Summary of Science, Activities, Programs, and 

Policies That Influence the Rangewide Conservation 

of Greater Sage-Grouse (Centrocercus urophasianus)

U.S. Department of the Interior

U.S. Geological Survey

Prepared in cooperation with the Bureau of Land Management

Open-File Report 2013–1098
Cover photos: Greater Sage-Grouse, by Gary Kramer, U.S. Fish and Wildlife Service; 

Tule Butte, east of Farson, Wyo., by Spencer Schell, Ecologist, U.S. Geological Survey.
Summary of Science, Activities, Programs, 

and Policies That Influence the Rangewide 

Conservation of Greater Sage-Grouse 

(Centrocercus urophasianus)

By D.J. Manier, D.J.A. Wood, Z.H. Bowen, R.M. Donovan, M.J. Holloran, 

L.M. Juliusson, K.S. Mayne, S.J. Oyler-McCance, F.R. Quamen, D.J. Saher, 

and A.J. Titolo

In cooperation with the Bureau of Land Management

Open-File Report 2013–1098

U.S. Department of the Interior

U.S. Geological Survey
U.S. Department of the Interior

SALLY JEWELL, Secretary

U.S. Geological Survey

Suzette M. Kimball, Acting Director 

U.S. Geological Survey, Reston, Virginia: 2013

For more information on the USGS—the Federal source for science about the Earth, its natural and living 

resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1–888–ASK–USGS.

For an overview of USGS information products, including maps, imagery, and publications, 

visit http://www.usgs.gov/pubprod

To order this and other USGS information products, visit http://store.usgs.gov

Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the 

U.S. Government.

Although this report is in the public domain, permission must be secured from the individual copyright owners to 

reproduce any copyrighted material contained within this report.

Suggested citation:

Manier, D.J., Wood, D.J.A., Bowen, Z.H., Donovan, R.M., Holloran, M.J., Juliusson, L.M., Mayne, K.S., OylerMcCance, S.J., Quamen, F.R., Saher, D.J., and Titolo, A.J., 2013, Summary of science, activities, programs, and 

policies that influence the rangewide conservation of Greater Sage-Grouse (Centrocercus urophasianus): 

U.S. Geological Survey Open-File Report 2013–1098, 170 p., http://pubs.usgs.gov/of/2013/1098/.

ISBN 978-1-4113-3595-0
iii

Contents

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

I. Social and Political Overview and Introduction ................................................................................2

A National Strategy ..............................................................................................................................6

Purpose and Suitable Application of This Report ...........................................................................7

Delineation of Preliminary Priority and General Habitats .............................................................7

Geospatial Analysis Methods.............................................................................................................9

Key Assumptions and Limitations ......................................................................................................9

II. Populations, Distributions, Trends, and Natural History ..............................................................10

Species Description and Taxonomy ...............................................................................................10

Population Distribution and Trends—Including Subpopulations and 

Management Zones .............................................................................................................10

Genetic Diversity, Population Structure, and Sustainability .......................................................11

Habitat Characteristics and Ecosystem Associations ................................................................21

Multiscale Habitat Selection ..................................................................................................23

III. Characterization of Important Threats and Issues ......................................................................23

Factor A: Habitat Change .................................................................................................................24

A1. Habitat Fragmentation and Connectivity.........................................................................25

A2. Conversion to Agriculture .................................................................................................26

A3. Urbanization ........................................................................................................................30

A4. Infrastructure ......................................................................................................................31

A5. Energy Development .........................................................................................................51

Wind Energy Developments............................................................................................59

In Situ Uranium..................................................................................................................60

Oil Shale and Tar Sands...................................................................................................60

Solar ................................................................................................................................66

Geothermal ........................................................................................................................70

Mining ................................................................................................................................70

A6. Fire ........................................................................................................................................71

A7. Invasive Plants ....................................................................................................................88

A8. Conifer Woodland Expansion and Encroachment ........................................................91

A9. Grazing .................................................................................................................................92

Wild Horses......................................................................................................................100

Water Developments......................................................................................................101

A10. Climate Dynamics ..........................................................................................................101

A11. Habitat Treatments and Vegetation Management ...................................................106

A12. Other Land Uses .............................................................................................................108

Recreation........................................................................................................................108

Training Facilities ............................................................................................................108

Factor B. Population Overutilization .............................................................................................110

B1. Hunting ...............................................................................................................................110

B2. Religious and Traditional .................................................................................................111

B3. Science and Education ...................................................................................................111
iv

Factor C: Population Disease and Predation ..............................................................................111

Disease .....................................................................................................................................111

Predation ..................................................................................................................................113

Predator Control..............................................................................................................114

Factor E: Pesticides and Contaminants .......................................................................................115

Pesticides..................................................................................................................................115

Herbicides ................................................................................................................................115

IV. Factor D: Policies and Programs Affecting Sage-Grouse Conservation ................................116

Rangewide Conservation Efforts....................................................................................................117

Canadian Conservation Efforts.......................................................................................................117

United States Federal Agency Conservation Efforts ..................................................................117

Natural Resources Conservation Service: Sage-Grouse Initiative ................................117

Farm Service Agency: Conservation Reserve Program....................................................120

Other Federal Agencies..........................................................................................................120

Fish and Wildlife Service, National Park Service, and Other Federal 

Designations ......................................................................................................120

Department of Defense .................................................................................................123

Department of Energy ....................................................................................................123

State and Local Working Group Conservation Efforts..............................................124

California/Nevada ..........................................................................................................124

Colorado ...........................................................................................................................125

Idaho ..............................................................................................................................125

Montana and the Dakotas.............................................................................................126

Oregon .............................................................................................................................127

Utah ..............................................................................................................................127

Wyoming...........................................................................................................................127

V. Risk, Policies, and Actions: Assessment of Dominant Threats and Potential 

Interactions within Management Zones .................................................................................128

Actions and Activities ......................................................................................................................128

Management Zone Summaries ......................................................................................................129

MZ I—Northern Great Plains ................................................................................................129

MZ II and VII—Wyoming Basin and the Colorado Plateau..............................................130

MZ III—Southern Great Basin and Western Colorado Plateau ......................................131

MZ IV—Snake River Plain......................................................................................................132

MZ V—Northern Great Basin................................................................................................133

MZ VI—Columbia Basin .........................................................................................................134

Acknowledgments.....................................................................................................................................134

References Cited........................................................................................................................................135

Appendix. Data Sources and Analysis for the Greater Sage-Grouse Threat Assessment...........152

Introduction........................................................................................................................................152

Methodology......................................................................................................................................152

Identification of Threats .........................................................................................................152

Determination of Direct and Indirect Distances.................................................................152

Collection of Geospatial Data ................................................................................................153
v

Base Layers ..............................................................................................................................153

Preliminary Priority Habitat/Preliminary General Habitat........................................153

WAFWA Management Zones .......................................................................................154

Federal Agency Management ......................................................................................154

Land Allocation and Management........................................................................................154

Federal Fluid Minerals—Areas Closed to Oil and Gas Leasing..............................154

Conservation Focused and Protected Areas ....................................................154

Current Threats ........................................................................................................................155

Agricultural Development .............................................................................................155

Urbanized Areas .............................................................................................................155

Major Power Lines and Associated Infrastructure ..................................................155

Communication Towers and Other Vertical Structures............................................155

Fences ..............................................................................................................................155

Interstate, Highway, and Secondary Roads...............................................................155

