagebrush 

ecosystems (Barbour et al. 2007; Boyd and Svejcar 2009; Chambers et al. 2014c; 

Forbis et al. 2006; Holmes and Miller 2010). These models describe the alternative 

states, ranges of variability within states, and processes that cause plant community 

shifts within states as well as transitions among states within ecological types or 

sites (Caudle et al. 2013). State-and-transition models use the concepts of states

(a relatively stable set of plant communities that are resilient to disturbance) and 

transitions (change among alternative states caused by disturbances or other drivers) to describe the range in composition and function of plant communities within 

ecological site descriptions (Stringham et al. 2003; see Appendix 1 for definitions).

The reference state is based on the natural range of conditions associated with the 

historical range of variation and often includes several plant communities (phases) 

that differ in dominant plant species relative to type and time since disturbance 

(Caudle et al. 2013). Alternative states describe new sets of communities that result 

from factors such as inappropriate livestock use, invasion by nonnative species, or 

changes in fire regimes. Changes or transitions among states often are characterized 

by thresholds or conditions that may persist over time without active intervention, 

potentially causing irreversible changes in community composition, structure, and 

function. Restoration pathways are used to identify the environmental conditions 

and management actions that will facilitate return to a previous state.

Generalized state-and-transition models that follow current interagency guidelines 

(Caudle et al. 2013) and that are aligned with the dominant ecological types in table 

6 are provided in Appendices 5 and 6. These state-and-transition models are generally applicable to MZ I (West-Central Semiarid Prairies), MZs II and VII (Wyoming 

Basin and Central Middle Rockies; Colorado Plateau and Southern Rockies), and 

MZs III, IV, and V (Central Basin and Range, Northern Basin and Range, and Snake 

River Plain).
92 USDA Forest Service RMRS-GTR-360. 2017.

9.2 Examples of How to Apply the Concepts and Tools

Examples of the approach discussed in the Science Framework are provided 

below for three areas that support GRSG populations but differ in relative resilience 

and resistance as indicated by soil temperature and moisture regimes and the dominant habitat threat.

9.2.1 Example 1: East-Central Montana

This area is characterized primarily by cool and summer moist bordering on 

dry soil temperature and moisture regimes (fig. 40) with moderate resilience and 

resistance (table 8 cells 2A, 2B, 2C). Most of the area is privately owned (fig. 41), 

and large cropland areas exist adjacent to PACs with moderate to high GRSG 

Figure 40—Soil temperature and moisture regimes by soil moisture subclass for 

an area with agricultural conversion in eastern Montana that is in the Northwestern 

Great Plains (EPA 2016) and Management Zone I (Stiver et al. 2006). The soil temperature and moisture regime data used in this report is explained in Appendix 2. 

This area is characterized largely by cool and summer moist bordering on dry soil 

temperature and moisture regimes with moderate resilience and resistance.
USDA Forest Service RMRS-GTR-360. 2017. 93

populations (figs. 42a, 43). Ensemble means from climate models project temperature increases in this area of 3.2 to 3.6 oF (1.8 and 2.0 oC; RCP 4.5 and RCP 8.5, 

respectively) by 2020−2050, and 5.4 to 9.7 oF (3.0 to 5.4 oC) by the end of the 21st

century (see Appendix 3). These temperature increases are projected to be slightly 

greater in both winter and summer than in spring. Most climate models project 

increasing precipitation over this landscape, and average changes range from 5 to 

15 percent increases (about 0.6 to 2.0 in yr-1 [15 to 50 mm yr-1]) with the greatest 

increases towards the end of the century (see Appendix 3). Most of the increase in 

precipitation is projected for winter and spring. Summer, by contrast, is likely to 

become slightly drier across most of this area with the exception of the north-central 

portion; this decline is projected in almost all climate models and for both emissions 

scenarios.

Figure 41—Surface land management for an area with agricultural conversion 

in eastern Montana that is in the Northwestern Great Plains (EPA 2016) and 

Management Zone I (Stiver et al. 2006); (see Appendix 8 for data source). Most of 

the area is privately owned.
94 USDA Forest Service RMRS-GTR-360. 2017.

Figure 42—(A) Percent annually tilled agricultural land (NASS 2014) within 5.0 km of each 

pixel for an area in eastern Montana that is in the Northwestern Great Plains (EPA 2016) 

and Management Zone I (Stiver et al. 2006). (B) Percent risk of cultivation for the same 

area derived from the Sage-Grouse Initiative (SGI) cultivation risk mapping tool (http://map.

sagegrouseinitiative.com/), which is based on climate, soils, and topography.

Longer-term management strategies in this area focus on reducing the impacts of 

land use and development stressors and promoting landscape connectivity. Areas 

on private lands that support high probabilities of suitable habitat and encompass 

or are adjacent to populations of GRSG or other at-risk species could be targeted 

for conservation easements, term easements, or other conservation tools to keep 

native rangelands intact. USDA and State-based initiatives may provide incentives 

for transitioning expiring Conservation Reserve Program or other cultivated lands 

to rangelands that support perennial plant communities. The Sage-Grouse Initiative 
USDA Forest Service RMRS-GTR-360. 2017. 95

Figure 43—Relative percent of the Greater sage-grouse population based on 

breeding abundance during 2010–2014 (Doherty et al. 2016) intersected with the 

resilience and resistance categories developed from soil temperature and moisture 

regimes for an area (Appendix 2) with agricultural conversion in eastern Montana 

that is in the Northwestern Great Plains (EPA 2016) and Management Zone I 

(Stiver et al. 2006). The high value represents 80 percent of the Greater sagegrouse breeding population; the low value represents the remaining 20 percent of 

the breeding population. Large cropland areas exist adjacent to PACs with moderate to high GRSG populations (see fig. 42).

Cultivation Risk layer (Smith et al. 2016; http://map.sagegrouseinitiative.com/) 

along with existing cropland cover maps can be used to help identify areas that have 

not yet been plowed but may be at high risk of future conversion due to suitable 

climate, soils, and topography (fig. 42b; Lipsey et al. 2015; Smith et al. 2016).

State-and-transition models provide information that can help managers determine 

effective strategies for managing threats. The alternative states and transitions for 

the dominant ecological type in this area are identified in a generalized state-andtransition model (Appendix 5 fig. A5.3). Following prolonged drought, improper 
96 USDA Forest Service RMRS-GTR-360. 2017.

grazing, and frequent sagebrush control treatments, the site can transition to an 

alternative state that is dominated by low statured, cool season and sod-forming 

grasses (Appendix 5 fig. A5.3). In the absence of fire and sagebrush control treatments, the site can transition to heavy sagebrush dominance with few grasses and 

forbs. These altered states are susceptible to a variety of nonnative invasive plants 

such as Russian knapweed (Centaurea repens), field brome, and cheatgrass (see 

http://invader.dbs.umt.edu/queryarea.asp for a complete county list), and EDRR 

can be used in all areas with high to moderate habitat probabilities and breeding 

bird concentrations to limit establishment of these invasive species (see table 9). 

Livestock management that maintains a balance of native perennial grasses (cool 

and warm season species) and forbs allows natural regeneration of sagebrush and 

increases competitive ability with nonnative invasive plants. Where introduced 

perennial grasses such as crested wheatgrass were seeded onto former croplands 

an altered or seeded state exists. These introduced perennial grasses can prevent 

establishment of sagebrush and other native species and spread into and dominate 

sagebrush ecosystems (Lesica and Deluca 1996). Thus further seeding of these species following disturbances is not recommended.

Monitoring of ecosystem status and trends (e.g., cover of native and invasive species, disturbance factors, soil and site stability) can provide the necessary information to track landscape change due to climate change and other stressors, evaluate 

the effectiveness of management strategies, and adapt management. Programs 

such as the Bureau of Land Management Assessment, Inventory, and Monitoring 

Program provide the mechanism for this type of comprehensive monitoring.

9.2.2 Example 2: Southwestern Wyoming

This area is characterized by mountainous terrain with sagebrush ecosystems that 

range from cold and summer moist to warm and dry bordering on summer moist 

and thus high to low resilience and resistance (fig. 44). Surface land management 

is primarily USFS, BLM, and private (fig. 45). The area has widespread oil 

and gas development along with high GRSG concentration areas (figs. 46, 47). 

Ensemble mean climate change projections suggest average temperature increases 

of 3.2 to 3.6 oF (1.8 and 2.0 oC; RCP 4.5 and RCP 8.5, respectively) by 2020−2050, 

and 5.7 to 10 oF (3.2 to 5.6 oC) by the end of the 21st century (Appendix 3). These 

temperature projections are relatively consistent throughout the year but are most 

pronounced in the southwestern portion of the area. Most models suggest precipitation increases between 5 and 15 percent in this area, although spatial patterns in 

precipitation change vary dramatically within this landscape due to the steep topography. Although most areas are likely to experience increases in precipitation of 5 to 

10 percent (0.8 to 1.2 in yr-1 [20 to 30 mm yr-1]), mountainous areas may receive increases of 20 to 30 percent (7.9 in yr-1 [>200 mm yr-1]) (Appendix 3). While climate 

models are evenly split between increases and decreases in summer precipitation, 

most models indicate modest increases in precipitation during winter and spring 

and all models suggest a decrease in the proportion of annual precipitation coming 

between May and October.

Minimizing the impacts of land use and development stressors and promoting 

landscape connectivity is a key management strategy. In areas with high GRSG 

breeding habitat probabilities and breeding concentration centers, avoiding development and fragmentation where feasible and consistent with existing State and 

Federal conservation plans can help prevent habitat loss regardless of resilience and 
USDA Forest Service RMRS-GTR-360. 2017. 97

resistance category (table 8 cells 1C, 2C, 3C). Reducing energy and other transport 

corridors as well as vehicle access where consistent with the above mentioned plans 

can minimize fragmentation. Also, conservation easements can be an important tool 

where exurban residential development is fragmenting habitats (fig. 48).

The ecological types and state-and transition models for this area provide 

information to help manage key threats. Because of the wide range of soil temperature and moisture regimes, the area supports several ecological types. Relevant 

state-and-transition models for these types are in Appendix 5 (figs. A5.5, A5.6, 

A5.7, A5.9, A5.10). In general, continuous heavy grazing of cool season grasses 

during the critical growth period can result in an alternative state dominated by 

Figure 44—Soil temperature and moisture regimes by soil moisture subclass for an 

area with oil and gas development in southwest Wyoming that is in the Wyoming 

Basin and Northern & Middle Rockies (EPA 2016) and Management Zone II (Stiver 

et al. 2006). The soil temperature and moisture regime data used in this report and 

the resilience and resistance categories are explained in Appendix 2. This area is 

characterized by mountainous terrain with sagebrush ecosystems that range from 

cold and summer moist to warm and dry bordering on summer moist and thus high 

to low resilience and resistance.
98 USDA Forest Service RMRS-GTR-360. 2017.

Figure 45—Surface land management for an area with oil and gas development in 

southwest Wyoming that is in the Wyoming Basin and Northern & Middle Rockies 

(EPA 2016) and Management Zone II (Stiver et al. 2006); (see Appendix 8 for data 

source). Surface land management is primarily USFS, BLM, and private.

grazing-tolerant species. Further grazing can result in an eroded state which is 

highly susceptible to nonnative invasive species. Fire is rare, but multiple chemical or mechanical treatments or biological disturbances that reduce sagebrush can 

result in a sprouting shrub state. For these states, livestock grazing strategies can be 

designed to improve the condition of native plant communities and decrease nonnative invasive plant species. Strategies that include periodic deferment from use 

during the critical growth period, especially for cool season grasses, can increase 

native species and minimize invasion. This strategy is particularly important in areas with low resilience and resistance. Given climate warming, management aimed 

at restoring and maintaining perennial grasses and forbs has the potential to increase 

resilience to both drought and fire and resistance to invasive plant species.

The area is susceptible to numerous nonnative invasive plants and proactive 

weed management strategies can help prevent their establishment and spread in all 

areas with high habitat suitability and breeding concentration centers (see table 9). 

Nonnative invasives include several Bromus species such as cheatgrass and field 

brome, Poa species such as bulbous bluegrass (P. bulbosa) and Kentucky bluegrass 
USDA Forest Service RMRS-GTR-360. 2017. 99

(P. pratense), spotted and Russian knapweed, diffuse knapweed (Centauria diffusa), 

Canada thistle (Cirsium arvense), and bull thistle (Cirsium vulgare) among others 

(http://invader.dbs.umt.edu/queryarea.asp). Preventing the spread of large weed infestations from areas with lower habitat probabilities can help protect higher quality 

habitat.

For disturbances that remove vegetation and cause soil disturbance such as well 

pads and roads, impacts can be minimized through best management practices 

identified in State and Federal conservation plans, such as top soil banking, using 

certified weed-free (including annual bromes) seed mixes, appropriate seeding 

technologies, and monitoring. Numerous introduced plant species including crested 

wheatgrass, and several Medicago species such as alfalfa and Trifolium species 

(clovers) occur in this area. Seeding these species for reclamation purposes or 

restoration of sagebrush habitat can be avoided, especially in cooler and moister 

Figure 46—Number of active oil and gas wells per square kilometer for an area in 

southwest Wyoming that is in the Wyoming Basin and Northern & Middle Rockies 

(EPA 2016) and Management Zone II (Stiver et al. 2006); (see Appendix 8 for data 

source). The area has widespread oil and gas development.
100 USDA Forest Service RMRS-GTR-360. 2017.

Figure 47—Relative percent of the Greater sage-grouse population based on 

breeding abundance during 2010–2014 (Doherty et al. 2016) intersected with 

resilience and resistance categories developed from soil temperature and moisture regimes (Appendix 2) for an area with oil and gas development in southwest 

Wyoming that is in the Wyoming Basin and Northern & Middle Rockies (EPA 

2016) and Management Zone II (Stiver et al. 2006). The high value represents 80 

percent of the Greater sage-grouse breeding population; the low value represents 

the remaining 20 percent of the breeding population. The area has high GRSG 

concentration areas within and adjacent to areas with oil and gas development (see 

fig. 46). 

areas where native species establish well. In low resilience and resistance areas, 

multiple interventions may be required to restore sagebrush habitat, and restoration 

to the original ecological site may not be possible in areas undergoing rapid climate 

change. Favoring existing genotypes for seeding and outplanting that are better 

adapted to future conditions because of pest resistance, broad tolerances, or other 

characteristics may help increase the success of restoration and rehabilitation efforts. Monitoring of ecosystem status and trends can provide the necessary information to track landscape change due to climate change and the interacting effects of 

other landscape stressors, and to adjust management where needed.
USDA Forest Service RMRS-GTR-360. 2017. 101

9.2.3 Example 3: Northeastern Nevada

This area is characterized by mountainous terrain with sagebrush ecosystems 

that range from cold and moist to warm and dry (fig. 49) and thus from high to 

low resilience and resistance. Surface land management is primarily BLM, USFS, 

and private (fig. 50). Mid- to high- elevation areas are exhibiting localized conifer 

expansion, primarily Utah juniper, and low- to mid-elevation areas are exhibiting 

cheatgrass invasion and spread (fig. 51). Since 2000, a relatively large portion of the 

area has burned in wildfires (fig. 51) in and around areas with high concentrations 

of breeding birds (fig. 52). Since 1984 about 30 percent of the total area burned; 20 

percent of the total area burned since 2000. Ensemble mean climate change projections suggest average temperature increases of 3.2 to 3.6 oF (1.8 and 2.0 oC; RCP 

4.5 and RCP 8.5, respectively) by 2020−2050, and 5.7 to 9.9 oF (3.2 to 5.5 oC) by 

the end of the 21st century (Appendix 3). The largest temperature increases are projected for the summer (July to September). Average precipitation forecasts over this 

area range from decreases of about 10 percent (0.8 to 1.2 in yr-1 [20-30 mm yr-1] to 

increases of more than 50 percent (7.9 in yr-1 [>200 mm yr-1]) (Appendix 3). The 

largest increases are projected consistently for the winter and the cooler, mountainous areas.

The state-and-transition models for the predominant ecological types provide 

information to help manage the primary threats (Appendix 6). In general, improper 

livestock use, such as heavy grazing during the critical growth period, can decrease 

perennial grasses and forbs and result in increases in woody species and fuel loads. 

Increases in woody species can result in a shrub or tree dominated state and the 

potential for higher fire severity. Progressive conifer expansion can result in an 

alternative state dominated by trees, and depending on soils, slope, and understory 

Figure 48—A conservation easement near Pinedale, Wyoming. Photo by Jeremy Roberts, 

Conservation Media; used with permission. Conservation easements can be an important 

tool where development is fragmenting habitats.
102 USDA Forest Service RMRS-GTR-360. 2017.

Figure 49—Soil temperature and moisture regimes by soil moisture subclass for 

an area with cheatgrass invasion and conifer expansion in northeast Nevada that 

is in the Northern Basin and Range (EPA 2016) and Management Zone IV (Stiver 

et al. 2006). The soil temperature and moisture regime data used in this report are 

explained in Appendix 2. This area is characterized by mountainous terrain with 

sagebrush ecosystems that range from cold and moist to warm and dry and thus 

from high to low resilience and resistance.

species, an eroded state. On relatively warm and dry sites, improper livestock use 

that depletes perennial grasses and forbs can decrease resistance to invasive annual 

grasses. Increases in invasive annual grasses may cause more frequent and continuous fires and result in conversion to alternative states dominated by annuals (Miller 

et al. 2013). Proper management of livestock and wild horse and burro grazing can 

promote native perennial grass and forb growth and reproduction and maintain or 

enhance resilience to wildfires and resistance to invasive annual grasses.

Various fire management strategies can be used to help maintain connected and 

functioning sagebrush ecosystems (table 9). Fuel loads and fuel continuity can 

be reduced to: (1) decrease fire size, alter burn patterns, decrease perennial grass 
USDA Forest Service RMRS-GTR-360. 2017. 103

Figure 50—Surface land management for an area with cheatgrass invasion and 

conifer expansion in northeast Nevada that is in the Northern Basin and Range 

(EPA 2016) and Management Zone IV (Stiver et al. 2006); (see Appendix 8 for data 

sources). Surface land management is primarily BLM, FS, and private.

mortality, and maintain landscape connectivity; (2) decrease competitive suppression of native perennial grasses and forbs by woody species; and thus (3) lower 

the longer-term risk of dominance by invasive annual grasses and other invaders. 

Wildfires can be suppressed in low to moderate resilience and resistance sagebrushdominated areas to prevent conversion to invasive annual grass states and maintain 

both ecological processes and ecosystem services. Wildfires can be suppressed 

adjacent to or within recently restored ecosystems to promote recovery and increase 

capacity to absorb future change. Finally, fuel breaks can be used in carefully targeted locations along existing roads where they have minimal effects on ecosystem 

processes and can aid fire suppression efforts (Maestas et al. 2016b)

Targeted tree removal in early- to mid-phase (Phase I and II), postsettlement 

piñon and juniper expansion areas can be used to maintain shrub/herbaceous cover 

and prevent conversion to a tree dominated state as well as reduce fuel loads (table 

9). The ability of GRSG to maintain active leks decreases significantly when conifer 

canopy exceeds 2 percent in the immediate vicinity (within 1,000 m) of the lek 
104 USDA Forest Service RMRS-GTR-360. 2017.

(Baruch-Mordo et al. 2013) and targeted tree removal can effectively increase habitat availability for nesting and brooding sage-grouse (Sandford et al. 2017; Severson 

et al. 2017). Guidance for selecting sites for conifer removal treatments and evaluating treatment types is in Miller et al. 2014.

Following fire in either sagebrush or conifer dominated areas, postfire rehabilitation can be used to accelerate sagebrush establishment and recovery of perennial 

native herbaceous species. Areas with moderate to high resilience and resistance are 

often capable of unassisted recovery and seeding is typically needed only in areas 

where perennial native grasses and forbs have been depleted (Miller et al. 2013, 

2015). Seeding introduced species like crested wheatgrass or forage kochia (Bassia 

prostrata) can retard recovery of native perennial grasses and forbs that are important to GRSG and is not recommended (Knutson et al. 2014). However, seeding or 

transplanting of sagebrush may be needed to accelerate establishment in target areas 

and increase connectivity. Guidance for determining when a site will recover on 

its own and when it would benefit from management intervention is in Miller et al. 