Major Railroads...............................................................................................................155

Large Wildfires................................................................................................................156

Moderate to High Probability of Cheatgrass Occurrence .......................................156

Pinyon-Juniper and Other Conifer Encroachment Risk ...........................................156

Grazing..............................................................................................................................156

Wild Horse and Burro Herd Management Areas (HMAs) .......................................156

Oil and Gas Development Related Wells ....................................................................156

Federal Managed Coal, Surface Mining Development ............................................156

Mining and Minerals Materials Disposal (Federal Minerals Only) ........................156

Wind Turbines..................................................................................................................156

Valid Existing Rights ................................................................................................................157

Federal Geothermal Leasing.........................................................................................157

Federally Managed Fluid Minerals—Leased Areas and Status.............................157

Oil Shale Leases..............................................................................................................157

BLM Wind Energy Rights of Way (ROW) ....................................................................157

Potential Threats......................................................................................................................157

Large Fire—High Burn Probability...............................................................................157

Coal Potential ..................................................................................................................157

Oil and Gas Potential......................................................................................................157

Geothermal Potential .....................................................................................................157

Solar Potential.................................................................................................................157

Oil Shale and Tar Sands.................................................................................................157

Wind Potential.................................................................................................................157
vi

Figures

1. Current distribution of Greater Sage-Grouse and pre-settlement distribution

of sagebrush habitats available for Greater Sage-Grouse....................................................3

2. Land ownership or management jurisdiction across sage-grouse management

zones...............................................................................................................................................5

3. Distribution of preliminary priority habitat and preliminary general habitats 

displayed with distribution of sagebrush..................................................................................8

4. Concentrations of strutting males at leks, an indication of the distribution 

of individuals, populations, and reproductive effort across management 

zones.............................................................................................................................................14

5. Greater Sage-Grouse populations and subpopulations ......................................................15

6. Spatial connectivity within sage-grouse population structure across the 

current species’ range...............................................................................................................18

7. Map of sampling sites for the microsatellite analysis assigned by ‘Structure’

analysis.........................................................................................................................................20

8. Seven major sagebrush biomes, including the southern Great Basin types

(Southern, Northern, and Colorado Plateau), northern sagebrush-steppe 

(Snake River Plain, Wyoming Basin, and Columbia Basin) and northern 

mixed prairies..............................................................................................................................22

9. Overlap of agricultural land development, potential indirect effects of 

agriculture, and preliminary priority habitats and preliminary general habitats 

for sage-grouse...........................................................................................................................29

10. Overlap of urbanized areas, potential indirect influences of urbanization, and

sage-grouse preliminary priority and general habitats........................................................34

11. Overlap of roads and potential indirect influences of roads and sage-grouse

preliminary priority and general habitats ...............................................................................37

12. Overlap of abandoned and non-abandoned railroads, potential indirect 

influences of non-abandoned railroads, and sage-grouse preliminary priority 

and general habitats ..................................................................................................................40

13A. Overlap of major power lines and associated infrastructure, indirect influences 

of these structures, and preliminary priority and preliminary general habitats ..............43

13B. Overlap of communication towers and other vertical structures (non-wind),

potential indirect influences of these structures, and sage-grouse preliminary

priority and preliminary general habitats ...............................................................................47

13C. Distribution of fences associated with Federally managed allotments across the

sage-grouse study area.............................................................................................................49

14. Density of active wells related to oil and gas development within preliminary 

priority and preliminary general habitats ...............................................................................54

15. Overlap of Federally managed, subsurface acres closed to oil and gas leasing 

and sage-grouse preliminary priority and preliminary general habitats...........................56

16A. Overlap of Federally managed, subsurface acres (held by production and

developed leases) and sage-grouse preliminary priority and preliminary 

general habitats ..........................................................................................................................57

16B. Overlap of oil and gas resource occurrence potential and sage-grouse 

preliminary priority and preliminary general habitats ..........................................................58

17. Overlap of wind turbines, potential indirect influences of wind turbines, and

preliminary priority and preliminary general habitats ..........................................................63
vii

18A. Distribution of wind occurrence potential (based on mean wind speeds) within

preliminary priority and preliminary general habitats ..........................................................64

18B. Overlap of Federal wind energy right-of-way leases with preliminary priority 

and preliminary general habitats .............................................................................................65

19A. Overlap of Federal oil shale leases and sage-grouse preliminary priority and

preliminary general habitats.....................................................................................................67

19B. Overlap of the most likely geological prospects for oil shale and tar sands

development and sage-grouse preliminary priority and preliminary general 

habitats.........................................................................................................................................68

20. Overlap of photovoltaic-based estimates of solar power potential and 

sage-grouse preliminary priority and preliminary general habitats ..................................69

21A. Overlap of Federal geothermal leases with sage-grouse preliminary priority 

and preliminary general habitats .............................................................................................72

21B. Overlap of geothermal occurrence potential in sage-grouse preliminary 

priority and preliminary general habitats ...............................................................................73

22. Overlap of Federally managed surface coal leases, potential indirect influences 

of these leases, and preliminary priority and preliminary general habitats .....................75

23. Overlap of coal occurrence and sage-grouse preliminary priority and 

preliminary general habitats.....................................................................................................76

24. Overlap of Federal mining- and mineral-material disposal sites, potential 

indirect influences of these areas, and sage-grouse preliminary priority and 

preliminary general habitats.....................................................................................................80

25. Overlap of fires reported to National Interagency Fire Center between 

2000–2012 and preliminary priority and preliminary general habitats ...............................84

26. Overlap of areas modeled with a high probability for occurrence of large 

fires and preliminary priority and preliminary general habitats .........................................87

27A. Overlap of moderate to high probability of cheatgrass occurrence and 

preliminary priority and preliminary general habitats in Management 

Zones III, IV and V (Great Basin) .............................................................................................89

27B. Overlap of pinyon pine, juniper, and other conifer encroachment risk and 

preliminary priority and preliminary general habitats in Management 

Zones III, IV, and V (Great Basin) .............................................................................................95

28. Overlap of grazing allotments not meeting Land Health Standards for 

wildlife habitat with grazing as the causal factor and preliminary priority 

and preliminary general habitats. Bureau of Land Management (BLM) 

lands only ....................................................................................................................................98

29A. Overlap of Federally managed Wild Horse and Burro Herd Management 

Areas and Territories and sage-grouse preliminary priority and preliminary 

general habitats ........................................................................................................................104

29B. Distribution of water developments on Bureau of Land Management lands 

overlapping sage-grouse preliminary priority and preliminary general

habitats across each Management Zone ............................................................................105

30. Overlap of Federal, State, and private (includes Non-government 

Organizations) conservation areas within preliminary priority and preliminary 

general habitats ........................................................................................................................122

A-1. Model-builder process flowchart..........................................................................................170
viii

Tables

1. Recognized populations and subpopulations of sage-grouse included in 

this analysis .................................................................................................................................12

2. Estimated trends in population size for each sagebrush Management Zone..................16

3. Male sage-grouse minimum population estimates (2007), percent change 

in number of males per lek, and percent change in number of active leks 

1965–2007 .....................................................................................................................................16

4. Summary of the direct and indirect influences of agricultural lands by acres 

of preliminary priority and preliminary general habitats .....................................................27

5. Summary of the direct and indirect influences of urban areas by acres of 

preliminary priority and preliminary general habitats .........................................................32

6. Summary of the direct and indirect influences of roads across preliminary 

priority and preliminary general habitats ..............................................................................35

7. Summary of the direct influences of railroads and indirect influences of 

non-abandoned railroads across preliminary priority and preliminary general 

habitats ........................................................................................................................................38

8. Summary of the distribution of power transmission lines (>115 kilovolt) across

sage-grouse habitats ................................................................................................................41

9. Summary of the direct and indirect influences of communication towers and 

other (non-wind) vertical structures across preliminary priority and preliminary 

general habitat............................................................................................................................45

10. Summary of the influence of fences across preliminary priority and preliminary 

general habitats ..........................................................................................................................48

11. Summary of the direct influence of active and abandoned well sites and 

indirect influence of active oil and natural gas development-related wells 

across preliminary priority and preliminary general habitats.............................................52

12. Summary of the areas closed to Federal oil and gas development across

preliminary priority and preliminary general habitats ..........................................................55

13. Summary of existing Federal oil and gas leases (currently held by production 

or undeveloped) across preliminary priority and preliminary general habitats ..............55

14. Summary of the direct and indirect influences of wind turbines across

preliminary priority and preliminary general sage-grouse habitats ................................61

15. Summary of geothermal leases across sage-grouse preliminary priority 

and preliminary general habitats .............................................................................................71

16. Summary of the direct and indirect influences of Federal surface coal 

leases across preliminary priority and preliminary general habitats ................................74

17A. Summary of the direct and indirect influences of mining and mineral 

materials disposal sites (not including energy sources) across preliminary 

priority and preliminary general habitats ...............................................................................77

17B. Summary of existing Federal mineral prospecting permits for non-energy, 

leasable resources within preliminary priority and preliminary general 

habitats.........................................................................................................................................79

18. Summary of fires reported to National Interagency Fire Center between 

2000–2012, across preliminary priority and preliminary general habitats ........................82

19. Summary of areas with fuel models that project a high probability of 

developing large fires across preliminary priority and preliminary 

general habitats .........................................................................................................................85
ix

20. Summary of lands with moderate to high probability for cheatgrass 

occurrence across preliminary priority and preliminary

general habitats ..........................................................................................................................90

21. Summary of spatial model describing pinyon pine, juniper, and other 

conifer encroachment risk across preliminary priority and preliminary 

general habitats .........................................................................................................................93

22. Summary of grazing allotments not meeting Land Health Standards for 

wildlife habitat with grazing as the causal factor by acres of preliminary 

priority and preliminary general habitats ...............................................................................97

23. Summary of Federally managed Wild Horse and Burro Herd Management 

Areas and Territories across preliminary priority and preliminary general 

habitats ......................................................................................................................................102

24. Interpreting range condition for treatment and restoration: An adaptable 

and consistent decision matrix ..............................................................................................109

25. Insecticides and herbicides certified for application and commonly applied 

on and around sagebrush habitats........................................................................................116

26. Summary of management jurisdiction across Management Zones by acres

of preliminary priority and preliminary general habitats ...................................................118

27. Sage-Grouse Initiative efforts by State (through 2011) with delineation of 

threats to sage-grouse targeted with mitigation.................................................................119

28. Summary of areas managed for conservation and protection across

Management Zones by acres of preliminary priority and preliminary general 

habitat ........................................................................................................................................121

A-1. Direct and indirect buffer distances used to represent effects of human

infrastructure and activities on Greater Sage-Grouse for this Report ...........................158

A-2. Internal (BLM) data sources...................................................................................................160

A-3. External data sources..............................................................................................................162

A-4. Summary of research documenting specific consequences, land-use 

development, and anthropogenic activities and infrastructure on Greater 

Sage-Grouse..............................................................................................................................165
x

Multiply By To obtain

Length

centimeter (cm) 0.3937 inch (in.)

meter (m) 3.281 foot (ft) 

kilometer (km) 0.6214 mile (mi)

meter (m) 1.094 yard (yd) 

Area

square meter (m2

) 0.0002471 acre 

hectare (ha) 2.471 acre

square kilometer (km2

) 247.1 acre

square centimeter (cm2

) 0.001076 square foot (ft2)

square meter (m2

) 10.76 square foot (ft2) 

square centimeter (cm2

) 0.1550 square inch (ft2) 

hectare (ha) 0.003861 square mile (mi2

) 

square kilometer (km2

) 0.3861 square mile (mi2)

Mass

gram (g) 0.03527 ounce (oz)

kilogram (kg) 2.205 pound (lb)

Conversion Factors

Temperature in degrees Celsius (°C) may be converted to degrees Fahrenheit (°F) using: 

°F=(1.8×°C)+32

Horizontal coordination information (in map figures) is referenced to with World Geographic 

System (WGS 84) with an Albers Equal Area projection.

Inch/Pound to SI
xi

Acronyms and Initialisms Used in This Report

AFB Air Force Base

AFMSS Automated Fluid Minerals Support System BLM

AUM animal unit month

BIA Bureau of Indian Affairs

BLM Bureau of Land Management

CCP Comprehensive Conservation Plan

CIRO City of Rocks National Reserve

CRMO Craters of the Moon National Monument and Preserve

CRP Conservation Reserve Program

DOI Department of Interior

DPS distinct population segment

FAA Federal Aviation Administration

FRA Federal Railroad Administration

FY fiscal year

GIS geographic information system

GSGCCS Greater Sage-Grouse Comprehensive Conservation Strategy

GSSP Geospatial Services Strategic Plan (BLM)

HMA herd management area

ICBEMP Interior Columbia River Basin Ecosystem Management Project

ID identification

INL Idaho National Laboratory

ISR in situ recovery

LUP land use plan

LWG local working group

MOU Memorandum of Understanding

MSF master summary file

mtDNA mitochondrial DNA

MW megawatt

MZ management zone

NASECA North American Sagebrush Ecosystem Conservation Act (proposed)

NIFC National Interagency Fire Center

NLCS National Landscape Conservation System

NRCS Natural Resources Conservation Service

NREL National Renewable Energy Laboratory
xii

OHV off-highway vehicle

PEIS Programmatic Environmental Impact Statement

PGH preliminary general habitat

PPH preliminary priority habitat

SAFE State Acres For Wildlife Enhancement

SGI Sage-Grouse Initiative

SMA surface management agency

USDA U.S. Department of Agriculture

USFS U.S. Forest Service

USFWS U.S. Fish and Wildlife Service

WAFWA Western Association of Fish and Wildlife Agencies

WNv West Nile virus
Summary of Science, Activities, Programs, and Policies 

That Influence the Rangewide Conservation of Greater 

Sage-Grouse (Centrocercus urophasianus)

By Manier, D.J.,1* D.J.A. Wood,2 Z.H. Bowen,3* R.M. Donovan,1 M.J. Holloran,4 L.M.Juliusson,5 K.S. Mayne,5

S.J. Oyler–McCance,3

 F.R. Quamen,2 D.J. Saher,6 A.J. Titolo5

1

Cherokee Services Group, LLC, contracted to U.S. Geological Survey, 

Fort Collins Science Center, 2150 Center Avenue, Building C, Fort Collins, 

CO 80526–8118.

2

Bureau of Land Management, National Operations Center, Denver Federal 

Center, Building 50, Denver, CO 80225.

3

U.S. Geological Survey, Fort Collins Science Center, 2150 Centre Avenue, 

Building C, Fort Collins, CO 80526–8118.