2015. Information on seed transfer guideline is in Appendix 11.

Figure 51—(A) Percent cheatgrass cover in northeast Nevada in 2015 at a 250 meter resolution (Boyte et 

al. 2015). (B) Perimeters of fires that occurred from 1984–2014 in an area in northeast Nevada. Data for 

fires larger than 1,000 acres are from MTBS (2014) and data for fires smaller than 1,000 acres are from 

GeoMAC (2015). (C) Estimate of tree canopy cover per acre in northeast Nevada at a 30 meter resolution 

(Falkowski et al. 2017). The area is in the Northern Basin and Range (EPA 2016) and Management Zone IV 

(Stiver et al. 2006). Priority Areas for Conservations (PACs; FWS 2013) are overlaid. Mid- to high- elevation 

areas are exhibiting localized conifer expansion, primarily Utah juniper, and low- to mid-elevation areas are 

exhibiting cheatgrass invasion and spread. Since 2000, a relatively large portion of the area has burned in 

wildfires.
USDA Forest Service RMRS-GTR-360. 2017. 105

Figure 52—Relative percent of the Greater sage-grouse population based on 

breeding abundance during 2010–2014 (Doherty et al. 2016) intersected with resilience and resistance categories developed from soil temperature and moisture 

regimes (Appendix 2) for an area with cheatgrass invasion and conifer expansion 

in northeast Nevada that is in the Northern Basin and Range (EPA 2016) and 

Management Zone IV (Stiver et al. 2006). The high value represents 80 percent of 

the Greater sage-grouse breeding population; the low value represents the remaining 20 percent of the breeding population. Wildfires have burned in and around 

areas with high concentrations of breeding birds in recent decades resulting in 

spread of cheatgrass (see fig. 51).

In areas with lower resilience and resistance and high breeding bird densities, 

large, contiguous areas of sagebrush with intact understories are a high priority for 

protective management (table 8 cell C3). In these areas, emphasis is on maintaining 

or increasing habitat conditions by minimizing stressors and disturbance (table 9). 

Following fires or surface disturbances, multiple interventions may be required 

to restore sagebrush habitat. Restoration may not be possible in areas undergoing 

rapid climate change, and favoring or restoring genotypes of native species that 

are expected to be better adapted to the future range of climatic and site conditions 
106 USDA Forest Service RMRS-GTR-360. 2017.

may help increase the success of restoration and rehabilitation efforts. Monitoring 

can provide information on landscape change in response to climate change and on 

the interacting effects of other landscape stressors like wildfire and invasive annual 

grasses. Monitoring can also provide information on the effectiveness of current 

management activities aimed at addressing these threats and on the need to adjust 

management.

9.3 Sources of Management Information

Several resources exist to assist in developing effective management strategies 

for persistent ecosystem threats. Archived information from the Center for Invasive 

Species Management website provides a variety of resources for managing nonnative invasive species, including information on individual species, inventory and 

monitoring, ecologically based invasive plant management, control methods, prevention, restoration and revegetation (http://www.weedcenter.org/). Also, a recent 

handbook on cheatgrass management is broadly applicable across the eastern portion of the range (Mealor et al. 2013). To address wildfire, invasive annual grasses, 

and conifer expansion in sagebrush ecosystems in the western portion of the range, 

field guides (Miller et al. 2014, 2015) and handbooks (Pyke et al. 2015 a,b) have recently been developed that explicitly incorporate resilience and resistance concepts. 

These resources can be adapted to MZs II and VII to help guide managers through 

the process of determining both the suitability of an area for treatment and the most 

appropriate treatment. Three treatment types are emphasized: (1) conifer removal 

(Miller et al. 2014), (2) postfire rehabilitation (Miller et al. 2015), and (3) rehabilitation and restoration (Pyke et al. 2015a,b). Additional information on implementing 

these types of management treatments is synthesized in Monsen et al. (2004) and 

Pyke (2011); additional information on treatment response is synthesized in Miller 

et al. (2013). 

General information on rangeland ecosystems is available through the Range 

Science Information System (http://arc.lib.montana.edu/range-science/), which includes a searchable bibliography and general information on MLRA Ecoregions and 

associated vegetation types. Information is available on grazing management from 

university extension services at Montana State University (http://animalrangeextension.montana.edu/range/grazing-management.html), the University of Wyoming 

(Cagney et al. 2010), and Colorado State University (http://extension.colostate.

edu/topic-areas/natural-resources/). Additional information on livestock management can be found on websites such as http://www.grazinglands.org/ and Grass: 

The Stockman’s Crop. Also, the different agencies have guidelines for livestock 

grazing (e.g., BLM Standards for Rangeland Health and Guidelines for Grazing 

Management; http://www.blm.gov/style/medialib/blm/mt/blm_programs/grazing.

Par.83445.File.dat/MCSG.pdf).

A variety of programs exist to help support ranchers and other private landowners and enhance their ability to maintain and enhance sagebrush habitat. Financial 

and technical assistance is available for planning and implementing conservation practices that can improve ecological conditions and natural resources on 

rangelands through the Environmental Quality Incentives Program (EQIP; http://

www.nrcs.usda.gov/wps/portal/nrcs/main/national/programs/financial/eqip/) and 

the FWS Partners for Fish and Wildlife Program (PFW). The FWS Ecological 

Services branch offers recovery funding to implement restoration actions, conduct 

research, and assist in the implementation of other conservation actions designed 
USDA Forest Service RMRS-GTR-360. 2017. 107

to restore and protect sagebrush habitat. State wildlife agencies also have private 

lands programs that vary by State, but that offer seed cost share for Conservation 

Reserve Program plantings and restoration projects, and technical assistance and 

infrastructure for wetland enhancement and range management systems. And 

non-governmental organizations, such as The Nature Conservancy and Wetlands 

Conservancy, offer community-based landowner programs, such as grassbanks, and 

provide technical assistance to landowners interested in enhancing sagebrush range 

conditions.

Resources also exist to assist in addressing land use and development threats. 

Long-term conservation easements are available through the Agricultural 

Conservation Easement Program that can help maintain large and intact sagebrush 

ecosystems by preventing cropland conversion and residential development (http://

www.nrcs.usda.gov/wps/portal/nrcs/main/national/programs/easements/acep/). In 

addition, State wildlife agencies private lands programs can include conservation 

easements and 30-year conservation leases, and non-governmental organizations 

such as The Nature Conservancy and Wetlands Conservancy, can hold conservation 

easements.

Information is available to help develop adaptation strategies for climate change. 

The Climate Change Resources Center (http://www.fs.usda.gov/ccrc/home), a USFS 

sponsored portal, is a web-based, national resource that connects land managers 

and decision makers with useable science to address climate change in planning 

and application (USFS 2011). The website contains links to numerous reports, papers, tools, and data for assessing climate change and climate change impacts. The 

FWS has worked with the National Oceanic and Atmospheric Administration, the 

States, and tribal partners to co-lead the National Fish, Wildlife and Plants Climate 

Adaptation Strategy (www.wildlifeadaptationstrategy.gov), and has also developed 

an internal Climate Change Strategic Plan. The FWS supports integration of climate 

change considerations into all aspects of agency work (https://www.fws.gov/home/

climatechange/). The FWS national training center offers interagency courses, both 

classroom and web-based, on climate change, climate change adaptation, vulnerability assessment, scenario planning, and communications. It offers a regular web 

conference on safeguarding wildlife from climate change and has produced several 

reports and guidance documents on potential impacts and responses to protect wildlife and wildlife habitat from climate change.

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Appendix 1—Definitions of Terms Used in This 

Document

At-risk community phase—A community phase that can be designated within the 

reference state and also in alternative states. This community phase is the most 

vulnerable to transition to an alternative state (Caudle et al. 2013). 

Community phase—A unique assemblage of plants and associated soil properties 

that can occur within a state (Caudle et al. 2013).

Ecological site (ES)—A conceptual division of the landscape that is defined as a 

distinctive kind of land based on recurring soil, landform, geology, and climate 

characteristics that differs from other kinds of land in its ability to produce 

distinctive kinds and amounts of vegetation and in its ability to respond similarly 

to management actions and natural disturbances (Caudle et al. 2013).

Ecological site descriptions (ESD)—Documentation of the characteristics of 

an ecological site. The documentation includes the data used to define the 

distinctive properties and characteristics of the ecological site, the abiotic and 

biotic characteristics that differentiate the site (i.e., climate, physiographic, soil 

characteristics, plant communities), and the ecological dynamics of the site that 

describes how changes in disturbance processes and management can affect the 

site. An ESD also provides interpretations about the land uses and ecosystem 

services that a particular ecological site can support and management alternatives 

for achieving land management (Caudle et al. 2013).

Ecological type—A category of land with a distinctive (i.e., mappable) combination 

of landscape elements. The elements making up an ecological type are climate, 

geology, geomorphology, soils, and potential natural vegetation. Ecological 

types differ from each other in their ability to produce vegetation and respond 

to management and natural disturbances (Winthers et al. 2005). In the Science 

Framework, ecological type is used in a broad sense and refers to ecological type 

or ecological site groups as described in Appendix 3.

Fire regime—The patterns of fire seasonality, frequency, size, spatial continuity, 

intensity, type (crown fire, surface fire, or ground fire), and severity in a 

particular area or ecosystem (Agee 1994; Heinselman 1973; Sugihara et al. 

2006). A fire regime is a generalization based on the characteristics of fires that 

have occurred over a long period. Fire regimes are often described as cycles or 

rotations because some parts of the fire histories usually get repeated, and the 

repetitions can be counted and measured.

Focal species—Sagebrush obligate, near-obligate, dependent, or associated species 

identified as: (1) at-risk, (2) influencing management actions and regional 

economies, (3) potentially being negatively influenced by management actions, 

and/or (4) serving as indicators of habitat quality or habitat niches such as 

riparian areas in sagebrush ecosystems.

Improper livestock grazing—Grazing that impedes progress toward or 

maintenance of ecological processes and the desired plant community 

composition and structure within a given set of site conditions and the natural 

range of variability, including climatic variability and natural disturbance 

regimes, expected within a management planning time horizon.
136 USDA Forest Service RMRS-GTR-360. 2017.

Invasive plant species—An invasive species is: (1) nonnative (or alien) to the 

ecosystem under consideration, and (2) its introduction causes or is likely to 

cause economic or environmental harm or harm to human health (Presidential 

Executive Order 13112, 1999).

Land use and development threats—Threats that include cropland conversion, 

energy development, mining, roads and other infrastructure, urban and exurban 

development, and recreation and can be regulated (FWS 2013).

Major land resource area—A geographic area, usually several thousand acres 

in extent, that is characterized by a particular pattern of soils, climate, water 

resources, land uses, and type of agriculture.

Management strategies—Coordinated management activities conducted at midto local scales to achieve vegetation and habitat objectives (e.g., strategically 

locating firefighting resources to protect habitat, coordinating Early Detection 

and Rapid Response activities for invasive plant species, positioning treatments 

to increase connectivity).

Persistent ecosystem threats—Threats that include invasion of nonnative invasive 

plant species, altered fire regimes, and conifer expansion (Knick et al. 2011: 

Miller et al. 2011), are difficult to regulate, and are managed using ecologically 

based approaches (Boyd et al. 2014a; Evans et al. 2013).

Projects—Projects are comprised of multiple treatments.

Reference state—Ecological potential and natural or historical range of variability 

of the ecological site. 

Resilience—Capacity of an ecosystem to reorganize and regain its fundamental 

structure, processes, and functioning when altered by stressors such as invasive 

plant species and disturbances such as improper livestock grazing and altered fire 

regimes (Holling 1973).

Resistance—Capacity of an ecosystem to retain its fundamental structure, processes 

and functioning (or remain largely unchanged) despite stresses, disturbances, or 

invasive species (Folke et al. 2004).

Resistance to invasion—Abiotic and biotic attributes and ecological processes of 

an ecosystem that limit the population growth of an invading species (D’Antonio 

and Thomsen 2004).

Restoration pathways—A description of the environmental conditions and 

practices that are required to recover a state that has undergone a transition 

(Caudle et al. 2013).

State—A suite of community phases and their inherent soil properties that interact 

with the abiotic and biotic environment to produce persistent functional and 

structural attributes associated with a characteristic range of variability (adapted 

from Briske et al. 2008). 

State-and-transition model—A method to organize and communicate complex 

information about the relationships among vegetation, soil, animals, hydrology, 

disturbances (fire, lack of fire, herbivory, drought, unusually wet periods, insects 

and disease), and management actions on an ecological site (Caudle et al. 2013). 
USDA Forest Service RMRS-GTR-360. 2017. 137

Thresholds—Conditions sufficient to modify ecosystem structure and function 

beyond the limits of ecological resilience, resulting in transition to alternative 

states (Briske et al. 2008). 

Transition—Transitions describe the biotic or abiotic variables or events, acting 

independently or in combination, that contribute directly to loss of state resilience 

and result in shifts between states. Transitions are often triggered by disturbances, 

including natural events (climatic events or fire) and/or management actions 

(grazing, prescribed fire, fire suppression). They can occur quickly as in the case 

of catastrophic events like fire or flood, or over a long period of time as in the 

case of a gradual shift in climate patterns or repeated stresses like frequent fires 

(Caudle et al. 2013).

Treatments—Local scale management actions that directly manipulate vegetation 

to achieve a vegetation or habitat objective (e.g., conifer removals, invasive 

annual grass controls, fuel treatments, or revegetation).

Woodland (Piñon and Juniper) phase I, II, III—In phase I trees are present but 

shrubs and herbs are the dominant vegetation influencing ecological processes 

on the site; in phase II trees are codominant with shrubs and herbs and all 

three vegetation layers influence ecological processes; in phase III trees are 

the dominant vegetation on the site and the primary plant layer influencing 

ecological processes on the site (Miller et al. 2005, 2014). 
138 USDA Forest Service RMRS-GTR-360. 2017.

Appendix 2—Explanation of Soil Temperature and 

Moisture Regimes Data and the Resilience and 

Resistance Categories

Soil climate regimes (temperature and moisture) are used in soil taxonomy to 

classify soils. They are important to consider in land management decisions because of their influence on (1) amounts and kinds of vegetation and (2) response 

to disturbance and management actions. Soil temperature and moisture regimes 

are assigned to soil map unit components as part of the National Cooperative 

Soil Survey program. Abbreviated definitions of predominant soil temperature 

and moisture regime classes are listed below (table A2.1). Complete descriptions can be found in the 12th edition of the Keys to Soil Taxonomy (Soil Survey 

Staff 2014) https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/survey/class/

taxonomy/?cid=nrcs142p2_053580.

Table A2.1—Definitions of the dominant soil temperature and moisture regimes.

Soil Temperature Regimes

Cryic (cold): Soils that have a mean annual soil temperature between 0 and 8 oC and do not 

have permafrost at a depth of 50 cm below the surface or at a restrictive feature, whichever is 

shallower.

Frigid (cool): Soils that have a mean annual soil temperature between 0 and 8 oC and the 

difference between mean summer and mean winter soil temperatures is greater than 6 oC at 

a depth of 50 cm below the surface or at a restrictive feature, whichever is shallower.

Mesic (warm): Soils that have a mean annual soil temperature of 8−15 oC and the difference 

between mean summer and mean winter soil temperatures is greater than 6 oC at a depth of 

50 cm below the surface or at a restrictive feature, whichever is shallower.

Soil Moisture Regimes

Udic (moist): Characteristic of high elevation areas with winter snowfall and/or summer precipitation. The soil is dry for less than 90 consecutive days in normal years.

Ustic (summer moist): Generally there is some plant-available moisture during the growing 

season, although significant periods of drought may occur. Summer precipitation allows presence of warm season plant species. The soil is dry for 90 or more cumulative days in normal 

years.

Xeric (winter moist; generally mapped at >12 inches mean annual precipitation): Characteristic of areas where winters are moist and cool and summers are warm and dry. The 

soil is dry for 45 or more consecutive days in the 4 months following the summer solstice but 

moist in some part for 90 or more consecutive days during the growing season.

Aridic (dry; generally mapped at <12 inches mean annual precipitation): Characteristic 

of arid regions. The soil is dry for at least half the growing season and moist for less than 90 

consecutive days.
USDA Forest Service RMRS-GTR-360. 2017. 139

Soil moisture regimes are further divided into moisture subclasses, which are 

often used to indicate soils that are transitional between moisture regimes. For 

example, a soil with an aridic moisture regime and a xeric moisture subclass may be 

described as “Aridic bordering on Xeric.” Understanding these gradients becomes 

increasingly important when making interpretations and decisions at the project 

scale where aspect, slope, and soils affect the actual moisture regime. More information on taxonomic moisture subclasses is available at http://www.nrcs.usda.gov/

wps/portal/nrcs/detail/soils/ref/?cid=nrcs142p2_053576. 

We used soil survey spatial and tabular data aggregated in October 2013 to facilitate broad scale analyses of resilience and resistance across the range of sage-grouse 

(all Management Zones; Maestas et al. 2016a). Soils data were derived from two 

primary sources: (1) completed and interim soil surveys available through the Soil 

Survey Geographic Database (SSURGO) (Soil Survey Staff a), and (2) the State 

Soils Geographic Database (STATSGO2) (Soil Survey Staff b). Data for the eastern 

range were updated in January 2016 to reflect the most current soil survey information available (fig. 6). In some cases, abrupt changes in soil temperature and moisture regimes are apparent when merging together STATSGO2 and SSURGO soil 

survey areas due to differences in data collection and publication, scale of interpretation, or changes in application of regime concepts. For example, the area near the 

border between southeastern Montana and northeastern Wyoming is in a transition 

zone between the frigid and mesic soil temperature regimes, which has resulted in 

an apparent abrupt change in temperature regime at the state border. Future updates 

to soil survey information will resolve these boundary issues along state lines, using 

current climate datasets and additional field data.

We used soil temperature regime and moisture regime subclass data to generate a 

simplified index of relative resilience and resistance that has three categories: high, 

moderate, and low (table A2.2). We used the relationships among the predominant 

ecological types, soil temperature and moisture regimes, and relative resilience and 

resistance (table 6) to inform these categories. Soils with high water tables, wetlands, or frequent ponding or uncommon regimes that would not typically support 

sagebrush were excluded. 

In the three cases where the primary rating for resilience and resistance of a soil 

temperature and moisture regime differed (Mesic/Ustic bordering on Aridic, Mesic/

Aridic bordering on Ustic, and Frigid/Aridic-Typic) in table 6, the final rating was 

based on expert opinion of ecosystem response to disturbance and resistance to invasive annual grasses. Also, because of the distinct climatic regimes and vegetation 

responses in the West-Central Semiarid Prairies in MZ I and Cold Deserts in MZ 

II and VII, and Cold Deserts in MZ III, IV, V, and VI, the rankings for these ecoregions were performed separately. The Mesic/Ustic bordering on Aridic and Mesic/

Aridic bordering on Ustic regimes were ranked as moderate in the West-Central 

Semiarid Prairies in MZ I (Prairies) and as low in the Cold Deserts in MZ II and 

VII (Cold Deserts). The rankings for the Cold Deserts in MZ II and VII, and Cold 

Deserts in MZ III, IV, V, and VI were similar. 
140 USDA Forest Service RMRS-GTR-360. 2017.

Table A2.2—Resilience and resistance (R&R) rating for the soil temperature and moisture 

regimes in the West-Central Semiarid Prairies in MZ I, Cold Deserts in MZ II and VII, and Cold 

Deserts in MZ III, IV, V, and VI. The information contained in the table is based on a sagebrush 

biome scale analysis that used data from the National Soil Information System (NASIS) to 

summarize soil temperature and soil moisture regimes (to soil moisture subclass) capable of 

supporting big sagebrush and to assign R&R categories.

Soil taxonomic name Common name R&R rating

Cryic/Udic-Typic Cold/moist High

Cryic/Ustic-Typic Cold/summer moist High

Cryic/Xeric-Typic Cold/winter moist High

Cryic/Xeric bordering on Aridic Cold/winter moist bordering on dry High

Cryic/Aridic bordering on Xeric Cold/dry bordering on winter moist Moderate

Frigid/Ustic-Typic Cool/summer moist High

Frigid/Xeric-Typic Cool/winter moist High

Frigid/Ustic bordering on Aridic Cool/summer moist bordering on dry Moderate

Frigid/Xeric bordering on Aridic Cool/winter moist bordering on dry Moderate

Frigid/Aridic bordering on Ustic Cool/dry bordering on summer moist Moderate

Frigid/Aridic-Typic Cool and dry Moderate

Frigid/Aridic bordering on Xeric Cool/dry bordering on winter moist Moderate

Mesic/Ustic-Typic Warm/summer moist Moderate

Mesic/Xeric-Typic Warm/winter moist Moderate

Mesic/Ustic bordering on Aridic Warm/summer moist bordering on dry Moderate (Prairies)

Low (Cold Deserts)

Mesic/Aridic bordering on Ustic Warm/dry bordering on summer moist Moderate (Prairies)

Low (Cold Deserts)

Mesic/Aridic bordering on Xeric Warm/dry bordering on moist Low

Mesic/Aridic-Typic Warm/dry Low

Soils geodatabases and categorized resilience and resistance layers can be accessed at: https://www.sciencebase.gov/catalog/item/538e5aa9e4b09202b547e56c.

This appendix was prepared by Steve Campbell and Jeremy Maestas. Karen 

Clause, Jeanne Chambers, Dave Pyke, and Mary Manning contributed to its 

development.
USDA Forest Service RMRS-GTR-360. 2017. 141

Appendix 3—Climate Change Projections for the 

Sagebrush Biome: Data, Methods, and Maps

Climate projections for key climate variables were developed for the sagebrush 

biome for this document. A summary of the climate projections for the sagebrush biome as a whole and the different ecoregions is in Section 5.2, “Persistent Ecosystem 

Threats: Climate Change.” The magnitude of change projected is illustrated in the 

maps and graphs in this appendix. These data layers can be used similarly to the 

data layers for other persistent ecosystem threats. 