4

Cherokee Services Group, LLC, contracted to U.S. Geological Survey, 

Fort Collins Science Center, 2150 Center Avenue, Building C, Fort Collins, 

CO 80526–8118 and Wyoming Wildlife Consultants, LLC, Pinedale, 

WY 82941.

5

Sanborn Mapping Company Inc., contracted to Bureau of Land Management, National Operations Center, Building 50, Denver, CO 80225.

6

Colorado State University, Natural Resource Ecology Laboratory, 200 NES 

Building, Fort Collins, CO 80524.

*

Contact: Zack Bowen bowenz@usgs.gov, 970–226–9218, or Dan Manier 

manierd@usgs.gov, 970–226–9466.

Executive Summary 

The sagebrush biome, including sagebrush-steppe 

and Great Basin sagebrush communities, interspersed with 

grasslands, salt flats, badlands, mountain ranges, springs, 

intermittent creeks and washes, and major river systems, is 

one of the most widespread and enigmatic components of 

Western U.S. landscapes. One of its most charismatic species, the Greater Sage-Grouse, has been observed, hunted, 

and counted for decades. Habitat conversion, degradation, 

and fragmentation have accumulated across the entire range 

such that local conditions as well as habitat distributions at 

local and regional scales are negatively affecting the long-term 

persistence of this species. Historic patterns of human use and 

settlement of the sagebrush ecosystem have contributed to 

the current condition and status of sage-grouse populations. 

The current framework of multiple use (including industrial, 

agricultural, recreation, and other activities) has been imposed 

over a system that never fully recovered from the intense use 

prior to the Taylor Grazing Act (1934). Repurposing of the 

most productive sagebrush ecosystems (regions with deep, 

loamy soils, for example) for agriculture and urban development means that sage-grouse have already been marginalized 

on lands they share with domestic livestock, industry, herds 

of introduced horses and burros, and other sagebrush inhabitants. But in spite of the accumulation of odds against them, 

many small and large sage-grouse populations persist across 

the range, albeit population counts have steadily declined in 

past decades. 

The accumulation of habitat loss, persistent habitat degradation, and fragmentation and perforation by industry and 

urban infrastructure, as indicated by U.S. Fish and Wildlife 

Service (USFWS) findings, presents a significant challenge 

for conservation of this species and sustainable management 

of the sagebrush ecosystem. Because of the wide variations 

in natural and human history across these landscapes, no 

single prescription for management of sagebrush ecosystems (including sage-grouse habitats) will suffice. However, 

specific activities that fall under the general categories of 

protecting the isolated pieces of intact and well-functioning 

sagebrush ecosystems, and improving, mitigating, and restoring less functional ecosystems, if well-informed, coordinated, 

and wide-ranging, should contribute to reducing the impacts 

of previous land uses and land-use patterns on current habitat conditions and population trends. Across the sage-grouse 

range, the impacts of extensive infrastructure are widespread, 

including roads, power transmission lines, pipelines, communication towers, and fencing, and localized human activities 

such as water retention and vegetation treatments have been 

recognized, but precise influences and remediation solutions 

are often not well understood. These activities interact with 

widespread, but generally less intense, pressures including 

large herbivores (domestic, introduced, and native ungulate 

populations) in determining range conditions. Range and habitat conditions may be improved, mitigated, and (or) regulated 

to reduce impacts and better balance the desires of land users 

with wildlife needs and conservation of public property and 

interests (lands and wildlife). Importantly, as recognized by 

Natural Resources Conservation Service (NRCS) Sage-Grouse 

Initiative (SGI) and others, continuing to improve habitat 

management is complementary to sound range management, 
2 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

and improving the composition, productivity, and resilience 

of sagebrush habitats should improve rangeland health for 

the benefit of all. Although a suite of direct mortality sources 

have been discussed and investigated, the evidence clearly 

suggests that critical aspects of population demographics, 

including nest success, brood-rearing success, predation risk, 

disease risk, hunting, and poisoning are only significant when 

habitat restrictions (that is, loss, fragmentation, and degradation) magnify their effects. Thus, concentrating on conservation and improved management of the sagebrush ecosystem 

as a solution for reducing the decline of sage-grouse requires 

the critical endorsement of the close relation between habitat 

availability, condition, and distribution with population fecundity. This relation is foundational in science and management 

of wildlife. The collective efforts of State wildlife management agencies and State and Federal land management agencies to improve range and habitat conditions, to the benefit 

of wildlife, public interests, and local landowners (especially 

public land lessees) are also based on this foundational relation. Current efforts are additionally complicated by evolving knowledge and changing roles of natural processes. For 

example, understanding of the relation between fire and sagebrush systems has evolved from a theory of purely negative 

effects to recognition of its importance as a natural process. 

Re-evaluations of preconceptions and continuing experimentation and observations indicate complicated relations between 

sagebrush and disturbances and imply a more irregular and 

lengthy interval between fires than previously described. Current understanding recognizes fire as a relevant tool, albeit 

with a potentially limited role in some systems, and certainly 

a complicated role in conserving the distribution and function 

of sagebrush ecosystems, due to interactions with other factors. Understanding and application of the natural role of fire 

in sagebrush ecosystems must be tempered by the realization 

that loss and fragmentation of mature sagebrush communities 

(given recent disturbance and land-use patterns) is a threat to 

sage-grouse conservation. Occurrence of large wildfires, often 

influenced by the distribution of cheatgrass, represents a direct 

threat to the successful conservation of those habitats and 

associated populations.

This report documents and summarizes several decades 

of work on sage-grouse populations, sagebrush as habitat, 

and sagebrush community and ecosystem functions based 

on the recent assessment and findings of the USFWS under 

consideration of the Endangered Species Act. As reflected 

here, some of these topics receive a greater depth of discussion because of the perceived importance of the issue for 

sagebrush ecosystems and sage-grouse populations. Though 

explicit connections to effects on sage-grouse populations 

are attempted throughout, these connections remain elusive 

and difficult to document. Understanding that perfect knowledge of these species and ecosystems is impossible due to 

natural complexity and human limitations, drawing connections between the direct effects on sagebrush ecosystems and 

the effect of ecosystem condition on habitat condition, and 

finally the connection between habitat quality and sage-grouse 

population dynamics remains the lofty goal of science and 

management. This effort is necessary and important, and 

despite the perception that these complicated, indirect relations 

are difficult to characterize and manage, many advances in 

understanding and application have been documented.

The distributions of habitats, species, and human land 

uses are notably heterogeneous across large landscapes, and 

understanding the relations and processes that create these 

patterns, including both positive and negative associations, 

will assist in long-term planning by helping to identify risks 

to habitat and resource conservation success, control and mitigate our activities to reduce impacts and insure resiliency, and 

protect and conserve our natural heritage and natural resources 

for future generations. Rather than any single source of habitat 

degradation, the cumulative and synergistic impact of multiple 

disturbances, continued spread and dominance of invasive 

species, and increased impacts of land use continue to have 

the most significant influence on the trajectory of sagebrush 

ecosystems and sage-grouse populations. Future patterns of 

land use, combined with effective restoration and management 

may improve, or degrade, the remaining sage-grouse ranges, 

but natural dynamics and unforeseen stochasticity promise to 

add complexity to future plans and landscapes.

I. Social and Political Overview and

Introduction

Greater Sage-Grouse (Centrocercus urophasianus, hereafter sage-grouse) are large, ground-dwelling birds that reside 

primarily in sagebrush ecosystems which were, and still are in 

some respect, ubiquitous across the intermountain regions of 

western North America. Whereas human settlement of these 

lands has been slower and more sparse than in more naturally 

productive parts of the country, conversion to suit human purposes, development of energy and mineral resources beneath 

the surface, and a long history of dispersed (but sometimes 

intensive) uses such as domestic grazing and off-highway 

vehicles (OHVs) have contributed to widespread loss and 

decline of sagebrush habitat quality and associated wildlife 

populations, as documented herein. The estimated distribution of contiguous sagebrush habitats, prior to Euro-American 

settlement (Schroeder and others, 2003), was nearly twice 

that which is available today (fig. 1). Although early documentation is sparse and potentially biased, it is suspected that 

similar reductions in sage-grouse abundance have occurred at 

a continental scale (Schroeder and others, 2004). Sage-grouse 

population trends are variable across their distribution, and 

though some populations appear stable, population numbers 

show long-term declines collectively and in several regions 

(Connelly and others, 2004). Proximate reasons for population declines differ across the sage-grouse distribution, but 

ultimately, the underlying cause is loss of suitable sagebrush 

habitat (Connelly and Braun, 1997; Leonard and others, 2000; 

Aldridge and others, 2008), which contrasts with direct effects 

such as predation, hunting, or other incidental mortality (such 

as collisions).
I. Social and Political Overview and Introduction 3

Figure 1. Current distribution (2004) of Greater Sage-Grouse and pre-settlement distribution of sagebrush habitats available for 

Greater Sage-Grouse across western North America. 
4 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Typically, variety in sagebrush-community composition (with variations in subspecies composition, co-dominant 

vegetation, shrub cover, herbaceous cover, and stand age) is 

necessary within the landscape to meet seasonal, and interseasonal, requirements for food, cover, and nesting of sage-grouse 

(Patterson, 1952; Connelly and others, 2000c). In this context, 

“the landscape” for sage-grouse encompasses large areas, 

roughly from 10s to 100s of square kilometers, to provide for 

multiple aspects of species life requirements, such as seasonal 

habitats (Beever and Aldridge, 2011; Connelly and others, 

2011a,b; Leu, 2011). Thus, conserving and managing sagegrouse is as much about the ecology, management and conservation of large, intact sagebrush ecosystems as it is about 

the dynamics and behaviors of the bird populations (Connelly 

and others, 2004; Crawford and others, 2004). The large areas 

used by sage-grouse to meet seasonal habitat needs in these 

environments, coupled with the mixed land ownership patterns 

typically found across the west (fig. 2), dictates that a conservation strategy for the species will rely on cooperation across 

multiple Federal, State, local, and private parties. The basis of 

these cooperative conservation strategies requires understanding and mitigating the distribution of multiple threats that, in 

combination, reduce available habitat for sage-grouse. 

Compounding the conservation challenge for governmental management agencies and private individuals alike, 

the sagebrush ecosystem is also important for the social and 

economic stability of the Western United States. Livestock 

grazing has been an important part of sagebrush ecosystems 

since the middle 1800s (Larson, 1978), and it continues to 

have important implications for the condition and management 

of these lands. Although grazing is critical for the economic 

and social structure of the region and an important contributor to the food supplies of the nation, the effects of grazing 

on public resources remain a contentious source of debate, 

research, and experimentation. Further, sagebrush rangelands 

have been steadily constricted by urban and exurban domestic 

development, mineral and energy industrial development, and 

a host of other land-use activities (and associated impacts) 

on surrounding natural areas (U.S. Fish and Wildlife Service, 

2010b; Knick and Connelly, 2011b; Leu and Hanser, 2011). 

Thus, the balance between societal demands, natural capacity, 

and wildlife conservation is a fundamental component of sagebrush management, but this balance has not always been met. 

Accumulation of direct and diffuse disturbances has led to 

limitations in sagebrush systems, as habitats, due to degradation of local shrub and grass cover, diminished size of habitat 

patches, and wide dispersion of high-quality, seasonal habitats. This indicates that proximity and juxtaposition of habitat 

patches, as well as condition of the matrix, affect travel effort 

and mortality risks between habitats and overall habitat quality 

(Miller, 2011; Knick, 2011). 

The multiple-scale attributes of sage-grouse habitat 

requirements make the current and historic roles of fire and 

other surface disturbances (for example, roads, industrial 

developments, agricultural conversion, and habitat treatments) 

important for monitoring and manipulation at regional scales 

as plans to manage for functional sagebrush ecosystems are 

implemented. Though wildfires likely played an important 

role historically in creating a mosaic of herbaceous dominated 

areas (recently disturbed) and mature sagebrush (less frequently disturbed), current and historic land-use patterns have 

defined a new mosaic that has restricted systemic ability to 

support wildfire regimes. Slow rates of growth and recovery of 

vegetation after disturbances (driven by low water availability 

and other environmental constraints) coupled with high rates 

of disturbance and conversion are largely responsible for the 

accumulating displacement and degradation of the sagebrush 

ecosystem, including natural disturbance regimes and patch 

dynamics that characterized historic landscapes (Christensen, 

1985; Pickett and White, 1985).

Finally, the basins where most sagebrush ecosystems 

reside are also the center of major oil and gas reserves (for 

example, Denver, Eastern Great, Green River, Niobrara, 

Powder River, Uinta-Piceance, and Williston Basins), which 

have a long history of industrial use, particularly on eastern 

portions of the range, especially Management Zones (MZs) I, 

II, and VII. The intensity of new energy development has varied through time due to various factors including economics, 

technology, and national policy, but accumulation of roads, 

pads, wells, and other infrastructure has greatly outpaced 

their removal. Current national energy policies and demand 

for domestic oil and gas indicate that removal and reclamation of these resources will remain an important aspect of 

multiple-use land management, including habitat and wildlife 

management, into the future. In addition, national emphasis on 

“renewable” resource development adds pressure to develop 

wind, solar, and geothermal energy facilities. Although 

research on direct effects of these developments on wildlife is 

still underway, as described here, recognition that these developments alter, degrade or entirely displace native ecosystems 

is ubiquitous as the basic set of impacts (roads, traffic, equipment noise, and lights) are common among industries. 

Imposition of modern land-use pressures on native 

ecosystems leads to direct habitat loss and habitat degradation. Even without added anthropogenic pressures, ecosystems 

are balanced between changing environmental conditions and 

demands for ecosystem services from people and wildlife such 

as clean water, abundant forage and prey, and domestic habitat. According to recent estimates, this combination of influences is tipping the scale, placing the sage-grouse on the verge 

of Federal listing under the Endangered Species Act (currently 

classified as “warranted, but precluded”). 