Data Sources 

The climate data layers developed for the Science Framework include both current and future climatic conditions developed for a 10 km resolution grid across 

western North America. The U.S. National Centers for Environmental Prediction, 

Climate Forecast System Reanalysis products (Saha et al. 2011) for current climate 

conditions (1980−2010), were used to extract daily maximum and minimum temperatures (2 m above-ground). The 6-hourly T382 products (Saha et al. 2010) were 

used to extract daily maximum and minimum precipitation. For future conditions, 

bias-corrected and spatially downscaled (BCSD) climate projections were downloaded as monthly time-series for two time periods, 2020−2050 and 2070−2100, 

from the fifth phase of the Climate Model Intercomparison Project (CMIP5) (Taylor 

et al. 2012). Output from 11 climate models and two representative concentration pathways (RCPs) (Moss et al. 2010), RCP 4.5 and RCP 8.5, were extracted 

from the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections 

archive (Maurer et al. 2007) at http://gdo-dcp.ucllnl.org/downscaled_cmip_projections/. Historical daily data (NCEP/NFSR) were combined with monthly General 

Circulation Model (GCM) predictions of historical and future conditions with a 

hybrid-delta downscaling approach to obtain future daily forcing (Hamlet et al. 

2010; Tohver et al. 2014). Climate models selected for this analysis from the large 

set of models in CMIP5 included the most independent models in terms of model 

design (Knutti et al. 2013) and the best performing models over the historical period 

for the northwestern United States (Rupp et al. 2013) and southwestern United 

States (Rupp, personal communication). The models used were CanESM2, CESM1-

CAM5, CNRM-CM5, CSIRO-Mk3-6-0, FGOALS-g2, FGOALS-s2, GISS-E2-R, 

HadGEM2-ES, inmcm4, IPSL-CM5A-MR, and MIROC-ESM.

Methods

Variables Examined 

From the 30-year time-series of daily precipitation and temperature data for each 

time period, we calculated 12 variables as general predictors of important climatic conditions for sagebrush ecosystems. In general, mean daily temperatures 

were calculated as the average of daily minimum and maximum, and total precipitation was calculated as the sum of daily precipitation. These temperature and 

precipitation variables were calculated for four time periods: annual (mean annual 

temperature and precipitation), winter (December through March), spring (April 

through June), and summer (July through September). We also quantified average 

daily maximum temperature in July (a metric of summer heat stress), average daily 

minimum temperature in January (a metric of winter frost exposure), and the annual 
142 USDA Forest Service RMRS-GTR-360. 2017.

mean proportion of precipitation that occurs between May and October (a measure 

of warm-season precipitation), and between July and September (a measure of midsummer monsoon season precipitation). 

Ensemble Calculations 

Future climatic conditions were represented by 44 projections derived from 

11 climate models simulating climate under two RCP scenarios over two time periods. For each RCP scenario and time period, we developed cell-specific ensemble 

grids of minimum, mean, and maximum values. These ensemble determinations 

are performed for each 10 km x 10 km grid cell. The minimum, mean, and maximum values are determined for each cell from the 11 values for that cell relating 

to the set of 11 climate models. Data for all ensemble levels are available through 

the U.S. Geological Survey ScienceBase (https://www.sciencebase.gov/catalog/

item/5850549ae4b0f24ebfd9368f).

Maps and Summaries of Climate Change Projections for the 

Ecoregions in the Sagebrush Biome

Climate change projections were developed for the entire sagebrush biome. To 

evaluate differences among EPA level III ecoregions or groups of ecoregions with 

similar topography and climate, data were summarized by the following ecoregions 

or ecoregion group: (1) Northwestern Glaciated Plains and Northwestern Great 

Plains; (2) Wyoming Basin (3) Colorado Plateau and AZ-NM Plateau; (4) Central 

Basin and Range; (5) Northern Basin and Range, Snake River Plain, and Columbia 

Plateau; (6) Wasatch and Uinta Mountains and Southern Rockies; (7) Sierra 

Nevada; (8) Eastern Cascades Slopes and Foothills and Blue Mountains; and 

(9) Idaho Batholith and Middle Rockies.

This appendix includes two pages for each climate variable. The first page shows 

current and projected climate conditions for a variable. The boxplots in the graph at 

the top of the page illustrate variability between current conditions (1980−2010, left 

box) and the 12 future climate projections for the sagebrush biome. For the future 

climate projections, the minimum, mean, and maximum values from the 11 climate 

models are shown for two RCPs and two future time periods. This graph allows 

comparison of current conditions with future projections, and provides perspective 

on the magnitude of uncertainty in the climate models for the different RCPs and 

time periods. For example, by contrasting the min, mean and max boxplots within a 

group, it is evident that climate model uncertainty is greater for the longer-term time 

period. 

This graph also allows assessment of the magnitude of difference between time 

periods and RCPs by comparing groups. For example, mean annual temperatures 

are projected to be greater under RCP 8.5 than RCP 4.5 and greater at the end of the 

21st century than in the middle of the century. In contrast, although uncertainty in 

mean annual precipitation (variability among min, mean, and max) is higher at the 

end of the century, the amount of precipitation expected does not show a consistent 

trend for either RCP or time period. 
USDA Forest Service RMRS-GTR-360. 2017. 143

Maps on the first page show mean conditions for 1980−2010 (center left), mean 

conditions for RCP 4.5 in 2020−2050 and 2070−2100 (upper center and right, respectively), and mean conditions for RCP 8.5 in 2020−2050 and 2070−2100 (lower 

center, and center right, respectively). These maps provide perspective on the geographic patterns of potential climate change and facilitate examination of specific 

locations within the sagebrush biome.

The second page for a variable shows changes in climate between current conditions and the 12 future climate projections for the sagebrush biome. The graph at 

the top of the page is structured similarly to the one on the first page. However, the 

12 boxplots show the differences between current conditions and future projections 

for the two RCPs and time periods. Positive values indicate projected increases in 

temperature or precipitation, and negative values indicate projections of decreases. 

Similar to the boxplots in the graph on the first page, the uncertainty in climate forecasts can be assessed by contrasting the min, mean, and max values within groups. 

The impact of concentration pathways and future time periods can also be evaluated 

by contrasting groups. 

Ranges for each boxplot in this graph are generally smaller than ranges from the 

graph on the first page, because the spatial variation in projected changes is smaller 

than the spatial variation in climate across the entire sagebrush biome. Also, while 

mean annual temperature is projected to increase everywhere, projected changes in 

mean annual precipitation include increases and decreases depending on location. 

The maps on the second page show the projected change in mean conditions 

between 1980−2010 and 2070−2100 for RCP 4.5 and RCP 8.5. At the bottom 

of the page, a map illustrating the nine ecoregion groups used in this analysis is 

shown. The graph beside the ecoregion map shows a boxplot of the change for each 

ecoregion group under RCP 8.5 between 1980−2010 and 2070−2100. This graph 

provides perspective on how the magnitude of change is projected to vary among 

ecoregions. 

The projected change in climate is particularly useful in evaluating management 

scenarios (see table 9). For example, in areas where climate change and its interactions with other stressors are projected to be relatively small, it may be possible to 

continue existing management practices, monitor outcomes, and adapt management 

as needed. However, where climate change and its interactions are expected to be 

severe, proactive management may be necessary to facilitate transition to a new site 

potential.

This appendix was prepared by John B. Bradford. Linda Joyce, 

Jeanne Chambers, Marian Talbert, Bryce Richardson, John Kim, and 

Steve Hanser contributed to its development.
144 USDA Forest Service RMRS-GTR-360. 2017.

Figure A3.1a.
USDA Forest Service RMRS-GTR-360. 2017. 145

Figure A3.1b.
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Figure A3.2a.
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Figure A3.2b.
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Figure A3.3a.
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Figure A3.3b.
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Figure A3.4a.
USDA Forest Service RMRS-GTR-360. 2017. 151

Figure A3.4b.
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Figure A3.5a.
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Figure A3.5b.
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Figure A3.6a.
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Figure A3.6b.
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Figure A3.7a.
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Figure A3.7b.
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Figure A3.8a.
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Figure A3.8b.
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Figure A3.9a.
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Figure A3.9b.
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Figure A3.10a.
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Figure A3.10b.
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Figure A3.11a.
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Figure A3.11b.
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Figure A3.12a.
USDA Forest Service RMRS-GTR-360. 2017. 167

Figure A3.12b.
168 USDA Forest Service RMRS-GTR-360. 2017.

Appendix 4—Methods for Determining the Predominant 

Ecological Types 

The ecological types in the Science Framework were developed for two earlier 

General Technical Reports (Chambers et al. 2014b, 2016a). For the purposes of 

the Science Framework, ecological type is used in a broad sense and refers to 

ecological type or ecological site groups. The ecological types are intended largely 

to inform mid-scale (ecoregion and Management Zone) analyses. The ecological 

type descriptions provide information on the relationships among soil temperature 

and moisture regimes, typical vegetation, resilience to disturbance, and resistance 

to invasive annual grasses for the dominant ecological types within sage-grouse 

habitat (FWS 2013) (see table 6). State-and-transition models for those ecological 

types that comprise the greatest area within sage-grouse habitat are in Appendices 5 

and 6. Together, the ecological type descriptions and state-and-transition models are 

intended to link prioritizations of sage-grouse breeding habitat and resilience and 

resistance (fig. 38) to specific sagebrush ecological types, their likely response to 

disturbance and management treatments, and appropriate management strategies.

The ecological types for the western range of Greater sage-grouse (GRSG) were 

based on Chambers et al. (2014b,c). An overview of the methods used to develop 

the ecological types for the eastern range of GRSG follows. (See Chambers et al. 

2016a for additional details.) 

 1. National Soil Information System (NASIS) data were exported for each EPA 

Level II Ecoregion, including Cold Deserts (10.1), Western Cordillera (6.2), 

and West Central Semiarid Prairies (9.3), within the eastern range of GRSG 

(Management Zones I, II, and VII) and the range of GUSG. The information 

exported included acreages of the dominant Ecological Site within the GRSG 

Priority Areas of Conservation and GUSG critical habitat as well as soil temperature regime, moisture regime, and moisture subclass assigned at the soil 

mapunit component level. The analyses were conducted by Steve Campbell, 

NRCS, Portland, OR.

 a. Ecological Site Descriptions were first sorted by Major Land Resource 

Area and State and then by soil temperature regime, moisture regime, 

and moisture subclass to evaluate the ecological sites most often correlated with the Priority Areas for Conservation. A map intersecting Level 

III Ecoregions with Major Land Resource Areas and Priority Areas 

for Conservation (fig. A4.1) was produced. Each Level II Ecoregion 

spreadsheet was filtered by central Major Land Resource Area concepts 

for the Ecoregion as described in Chambers et al. 2016a.

 2. The Ecological Site Information System was used to query dominant ecological site descriptions supporting big sagebrush plant communities based on 

National Soil Information System data, Major Land Resource Area concepts, 

and consultation with NRCS State Rangeland Management Specialists or 

equivalent. In some cases, ecological site concepts exist with no state-andtransition models or there are variable state-and-transition model concepts 

depending on the age of the Ecological Site Descriptions. The most contemporary state-and-transition models were prioritized for consideration, but older 

products were used when they were the best available product to represent a 

regime concept.
USDA Forest Service RMRS-GTR-360. 2017. 169

3. Potentially representative ecological sites were downloaded into folders 

and organized by soil temperature/moisture regime concepts. The various 

resources used were not always in agreement, and each area was reviewed 

to determine the best source of data. Resources used to determine the regime 

included:

 a. Ecological Site Description climate section;

 b. Land Resource Unit concept or State ecological zones, when available;

 c. Major Land Resource Area description climate section—edits to 

Major Land Resource Area descriptions are anticipated by local staff 

providing input on these descriptions, and have been incorporated as 

appropriate;

Figure A4.1—Overlay of the level III ecoregions (EPA 2016) and the Major Land 

Resource Areas (NRCS 2006) used to develop ecological types in the eastern portion of the range.
170 USDA Forest Service RMRS-GTR-360. 2017.

d. National Soil Information System assigned temperature and moisture 

regime by mapunit component and accompanying map—some areas 

are populated with older mapping concepts or are not populated in the 

National Soil Information System;

 e. PRISM maps; and

 f. Local experts (see names in Chambers et al. 2016a).

 4. Regime concepts with representative Major Land Resource Areas and 

Ecological Site Descriptions were derived and are in Chambers et al. 2016a. 

These were used to develop the ecological types. The ecological types were 

characterized by soil temperature and moisture regimes (to moisture subclass), 

vegetation, resilience to disturbance, and resistance to invasive annual grasses. 

In order to more accurately describe the temperature regime of the ecological 

types, a soil temperature subclass was derived for temperature regimes bordering on two different regimes. The terminology for soil temperature subclass is 

similar to the one used for soil moisture subclasses in the Soil Survey. 

This appendix was prepared by Karen J. Clause. Steve Campbell, Jeanne 

Chambers, Jeremy Maestas, Dave Pyke, and Mary Manning contributed to the 

development of the methods used to derive the ecological types.
USDA Forest Service RMRS-GTR-360. 2017. 171

Appendix 5—Generalized State-and-Transition Models 

for Predominant Sagebrush Ecological Types in the 

West-Central Semiarid Prairies (MZ I), and Western 

Cordillera and Cold Desert (MZ II, VII) in the Eastern 

Portion of the Range

These generalized state-and-transition models are for a subset of the ecological 

types in table 6 and are based on comparisons of multiple individual Ecological 

Site Descriptions. See Appendix 4 for a description of the methods used to develop 

the ecological types. State-and-transition model development was prioritized for 

ecological types with the highest relative acreage in Priority Areas for Conservation 

(FWS 2013). These state-and-transition models can inform planning efforts at midto local scales, but for project scale planning efforts, state-and-transition models 

for specific ecological sites are most appropriate if available. Large boxes illustrate 

states that are comprised of community phases (smaller boxes). Transitions among 

states are shown with arrows starting with T; restoration pathways are shown with 

arrows starting with R. The “at risk” community phase is most vulnerable to transition to an alternative state.

This appendix was prepared by Karen J. Clause and Mary Manning. Jeanne 

Chambers, Brian Mealor, and numerous resource professionals contributed to the 

development of these state-and-transition models.
172 USDA Forest Service RMRS-GTR-360. 2017.

Altered/Seeded State

Clubmoss/Perennial

Cool and Warm

Season ShortGrasses/Early

Successional Forbs/

Minor Invasives

Clubmoss State

Sagebrush increases and proportion of cool

season mid-grass Functional/Structural Group

decreases due to disturbances such as drought

(3-5 years) and spring grazing.

Normal precipitation patterns favor

herbaceous understory. Grazing intensity

and/or duration is reduced to allow for

herb recovery.

Sagebrush increases and proportion of cool

and warm season mid-and short-grass

Functional/Structural Groups increases due to

prolonged drought (5-7 years), increased grazing

intensity and duration, and lack of fire. Plant

community is at-risk of leaving reference state

with extended drought and continued grazing

pressure.

With favorable precipitation, disturbance such

as fire, and a grazing system that provides rest

and recovery of preferred species, cool season

mid-grass Functional/Structural Groups increase.

Extended drought (>7 years) along with

high intensity and long duration grazing result

in transition to a state resistant to grazing that

is dominated by cool and warm season

short-grass Functional/Structural Groups.

Silver sagebrush cover is at its highest, and early

seral forbs are present. There is potential for

invasive species such as field brome in high

moisture years and/or due to removal of grazing,

lack of fire, and other conditions causing

accumulation of excessive litter.

Normal precipitation patterns, fire or fire

surrogates (herbicides and/or mechanical

treatments), and a grazing regime with proper

timing and intensity that varies season of use

can return the site to the reference state.

Extended drought (>7 years) may result in

dense stands of clubmoss. However, no grazing,

light grazing, and rotational grazing combined

with drought can result in more rapid increase

in clubmoss than drought alone. Lack of fire

may contribute to this transition as well.

Potential for invasives such as field brome is

minor, and this transition occurs more often on

older, more developed soils with an argillic horizon.

Extended periods of normal and above

average precipitation, mechanical renovation,

chemical treatment, fertilizer/manure application,

seeding (if an adequate seedbank does not exist),

fire, and/or periods of rest or light grazing can

return the site to the reference state.

Former cropland seeded to introduced and/or

native perennial grasses, largely funded by

government programs. In the 1960-1970s

seedings were primarily introduced species such

as crested wheatgrass, intermediate wheatgrass,

and smooth brome. From 1985 to present both

introduced and native species were used, mainly

under the Conservation Reserve Program.

Sagebrush is largely absent from this state

There is potential for invasive species such as

field brome in high moisture years and/or due to

removal of grazing, lack of fire, and other

conditions that would result in an accumulation

of excessive litter.

A.5.1 WEST CENTRAL SEMIARID PRAIRIES

FRIGID BORDERING ON CRYIC/USTIC BORDERING ON ARIDIC

GRASS DOMINATED W/ SILVER SAGEBRUSH (10-14 IN PZ)

High Resilience and Resistance

Reference State

Perennial Warm Season

Short- and Cool Season MidGrasses /Annual and

Perennial Forbs/

Sagebrush (at-risk)

Perennial Cool and

Warm Season ShortGrasses/Annual and

Perennial

Forbs/Sagebrush/

Invasives

Unsustainable

Grazing State

Go Back Land

(former cropland,

seeded to perennial

grasses)

Perennial Cool Season

Mid-Grasses/Perennial

Forbs/Sagebrush

T5

T4

2

3

R4

1b

1a

R5

T6

1a

1b

Perennial Cool Season 

Mid- and Warm Season 

Short Grasses/Perennial 

Forbs/Sagebrush

3 2

T4 R4

T5 R5

T6
USDA Forest Service RMRS-GTR-360. 2017. 173

Altered/Seeded State

Grazing Resistant

without Fire State

Proportion of cool and warm season tall

and mid-grass Functional/Structural

Groups decreases due to disturbances

such as drought and spring grazing with

a lack of disturbances such as fire.

Fire and normal precipitation patterns

favor herbaceous understory. Reduced

grazing intensity and/or duration allows

for herbaceous recovery.

Extended drought, high intensity and

long duration grazing, and a normal

fire regime or fire surrogate (herbicides

and/or mechanical treatments) will result

in a transition to a grazing resistant state

dominated by warm and cool season

short-grass Functional/Structural Groups

and silver sagebrush and prickly pear cactus.

Forbs are early seral. 

Normal precipitation patterns and proper

timing and intensity of grazing that varies

season of use can return the site to the

reference state. Mechanical treatments

are often used to renovate and return the

site to one resembling the reference state.

Extended drought, high intensity and

long duration grazing, and lack of fire will

result in a transition to a grazing resistant

state dominated by short-statured warm

and cool season grasses. Forbs are early seral.

Extended periods of normal precipitation,

possibly seeding (if an adequate seedbank

does not exist), mechanical renovation,

and reduced grazing pressure that varies

season of use can return the site to one

resembling the reference state.

Introduction of fire results in loss of

Wyoming big sagebrush and an increase

in silver sagebrush. Continued high

intensity and long duration grazing

results in the increase of undesirable

species like prickly pear cactus.

Former cropland seeded to introduced

and/or native perennial grasses, largely

funded by government programs. In the

1960-1970s seedings were primarily

introduced species such as crested

wheatgrass, intermediate wheatgrass,

and smooth brome. From 1985 to present

seedings used both introduced and native

species, mainly under the Conservation

Reserve Program. An invaded plant

community is possible if seed source is

introduced or adjacent to area. Dominant

species include field brome, smooth brome,

Kentucky bluegrass, thistles, bindweed,

knapweed, leafy spurge, hoary cress, and

other introduced weedy species. Sagebrush

is largely absent from this state.

A.5.2 WEST CENTRAL SEMIARID PRAIRIES

FRIGID/USTIC

GRASS DOMINATED (13-18 IN PZ)

Moderate to High Resilience and Resistance

Reference State

Perennial Cool and

Warm Season ShortGrasses/Annual and

Perennial Forbs/ silver

sagebrush/Prickly

pear cactus

Unsustainable Grazing

with Fire State

Go Back Land

ALL STATES

Invaded

1a

1b

T4 R4

R5

T6

T4

R4

T5

1b

1a

Perennial Cool and

Warm Season Tall and

Mid-Grasses/

Perennial Forbs/Minor

silver sagebrush

Perennial Cool and

Warm Season Mid-and

Short-Grasses/

Perennial Forbs/Minor

silver sagebrush

Perennial Cool and

Warm Season ShortGrasses/Annual and

Perennial Forbs/

Sagebrush

T5 R5

T6

T7

T7
174 USDA Forest Service RMRS-GTR-360. 2017.

Altered/Seeded State

Heavy Sagebrush/

Perennial Cool and

Warm Season

Grasses/Perennial

Forbs

Non-fire State

Sagebrush decreases due to fire and

normal precipitation patterns that favor

the herbaceous understory. Grazing

intensity and/or duration is reduced to

allow for herbaceous recovery. 

Sagebrush increases and proportion of

cool season grasses decrease due to

disturbances such as drought and grazing,

along with a lack of disturbances such as fire. 

Prolonged drought, improper grazing, and

frequent sagebrush control using fire or

fire surrogates (herbicides and/or mechanical

treatments) will result in transition to a

grazing resistant state dominated by warm

and cool season short-and sod-forming grass

Functional/Structural Groups and undesirable

species such as prickly pear cactus. Invasive

species (e.g., cheatgrass, field brome) can

occur in disturbed areas. Field brome invasion

can occur in undisturbed rangelands at the

upper end of the precipitation range.

Normal precipitation patterns, reducing

the frequency and severity of disturbances

that kill sagebrush, and proper timing and

intensity grazing regime that varies season

of use can return the site to the reference state.

Extended drought, frequent and severe

grazing, and removal of fire and fire

surrogates (herbicides and/or mechanical

treatments) will result in transition to a

state dominated by sagebrush with minor

warm and cool season short-grass and

forb Functional/Structural Groups.

Invasion can occur as bare ground increases

in sagebrush canopy interspacesin disturbed

areas.

Extended periods of normal precipitation,

treatment with fire surrogates, seeding

(if adequate seedbank does not exist),

and reduced grazing pressure that varies

season of use can return the site to the

reference state. 

Former cropland that has been seeded to

introduced and/or native perennial grasses,

largely funded by government programs.

In the 1960-1970s seedings were primarily

introduced species such as crested wheatgrass,

intermediate wheatgrass, and smooth brome.

From 1985 to present both introduced and

native grasses were used, mainly under the

Conservation Reserve Program. Sagebrush is

largely absent.

A.5.3 WEST CENTRAL SEMIARID PRAIRIES

FRIGID/USTIC BORDERING ON ARIDIC

WYOMING BIG SAGEBRUSH (10-14 IN PZ)

Moderate to High Resilience and Resistance

Reference State

Perennial Cool and 

Warm Season 

Grasses, sodforming/Annual and 

Perennial Forbs

Unsustainable

Grazing State Go Back Land 

(former cropland,

seeded to perennial

grasses)

T2

1a

1b

R2 T4

Sagebrush/Perennial

Cool and Warm Season

Grasses/

Perennial Forbs

R3

T2

R2

T3

1b

1a

Perennial Cool and

Warm Season

Grasses/Annual and

Perennial Forbs

T3 R3

T4
USDA Forest Service RMRS-GTR-360. 2017. 175

Altered/Seeded State

Heavy Sagebrush/ 

Perennial Cool and

Warm Season

Grasses/Perennial

Forbs/Invasives

Non-fire State

Sagebrush increases and proportion of

cool season grasses decrease due to

disturbances such as drought and grazing

with a lack of disturbances such as fire.

Sagebrush decreases due to fire and

normal precipitation patterns that favor

an herbaceous understory. Reduced

grazing intensity and/or duration allows

for herbaceous recovery.

Extended drought, frequent and severe

grazing, and frequent sagebrush control

using fire or fire surrogates result in a

transition to a grazing resistant state

dominated by warm and cool season

short- and sod-forming grass

Functional/Structural Groups and

undesirable species such as prickly pear

cactus. Invasion of cheatgrass and/or

field brome can occur.

Normal precipitation that reduces the

frequency and severity of sagebrush killing

disturbances, and proper timing and intensity

grazing that varies season of use can return

the site to the reference state.

Extended drought, frequent and severe

grazing, and removal of fire and fire

surrogates will result in transition to a

state dominated by sagebrush with minor

warm and cool season short-grass and forb

Functional/Structural Groups. Invasion often

occurs as bare ground increases in sagebrush

canopy interspaces.

Extended periods of normal precipitation,

treatment with fire surrogates, seeding

(if adequate seedbank does not exist), and

reduced grazing pressure that varies season

of use can return the site to the reference state.

Former cropland that has been seeded to

introduced and/or native perennial grasses,

largely funded by government programs. In

the 1960-1970s seedings were primarily

introduced species such as crested wheatgrass,

intermediate wheatgrass, and smooth brome.

From 1985 to present seedings used both

introduced and native grasses, mainly under

the Conservation Reserve Program. Sagebrush

is largely absent.

Fire and fire surrogates, followed by warm

and wet springs and year-long grazing can

result in an invaded state co-dominated by

annual grasses (cheatgrass) and short-stature

warm and cool season perennial grasses.

Shrubs are largely absent.

A.5.4 WEST CENTRAL SEMIARID PRAIRIES

MESIC/USTIC BORDERING ON ARIDIC

WYOMING BIG SAGEBRUSH (10-14 IN PZ)

Low to Moderate Resilience and Resistance

Reference State

Perennial Cool and

Warm Season

Grasses, sodforming/Annual and

Perennial Forbs/

Invasives

Unsustainable

Grazing State

Go Back Land

(former cropland,

seeded to perennial

grasses)

Perennial Warm and

Cool Season GrassesInvasives

Invaded State

R3

T4

T2

R2

T3

1b

1a

T2 R2 T4

T3 R3

Perennial Cool and

Warm Season

Grasses/Annual and

Perennial Forbs

Sagebrush/Perennial

Cool and Warm Season

Grasses/

Perennial Forbs

1a

1b

T5

T6

T5

T6
176 USDA Forest Service RMRS-GTR-360. 2017.

Perennial cool

season bunch

grasses/annual and

perennial forbs/

sprouting shrubs

Sagebrush/

sprouting shrubs

perennial grass/forb

Reference state

Root-sprouting

shrubs/perennial

cool season

grasses/annual and

perennial forbs

Sprouting Shrub State

Sagebrush/root

sprouting shrubs,

perennial cool

season short-stature

bunchgrasses and

rhizomatous

grasses/mat-forming

forbs

Grazing Resistant State

Perennial grass, forbs and sprouting shrubs increase

and dominate due to disturbances that decrease

sagebrush, primarily wildfire.

Sagebrush and other shrubs increase with time

until co-dominant with herbaceous species.

Perennial grass, forbs, and sprouting shrubs

increase due to disturbances that decrease

sagebrush, e.g., wildfire, insects, and disease.

Sagebrush and other shrubs increase with time. 

Perennial grass, forbs, and sprouting shrubs

increase due to minor disturbances that decrease

sagebrush like cool fire, insects, and disease.

Continuous grazing with cattle during the critical

growth period of cool season grasses results in

dominance of sagebrush and an increase in

grazing tolerant native forbs (e.g., lupine,

pussy-toes). As bare ground increases, surface

erosion (e.g., rills, sheet erosion) may occur,

resulting in loss of the surface soil horizon, and

pedestalled plants. 

Sagebrush treatment via chemical, mechanical, or

prescribed fire combined with a grazing system

that allows periodic deferment during the critical

growth period can result in return to the reference. 

Increased disturbance frequency and/or intensity

(e.g., fire, fire surrogates, and/or mechanical types

of disturbance, and/or high density/frequency

grazing) will result in dominance of root-sprouting

shrubs.

Removal of disturbances and a grazing regime that

allows for adequate rest and recovery of native

perennial grasses and forbs can eventually result

in a return to the reference state.

Perennial cool season short-stature bunchgrasses

and rhizomatous grasses, mat-forming forbs, and

sprouting shrubs increase in dominance due to

disturbances that decreased sagebrush (e.g.,

wildfire, insects, disease).

Sagebrush, non-browsed shrubs, and mat-forming 

orbs increase with time.

An increase in disturbance frequency, fire, fire

surrogates, mechanical types of disturbance and/or

high density/frequency grazing will result in

dominance of root-sprouting shrubs.

Introduction of grazing tolerant non-native species,

such as Kentucky bluegrass during homesteading days

or smooth brome during reclamation results in

transition to this state.

Grazing tolerant non-native species are seeded,

and disturbances are removed reducing sagebrush. 

Sagebrush and other shrubs increase.

Perennial grass, forbs, and sprouting shrubs

increase due to disturbances that decrease sagebrush

(e.g., wildfire, insects, disease).

Sprouting shrubs, forbs, and non-native perennial

grasses increase due to disturbances that decrease

sagebrush (e.g., wildfire, insects, disease) or

treatments that remove or reduce sagebrush.

Sagebrush and other shrubs increase. 

High levels of fuel reduction through grazing and

fire suppression can lead to conifer expansion

outside the normal range of variability for a site. 

Above average precipitation and/or reduced

grazing pressure allow fine fuel accumulation,

and the use of fire or fire surrogates can result

in return to the Grazing Resistant State, but

return to the Reference State is only achievable

through (R4) with the appropriate grazing

prescription.

A.5.5 WESTERN CORDILLERA – CRYIC/TYPIC USTIC

MOUNTAIN BIG SAGEBRUSH/

MIXED MOUNTAIN SHRUBS (15 -19 IN + PZ)

High Resilience and Resistance

Perennial cool

season bunch

grasses-sprouting

shrubs-sagebrush/

perennial forbs

Sagebrush/root

sprouting shrubs/

non-native Perennial

grass

Altered/Seeded State

Sprouting shrubs/

annual and

perennial forbs/

non-native Perennial

grass

Root-sprouting

shrubs/Perennial

cool season

grasses/annual and

perennial forbs/

sagebrush Perennial cool

season short-stature

and rhizomatous

grasses/mat-forming

forbs/

Sagebrush - root

sprouting shrubs

Wooded State

Conifer Expansion

T4

1

2a

R4 R5

R4

T4

2b

3a

3b

2a

1

3b

2b

3a

6a 6b

T5

10a 10b

T9

11a 11b

T7

T8

T12 T13

T5

R5

6a

6b

T7

T8

T9

10a

10b

11a

11b

T12

T12
USDA Forest Service RMRS-GTR-360. 2017. 177

Altered/Seeded State

Sagebrush/ Bare

Ground/

(at-risk phase)

Eroded State

Perennial grass, sprouting shrubs, and forbs become

dominant due to disturbances that decrease sagebrush

like prolonged or severe drought, freezing, flooding,

wildfire, insects, disease, and pathogens. Fire is rare.

Sagebrush increases with time until it is co-dominant

with the herbaceous understory.

Perennial grass, sprouting shrubs, and forbs become

dominant due to disturbances that decrease sagebrush

like prolonged or severe drought, freezing, flooding,

wildfire, insects, disease, and pathogens.

Sagebrush increases with time until dominant.

Perennial grass and forbs increase due to minor

disturbances that decrease sagebrush.

Continuous spring grazing during the critical growth

period of cool season grasses results in dominance of

grazing tolerant species, like short-statured bunchgrasses

(e.g. Sandberg bluegrass) and rhizomatous species. As

bareground increases, surface erosion (e.g., rills, sheet

erosion)and pedestalled plants (especially bunchgrasses)

result. 

Light to moderate grazing with periodic rest during

critical growth periods along with fire, herbicides, and/or

mechanical treatments result in return to reference state. 

An increase in fire, fire surrogates, mechanical

disturbance, and/or high density/frequency grazing

results in disturbance-adapted sprouting shrubs

like rabbitbrush.

Sagebrush increases with time until dominant.

Grazing tolerant perennial cool season grasses increase

due to disturbances that decrease sagebrush.

Perennial grasses and forbs are eliminated and

sagebrush increases with high density/frequency

grazing by cattle, resulting in altered biotic, hydrologic,

and soil function. This state is at-risk of invasion by

annuals after a catastrophic sagebrush killing event. 

Chemical or mechanical treatments to reduce sagebrush

in the 1940s through 70s followed by improper stocking

rates and seasons of use resulted in a shift toward

sprouting shrubs, such as rabbitbrush.

Sagebrush increases with removal of disturbances

over time until co-dominant with sprouting shrubs.

Perennial cool season grasses and sprouting shrubs

increase due to disturbances that decrease sagebrush.

Chemical or mechanical treatments to reduce sagebrush

in the 1940s through 70s followed by improper stocking

rates and seasons of use resulted in a shift toward

sprouting shrubs, such as rabbitbrush.

All states are subject to disturbance from oil and gas

exploration or other mechanical disturbances that

remove surface soils. Restoration success on good

soil management, proper seeding techniques, and

weather. Due to native seed availability, grass and

shrubs can be restored, but forb diversity and

applicability to site conditions can be a limiting factor

for biotic integrity. Something resembling the reference

state may be achieved with key differences in soil and

hydrologic function. 

Many abandoned oil and gas wells without proper

reclamation practices (no top soil

management/replacement or seeding) from the

1980s are now in the Eroded State.

Sagebrush increases with time and no disturbances

until co-dominant with the herbaceous understory.

Perennial grass and forbs become dominant due to

disturbances that decrease sagebrush.

Sagebrush increases with no disturbances over time.

Perennial grass and forbs become dominant due to minor

disturbances that decrease sagebrush.

Annual forbs become dominant due to disturbances that

remove existing perennial vegetation.

A.5.6 COLD DESERTS – FRIGID/USTIC BORDERING ON ARIDIC

WYOMING BIG SAGEBRUSH (9-14 IN PZ)

Moderate to Low Resilience and Moderately High Resistance

Perennial Cool Season

Grasses/Sprouting

Shrubs/

Annual and Perennial

Forbs

Sagebrush/

Perennial Cool Season

Grasses/

Perennial Forbs

Reference State

Perennial Cool Season

Grasses-Sagebrush/

Perennial Forbs

Sagebrush/

Perennial cool season

rhizomatous & short 

grasses/mat-forming

forbs

Perennial cool season

rhizomatous & short

grasses/sagebrush

Grazing Resistant State

Sprouting Shrubs/

Perennial cool season

grasses/annuals

Sprouting ShrubsSagebrush/

Perennial cool season

grasses

Sprouting Shrub State

All States

T4 R4 T5

R4

T4

2b

3a

3b

2a

1

1

2b 3b 3a 2a

6a 6b T8

9a 9b

T7 T10

T12

R11

Annual Forbs/Bare

Ground

Perennial grassesSagebrush/

Sagebrush/

Perennial Grasses

15

14a 14b

13a 13b

6b

6a

T5

9a

T8

T7

R11

T10

9b

13b

13a

T12

14b

14a

15
178 USDA Forest Service RMRS-GTR-360. 2017.

Invaded state

Altered/Seeded State

Sagebrush/Bare

Ground/

(at-risk phase)

Eroded State

Perennial grass, sprouting shrubs, and forbs become

dominant due to disturbances that decrease sagebrush

like prolonged or severe drought, freezing, flooding,

wildfire, insects, disease, and pathogens.

Sagebrush increases with time until co-dominant

with the herbaceous understory.

Perennial grass, sprouting shrubs, and forbs become

dominant due to disturbances that decrease sagebrush.

Sagebrush increases with time until dominant.

Perennial grass and forbs increase due to

disturbances that decrease sagebrush.

Continuous spring grazing with cattle during the

critical growth period of cool season grasses results in

dominance of grazing tolerant species that may include

warm season grasses (e.g., blue grama). As bare ground

increases, surface erosion (e.g., rills, sheet erosion) and

pedestalled plants (especially bunchgrasses) may result. 

Light to moderate grazing with periodic rest during

critical growth periods along with fire, herbicides,

and/or mechanical treatments can result in return

to reference state. 

An increase in the disturbance cycle by fire, fire

surrogates, mechanical types of disturbance, and/or

high density/frequency grazing will favor sprouting

shrubs such as rabbitbrush. Annual invasives can occur.

Sagebrush increases with time. Cheatgrass and

other weeds can be present, but do not dominate.

Perennial cool season grasses increase due to

disturbances that decrease sagebrush. A temporary

flush of annual invaders is expected.

Sagebrush increases with time and removal of

disturbances until co-dominant with herbaceous

understory.

Perennial cool season grasses and sprouting shrubs

increase due to disturbances that decrease sagebrush.

Perennial grasses and forbs are eliminated and

sagebrush increases with high density/frequency

grazing by cattle, resulting in altered biotic, hydrologic,

and soil function. This state is at-risk to invasion by

annuals such as cheatgrass, especially after a

stand-replacing, sagebrush killing event. 

If a cheatgrass seed source is introduced, and

weather conditions are conducive to establishment

(warm wet spring), it will invade, especially after a

stand-replacing event that eliminates sagebrush.

Fire and fire surrogates that kill sagebrush will

dramatically increase cheatgrass. 

Multiple chemical and/or mechanical treatments or

biological disturbances that reduce sagebrush will result

in a shift toward sprouting shrub dominance with

potential for cheatgrass to invade.

Catastrophic climatic events and/or fire can result

in cheatgrass dominance, especially when in the

sagebrush dominant phase of the altered state.

A restoration treatment, including chemical treatment

for cheatgrass and seeding can restore a perennial

grass community and eventually support an altered

sagebrush community with invaders.

Sagebrush increases with time and no disturbances

until co-dominant with the herbaceous understory,

but cheatgrass will be present.

Perennial grass and forbs become dominant due to

disturbances that decrease sagebrush.

Sagebrush increases with time and no disturbances

until dominant, but cheatgrass may be present.

Perennial grass and forbs become dominant due to

minor disturbances that decrease sagebrush.

Perennial grass and annual/perennial forbs become

dominant due to disturbances that decrease sagebrush.

A.5.7 COLD DESERTS – FRIGID/USTIC BORDERING ON ARIDIC

WYOMING BIG SAGEBRUSH (10-14 IN PZ)

Moderate Resilience and Resistance

Reference State

Perennial Cool Season

Grasses-Sagebrush/

Warm Season Sod-forming

Grasses/Annual and

Perennial Forbs

Sagebrush/

Perennial cool season

rhizomatous, short

and/or sod-forming

warm season grasses/

mat-forming forbs

Perennial cool season

rhizomatous, short

and/or sod-forming

warm season grassesSagebrush

Grazing Resistant State

Sprouting Shrubs/

Perennial cool season

grasses/Annuals

Sprouting ShrubsSagebrush/

Perennial cool season

grasses

Sprouting Shrub State

Sagebrush/

Annual invasives

Cheatgrass

Perennial grasses/

Annual and

Perennial Forbs/

Sprouting Shrubs

Cheatgrass

Perennial grassesSagebrush/

Cheatgrass

Sagebrush/

Perennial Grasses/

Cheatgrass

(at-risk phase)

T4 R4

R12

6a

T5

3b

T4

R4

3a

1

Sagebrush/

Perennial Cool Season

Grasses/

Minor Warm Season

Sod-forming Grasses/

Perennial Forbs

Perennial Cool Season

Grasses-Sprouting

Shrubs/Annual and

Perennial Forbs/

Warm Season Sodforming Grasses

1

3b 3a 2a 2b

T11

10

7b

T8

T9

7a

6b

15

14b

13a

13b

14a

R12

T12

7a 7b

T5

2b

2a

6a 6b

T8

T11

T9

T12

10

14a 14b

13a 13b

15
USDA Forest Service RMRS-GTR-360. 2017. 179

Reference State

Phase III Woodland

Trees dominant/

Perennial cool

season grass rare/

Cheatgrass 

increases 

(at-risk phase)

Phase II

Wooded State

Trees dominant

Bare ground

understory

Eroded State

Phase I Woodland

Sagebrush/

Perennial Cool Season

Grasses/Trees

(at-risk phase)

Phase II Woodland

Trees/

Perennial cool

season grasses/

Shrubs minor

Disturbances such as wildfire, insects, disease, and pathogens result in less sagebrush and more perennial cool season grasses, forbs, and sprouting shrubs like

rabbitbrush. 

Sagebrush increases with time until dominant.

Time without fire or fire surrogates combined with

seed sources for piñon and/or juniper trigger a

Phase I Woodlandinvasion and an at-risk phase.

Fire and/or fire surrogates (herbicides and/or mechanical

treatments) that remove trees may restore perennial cool

season grasses and forbs, but these activities often also

reduce sagebrush temporarily. 

Increasing tree abundance results in a Phase II

woodland with decreasing sagebrush cover due

to competition for sunlight, water and nutrients,

and a transition to a tree-dominated state.

Cheatgrass invasion is common during this transition.

Fire and fire surrogates (herbicides and/or mechanical

treatments) that remove trees may restore perennial cool

season grasses, annual/perennial forbs, and eventually

sagebrush dominance if treated during Phase II invasion.

An increase in fire, fire surrogates, mechanical types of

disturbance and/or high density/frequency grazing will

favor sprouting shrubs like rabbitbrush. Cheatgrass

often invades.

Removal of disturbances can result in a restored state

over time. Seeding may be necessary depending on the

type and amount of disturbance.

Infilling of trees and/or improper grazing can result in

further increase in tree canopy cover, resulting in near

complete loss of sagebrush component, decreased

perennial cool season grasses, and increased risk of

high severity crown fires. Cheatgrass will likely increase

with favorable climate conditions.