In the last decade, concern for the species prompted a 

series of petitions to list the sage-grouse under the Endangered Species Act (Stiver, 2011). The details of these petitions are well documented (U.S. Fish and Wildlife Service, 

2010b; Stiver, 2011). More recently, on March 23, 2010, the 

USFWS released its 12-Month Findings for Petitions to list the 

Greater Sage-Grouse (Centrocercus urophasianus) as Threatened or Endangered (“2010 Listing Decision”; U.S. Fish and 

Wildlife Service, 2010b). In the 2010 Listing Decision, the 

USFWS concluded that listing the sage-grouse (rangewide) 
I. Social and Political Overview and Introduction 5

Figure 2. Land ownership or management jurisdiction across sage-grouse Management Zones (MZ). Note that small parcels and many 

details are omitted from a map of this resolution, in particular, private lands will appear underrepresented. This representation is for 

explanatory purposes only; it does not imply or infer any legal or other designation, re-designation, ownership rights or right-of-way.
6 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

was warranted, but precluded by higher priority listing actions 

(U.S. Fish and Wildlife Service, 2010b). The listing decision 

focused on two factors: (1) habitat fragmentation and degradation and (2) inadequate regulatory mechanisms. The USFWS 

will continue to annually evaluate changes to listing factors 

and update listing decisions regarding sage-grouse; however, 

the current urgency (time line) has been dictated by a work 

plan developed in response to a series of court approved 

settlement agreements (Judge Emmet Sullivan, U.S. District 

Court, Washington, D.C., September 9, 2011). Through these 

agreements and the plan, the agency agreed to make a final 

listing decision regarding the status of the sage-grouse by 

the end of fiscal year 2015. (Legal documentation and the 

work plan are available at http://www.fws.gov/endangered/

improving_ESA/listing_workplan.html.) Under the terms of the 

settlement agreements, the USFWS must either determine that 

sage-grouse are warranted for listing and publish a proposed 

rule implementing that listing or make a not-warranted finding 

(“warranted, but precluded” will not satisfy legal agreements). 

Building upon local working groups and interagency 

agreements, State and Federal land and wildlife management 

agencies are developing coordinated conservation strategies to 

secure the long-term future of the sage-grouse; unprecedented 

actions aimed at revising management and conservation so 

that listing (of the sage-grouse under the Endangered Species Act, ESA) is not necessary due to improved regulatory 

mechanisms providing for long-term sustainability of the species without further regulation. In direct response to concerns 

over regulatory mechanisms across the sage-grouse range, 

which transcend local, State, and Federal boundaries, these 

same entities are engaged in revising population conservation strategies, land management regulations, and management plans. This report provides a critical information source 

to these efforts by collecting and summarizing the scientific 

information important for understanding the impact of threats 

to sage-grouse and the spatial juxtaposition, and therefore 

relative magnitude of these issues, across the west and for 

different conservation partners. The primary focus is twofold; 

it should (1) inform the Bureau of Land Management (BLM) 

and U.S. Forest Service (USFS) Greater Sage-Grouse Land 

Use Planning Strategy (Bureau of Land Management, 2011a) 

with consistent assessment and application of the most recent 

information and understanding regarding sage-grouse and their 

habitats, and (2) it should provide a quantitative summary 

of identified threats to establish a foundation for understanding and managing these impacts at biologically meaningful 

scales (such as, the Western Association of Fish and Wildlife 

Agencies, WAFWA, Management Zones). It will be important to address cumulative and interactive impacts of multiple 

disturbances and impacts in these planning efforts because 

they have been found, individually and in combination, to 

contribute to the decline of sage-grouse habitats (Connelly and 

others, 2004; U.S. Fish and Wildlife Service, 2010b; Connelly 

and others, 2011d). This summary assessment, along with 

associated analyses and applications, describe the environmental conditions and characterize the legal, natural resources, 

and human perspectives at a regional scale to help inform the 

large-scale context required for planning efforts.

A National Strategy

The National Greater Sage-Grouse Land Use Planning Strategy represents a planning framework and process 

to incorporate effective regulatory mechanisms (conservation measures) into Land Use Plans (LUP), especially BLM 

Resource Management Plans (RMP) and USFS Forest 

Management Plans (FMP), across the range of the sage-grouse 

(Bureau of Land Management 2011c, 2012). The strategy 

includes review of existing regulatory mechanisms and revision of these as necessary to conserve and restore the sagegrouse and their habitats on USFS- and BLM-administered 

lands across the species’ range and to ensure these measures 

are carried forward into future planning efforts on the public lands. This planning framework includes the following 

elements:

• The need for science-based objectives, measures, and 

LUP decisions,

• The need for common data and regional perspectives to 

support local and regional cumulative impacts analyses,

• Consistency across jurisdictional boundaries and within 

defined ecoregional areas,

• The principal threats identified by the USFWS within 

different portions of the range, and

• Objectives expressed by the USFWS and WAFWA 

directives.

This approach articulates a structure and process capable 

of responding to national policy as well as the different 

ecological attributes and threats within regions by dividing 

the range into two broad regions—Great Basin and Rocky 

Mountains. As envisioned, each region develops a separate 

but similar planning strategy based on a cooperative planning effort with State wildlife management agencies and the 

USFWS. Information in this report is expected to support and 

inform the planning approach for these five elements of the 

National Planning Strategy. The primary focus of the planning 

effort, and hence this report, is Greater Sage-Grouse (Centrocercus urophasianus). The Gunnison Sage-Grouse (Centrocercus minimus), Greater Sage-Grouse Bi-State Distinct Population Segment (DPS), and Greater Sage-Grouse Columbia 

Basin DPS will be addressed in separate planning efforts and 

therefore are outside the scope of this report (Bi-State Local 

Planning Group, 2004). 

This report is focused on providing support and regional 

consistency among these functional planning and implementation units through compilation, assessment and summary 

of data, and information from across the species’ range (East 

and West). Rangewide and subregional distributions were the 
I. Social and Political Overview and Introduction 7

subject of targeted geospatial analyses to facilitate assessment 

of cumulative effects of development and other land uses 

beyond typical planning-unit boundaries. By compiling and 

summarizing data and technical literature that represent and 

address resource distributions, conservation units, potential 

threats, and other factors affecting the health and distribution 

of sage-grouse populations and habitats, it is anticipated that a 

common understanding may be carried forward by local working and planning groups.

Purpose and Suitable Application of This Report

Because of their broad range, variations in population 

traits and characteristics across this range, and the variability 

in habitat conditions and threats within this range, conservation of sage-grouse is a unique challenge compared to isolated 

or range-restricted species, primarily due to the scale of the 

effort. This complexity is increased because sage-grouse 

have habitat requirements that can be recognized at multiple 

scales with the broadest transcending traditional management 

boundaries. An area has suitable habitat if it (a) is large with 

contiguous acres of sagebrush; (b) contains a mosaic of sagebrush, grass, and forb cover, which provides suitable cover 

and forage opportunities (good condition) within proximity 

to allow seasonal movement and use; (c) contains healthy, 

productive, and sufficiently isolated (safe) local habitats that 

provide specific seasonal requirements, such as sagebrush, 

grasses, forbs and insects in spring-summer and sagebrush 

without snow-cover in winter; and (d) has sufficient specific 

microsite conditions that provide daily needs such as nest 

sites. Similarly, planning for conservation and management 

occurs at multiple scales. 

Current efforts to prioritize areas across the range for 

conservation have focused on identifying large expanses of 

sagebrush for protection (casting a broad net to protect sagebrush ecosystems) or specifying regional expanses based on 

the “core areas” concept based on breeding density of the birds 

(numbers of males on leks; Doherty and others, 2010c). The 

National Greater Sage-Grouse Land Use Planning Strategy 

focuses at these broader scales; therefore, to accomplish this 

assessment, local details, for example the amount of shrub 

canopy, which vary in space and time, are necessarily grouped 

and averaged within map units (grid-cells or shapes) precluding fine-scale evaluation. However, regional trends and patterns that develop during periods of years may be recognized 

and highlighted at scales useful for assessment, planning, and 

management processes. This document is designed to inform 

and advance large-area, regional conservation efforts by 

consolidating information regarding rangewide and regional 

information about sage-grouse populations and habitats and to 

act as a bridge between these large-area efforts and regional 

and local management efforts (that is, forest and range management plans) by providing spatial and information context.