As crown canopy increases, all other vegetation,

including perennial understory and cheatgrass

decreaseuntil trees are almost the only remaining

vegetation.

Seeding after fire or fire surrogates may be necessary

on sites with depleted perennial cool season grasses,

forbs, and shrubs. If soils are not highly altered and

native species seeded, it is possible to transition to a

state that is similar to the Reference State, but with

altered biotic function.

Catastrophic fire without proper rehabilitation can

result in an abiotic hydrologic and biotic threshold

crossing to an eroded state depending on soils, slope,

and understory species. Key soil properties can

change, altering site potential. Cheatgrass dominates

the system and it burns before perennial vegetation

becomes established.

Seeding after catastrophic fire or fire surrogates

will be necessary due to lack of a perennial cool

season grass, forb, and shrub seedbank. Seeding

with nonnatives may decrease annual invasives,

but will also reduce native species. Biotic and

hydrologic function may be irreversibly altered.

Restoration could be cost prohibitive.

Disturbances result in less sagebrush and more

perennial cool season grasses, forbs, and

sprouting shrubs like rabbitbrush. Increases in

soil water and nutrient availability result in

increased cheatgrass.

Sagebrush increases until co-dominant with

the herbaceous species. Cheatgrass decreases,

but is present.

Time combined with seed sources for piñon and/or

juniper trigger a Phase I Woodland and an at-risk phase.

Fire and or fire surrogates (herbicides and/or

mechanical treatments) that remove trees may

restore perennial cool season grasses and

annual/perennial forbs, but these activities

often reduce sagebrush and increase cheatgrass

temporarily. 

Increasing tree abundance results in a Phase II

woodland with decreasing sagebrush due to

competition, resulting in a transition to a Phase I

Wooded State.

Altered/Seeded State

A.5.8 COLD DESERTS – FRIGID BORDERING ON MESIC/USTIC

WYOMING BIG SAGEBRUSH (14-18 IN PZ)

Piñon pine and/or juniper potential

Moderate to High Resilience and Moderate Resistance

Cheatgrass

dominant

Sprouting Shrubs

dominant

Cheatgrass invasion

Sprouting Shrub State

Phase III

Wooded State

Perennial Cool Season

Grasses/Annual and

Perennial Forbs/

Sprouting Shrubs

Sagebrush/

Perennial Cool

Season Grasses/

Perennial Forbs

1a

1b

2 3

T4 R4?

T7

T6

T4

R4

T5

3

1a

12b

T10

R11

12a

R9

8

T15

14

13

T5

2

1b

T7

8

T6

Phase I Woodland

Sagebrush/

Perennial Cool

Season Grasses/

Trees/Cheatgrass

(at-risk phase)

14

SagebrushPerennial cool

season grasses/

Perennial Forbs/

Cheatgrass

Perennial cool

season grasses/

Annual and

Perennial Forbs/

Sprouting Shrubs

Cheatgrass

13

12b 12a

T10

R11

R9

T15
180 USDA Forest Service RMRS-GTR-360. 2017.

Altered/Seeded State

Sagebrush/Bare

Ground/

(at-risk phase)

Eroded State

Perennial grass and forbs become dominant due to disturbances that decrease sagebrush like prolonged or severe drought, freezing, flooding, wildfire, insects,

disease, and pathogens. Fire is rare in this system.

Sagebrush increases with time until co-dominant

with the herbaceous understory.

Perennial grass/annual and perennial forbs become

dominant due to disturbances that decrease sagebrush

like prolonged or severe drought, freezing, flooding,

wildfire, insects, disease, and pathogens. Fire is rare.

Sagebrush increases with time until dominant.

Perennial grass and forbs increase due to minor

disturbances that decrease sagebrush.

Continuous spring grazing with cattle during the

critical growth period of cool season grasses results

in dominance of grazing tolerant species which may

include warm season grasses (e.g., blue grama). As

bare ground increases, surface erosion (e.g., rills,

sheet erosion and pedestalled plants [especially

bunchgrasses] result. 

Light to moderate grazing that includes periodic rest

during critical growth periods along with herbicide

and/or mechanical treatments can result in return to

the Reference State. 

An increase in mechanical treatments, high

density/frequency grazing, or fire/fire surrogates

will favor sprouting shrubs such as rabbitbrush

and/or greasewood. Fire is rare. Cheatgrass can

occur.

Sagebrush increases with time. Cheatgrass is often

present with other weedy species.

Perennial cool season grasses increase due to

disturbances that decrease sagebrush. Cheatgrass

is often present with other weedy species.

Perennial grasses and forbs are eliminated and

sagebrush increases with high density/frequency grazing,

resulting in altered biotic, hydrologic, and soil function.

This state is at-risk to invasion by annual grasses. 

Multiple chemical or mechanical treatments, or

biological disturbances to reduce sagebrush can

result in a shift toward sprouting shrub dominance

with potential for cheatgrass to invade.

Sagebrush increases with time and removal of disturbances

until co-dominant with sprouting shrubs.

Perennial cool season grasses, sprouting shrubs, and annuals

increase due to disturbances that decrease sagebrush.

Multiple treatments of chemical, mechanical, or

biological disturbances to reduce sagebrush will

result in a shift toward sprouting shrub dominance

with potential for cheatgrass to occur.

A restoration treatment, including chemical

treatment for cheatgrass and seeding can restore

a perennial grass community and eventually

support an altered sagebrush community with

some invaders.

Sagebrush increases with time and no disturbances

until co-dominant with the herbaceous understory, but

cheatgrass may be present.

Perennial grass/annual and perennial forbs become

dominant due to disturbances that decrease sagebrush like

drought, freezing, flooding, insects, disease, and pathogens.

There may be a temporary flush of annuals.

Sagebrush increases with time and no disturbances

until dominant, but cheatgrass will be present.

Perennial grass and forbs become dominant due to

minor disturbances that decrease sagebrush. There

may be a temporary flush of annuals.

Perennial grass/annual and perennial forbs become

dominant due to disturbances that decrease sagebrush.

There may be a temporary flush of annuals.

Perennial grasses and forbs are eliminated and

sagebrush increases with high density/frequency

grazing, resulting in altered biotic, hydrologic, and

soil function. Cheatgrass is often present in the

understory, and could be considered an “invaded”

state, except that it does not alter fire regimes and

ecological dynamics of the site. 

A.5.9 COLD DESERTS – FRIGID/ARIDIC BORDERING ON USTIC

WYOMING BIG SAGEBRUSH (7-10 IN PZ)

Moderate to Low Resilience and Moderate Resistance

Reference State

Perennial Cool Season

Grasses-Sagebrush/Annual

and Perennial Forbs

Sagebrush/

Perennial cool season

rhizomatous & short

grasses/ mat-forming

forbs

Perennial cool season

rhizomatous & short

grasses/Sagebrush

Grazing Resistant State

Sprouting Shrubs/

Perennial cool season

grasses/Annuals

Sprouting ShrubsSagebrush/

Perennial cool season

grasses

Sprouting Shrub State

ALL STATES

T4 R4

R4

T4

2b

3a

3b

2a

1

Sagebrush/

Perennial Cool Season

Grasses/

Perennial Forbs

Perennial Cool Season

Grasses/Annual and

Perennial Forbs/

Sprouting Shrubs

1

3b 3a 2a 2b

6a 6b

T7

T10

T15

T5

9a 9b

T8

R11

Perennial grassesSagebrush/

Cheatgrass

13a 13b

Sagebrush/

Perennial Grasses/

Cheatgrass

(at-risk phase)

Annual Forbs/Bare

Ground

14

12a 12b

T7

6b

T5

6a

9b

9a

T8

T10

12b

12a

R11

13a

T15

14

13b
USDA Forest Service RMRS-GTR-360. 2017. 181

Invaded state

Altered/Seeded State

Sagebrush/Bare

Ground/

(at-risk phase)

Eroded State

Perennial grass/annual and perennial forbs become

dominant due to disturbances that decrease sagebrush

like prolonged or severe drought, freezing, flooding,

wildfire, insects, disease, and pathogens.

Sagebrush increases with time until co-dominant with

the herbaceous understory.

Perennial grass and forbs become dominant due to

disturbances that decrease sagebrush.

Sagebrush increases with time until dominant.

Perennial grass and forbs increase due to minor

disturbances that decrease sagebrush.

Continuous spring grazing with cattle during the

critical growth period of cool season grasses results

in dominance of grazing tolerant species and increases

in warm season species. As bare ground increases,

surface erosion (e.g., rills, sheet erosion) and

pedestalled plants (especially bunchgrasses) result. 

Light to moderate grazing that includes periodic rest

during critical growth periods along with fire, herbicides,

and/or mechanical treatments can restore perennial cool

season perennial grasses and eventually sagebrush. 

An increase in fire, fire surrogates, mechanical types

of disturbance, and or high density/frequency grazing

favors sprouting shrubs like rabbitbrush. Cheatgrass

can invade.

Sagebrush increases with time until dominant.

Cheatgrass and other weedy species are often present.

Perennial cool season grasses increase due to

disturbances that decrease sagebrush.

Sagebrush increases with time and removal of

disturbances until co-dominant with sprouting shrubs.

Perennial cool season grasses and sprouting shrubs

increase in dominance due to disturbances that

decrease sagebrush.

Perennial grasses and forbs are eliminated and

sagebrush increases with high density/frequency

grazing, resulting in altered biotic, hydrologic, and

soil function. This state is at-risk to invasion by

annuals such as cheatgrass, especially with loss

of sagebrush. 

If a cheatgrass seed source is introduced, and climatic

conditions are conducive to establishment (warm wet

spring), cheatgrass will invade.

A sagebrush killing event, such as fire and fire

surrogates results in conversion to cheatgrass.

Some perennial species may be present, but the

system dynamics will be driven by annual invasives.

Multiple treatments of chemical, mechanical, or

biological disturbances to reduce sagebrush will

result in a shift toward sprouting shrub dominance

with potential for cheatgrass to occur.

Catastrophic climatic events and/or fire can result in

cheatgrass dominance, especially when in the sagebrush

dominant phase of the altered state.

A restoration treatment after severe ground disturbing

activities, including mechanical treatment, seeding with

non-native perennials can restore a perennial grass

community and eventually support an altered sagebrush

community with some invaders present. Sagebrush will

be slow to reestablish.

Sagebrush increases with time and no disturbances

until co-dominant with the herbaceous understory,

but cheatgrass will be present.

Perennial grass and forbs become dominant due to

disturbances that decrease sagebrush. There will likely

be a temporary flush in annual invasives.

A restoration treatment after ground disturbing

activities, including mechanical treatment, seeding with

native perennials adapted to site conditions can result

in a perennial grass community and eventually support

an altered sagebrush community with some invaders

present. Sagebrush will be slow to reestablish.

A.5.10 COLD DESERTS – MESIC/ARIDIC BORDERING ON USTIC

WYOMING BIG SAGEBRUSH (8-12 IN PZ)

Moderate to Low Resilience and Low Resistance

Perennial Cool Season

Grasses/Annual and

Perennial Forbs/

Warm Season Sodforming Grasses/

Sprouting Shrubs

Sagebrush/

Perennial Cool Season

Grasses/

Minor Warm Season

Sod-forming Grasses/

Perennial Forbs

Reference State

Perennial Cool Season

Grasses-Sagebrush/Warm

Season Sod-forming

Grasses/Annual and

Perennial Forbs/

Sagebrush/

Perennial cool season

rhizomatous, short

and sod-forming

warm season grasses/

mat-forming forbs

Perennial cool season

rhizomatous, short

and sod-forming

warm season

grasses/Sagebrush

Grazing Resistant State

Sprouting Shrubs/

Perennial cool season

grasses/Annuals

Sprouting ShrubsSagebrush/

Perennial cool season

grasses

Sprouting Shrub State

Sagebrush/

Annual invasives

Cheatgrass

Perennial grasses/

Annual and

Perennial Forbs/

Sprouting Shrubs

Cheatgrass

Perennial grassesSagebrush/

Cheatgrass

ALL STATES

R4

T4

2b

3a

3b

2a

1

1

3a 3b 2a 2b

T4 R4 T5

6a 6b

T8

T9

10

7a 7b

T11 R12

T12 13a 13b

T9

T8

6b

7a

7b

6a

T5

13b

13a

T11

T12

R12

10

T16
182 USDA Forest Service RMRS-GTR-360. 2017.

Invaded state

Sagebrush/ Bare Altered/Seeded State

Ground/

(at-risk)

Eroded State

Perennial grass/annual and perennial forbs become

dominant due to disturbances that decrease sagebrush

like prolonged or severe drought, freezing, flooding, wildfire, insects, disease, and pathogens. Fire is rare in this system.

Sagebrush increases with time until co-dominant

with the herbaceous understory.

Perennial grass and forbs become dominant due to

disturbances that decrease sagebrush. Fire is rare.

Sagebrush increases with time until dominant.

Perennial grass and forbs increase due to minor

disturbances that decrease sagebrush.

Frequent and severe grazing coupled with frequent

brush management and/or drought results in

dominance of grazing tolerant and sod-forming

warm and cool season species. As bare ground

increases, surface erosion (e.g., rills, sheet erosion)

and pedestalled plants (especially bunchgrasses) result. 

Improper grazing, consisting of frequent and severe

grazing without other disturbances such as fire or

drought, results in dominance of sagebrush with

excessive bare ground, resulting in altered hydrologic

function and compromised soil stability.

Annual invasives are introduced to the site through

ground disturbing activity. Site is dominated by sprouting

shrubs such as rabbitbrush and/or greasewood.

Sagebrush increases with time and removal

of disturbances until dominant.

Perennial cool season sod-forming grasses and

cactus increase due to disturbances that decrease

sagebrush such as sagebrush treatment, drought,

freezing, flooding, insects, disease, and pathogens.

Perennial grasses and forbs are eliminated and

sagebrush increases with high density/frequency

grazing by cattle and absences of sagebrush

killing disturbances, resulting in altered biotic,

hydrologic, and soil function. This state is at-risk

of cheatgrass invasion. 

If a cheatgrass seed source is introduced, and

catastrophic event occurs to kill perennial vegetation,

such as drought followed by wet spring, cheatgrass

can invade and dominate.

A sagebrush killing event, such as fire and fire

surrogates will dramatically increase cheatgrass

while removing sagebrush from the system. 

A restoration treatment, including chemical

treatment for cheatgrass and seeding (native

or introduced mix), favorable climatic conditions

(wet spring), rest from grazing during

establishment, and a grazing system that allows

for adequate rest and recovery of perennial

forage species can restore a perennial grass

community and eventually support an altered

sagebrush community with invaders present.

Sagebrush will not likely dominate in the

foreseeable future. The Altered/Seeded State is

possible from any state after a severe ground

disturbing activity such as mineral extraction.

A catastrophic event such as fire or drought,

followed by a wet spring can result in a system

dominated by annual invasive species.

Sagebrush increases with time and no disturbances

until co-dominant with the herbaceous understory, but

cheatgrass will be present. Introduced species are likely

present if seeded during a restoration activity.

Perennial grass/annual and perennial forbs become

dominant due to disturbances that decrease sagebrush.

There will commonly be a temporary flush of annual

invasives.

Reference State

Perennial Cool Season

Grasses-Sagebrush/

Warm Season Sod-forming

Grasses/Annual and

Perennial Forbs

Sagebrush/

Perennial cool and

warm season sodforming grasses

Perennial cool and

warm season sodforming grasses/

Prickly pear cactus

Grazing Resistant State

Annual and perennial

invasives

Perennial grasses/

Annual and

Perennial Forbs/

Sprouting Shrubs

Cheatgrass

Perennial grassesSagebrush/

Cheatgrass

A.5.11 COLD DESERTS – MESIC/ARIDIC-TYPIC

WYOMING BIG SAGEBRUSH (5-9 IN PZ)

Low Resilience and Resistance

Sprouting Shrub State

Sprouting

shrubs/Annuals

ALL STATES

T4

T5

T4

2b

3a

3b

2a

1

Sagebrush/

Perennial Cool Season

Grasses/

Minor Warm Season

Sod-forming Grasses/

Perennial Forbs

Perennial Cool Season

Grasses/Annual and

Perennial Forbs/

Warm Season Sodforming Grasses

1

3b 3a 2a 2b

T5 T6

7a 7b

T9 T8

T10

T12

R11

13a 13b

T10

T9

7a

7b

T8

T6

13a

T12

R11

13b
USDA Forest Service RMRS-GTR-360. 2017. 183

Appendix 6—Generalized State-and-Transition Models 

for Predominant Sagebrush Ecological Types in the 

Cold Deserts (MZ III, IV, V) in the Western Portion of the 

Range 

These generalized state-and-transition models are for a subset of the ecological 

types in table 6 and are derived from Chambers et al. 2014b, c. These state-and-transition models can inform planning efforts at mid- to local-scales. However, for project scale planning efforts, state-and-transition models for specific ecological sites 

are most appropriate if available. Large boxes illustrate states that are comprised of 

community phases (smaller boxes). Transitions among states are shown with arrows 

starting with T; restoration pathways are shown with arrows starting with R. The “at 

risk” community phase is most vulnerable to transition to an alternative state.

R3

T4

T2

R2

T3

1b

1a Reference State Perennial grass/forb increases

due to disturbances that decrease

sagebrush like wildfire, insects,

disease, and pathogens. 

Sagebrush and other shrubs

increase with time. 

Improper grazing triggers a

shrub dominated state. 

Proper grazing results in return

to the reference state. 

Fire or other disturbances

that remove sagebrush result in

dominance by root-sprouting shrubs

and an increase in native forbs like

lupines. 

Proper grazing and time result in

return to the reference state. 

Note: Resilience is lower on cold cryic

sites due to short growing seasons.

A.6.1 COLD DESERTS – CRYIC/XERIC-TYPIC

MOUNTAIN BIG SAGEBRUSH/MOUNTAIN BRUSH (14 IN + PZ)

Moderately High Resilience and High Resistance

Sagebrush/root

sprouting shrubs

Perennial grass/forb

Perennial grass/forb

Root sprouting 

shrubs/sagebrush

Shrub State

Sagebrush/root

sprouting shrubs

Perennial grass/forb

rare

Shrub/Forb State

Root-sprouting 

shrubs/forbs

Perennial grass rare

T2

1a

1b

R2 T3 R3

T4
184 USDA Forest Service RMRS-GTR-360. 2017.

R9

3 5

1a

R6

Reference State

Phase III Woodland

Trees dominant

Sagebrush and 

Perennial grass/

forb rare

Wooded State

Trees dominant

Sagebrush and

Perennial grass/

forb rare

Eroded State

Phase I Woodland

Sagebrush

Perennial grass/forb

Trees

Phase II Woodland

Trees/sagebrush

Perennial grass/forb 

(at-risk phase)

Perennial grass

forbs/shrubs

Annual Invasives

Seeded State

A.6.2 COLD DESERTS – FRIGID/XERIC-TYPIC

MOUNTAIN BIG SAGEBRUSH (12-22 IN PZ)

Piñon pine and/or juniper potential

Moderately High Resilience and Moderate Resistance

Depending on seed mix and grazing,

return to the reference state may be

possible if an irreversible threshold has not

been crossed.

Seeding after treatments or fire

may be required on sites with depleted

perennial grass/forb, but seeding with

aggressive introduced species can decrease

native perennial grass/forb. Annual

invasives are typically rare. Seeded eroded

states may have lower productivity.

An irreversible abiotic threshold

crossing to an eroded state can occur

depending on soils, slope, and understory

species. 

Fire, herbicides and/or mechanical

treatments that remove trees may restore

perennial grass/forb and sagebrush

dominance. 

Infilling of trees and/or improper

grazing can result in a biotic threshold

crossing to a wooded state with increased

risk of high severity crown fires. 

Fire surrogates (herbicides and/or

mechanical treatments) that remove trees

may restore perennial grass/forb and

sagebrush dominance.

Disturbances such as wildfire, insects,

disease, and pathogens result in less

sagebrush and more perennial grass/forb. 

Sagebrush increases with time. 

Time combined with seed sources for

piñon and/or juniper trigger a Phase I

Woodland. 

Fire and or fire surrogates

(herbicides and/or mechanical treatments)

that remove trees may restore perennial

grass/forb and sagebrush dominance. 

Increasing tree abundance results in a

Phase II woodland with depleted perennial

grass/forb and shrubs and an at-risk phase. 

Sagebrush

Perennial grass/forb

Perennial grass/forb

Sagebrush

R10

T6

4a

4b

1b

2

R8

T7

R9

R8

R10

T7

R6

T6

4b

4a

3

5

2

1b

1a
USDA Forest Service RMRS-GTR-360. 2017. 185

T7

R8

R9

1a

Reference State

Annual invasives

Invaded State

Annual invasives

Perennial grass/forb 

rare

Annual State

Perennial

grass/forbs/shrubs

Annual invasives

Seeded State

Sagebrush

Annual invasives

Perennial grass/forb 

rare

Sagebrush/annual

State

Sagebrush increases with time.

A.6.3 COLD DESERTS – FRIGID BORDERING ON MESIC/XERIC-TYPIC

MOUNTAIN BIG SAGEBRUSH (12-16 IN PZ)

Moderate Resilience and Resistance

T2

1b

R2

Cooler and wetter sites may return

to the invaded or possibly reference state

depending on seeding mix, grazing and

weather. 

Seeding following fire and/or

invasive species control results in

a seeded state. Sagebrush may

recolonize depending on patch size, but

annual invaders are still present. 

Cooler and wetter sites may return

to the invaded or reference state with

lack of fire, proper grazing, and favorable

weather. 

Fire or other disturbances

that remove sagebrush result in

an annual state. Perennial grass/forb are

rare and recovery potential is reduced.

Repeated fire can result in a biotic

threshold crossing to annual dominance

on warmer/drier sites, and root-sprouting

shrubs may increase. 

Proper grazing may facilitate return

to the invaded state on cooler/wetter

sites if sufficient grass/forb remains.

Improper grazing results in a

sagebrush/annual state.

Proper grazing, herbicides, or

mechanical treatments that reduce

sagebrush may increase perennial

grass/forb and decrease invasives. 

Perennial grass/forb decreases and

sagebrush and invasives increase with

improper grazing by livestock resulting in

an at-risk phase. Decreases in sagebrush

due to insects, disease, or pathogens can

further increase invasives. 

Perennial grass/forb increases due

to disturbances that decrease sagebrush

like wildfire, insects, disease, and

pathogens.

An invasive seed source and/or

improper grazing trigger an invaded state. 

Proper grazing, fire, herbicides,

and/or mechanical treatments may

restore perennial grass/forb and

sagebrush dominance with few invasives.

1a

1b

T2

R2

3a

3b

T4

R4

T5

T7

R5

R6

R8

R9

R10

Sagebrush

Perennial grass/forb

Perennial grass/forb

Sagebrush

Sagebrush

Perennial grass/forb

Sagebrush

Annual invasives

Perennial grass/forb

(at-risk phase)

3a

3b

T4 R4? T5 R5?

R10

R6
186 USDA Forest Service RMRS-GTR-360. 2017.

3

Reference State

Annual invaders

Perennial grass/forb

rare

Annual State

Perennial grass

forbs/shrubs

Annual Invaders

Seeded State

Trees dominant

Sagebrush and

Perennial grass/

forb rare

Eroded State

State

A.6.4 COLD DESERTS – MESIC BORDERING ON FRIGID/XERIC-TYPIC

BASIN BIG SAGEBRUSH (12-16 IN PZ)

Piñon pine and/or juniper potential

Moderate Resilience and Moderately Low Resistance

Sagebrush

Perennial grass/forb

Phase III Woodland

Trees dominant

Sagebrush and 

Perennial grass/

forb rare

Wooded State

Sagebrush increases with time.

R15

R11

Depending on seed mix, grazing,

and level of erosion, return to the

reference state may occur on cooler and

wetter sites if an irreversible threshold

has not been crossed. 

Seeding after fire and/or

invasive species control increases

perennial grass/forb. Sagebrush

may recolonize depending on

seed sources, but annual invaders are

still present. Seeded eroded states

may have lower productivity.

R12

R13

R14

Fire or other disturbances that

remove trees and sagebrush can result in

a biotic threshold crossing to annual

dominance on warmer/drier sites with

lower resistance. 

T10

An invasive seed source and/or

improper grazing can trigger a

wooded/invaded state. 

T8

T8

An irreversible abiotic threshold

crossing to an eroded state can occur

depending on soils, slope, and

understory species. 

T7

Fire, herbicides and/or mechanical

treatments that remove trees may

restore perennial grass/forb and

sagebrush dominance on cooler/wetter

sites. Seeding may be required.

R6

Infilling of trees and improper

grazing can result in a biotic threshold

crossing to a wooded state with

increased risk of high severity crown

fires. 

T6

Fire surrogates (herbicides and/or

mechanical treatments) that remove

trees may restore sagebrush and

perennial grass/forb dominance.

4b

Increasing tree abundance results in

a Phase II woodland with depleted

perennial grass/forb and shrubs and

an at-risk phase. 

4a

Fire and or fire surrogates

(herbicides and/or mechanical

treatments) that remove trees may

restore perennial grass/forb and

sagebrush dominance on cooler/wetter

sites. On warmer/drier sites with low

perennial grass/forb abundance

resistance to invasion is moderately low. 

3

5

Time combined with seed sources for

piñonand/or juniper trigger a Phase I

Woodland.

2

1b

Disturbances such as wildfire,

insects, disease, and pathogens result in

less sagebrush and more perennial

grass/forb. 

1a

Perennial grass/forb

Sagebrush

1a

1b

2 5

Phase I Woodland

Sagebrush

Perennial grass/forb

Trees

Phase II Woodland

Trees/sagebrush

Perennial grass/forb

(at-risk phase)

4a

4b

T6 R6 T8

T7

T9

Phase I-III Woodland

Sagebrush/trees

Perennial grass/forb

Annual invaders

Wooded/invaded

R15

T10 R11

R13 R14

R12
USDA Forest Service RMRS-GTR-360. 2017. 187

Reference State

Sagebrush

Perennial grass

Annual invasives

Sagebrush

Annual invasives

Perennial grass

(at-risk phase)

Invaded State

Perennial grass increases due to

disturbances that decrease sagebrush

like wildfire, insects, disease,

and pathogens.

Sagebrush increases with time. 

A.6.5 COLD DESERTS – FRIGID BORDERING ON MESIC/ARIDIC-TYPIC

WYOMING BIG SAGEBRUSH (6-12 IN PZ)

Low Resilience and Moderately Low Resistance

R9

R6

R8

Sagebrush

Perennial grass

Perennial grass

Sagebrush

1a

1b

T2 R2?

Seeding effectiveness and return

to the invaded state are related to

site conditions, seeding mix, and

post-treatment weather.

R10

Seeding following fire and/or

invasive species control results

in a seeded state. Sagebrush may

recolonize depending on patch size,

but annual invasives are still present. 

Fire or other disturbances that

remove sagebrush result in an

annual state.Perennial grass is

rare and recovery potential is

low on sites with low precipitation.

Repeated fire can cause further

degradation.

T5

T7

Improper grazing triggers a

largely irreversible threshold

to a sagebrush/annual state.

T4

Proper grazing and herbicides or

mechanical treatments that reduce

sagebrush may restore perennial grass

and decrease invaders on wetter sites

(10-12”). Outcomes are less certain on

drier sites (6-10”) and/or sites with low

abundance of perennial grass. 

3b

Perennial grass decreases and both

sagebrush and invasives increase with

improper grazing resulting in an at-risk

phase. Decreases in sagebrush due to

insects, disease or pathogens can further

increase invasives. 

3a

Proper grazing, fire, herbicides

and/or mechanical treatments may

result in return to the reference state

on wetter sites.

R2

An invasive seed source and/or

improper grazing trigger an

invaded state. 

T2

1b

1a

3a

3b

T4 T5 R6

R9?

?

R10

Sagebrush

Annual invasives

Perennial grass

rare

Sagebrush/annual

State Annual invasives

Perennial grass 

rare

Annual State

T7

R8

Perennial

grass/shrubs

Annual invasives

Seeded State
188 USDA Forest Service RMRS-GTR-360. 2017.

Reference State

Invaded State

Annual invasives

Perennial grass 

rare

Annual State

Sagebrush

Annual invasives

Perennial grass 

rare

Sagebrush/annual

State

Perennial 

grass/shrubs

Annual invasives

Seeded State

Perennial grass increases due to

disturbances that decrease sagebrush

like wildfire, insects, disease, and

pathogens.

Sagebrush increases with time. 

An invasive seed source and/or improper

grazing trigger an invaded state. 

Proper grazing, fire, herbicides and/or

mechanical treatments are unlikely to

result in return to the reference state

on all but the coolest and wettest sites.

Perennial grass decreases and both

sagebrush and invasives increase with

improper grazing resulting in an at-risk

phase. Decreases in sagebrush due to

insects, disease or pathogens can

further increase invasives. 

Proper grazing and herbicides or

mechanical treatments that reduce

sagebrush may restore perennial grass

and decrease invaders on wetter sites

(10-12”). Outcomes are less certain on

drier sites (8-10”) and/or low abundance

of perennial grass. 

Improper grazing triggers a largely

irreversible threshold to a

sagebrush/annual state.

Fire or other disturbances that remove

sagebrush result in an annual state.

Perennial grass is rare and recovery

potential is low due to low precipitation

and competition from annual invasives.

Repeated fire can cause further degradation.

Seeding following fire and/or invasive

species control results in a seeded state.

Sagebrush may recolonize depending

on patch size, but annual invasives are

still present. 

Seeding effectiveness and return to the

invaded state are related to site conditions,

seeding mix, and post-treatment weather.

A.6.6 COLD DESERTS – MESIC/ARIDIC BORDERING ON XERIC

WYOMING BIG SAGEBRUSH (8-12 IN PZ)

Low to Moderate Resilience and Low Resistance

?

R10

1a

1b

Sagebrush

Perennial grass

Perennial grass

Sagebrush

T2 R2?

Sagebrush

Perennial grass

Annual invasives

Sagebrush

Annual invasives

Perennial grass

(at-risk phase)

3a

3b

T4 T5 R6

R9?

T7

R8

R9

R6

R8

R10

T5

T7

T4

3b

3a

R2

T2

1b

1a
USDA Forest Service RMRS-GTR-360. 2017. 189

Appendix 7—Explanation of the Use of Landscape 

Measures to Describe Sagebrush Habitat

Understanding landscape concepts of plant cover relative to typical management 

concepts of plant cover is important for prioritizing lands for management of sagegrouse. Ground-based measurements of sagebrush canopy cover (for example, using 

line-intercept measurements) should not be confused with landscape cover due to 

vast differences in measurement scale (e.g., square meters for management units 

and square kilometers for landscapes).

A landscape is defined rather arbitrarily as a large area in total spatial extent, 

somewhere in size between sites (acres or square miles) and regions (100,000s 

of square miles). The basic unit of a landscape is a patch, which is defined as a 

bounded area characterized by a similar set of conditions. A habitat patch, for example, may be the polygonal area on a map representing a single land cover type. 

Landscapes are composed of a mosaic of patches. The arrangement of these patches 

(the landscape configuration or pattern) has a large influence on the way a landscape 

functions and for landscape species, such as sage-grouse, sagebrush habitat patches 

are extremely important for predicting if this bird will be present within the area 

(Connelly et al. 2011).

Remotely sensed data of land cover is typically used to represent landscapes. 

These data may combine several sources of data and may include ancillary data, 

such as elevation, to improve the interpretation of data. These data are organized 

into pixels that contain a size or grain of land area. For example, Landsat Thematic 

Mapper spectral data used in determining vegetation cover generally have pixels 

that represent ground areas of 900 m2

 (30 x 30 m). Each pixel’s spectral signature 

can be interpreted to determine what type of vegetation dominates that pixel. 

Groups of adjacent pixels with the same dominant vegetation are clustered together 

into polygons that form patches. 

Landscape cover of sagebrush is determined initially by using this vegetation 

cover map, but a rolling window of a predetermined size (e.g., 5 km2

 or 5,556 pixels 

that are 30 by 30 m in size) is then moved across the region one pixel at a time to 

smooth the data. In this process, the central pixel of the window is reassigned a 

value equal to the proportion of pixels in the window for which sagebrush is the 

dominant vegetation. The process is repeated until the value for each pixel within 

the analysis region has been reassigned to represent the landscape cover of sagebrush within a 5-km2

 window. 

This appendix was prepared by David A. Pyke.
190 USDA Forest Service RMRS-GTR-360. 2017.

Appendix 8—Data Sources and Websites for the Maps 

in This Report 

Annually tilled agriculture (cropland)

Source: USDA National Agricultural Statistics Service Cropland Data Layer. 

2014. Published crop-specific data layer. UDSA-NASS, Washington, 

DC. http://nassgeodata.gmu.edu/CropScape/ [Accessed Sept 16, 2015].

Available: http://nassgeodata.gmu.edu/CropScape/ 

Figures: 14, 42

Climate change: Climate variables

Source: Appendix 3

Available: https://www.sciencebase.gov/catalog/item/5850549ae4b0f24ebfd9368f

Figures: Appendix 3

Climate change: Wyoming big sagebrush climate niche models

Source: Still, S.M.; Richardson, B.A. 2015. Projections of contemporary and 

future climate niche for Wyoming big sagebrush (Artemisia tridentata

subsp. wyomingensis): A guide for restoration. Natural Areas Journal. 

35: 30–43. 

Available: https://www.sciencebase.gov/catalog/item/58516105e4b0f99207c4f063

Figure: 35

Cultivation risk

Source: Smith, J.T.; Evans, J.S.; Baruch-Mordo, S.; [et al.]. 2016. Reducing 

cropland conversion risk to sage-grouse through strategic conservation 

of working rangelands. Biological Conservation. 201: 10–19. http://

dx.doi.org/10.1016/j.biocon.2016.06.006

Available: http://map.sagegrouseinitiative.com/

Figure: 42

Ecoregions: Levels II and III

Source: U.S Environmental Protection Agency [EPA]. 2016 Level II and III 

Ecoregions of North America. https://www.epa.gov/eco-research/ecoregions-north-america [Accessed Sept 16, 2015].

Available: https://www.epa.gov/eco-research/ecoregions-north-america

Figures: 1, 3, 5, 6, 7, 10, Appendix 3

Precipitation and temperature data: 30 year normals

Source: PRISM Climate Group, Northwest Alliance for Computational Science 

and Engineering. 2016. 30-year Normals. http://prism.oregonstate.edu/

normals [Accessed Sept 16, 2015].

Available: http://prism.oregonstate.edu/normals 

Figures: 2, 3 
USDA Forest Service RMRS-GTR-360. 2017. 191

Fire perimeters: Geomac

Source: Walters, S.P; Schneider, N.J.; Guthrie, J.D. 2011. Geospatial MultiAgency Coordination (GeoMAC) wildland fire perimeters, 2008. Data 

Series 612. Washington, DC: U.S. Department of the Interior, U.S. Geological Survey. 6 p. http://www.geomac.gov/ [Accessed Feb 1, 2016].

Available: http://www.geomac.gov/

Figures: 7, 51

Fire perimeters: MTBS

Source: Eidenshink, J.; Schwind, B.; Brewer, K.; [et al.]. 2007. A project for 

monitoring trends in burn severity: Fire Ecology. 3: 3–21. http://www.

mtbs.gov/nationalregional/burnedarea.html [Accessed Sept 15, 2015].

Available: http://www.mtbs.gov/nationalregional/burnedarea.html

Figures: 7, 51

Fire risk

Source: Crist, M.R.; Chambers, J.C.; Haas, J.R.; [et al.]. 2016. Fire Risk Assessment for the Greater Sage-Grouse Raster. Washington, DC: U.S. Department of the Interior, Bureau of Land Management.

Available: https://www.sciencebase.gov/catalog/item/5846d366e4b04fc80e52376b

Figures: A.10.1

Greater sage-grouse breeding habitat model

Source: Doherty, K.E.; Evans, J.S.; Coates, P.S.; [et al.]. 2016. Importance of 

regional variation in conservation planning: A rangewide example of the 

Greater sage-grouse. Ecosphere. 7(10): Article e01462. http://onlinelibrary.wiley.com/doi/10.1002/ecs2.1462/full

[Accessed Nov 9, 2016].

Available: https://www.sciencebase.gov/catalog/item/57a26bbae4b006cb45553f57

Figures: 25, 38

Greater sage-grouse connectivity for Priority Areas for Conservation

Source: Crist, M.R.; Knick, S.T.; Hanser, S.E. 2017. Range-wide connectivity 

of priority areas for Greater sage-grouse: Implications for long-term 

conservation from graph theory. Condor. 117: 44–57.

Available: https://www.sciencebase.gov/catalog/item/58504cebe4b0f24ebfd93670

Figure: A.9.1

Greater sage-grouse population index model

Source: Doherty, K.E.; Evans, J.S.; Coates, P.S.; [et al.]. 2016. Importance of 

regional variation in conservation planning: A rangewide example of the 

Greater Sage-Grouse. Ecosphere. 7(10): Article e01462. http://onlinelibrary.wiley.com/doi/10.1002/ecs2.1462/full
192 USDA Forest Service RMRS-GTR-360. 2017.

[Accessed Nov 9, 2016].

Available: https://www.sciencebase.gov/catalog/item/57a379ffe4b006cb455690aa

Figures: 26, 39, 43, 47, 52, A.10.1

Greater sage-grouse lek data

Source: Western Association of Fish and Wildlife Agencies (WAFWA)

Contact: Tom Remington, WAFWA, 2700 W. Airport Way, Boise, ID 83705; remingtontom@msn.com.

Table: 7

Human disturbance

Source: NLCD 2011 Percent Developed Imperviousness 2014. 2011 Edition, 

amended 2014. Metadata. Sioux Falls, SD: U.S. Department of the 

Interior, U.S. Geological Survey. http://www.mrlc.gov/nlcd11_data.php

[Accessed May 11, 2016]

Available: http://www.mrlc.gov/nlcd11_data.php 

Figure: 18

Land cover: Cheatgrass occurrence (historic range of sage-grouse)

Source: Downs, J.L.; Larson, K.B.; Cullinan, V.I. 2016. Mapping cheatgrass 

across the range of the Greater sage-grouse: Linking biophysical, climate and remote sensing data to predict cheatgrass occurrence. PNNL 

22517. Richland, WA: Pacific Northwest National Laboratory. 16 p. 

Available: https://www.sciencebase.gov/catalog/item/585169aae4b0f99207c4f093

Figure: 33

Land cover: Cheatgrass (Northeast Nevada)

Source: Boyte, S.P.; Wylie, B.K. 2016. Near-real-time cheatgrass percent cover 

in the Northern Great Basin, USA, 2015. Rangelands. 38: 278–284. 

http://www.bioone.org/doi/full/10.1016/j.rala.2016.08.002 [Accessed 

Nov 9, 2016].

Available: https://www.sciencebase.gov/catalog/item/55ad3a16e4b066a2492409d5

Figure: 51

Land cover: Conifer

Source: U.S. Geological Survey (USGS). 2012. LANDFIRE 1.3.0 Existing Vegetation Type layer. Updated December 17, 2014. Washington, DC: U.S. 

Department of the Interior, Geological Survey. http://landfire.cr.usgs.

gov/viewer/ [Accessed Aug 26, 2015].

Available: http://landfire.cr.usgs.gov/viewer/

Figure: 10

Land cover: Conifer (Northeast Nevada)

Source: Falkowski, M.J.; Evans, J.S.; Naugle, D.E.; [et al.]. 2017. Mapping 

tree canopy cover in support of proactive prairie grouse conservation 
USDA Forest Service RMRS-GTR-360. 2017. 193

in western North America. Rangeland Ecology and Management. 70: 

15–24. http://dx.doi.org/10.1016/j.rama.2016.08.002.

Available: http://map.sagegrouseinitiative.com/

Figure: 51

Land cover: Sagebrush

Source: U.S. Geological Survey [USGS]. 2012. LANDFIRE 1.3.0 Existing Vegetation Type layer. Updated December 17, 2014. Washington, DC, U.S. 

Department of the Interior, Geological Survey. http://landfire.cr.usgs.

gov/viewer/ [Accessed Aug 26, 2015].

Available: http://landfire.cr.usgs.gov/viewer/

Figures: 5, 28, 29

Large fire probability

Source: Short, K.C.; Finney, M.A.; Scott, J.H.; [et al.]. 2016. Spatial dataset 

of probabilistic wildfire risk components for the conterminous United 

States. Fort Collins, CO: Forest Service Research Data Archive. https://

doi.org/10.2737/RDS-2016-0034.

Available: https://www.sciencebase.gov/catalog/item/58516a0be4b0f99207c4f096

Figure: 34, A.10.1

Major Land Resource Area

Source: USDA Natural Resource Conservation Service [NRCS]. 2006. 

2006 MLRA Geographic Database, version 4.2. Washington, DC: 

U.S. Department of Agriculture, Natural Resource Conservation 

Service. https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/

survey/?cid=nrcs142p2_053624. [Accessed Dec 1, 2016] 

Available: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/soils/

survey/?cid=nrcs142p2_053624

Figure: A.3.1

Oil and gas wells

Source: Point density analysis conducted by the Bureau of Land Management 

and derived from AFMSS Currently Active Oil and Gas Well Points 

2015; IHS Currently Active Oil and Gas Well Points 2015. https://www.

ihs.com/products/us-well-data.html [Accessed May 11, 2016].

Available: https://www.ihs.com/products/us-well-data.html

Figures: 16, 46

Roads

Source: Line density analysis conducted by the Bureau of Land Management 

and derived from ESRI Street Maps Premium. Copyright © 1995–2014 

ESRI. All rights reserved. Published in the United States of America. 

http://www.esri.com/data/streetmap [Accessed May 11, 2016].