Delineation of Preliminary Priority and General 

Habitats 

BLM national policy during the last decade has also 

focused on delineation and protection of large expanses of 

sagebrush with high densities of sage-grouse. In 2008, the 

BLM directed field and State offices to prioritize “key habitat 

areas” (large expanses of sagebrush) for protection from 

wildfire (Bureau of Land Management, 2008). Similarly a 

core-area strategy was proposed in the eastern portion of the 

range to help delineate landscape planning units by distinguishing areas of high biological value based on location of 

important breeding areas to help balance habitat requirements 

with demand for energy development (Doherty and others, 2011b; State of Wyoming, 2011). This core area method 

was adopted by many State fish and wildlife agencies who 

used Statewide breeding-bird data supplemented by local 

knowledge and interpretation to delineate habitat areas, for 

example Wyoming’s Core Areas (State of Wyoming, 2011). 

The Doherty approach was expanded by the BLM rangewide 

to create a Breeding Bird Density Map—across the range 

of the sage-grouse where the highest densities of breeding males were found on leks (Doherty and others, 2010c). 

Currently, the rangewide map has also been applied by the 

U.S. Department of Agriculture (USDA) through the NRCS 

to guide the SGI in prioritization of conservation actions on 

private lands within the sage-grouse range (Natural Resources 

Conservation Service, 2011). In an effort to consistently 

identify highly valuable areas that combine habitat-quality 

and bird-density approaches to identification and delineation, 

BLM has adopted “Preliminary Priority Habitat” (PPH) and 

“Preliminary General Habitat” (PGH) maps; these determinations and products were created cooperatively with State fish 

and wildlife agencies (Bureau of Land Management, 2011b). 

PGH and PPH are mutually exclusive habitat classes. PPH 

represents the habitat designated to maintain distribution and 

sustainable sage-grouse populations. PGH represents additional sage-grouse habitat with smaller populations, current or 

imminent threats, or other factors that affect management and 

conservation opportunities, which may be managed for habitat 

conservation and (or) restoration based on needs for connectivity, potential for restoration, or other local issues (fig. 3). 

This approach combines both the bird density and valuable 

habitat approaches and adopts State-agency knowledge and 

perspectives to identify the seasonal habitats needed for sagegrouse persistence. It represents a collective of biological, 

socioeconomic, and management understanding combined to 

identify areas that need assessment of threats for amelioration 

or protection, regulatory enforcement mechanisms, monitoring 

of sage-grouse population trends, and adaptive management 

as needed, and it should complement, not replace, locally 

specified priorities when these are aligned with regional 

issues (Conservation Objectives Team and others, 2013). This 

cooperative approach identified habitat across 10 States utilizing a planning process that extended across multiple jurisdictions. Ongoing applications through the land-use planning 
8 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 3. Distribution of preliminary priority habitat and preliminary general habitats (PPH and PGH, respectively) displayed with 

additional (current) distribution of sagebrush.
I. Social and Political Overview and Introduction 9

process, especially BLM and USFS, may refine PPH and PGH 

to (1) improve and update Priority Habitat area definitions, 

(2) analyze actions within Priority Habitat areas to conserve, 

or improve, sage-grouse habitat functionality, (3) formally 

recognize General Habitat areas and assess habitat condition 

and use in these areas, and (4) analyze actions within General 

Habitat areas that affect the ability of the system to provide 

important sage-grouse functional requirements (such as suitability for breeding, migration, or winter survival). 

Because of the different objectives for priority and 

general habitat, this report uses the current PPH and PGH 

delineations (as defined, June 26, 2012) to characterize the 

relative magnitudes and locations of threats within current 

management, planning, and assessment units. Potential applications include identification of local habitats within a regional 

context of PPH and PGH, understanding the distribution of 

threats within PPH and PGH areas, providing spatial context 

such that priority habitat can be delineated or adjusted, and 

management actions can be devised to meet conservation and 

management objectives. 

Geospatial Analysis Methods

Geospatial data were acquired for all threats identified in 

the USFWS listing decision that can be represented spatially. 

These data were acquired rangewide, as available, from both 

internal (BLM and USFS) and external sources beginning in 

August 2011 (see appendix). All data, both internal and external, were considered the “best available” at the time of data 

collection. National dataset collection stopped in July 2012 

(although verification and adjustments of some of the datsets 

continued through December 2012), whereas other data (for 

example, compiled from other sources) were the most current 

available based on the supplying office, agency, or organization. Internal data were compiled using intra-agency data calls 

and often included data submitted in segments from different 

administrative units across the BLM and USFS management 

areas. These datasets were aggregated and reviewed, but time 

constraints limited the ability to revise these data for quality 

and completeness, such as properly addressing all geometry 

errors (gaps and overlaps) and edge-matching across jurisdictions. After data collection was complete, input datasets were 

preprocessed. Preprocessing steps included reclassification, 

attributing, buffering, and other formatting tasks. Categorizing datasets into relevant attributes and supplementing them 

with additional attributes was necessary for data compatibility. Buffers were developed based on area-of-influence 

distances provided in peer-reviewed literature to represent 

direct (footprint) and indirect (buffer distances ranging from 

1.5 to11.8 mi [2.5–19 km]) effects on sage-grouse populations. 

(Also, see Appendix A-1.) Collaboratively developed priority habitat designations (PPH and PGH) were combined with 

surface management responsibilities and WAFWA Management Zone polygons into one master summary file with a 

unique identifier reflecting the specific combination of habitat, 

surface management, and MZ for each polygon to provide for 

efficient, repeatable, and consistent data summaries. Finally all 

datasets were clipped to the rangewide study area, and small 

or superfluous polygons were dissolved to reduce the number 

of features and remove unnecessary attributes. Finally, data 

was sorted into point, line, and polygon features for different 

analyses that reflected the footprint and effects representation.

Overlay comparisons were generated using ArcGIS 

Model Builder (version 10.0) with separate models created 

for point, line, and polygon input data (see appendix for 

details). In brief, these models intersected the input data with 

the master summary file, which included representation of the 

spatial summary units (MZs, and so forth), and dissolves extra 

boundaries based on the unique identification assigned in the 

intersection. Finally, summary data were calculated for each 

threat overlay using the number of points, linear miles, or area 

within the specific combination of habitat type, land management, and MZ. Attribute data were exported to spreadsheets 

for summary calculations. 

Key Assumptions and Limitations

The data and information included here are the most 

accurate available; however, these data and associated risk 

assessments remain based in present knowledge. Simulation 

of future conditions was not a component of this assessment, 

and these data are not predictions of future events or conditions. Spatial data informing these analyses were compiled to 

establish a consistent information and analytical basis across 

the entire region (Sage-Grouse Management Area), but in 

order to attain this consistently across State, ownership, and 

management boundaries, some local details have been omitted. As such, these data and analytical approaches provide a 

regional assessment tool suitable for guiding regional mid- to 

long-term planning scenarios over broad spatial scales. Local 

expertise and data are needed to complement these landscape 

data when developing specific management plans using these 

regional guides. 