Available: http://www.esri.com/data/streetmap

Figure: 20
194 USDA Forest Service RMRS-GTR-360. 2017.

Sage-grouse Management Zones

Source: Stiver, S.J.; Apa, A.D.; Bohne, J.R.; [et al.]. 2006. Greater sage-grouse 

comprehensive conservation strategy. Cheyenne, WY: Western Association of Fish and Wildlife Agencies. 442 p. http://wdfw.wa.gov/publications/01317/wdfw01317.pdf [Accessed Aug 2, 2016].

Available: https://www.sciencebase.gov/catalog/item/56f96b30e4b0a6037df06216

Figures: 1, 2, 3, 5, 6, 7, 10, 14, 16, 18, 20, 25, 26, 28, 29, 32, 33, 34, 35, 38, 39, 

49, 50, 51, 52, A.3.1, A.9.1, A.10.1

Sage-grouse Priority Areas for Conservation

Source: U.S. Fish and Wildlife Service [FWS]. 2013. Greater sage-grouse (Centrocercus urophasianus) Conservation Objectives: Final Report. Denver, 

CO: U.S. Fish and Wildlife Service. 91 p. https://www.fws.gov/greatersagegrouse/documents/COT-Report-with-Dear-Interested-Reader-Letter.

pdf [Accessed Aug 8, 2016].

Available: https://www.sciencebase.gov/catalog/item/56f96d88e4b0a6037df066a3

Figures: 25, 26, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 49, 50, 51, 52, A.3.1, A.9.1

Seed zones: Provisional

Source: Bower, A.D.; St. Clair, J.B.; Erickson, V. 2014. Generalized provisional 

seed zones for native plants. Ecological Applications. 24: 913–919.

Available: http://www.fs.fed.us/wwetac/threat-map/TRMSeedZoneData.php

Figure: A.11.1

Seed zones: Adaptive seed zones for bluebunch wheatgrass (Pseudoroegneria 

spicata)

Source: St. Clair, J.B.; Kilkenny, F.F.; Johnson, R.C.; [et al.]. 2013. Genetic 

variation in adaptive traits and seed transfer zones for Pseudoroegneria 

spicata (bluebunch wheatgrass) in the northwestern United States. Evolutionary Applications. 6: 933–938.

Available: http://www.fs.fed.us/wwetac/threat-map/TRMSeedZoneData.php

Figure: A.11.2

Soil data (SSURGO)

Source: Soil Survey Staff. 2014a. Soil Survey Geographic (SSURGO) Database. 

Washington, DC: U.S. Department of Agriculture, Natural Resources 

Conservation Service. http://sdmdataaccess.nrcs.usda.gov/ [Accessed 

Oct 3, 2015].

Available: http://sdmdataaccess.nrcs.usda.gov/ 

Figures: 6, 32, 38, 39, 40, 43, 44, 47, 49, 52

Soil data (STATSGO)

Source: Soil Survey Staff. 2014b. Soil Survey Geographic (STATSGO2) Database. 

United States Department of Agriculture, Natural Resources Conservation 

Service. http://sdmdataaccess.nrcs.usda.gov/ [Accessed Oct 3, 2015].
USDA Forest Service RMRS-GTR-360. 2017. 195

Available: http://sdmdataaccess.nrcs.usda.gov/ 

Figures: 6, 32, 38, 39, 40, 43, 44, 47, 49, 52, A.10.1

Soil temperature and moisture regimes

Source: Campbell, S.B. 2016. Soil temperature and moisture regimes across sagegrouse range. Data product. Portland, OR: U.S. Department of Agriculture, 

Natural Resources Conservation Service. https://www.sciencebase.gov/catalog/item/538e5aa9e4b09202b547e56c [Accessed May 10, 2016].

Available: https://www.sciencebase.gov/catalog/item/538e5aa9e4b09202b547e56c

Figures: 6, 32, 38, 39, 40, 43, 44, 47, 49, 52, A.10.1

Surface land management

Source: Surface Management Agency. Complied and maintained by the Department of the Interior, Bureau of Land Management. 2015. http://www.

geocommunicator.gov/GeoComm/ [Accessed May 7, 2016].

Available: http://www.geocommunicator.gov/GeoComm/ 

Figures: 41, 45, 50

This appendix was prepared by Jacob D. Hennig, Steven E. Hanser, and Jeanne C. 

Chambers with input from Victoria Smith-Campbell and Megan Waltz.
196 USDA Forest Service RMRS-GTR-360. 2017.

Appendix 9—Connectivity Between Priority Areas for 

Conservation of Greater Sage-Grouse

Focusing conservation actions for sage-grouse within Priority Areas for 

Conservation (PACs; FWS 2013) or higher level habitat designations can have the 

greatest habitat benefits with limited resources. However, management actions in 

regions surrounding PACs could potentially lead to a spatially disjunct set of areas 

that no longer retain the characteristics necessary to sustain Greater sage-grouse 

(GRSG) populations and sagebrush-dependent species that utilize similar habitat 

conditions. In addition, priorities and land use plans often differ among state 

and federal management agencies both within and outside of the PAC structure 

(Copeland et al. 2014; Knick and Connelly 2011). These different conservation 

and management priorities among administrative units could disrupt the current 

sage-grouse population spatial structure leading to greater isolation and potentially 

initiate or accelerate population declines.

A recent evaluation of habitat connectivity among the PACs found that a majority 

of PACs had limited connectivity (Crist et al. 2017). https://www.sciencebase.gov/

catalog/item/58504cebe4b0f24ebfd93670). The PACs with few habitat connections 

averaged greater environmental resistance to movement along connecting pathways. 

Without maintaining corridors to larger PACs or a clustered group, isolation of 

small PACs could lead to regional loss of GRSG.

Crist et al. (2017) used circuit theory to model potential movement pathways 

(McRae et al. 2008) and graph theory (Urban and Keitt 2001) to measure the 

strength of connectivity among PACs as a network. A rangewide map of habitat 

suitability for GRSG was created at 1-km2

 resolution from a model of ecological 

minimum requirements following similar protocols developed previously for the 

western portion of the range (Knick et al. 2013). However, Crist et al. (2017) used 

a random sample of habitat conditions within PACs rather than those within 5 km 

of lek locations, which were used in Knick et al. 2013. The sage-grouse habitat 

suitability map was transformed to environmental resistance to movement under the 

assumption that the likelihood of sage-grouse movement through a 1-km2

 grid cell 

follows an inverse relationship to habitat suitability.

Circuitscape (Circuitscape version 4.0, http://www.circuitscape.org; McRae 

and Shah 2008) was used to model potential movement pathways between PACs. 

The capacity for movement is based on an effective resistance (ER) that combines 

distance and the mapped environmental resistance (described above) in electric current density algorithms (McRae 2006; McRae et al. 2008). Effective resistance is a 

measurement on a scale between complete absence of environmental resistance (in 

which all PACs are interconnected because there is no cost of movement) to total 

barrier (all PACs are isolated from each other). A low ER between pairs of PACs 

represented a relatively high potential pathway for GRSG movement. A final map of 

maximum current density represents the spatial structure of connectivity (movement 

pathways) for the network of PACs (fig. A9.1). Locations of high current densities 

may function as bottlenecks (pinch points) to Greater sage-grouse connectivity 

where movement is constricted or alternative pathways are not available (Dickson et 

al. 2013; McRae et al. 2008). 
USDA Forest Service RMRS-GTR-360. 2017. 197

Landscape connectivity is often assessed to identify critical habitat connections 

where, if severed, could potentially isolate populations (Bunn et al. 2000; LaPoint 

et al. 2013; Urban and Keitt 2001). Characteristics of these habitat connections 

between PACs can help land managers target conservation actions to help ensure 

sage-grouse seasonal and dispersal movements (Crist et al. 2017). Areas of high 

movement potential (fig. A9.1) can be used to identify the critical locations where 

movement is constrained. If resources are limited, sagebrush restoration efforts that 

improve or expand habitat areas at pinch points between PACs might enhance potential corridors and preserve the likelihood of population persistence by facilitating 

movements that sustain or augment populations and for dispersal and gene flow.

Figure A9.1— Estimated potential for sage-grouse movement between Priority 

Areas for Conservation (Crist et al. 2017). Areas of high to medium movement potential represent pinch points.
198 USDA Forest Service RMRS-GTR-360. 2017.

The current network structure of PACs has many important characteristics for 

maintaining GRSG populations (Crist et al. 2017). For example, the range of large 

and small sizes of PACs may provide different functions, particularly as sources and 

connecting habitat along movement corridors. Conservation actions that maintain 

connectivity between clusters of PACs will be important to retain movement potential among PACs that might be too small individually to sustain viable populations. 

Also, decision support tools can be developed using modeled surfaces of genetic 

divergence, isolation, and landscape resistance. Such spatially explicit tools would 

be used to identify and prioritize areas for habitat restoration (e.g., conifer removal) 

that reduce barriers to movement and increase gene flow among populations and 

PACs. 

This appendix was prepared by Michele R. Crist, Steve E. Hanser, and Peter S. 

Coates.
USDA Forest Service RMRS-GTR-360. 2017. 199

Appendix 10—Fire Risk Assessment for Greater SageGrouse Breeding Habitat

An assessment of wildfire risk for Greater sage-grouse (GRSG) habitat can offer 

a consistent means for understanding and comparing the threat of fire to GRSG, as 

well as predicting and prioritizing investments in management activities that mitigate fire risk. In the context of the Science Framework, wildfire processes may have 

varying negative and positive effects on sagebrush ecosystems depending on the 

relative resilience of a site to disturbance and resistance to invasive annual grasses. 

Geospatial analyses can be used to assess the relative resilience and resistance, and 

thus recovery potential, of areas that support species or resources at-risk. They can 

also be used to assess the probability of wildfire occurring within these same areas 

and the interactions of wildfire with resilience and resistance and sagebrush habitat. 

For species at risk, like sage-grouse, the process involves overlaying key data layers to both visualize and quantify: (1) species locations and abundances, (2) the 

probability that an area has suitable habitat for the species of interest, (3) the likely 

response of the area to either wildfire or management treatments, and (4) the dominant threats, such as wildfire, for the assessment area. Calculating the areas within 

different resilience and resistance and habitat categories along with the different 

burn probabilities can be another step in the process.

This fire risk assessment was conducted to understand how resilience and resistance and sage-grouse breeding bird habitat may inform wildland fire management 

decisions including preparedness, suppression, fuels management and postfire recovery across the sagebrush biome (Crist et al. 2016; https://www.sciencebase.gov/

catalog/item/5846d366e4b04fc80e52376b). The assessment is based on the premise 

that risk is equal to the probability of a threat and the consequences of that threat 

(negative or positive). Fire risk was determined by the probability of a large wildfire 

(>300 acres in shrub/grass systems) and the consequences of fire on GRSG breeding 

habitat. These consequences were modified by resilience to disturbance, or recovery 

potential, and resistant to invasive annual grasses of sage-grouse habitat. The focus 

area for the assessment was the dominant sagebrush ecological types and grassland 

with sagebrush components ecological types in LANDFIRE that occur across portions of eleven western States: Washington, Oregon, California, Idaho, Nevada, 

Utah, Montana, Wyoming, Colorado, North Dakota and South Dakota. 

Three GIS datasets described in Section 8 were modified and used in the assessment: large fire burn probability extracted for the sagebrush biome (fig. 34; Short 

et al. 2016), GRSG breeding habitat probabilities (fig. 25; Doherty et al. 2016), 

and resilience and resistance as indicated by soil temperature and moisture regimes 

(fig. 32; Maestas et al. 2016a). The large fire probability spatial dataset was derived 

by simulating fire ignition and growth using the Fire Simulation (FSim) system 

(Finney et al. 2011; Short et al. 2016). Contemporary weather scenarios were generated for each simulation unit using: (1) a fire danger rating index known as the 

Energy Release Component (ERC), which is a proxy for fuel moisture; (2) a timeseries analysis of ERC to represent daily and seasonal trends and variability; and 

(3) distributions of wind speed and direction from surface weather records. Fire 

growth was based on the characteristics of relatively large and generally fast moving fires because they account for the majority (80−97 percent) of total area burned, 

and thus contribute the most to the probability of a wildland fire burning a given 

parcel of land therein. Fire occurrence in FSim is stochastically modeled based on 
200 USDA Forest Service RMRS-GTR-360. 2017.

historical relationships between large fires (largest 3−5 percent for each simulation 

unit) and ERC. Because its objective is to simulate the behavior of large, spreading 

fires, FSim restricts fire growth to days on which ERC reaches or exceeds the 80th 

percentile condition. Final burn probabilities indicate, for each 270 m pixel, the 

number of times that cell was burned by an FSim-modeled fire, divided by the total 

number of annual weather scenarios simulated. The burn probabilities are intended 

to support an actuarial approach to quantitative wildfire risk analysis.

 The Greater sage-grouse breeding habitat probabilities dataset provides an estimate of the probability of occupied breeding habitat at a spatial resolution of 120 by 

120 m based on habitat characteristics for each Greater sage-grouse Management 

Zone. Greater sage-grouse breeding habitat probabilities were combined into three 

categories: low, equal to a habitat probability ranging from 0.26–0.50; moderate, 

equal to a habitat probability ranging from 0.5–0.75; and high, equal to a habitat 

probability ranging from 0.76–1.00. 

 The following values were assigned to the three categories: Low Habitat 

Probability had a value of 10, Moderate Habitat Probability had a value of 20, and 

High Habitat Probability had a value of 30. The resilience and resistance dataset 

was resampled using a nearest neighbor assignment to a 120-m resolution and 

assigned a value of 1 to the high category of resilience and resistance; a value of 

2 was assigned to the moderate category, and a value of 3 to the low category. 

 The three datasets were combined by summing the values in a raster grid format. 

The resulting fire exposure map depicts 27 different combinations of sage-grouse 

breeding habitat probability, resilience and resistance, and burn probability 

(fig. A10.1). 

 The final fire risk map identifies areas where sagebrush and sage-grouse habitats 

are at highest risk from fire across the sagebrush biome and historic sage-grouse 

range. It also identifies the relative resilience to disturbance and resistance to invasive annual grasses of areas that are at high risk from fire. The assessment shows 

the differences in fire among Management Zones and ecoregions. The fire risk 

assessment can be used to help: (1) evaluate the level of risk to vegetation types 

and species to wildfire, (2) target areas for wildfire management, and (3) determine 

the most appropriate types of fire management actions at the biome and ecoregion 

or Management Zone scales. Incorporating information on invasive annual grasses 

and land cover of juniper expansion further informs the type of management actions 

and the allocation of resources at broad to mid-scales and the specific types of treatments at local scales. 

This appendix was prepared by Michele R. Crist, Jeanne C. Chambers, Jessica R. 

Haas, and Kevin E. Doherty. Dave Calkin, Karen Short, Susan Goodman, Matthew 

Brooks, Douglas Shinneman, Kurtis Nelson, Nathan Benson, Tonja Oppermen, 

Victoria Smith-Campbell, Craig Thomson, Matthew Reeves, Krista Gollnick-Wade, 

Kim Van Hemelryck, Douglas Havlina and Joesph Kafka contributed to the development and review of methodology for the fire risk assessment.
USDA Forest Service RMRS-GTR-360. 2017. 201

Figure A10.1— Fire risk map depicting 27 different combinations of sage-grouse 

breeding habitat probability (Doherty et al. 2016), resilience and resistance 

(Maestas et al. 2016a), and large fire probability (Short et al. 2016). The map identifies areas where sagebrush and sage-grouse habitats are at highest risk from fire 

across the sagebrush biome and historic sage-grouse range. It also identifies the 

relative resilience to disturbance and resistance to invasive annual grasses of areas that are at high risk from fire.
202 USDA Forest Service RMRS-GTR-360. 2017.

Appendix 11—Explanation of Seed Transfer Guidance 

Ecosystem resilience to disturbance and resistance to invasive annual grasses can 

be increased by selecting appropriate seed mixtures for restoration. The capacity 

of a plant species to establish and persist following seeding depends on whether or 

not it is adapted to the environmental conditions on the site. Common garden and 

reciprocal transplant studies, where plants from two or more climatic regimes are 

seeded together into each of the different climatic regimes and their performance 

is monitored, have often shown that plant populations are adapted to local environmental conditions (e.g., Clausen et al. 1941; Hiesey et al. 1942; Joshi et al. 2001; 

Turesson 1922). For restoration projects this means that locally adapted plants can 

generally outperform plants from other areas (e.g., Bischoff et al. 2006; Humphrey 

and Schupp 2002; Leimu and Fischer 2008; Rice and Knapp 2008; Rowe and Leger 

2012). Poor seed source choices may have long-term consequences for plant communities including genetic degradation of the surrounding plant population, loss of 

fitness, and loss of evolutionary potential (Crémieux et al. 2010; McKay et al. 2005; 

Mijnsbruggea et al. 2010; Schröder and Prasse 2013). Ultimately, the seed sources 

used in restoration can affect future plant community resilience and resistance. The 

National Seed Strategy for Rehabilitation and Restoration (Seed Strategy; PCA 

2015) provides a coordinated approach for developing and procuring native and 

genetically appropriate seed sources that are adapted to individual restoration and 

vegetation management project areas. The Seed Strategy also identifies research, 

technology, and monitoring actions needed to integrate and manage genetic diversity of plant communities across the sagebrush biome.

The use of locally adapted and genetically appropriate native seed and plant materials ensures the best genetic fit between a restoration site and the seed source used 

for the project. However, under many circumstances, using locally adapted seeds 

and plant materials may not be the most practical solution. Project-specific seed 

collections and grow-outs can add 2 to 5 years to project implementation schedules. Local seed may not be available because the species may be locally extinct, 

or local seed sources may no longer be the best genetic fit for the site because of 

climate change. Through seed zones and seed transfer guidelines, the National Seed 

Strategy provides a way for integrating agronomic approaches for seed production 

while managing for genetics and local adaptation. 

Originally developed in forestry, seed zones and seed transfer guidelines are a 

science based tool used to describe local adaptation. Seed zones and seed transfer 

guidelines define acceptable distances from the original source that plant materials 

can be seeded or transplanted and still preserve ecological and evolutionary relationships (Kilkenny 2015). When coupled with climate models, the predicted shifts 

in seed transfer zones can be used to guide seed sourcing decisions and anticipate 

vegetation management and seed procurement needs under future climate conditions. In particular, vulnerable source populations can be identified and the direction 

of shifts in optimal plant traits can be identified.

Generalized seed zones (also called provisional seed zones) are based on climate 

variables that have been shown to be important to plant establishment and survival, 

or are based on other broad scale ecological considerations, such as plant communities or soil types. A recent generalized seed zone approach developed by Bower et 

al. (2014) uses minimum temperature and aridity variables to define generalized 

seed zones for the U.S. Omernik’s (1987) ecoregional classification. Bower’s 
USDA Forest Service RMRS-GTR-360. 2017. 203

approach for delineating ecosystem boundaries at various scales is based primarily on vegetation classes and has also been adapted for use as a generalized seed 

zone map. When generalized seed zones are combined with level III ecoregions (as 

defined by Omernik), the resulting map captures much of the variation existing in 

adaptive seed zones (fig. A11.1; Bower et al. 2014; Kramer et al. 2015). Therefore, 

the combined generalized seed zone and ecoregion mapping approach is a good 

starting place to incorporate adaptive genetic variation into seeding decisions 

(Miller et al. 2011b). 

Recently, adaptive seed zones (also called empirical seed zones) have been 

constructed for a number of non-tree species in western North America, including 

grasses (e.g., St. Clair et al. 2013), forbs (e.g., Johnson et al. 2013), and shrubs 

(Horning et al. 2010). Adaptive seed zones are species specific and are developed 

through common garden studies of plant adaptive traits and correlation of these 

traits with climate. Information from these studies is then synthesized into seed zone 

maps that delineate regions where specific seed sources are likely to be well adapted 

(fig. A11.2; Kilkenny 2015; St. Clair et al. 2013). Common garden and reciprocal 

transplant studies can define the full adaptive range of the seed sources in the study, 

as well as test the efficacy of existing adaptive seed zones. Common garden studies 

are data rich, so that products other than seed zone maps can be produced. In particular, models of traits, such as growth or reproduction, and their interactions with 

climate can be constructed. These models are especially useful in predicting the 

effects of climate change on the performance of different seed sources in restoration 

seedings.

DNA marker sampling across the range of a species can also be used to describe 

the distribution of genetic variation of populations and develop genomic seed zone 

maps (De Kort et al. 2014; Narum et al. 2013). Genomic seed zones are useful 

for determining the level of relatedness and genetic diversity among seed sources. 

Genomic seed zones can also be used to conserve the genetic makeup of a population and to prevent poor genetic fit between seeded and local plant populations. 

Figure A11.1—Provisional seed zones for native plants (color polygons) overlain with Omernik’s (Omernick 

1987) level III ecoregion boundaries (black lines). Provisional seed zones are the first step in defining seed 

transfer guidelines, and level III ecoregions can be used to refine seed movement within a provisional seed 

zone. In the legend, the first range of numbers is the temperature class band (°F) and the second range of 

numbers is the AH:M index class bands (°C/m precipitation) (from Bower et al. 2014). 
204 USDA Forest Service RMRS-GTR-360. 2017.

This can help prevent the degradation of local plant populations and future genetic 

resources from swamping by genetically inappropriate seed sources. Given the 

reduced cost of genetic testing, most studies that construct adaptive seed zones will 

also include genetic marker information in the future.

 In addition to generalized and adaptive seed zones and transfer guidelines, 

another approach to understanding local adaptation is to use species distribution 

models to describe the climatic envelope of a species (describes the climate where 

a species currently lives, i.e., its “envelope,” and maps the geographic shift of that 

envelope under climate change) (Elith and Leathwick 2009). Species distribution 

models are generally developed by statistically associating spatially explicit climate 

data with geo-referenced presence and/or absence data. Species distribution models, 

Figure A11.2—Adaptive seed zones (labeled 1–7b) for bluebunch wheatgrass 

(Pseudoroegneria spicata). Ecotypes correspond to small, medium, or large plant size; early 

or late phenology; and narrow or wide leaf width. Percentages of the total areas within study 

area for each seed zone are given in the legend (from St. Clair et al. 2013). 
USDA Forest Service RMRS-GTR-360. 2017. 205

by themselves, have limited usefulness in plant restoration because they treat plant 

species as single entities without considering the existence of local or regional ecotypes. However, species distribution models can be combined with data from studies 

of adaptive and/or genomic characteristics to inform seed transfer guidelines (Still 

and Richardson 2015), and may be especially useful in studies of how climate may 

affect seed zones (Kilkenny 2015). 

Once seed zones are defined, seeds can be collected and developed for use in restoration. For example, bluebunch wheatgrass is a grass species that occurs throughout most of the sagebrush biome and is a workhorse restoration species. Seeds of 

bluebunch wheatgrass were collected based on empirical seed zones, are currently 

being increased, and will be available for use by emergency stabilization and rehabilitation projects within the next few years (Shock et al. 2016; St. Clair et al. 2013). 

Additionally, seeds and plant materials that were developed prior to seed zone construction for a particular species, or initially collected without using an existing seed 

zone framework, can be incorporated into either generalized or empirical frameworks as long as the seeds or plant materials are source-identified. For example, 

several source-identified forb releases, that are important in the diets of sage-grouse, 

are being incorporated into the Bower et al. (2014) seed zone framework to be used 

in restoration (such as species identified in Johnson and Bushman 2016). Seeds and 

plant materials that are not specifically source-identified, or that have been selected 

over long time periods or from mixed stock, may be incorporated into the seed zone 

framework if their traits and characteristics are well known and can be placed in 

categories that fit seed zone models.

This appendix was prepared by Sarah M. Kulpa, 

Fred Edwards, and Francis F. Kilkenney.
206 USDA Forest Service RMRS-GTR-360. 2017.

Figure A12.1—Relative resilience and resistance in thousands of acres for (A) the 

Management Zones (MZs; Stiver et al. 2006) and (B) the Priority Areas for Conservation 

(PACs; FWS 2013) within each Management Zone. The resilience and resistance categories 

are explained in Appendix 2. 

Appendix 12—Tables and Figures Summarizing the 

Relative Resilience and Resistance, Greater SageGrouse Breeding Habitat Probabilities, and Greater 

Sage-Grouse Breeding Populations for the Sagebrush 

Biome

This appendix was prepared by Jacob D. Hennig and Jeanne C. Chambers.
USDA Forest Service RMRS-GTR-360. 2017. 207 Table A12.1—Area and percentage of resilience and resistance classes for (A) the Management Zones (MZs; Stiver et al. 2006) and (B) the Priority Areas for Conservation (PACs; FWS 2013) within each Management Zone. A Resilience and resistance Management High Moderate Low Total Zone Acres km2 % Acres km2 % Acres km2 % Acres MZ I 21,993,546 89,005 28 55,414,038 224,253 71 145,724 590 1 77,553,308 MZ II 25,270,281 102,265 43 23,466,452 94,966 40 9,913,884 40,120 17 58,650,618 MZ III 12,510,192 50,627 17 9,429,555 38,160 13 52,943,498 214,255 71 74,883,246 MZ IV 38,184,371 154,527 51 15,925,610 64,449 21 21,460,005 86,846 28 75,569,986 MZ V 12,945,989 52,391 35 12,970,545 52,490 35 11,090,422 44,881 30 37,006,957 MZ VI 2,879,898 11,655 19 3,041,919 12,310 20 9,393,392 38,014 61 15,315,210 MZ VII 17,614,769 71,285 47 3,830,409 15,501 10 16,297,510 65,954 43 37,742,688 B Priority Areas for Conservation Resilience and resistance Management High Moderate Low Total Zone Acres km2 % Acres km2 % Acres km2 % Acres MZ I PACs 901,296 3,647 8 10,549,022 42,690 91 97,818 396 1 11,548,135 MZ II PACs 3,450,456 13,964 21 10,384,371 42,024 62 2,871,828 11,622 17 16,706,655 MZ III PACs 3,067,357 12,413 21 4,002,108 16,196 27 7,635,757 30,901 52 14,705,223 MZ IV PACs 7,244,058 29,316 33 7,264,048 29,397 33 7,643,628 30,933 35 22,151,734 MZ V PACs 899,886 3,642 11 3,564,318 14,424 45 3,512,093 14,213 44 7,976,298 MZ VI PACs 6,426 26 1 427,666 1,731 16 2,164,763 8,760 83 2,598,856 MZ VII PACs 210,705 853 90 20,400 83 9 2,121 9 1 233,226 
208 USDA Forest Service RMRS-GTR-360. 2017. Table A12.2—Area and percentage of Greater sage-grouse breeding habitat probability category for (A) the Management Zones (MZs; Stiver et al. 2006) and (B) the Priority Areas for Conservation (PACs; FWS 2013) within each Management Zone. A Breeding Habitat Probability Management High Moderate Low Unsuitable Total Zone Acres km2 % Acres km2 % Acres km2 % Acres km2 % Acres km2 MZ I 5,488,682 22,212 12 13,919,754 56,331 30 15,693,021 63,508 34 10,924,858 44,211 24 46,026,314 186,262 MZ II 6,586,037 26,653 18 13,311,428 53,870 36 11,330,253 45,852 31 5,647,767 22,856 15 36,875,485 149,230 MZ III 6,110,305 24,728 20 7,923,361 32,065 26 8,564,917 34,661 29 7,405,146 29,968 25 30,003,729 121,421 MZ IV 7,360,774 29,788 19 10,498,707 42,487 28 10,146,221 41,060 27 9,793,051 39,631 26 37,798,753 152,966 MZ V 2,033,547 8,229 11 4,317,304 17,472 23 5,363,839 21,707 28 7,288,409 29,495 38 19,003,098 76,903 MZ VI 876,498 3,547 35 621,157 2,514 25 508,757 2,059 20 500,605 2,026 20 2,507,016 10,146 MZ VII 114,492 463 10 386,027 1,562 33 532,736 2,156 45 147,250 596 12 1,180,506 4,777 B Priority Areas for Conservation Breeding Habitat Probability Management High Moderate Low Unsuitable Total Zone Acres km2 % Acres km2 % Acres km2 % Acres km2 % Acres km2 MZ I PACs 3,914,390 15,841 33 5,328,819 21,565 46 2,170,323 8,783 19 291,090 1,178 2 11,704,623 47,367 MZ II PACs 5,285,823 21,391 31 7,406,972 29,975 43 3,564,243 14,424 21 882,906 3,573 5 17,139,944 69,363 MZ III PACs 5,085,621 20,581 34 4,950,779 20,035 33 3,439,187 13,918 23 1,509,144 6,107 10 14,984,731 60,641 MZ IV PACs 6,532,758 26,437 29 7,233,347 29,272 32 5,264,494 21,305 23 3,454,484 13,980 15 22,485,084 90,994 MZ V PACs 1,746,686 7,069 22 2,667,368 10,794 33 2,239,345 9,062 28 1,399,445 5,663 1 8,052,844 32,589 MZ VI PACs 861,457 3,486 35 609,859 2,468 25 497,192 2,012 20 480,956 1,946 20 2,449,464 9,913 MZ VII PACs 96,865 392 42 68,201 276 29 55,599 225 24 11,614 47 5 232,279 940
USDA Forest Service RMRS-GTR-360. 2017. 209

Table A12.3—Area and percentage of Greater sage-grouse breeding habitat probability 

category by resilience and resistance class for (A) the Management Zones (MZs; 

Stiver et al. 2006) and (B) the Priority Areas for Conservation (PACs; FWS 2013) 

within each Management Zone. Percentages for a Management Zone add to 100.

A

Breeding Resilience and Resistance

Habitat Low Moderate High

Probability Acres % Acres % Acres %

MZ I

High 18,503 0 4,991,493 11 443,768 0

Moderate 69,366 0 12,986,234 29 720,665 2

Low 34,089 0 13,974,961 31 1,477,070 3

Unsuitable 12,319 0 7,503,099 17 3,241,274 7

Total 134,276 0 39,455,788 88 5,882,776 12 

MZ II

High 796,172 2 4,586,273 13 1,121,366 3

Moderate 2,144,299 6 8,979,738 25 1,975,062 5

Low 2,313,881 6 6,325,700 18 2,411,600 7

Unsuitable 2,328,125 6 1,574,251 4 1,571,550 4

Total 7,582,478 20 21,465,962 60 7,079,578 19

MZ III

High 3,282,368 11 1,655,280 6 1,048,389 4

Moderate 4,343,197 15 2,033,276 7 1,345,451 5

Low 5,311,460 18 1,836,801 6 1,219,423 4

Unsuitable 5,488,860 19 748,057 3 902,338 3

Total 18,425,886 63 6,273,414 22 4,515,601 16

MZ IV

High 1,827,805 5 2,723,165 7 2,688,714 7

Moderate 3,499,600 9 3,504,581 9 3,190,375 9

Low 4,293,957 12 2,823,101 8 2,774,042 8

Unsuitable 4,188,550 11 1,625,985 4 3,766,790 10

Total 13,809,912 37 10,676,833 28 12,419,922 34

MZ V

High 542,091 3 1,330,346 7 138,436 1

Moderate 1,846,639 10 2,016,965 11 421,027 2

Low 2,321,041 13 2,278,551 13 622,480 3

Unsuitable 3,064,102 17 2,447,866 13 1,138,340 6

Total 7,773,873 43 8,073,728 44 2,320,283 12

MZ VI

High 703,215 29 166,077 7 1,146 0

Moderate 466,683 19 124,915 5 982 0

Low 381,042 16 89,452 4 3,085 0

Unsuitable 447,209 19 29,210 1 875 0

Total 1,998,149 83 409,654 17 6,088 0

MZ VII

High 1,530 0 4,277 0 108,532 9

Moderate 236,219 20 23,873 2 125,936 11

Low 173,717 15 102,109 9 256,693 22

Unsuitable 18,368 2 48,244 4 80,532 7

Total 429,833 37 178,503 15 571,693 49

(Continued)
210 USDA Forest Service RMRS-GTR-360. 2017.

Table A12.3—(Continued). 

B

Breeding Resilience and Resistance

Habitat Low Moderate High

Probability Acres % Acres % Acres %

MZ I PACs

High 17,400 0 3,507,329 30 359,745 3

Moderate 59,363 1 4,882,662 42 301,332 3

Low 20,147 0 1,919,033 17 192,156 2

Unsuitable 911 0 238,578 2 47,959 0

Total 97,822 1 10,547,602 91 901,192 8

MZ II PACs

High 673,119 4 3,547,203 21 993,466 6

Moderate 1,268,264 8 4,858,003 29 1,140,357 7

Low 799,051 5 1,734,161 10 881,707 5

Unsuitable 131,216 1 244,175 1 431,869 3

Total 2,871,650 18 10,383,542 61 21

MZ III PACs

High 2,714,174 19 1,434,391 10 839,004 6

Moderate 2,421,787 17 1,392,232 9 1,019,175 7

Low 1,667,920 11 962,210 7 738,129 5

Unsuitable 810,865 6 213,047 1 457,001 3

Total 7,614,745 53 4,001,880 27 3,053,309 21

MZ IV PACs

High 1,647,168 7 2,445,083 11 2,328,631 11

Moderate 2,588,270 12 2,503,692 11 1,943,482 9

Low 2,085,224 9 1,648,712 7 1,439,786 7

Unsuitable 1,303,025 6 657,672 3 1,455,823 7

Total 7,623,687 34 7,255,160 32 7,167,721 34

MZ V PACs

High 494,897 6 1,112,332 14 118,204 1

Moderate 1,325,037 17 1,105,710 14 219,886 3

Low 1,102,262 14 887,674 11 216,505 3

Unsuitable 569,967 7 453,059 6 343,722 4

Total 3,492,163 44 3,558,775 45 898,317 11

MZ VI PACs

High 693,992 29 160,263 7 1,146 0

Moderate 458,613 19 121,744 5 982 0

Low 371,502 16 88,104 4 3,085 0

Unsuitable 435,285 18 28,762 1 875 0

Total 1,959,392 82 398,873 17 6,088 0

MZ VII PACs

High 206 0 2,320 1 94,452 41

Moderate 1,591 1 3,512 2 63,245 27

Low 267 0 10,799 5 44,166 19

Unsuitable 25 0 3,384 1 8,156 4

Total 2,089 1 20,016 9 210,019 91
USDA Forest Service RMRS-GTR-360. 2017. 211

Table A12.4—Relative percentage of the Greater sagegrouse population by resilience and resistance class for 

(A) the Management Zones (MZs; Stiver et al. 2006) and 

(B) the Priority Areas for Conservation (PACs; FWS 2013) 

within each Management Zone.

A

Breeding 

 Bird Resilience and Resistance

Density % Low % Moderate % High

MZ I

High 0 72 8

Low 0 18 2

MZ II

High 6 57 17

Low 4 13 3

MZ III

High 38 23 19

Low 10 6 4

MZ IV

High 15 28 37

Low 6 8 6

MZ V

High 29 45 6

Low 8 9 3

MZ VI

High 76 3 1

Low 16 3 1

MZ VII

High 0 6 74

Low 0 5 15

B

Breeding 

 Bird Resilience and Resistance

Density % Low % Moderate % High

MZ I PACs

High 0 49 7

Low 0 6 0

MZ II PACs

High 3 49 15

Low 2 6 1

MZ III PACs

High 34 22 17

Low 3 4 6

MZ IV PACs

High 34 26 14

Low 5 5 4

MZ V PACs

High 5 43 28

Low 6 5 2

MZ VI PACs

High 74 6 0

Low 15 5 0

MZ VII PACs

High 0 1 67

Low 0 1 12
212 USDA Forest Service RMRS-GTR-360. 2017.

Table A13.1—Area and percentage of fires greater than1,000 acres (4 km2) (MTBS 

2014) that burned within the occupied range of Greater sage-grouse from 1984–

1999 and from 2000–2015 by resilience and resistance category. Areas are included 

that may have burned more than once during the time span.

Fire area

Resilience and 1984–1999 2000–2015

Resistance Acres km2 % Acres km2 %

MZ I

High 113,935 461 21 147,621 597 14

Moderate 428,174 1,733 79 919,203 3,720 86

Low 0 0 0 0 0 0

Total 542,109 2,194 100 1,066,825 4,317 100

MZ II

High 65,329 264 19 231,739 938 44

Moderate 154,704 626 44 275,368 1,114 52

Low 131,164 531 37 22,090 89 4

Total 351,198 1,421 100 529,197 2,142 100

MZ III

High 106,223 430 5 161,181 652 7

Moderate 575,204 2,328 28 494,206 2,000 23

Low 1,380,173 5,585 67 1,529,378 6,189 70

Total 2,061,599 8,343 100 2,184,766 8,841 100

MZ IV

High 914,415 3,701 24 1,537,599 6,222 20

Moderate 831,720 3,366 22 2,345,103 9,490 30

Low 2,044,719 8,275 54 3,989,292 16,144 50

Total 3,790,853 15,341 100 7,871,994 31,857 100

MZ V

High 167,080 676 14 332,315 1,345 17

Moderate 456,263 1,846 37 865,852 3,504 42

Low 599,612 2,427 49 842,274 3,409 41

Total 1,222,955 4,949 100 2,040,441 8,257 100

MZ VI

High 1,927 8 2 1,762 7 0

Moderate 29,802 121 26 106,284 430 32

Low 81,570 330 72 228,644 925 68

Total 113,299 459 100 336,691 1,363 100

MZ VII

High 0 0 0 0 0 0

Moderate 0 0 0 0 0 0

Low 0 0 0 0 0 0

Total 0 0 0 0 0 0

Total

High 1,368,908 5,540 17 2,412,217 9,762 17

Moderate 2,475,868 10,019 31 5,006,016 20,259 36

Low 4,237,237 17,148 52 6,611,679 26,757 47

Total 8,082,013 32,707 100 14,029,912 56,777 100

Appendix 13—Tables Summarizing Fire Area by 

Resilience and Resistance Category 

 This appendix was prepared by Jacob D. Hennig and Jeanne C. Chambers. 
USDA Forest Service RMRS-GTR-360. 2017. 213

Table A13.2—Area and percentage of fires greater than 1,000 acres (4 km2) (MTBS 

2014) that burned within the Priority Areas for Conservation (PACs; FWS 2013) 

within each Management Zone (MZ; Stiver et al. 2006) from 1984−1999 and from 

2000−2015 by resilience and resistance category. Areas are included that may have 

burned more than once during the time span.

Fire area

Resilience and 1984–1999 2000–2015

Resistance Acres km2 % Acres km2 %

MZ I 

High 2,129 9 5 5,651 23 3

Moderate 40,590 164 95 159,219 644 97

Low 0 0 0 0 0 0

Total 42,719 173 100 164,870 667 100

MZ II 

High 32,978 133 14 35,245 143 22

Moderate 103,489 419 42 116,936 473 72

Low 106,843 432 44 10,147 41 6

Total 243,311 985 100 162,328 657 100

MZ III 

High 48,406 196 9 112,775 456 24

Moderate 192,863 780 35 162,367 657 34

Low 310,649 1,257 56 201,052 814 42

Total 551,918 2,234 100 476,194 1,927 100

MZ IV 

High 513,016 2,076 31 891,356 3,607 22

Moderate 442,928 1,792 26 1,611,892 6,523 41

Low 716,665 2,900 43 1,485,580 6,012 37

Total 1,672,609 6,769 100 3,988,828 16,142 100

MZ V 

High 39,151 158 9 208,092 842 16

Moderate 210,864 853 45 574,212 2,324 44

Low 214,153 867 46 518,924 2,100 40

Total 464,167 1,878 100 1,301,228 5,266 100

MZ VI 

High 1,927 8 2 1,762 7 0

Moderate 29,802 121 26 106,284 430 32

Low 80,836 327 72 227,592 921 68

Total 112,565 456 100 335,638 1,358 100

MZ VII

High 0 0 0 0 0 0

Moderate 0 0 0 0 0 0

Low 0 0 0 0 0 0

Total 0 0 0 0 0 0

Total 

High 637,607 2,580 21 1,254,882 5,078 20

Moderate 1,020,536 4,130 33 2,730,910 11,052 42

Low 1,429,146 5,784 46 2,443,294 9,888 38

Total 3,087,289 12,494 100 6,429,086 26,018 100



In accordance with Federal civil rights law and U.S. Department of Agriculture (USDA) 

civil rights regulations and policies, the USDA, its Agencies, offices, and employees, and 

institutions participating in or administering USDA programs are prohibited from discriminating based on race, color, national origin, religion, sex, gender identity (including gender 

expression), sexual orientation, disability, age, marital status, family/parental status, income 

derived from a public assistance program, political beliefs, or reprisal or retaliation for prior 

civil rights activity, in any program or activity conducted or funded by USDA (not all bases 

apply to all programs). Remedies and complaint filing deadlines vary by program or incident.

Persons with disabilities who require alternative means of communication for program information (e.g., Braille, large print, audiotape, American Sign Language, etc.) should contact 

the responsible Agency or USDA’s TARGET Center at (202) 720-2600 (voice and TTY) or 

contact USDA through the Federal Relay Service at (800) 877-8339. Additionally, program 

information may be made available in languages other than English.

To file a program discrimination complaint, complete the USDA Program Discrimination 

Complaint Form, AD-3027, found online at http://www.ascr.usda.gov/complaint_filing_

cust.html and at any USDA office or write a letter addressed to USDA and provide in the 

letter all of the information requested in the form. To request a copy of the complaint form, 

call (866) 632-9992. Submit your completed form or letter to USDA by: (1) mail: U.S. 

Department of Agriculture, Office of the Assistant Secretary for Civil Rights, 1400 Independence Avenue, SW, Washington, D.C. 20250-9410; (2) fax: (202) 690-7442; or (3) email: 

program.intake@usda.gov. 

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