Because of the scale of summary and the existence of 

other guiding documents, this report was developed to play a 

particular role in organizing and assessing the character and 

distribution of threats to the persistence of sage-grouse. Data 

and summary information were compiled rangewide providing sufficient resolution to address relative distribution and 

magnitude of effects within the seven sagebrush Management 

Zones (MZs) defined to support sage-grouse conservation 

planning, but these may require local supplementation. Within 

these Management Zones, current delineations of PPH and 

PGH cross management entities and represent Federal and 

State perspectives on the areas needed to maintain sustainable 

populations and the areas to evaluate to maintain connectivity 

between these populations (see tables for summary statistics representing PPH and PGH by Management Zone and 

entity). For the purposes of this report, focus on the Greater 

Sage-Grouse (without the Bi-State and Columbia Basins 
10 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

populations) includes BLM and USFS units within sagegrouse range. The study area roughly follows the Management 

Zone boundaries, but limits analyses to overlapping areas 

within specific planning unit boundaries (fig. 3). Therefore, 

this assessment concentrates on currently occupied habitats 

and uses slightly different delineations than found in previous, 

related works (for example, Stiver and others, 2006; Knick 

and others, 2011). The natural and human processes of interest 

are active across multiple spatial-temporal scales; therefore 

this assessment necessarily includes topics and discussion that 

cross between national-, regional-, and local-level planning 

and implementation. However the primary goal of this report 

is to provide broad-scale perspective (in data and literature), 

which may be combined, subsequently, with local knowledge and directives to develop specific forest and resource 

management plans.

II. Populations, Distributions, Trends, 

and Natural History 

Species Description and Taxonomy (Rangewide) 

Sage-grouse (Centrocercus spp.) are the largest grouse 

found in North America. They are a ground-dwelling, 

sagebrush-obligate species. Historically, sage-grouse were 

considered to be one species with a pre-settlement range that 

included 14 U.S. States and 3 Canadian Provinces (fig. 1; 

Aldrich, 1963; Johnsgard, 1983; Connelly and others, 2004; 

Schroeder and others, 2004). In 1946, Aldrich described 

two subspecies, an eastern (C. u. urophasianus) and western 

sage-grouse (C. u. phaios) based on slight color differences 

in 11 individuals collected from Washington, Oregon, and 

California (Aldrich, 1946). In the 1990s, research in southwestern Colorado revealed morphological (Hupp and Braun, 

1991) and behavioral (Young and others, 1994) evidence 

suggesting that the sage-grouse in southwestern Colorado and 

southeastern Utah were distinct from sage-grouse elsewhere 

across their range and might be a new species. Genetic data 

(Kahn and others, 1999; Oyler-McCance and others, 1999) 

revealed patterns consistent with a lack of gene flow between 

sage-grouse in southwestern Colorado-southeastern Utah and 

northern Colorado, which supported the idea that this group 

of sage-grouse was a different species. In 2000, the American 

Ornithologists’ Union recognized the formal description of 

this group of sage-grouse as a new species, named Gunnison 

Sage-Grouse (C. minimus; Young and others, 2000). All other 

sage-grouse were subsequently renamed Greater Sage-Grouse 

(C. urophasianus). 

This reassessment of sage-grouse taxonomy spurred a 

reexamination of the subspecies classification of the sagegrouse. The geographic delineation separating the eastern and 

western subspecies is ambiguous and has changed through 

time (Aldrich, 1946; Aldrich and Duvall, 1955; American 

Ornithologists’ Union, 1957; Aldrich, 1963). Morphological 

comparisons by Schroeder (2008) revealed slight variations 

among individuals and some populations, yet the magnitude 

of the differences were not sufficient to be recognized as 

distinct subspecies using current taxonomic standards, and the 

patterns of variation were not consistent with geographically 

described subspecies. Schroeder (2008) and Taylor and Young 

(2006) both examined strutting behavior and did find some 

regional differences, but those differences were inconclusive 

in distinguishing the purported eastern and western subspecies. 

Genetic data (using both mitochondrial and nuclear genetic 

markers) collected from individuals across the range were not 

differentiated at the subspecies boundary (Benedict and others, 

2003; Oyler-McCance and others, 2005b), yet a population 

that spans the border between California and Nevada (Bi-State 

population) was found to be unique genetically. This Bi-State 

population, although genetically unique, does not appear to 

have obvious morphological or behavioral differences as was 

seen in the Gunnison Sage-Grouse (Taylor, 2006; Schroeder, 

2008). Though the taxonomic status of the Bi-State population 

has been widely debated, no formal taxonomic change regarding this population has been made. Additionally, the U.S. Fish 

and Wildlife Service no longer considers listing consideration 

at the subspecies level based on the multiple lines of evidence that do not support the eastern and western subspecies 

delineation in sage-grouse.

Population Distribution and Trends—Including 

Subpopulations and Management Zones 

The current range of sage-grouse includes 11 U.S. States 

and 2 Canadian provinces (fig. 1) and is thought to be a reduction of 44 percent from the pre-settlement range (Connelly and 

Braun, 1997; Schroeder and others, 2004). Although specific 

reasons for population decline differ across the range, the 

underlying cause is the loss, degradation, and fragmentation of 

suitable sagebrush habitat (Connelly and Braun, 1997; Leonard and others, 2000; Aldridge and others, 2008). As sagebrush habitats increasingly overlap with natural resources (for 

example, oil, gas, wind, minerals, agriculture, and recreation 

areas) and face increased landscape-level changes caused by 

invasive plants, fire, and conifer encroachment (Connelly and 

others, 2004), populations have declined substantially raising 

conservation concern for the species. 

The broad distribution of sage-grouse encompasses a 

diverse collection of environments with an equally varied 

assortment of ecological pressures. Therefore, management 

practices and conservation strategies are often quite dissimilar 

in different portions of the range (Stiver and others, 2006a). 

To facilitate development of management and conservation 

actions that are more consistent within ecological regions, 

instead of political boundaries, the sage-grouse range was 

divided into seven sage-grouse Management Zones based on 

similarities in geography, climate, topography, and floristics 

(West, 1983; Miller and Eddleman, 2000; Connelly and others, 

2004; Stiver and others, 2006a; fig. 2). 
II. Populations, Distributions, Trends, and Natural History 11

Sage-grouse MZ I includes seven sage-grouse populations on the northwestern Great Plains (Connelly and others, 

2004) in parts of Montana, Wyoming, North Dakota, South 

Dakota, Saskatchewan, and Alberta (fig. 3 and table 1). Three 

of these populations are considered large and are loosely connected to adjacent populations (Connelly and others, 2004). 

The Wyoming Basin (MZ II) consists of 13 populations covering parts of Montana, Wyoming, Colorado, Idaho and Utah. 

Three populations are considered to be large and connected 

to adjacent populations (Connelly and others, 2004), and the 

Wyoming Basin proper includes five subpopulations that are 

perceived to be well connected. Management Zone III represents the Southern Great Basin and consists of 13 populations 

in parts of California, Nevada, and Utah. Only two of these 

populations have been described as large (table 1; Connelly 

and others, 2004). The Mono Lake (Bi-State Local Planning) population is included in MZ III; however, that Distinct 

Population is being addressed through a separate planning 

process involving California and Nevada working groups. The 

Snake River Plain and associated drainage basins characterize MZ IV; this region includes 14 sage-grouse populations in 

Oregon, Montana, Idaho, Nevada, and Utah, and two of these 

populations are considered to be large (Connelly and others, 

2004). Management Zone V consists of five populations in the 

Northern Great Basin. These populations are found in Oregon, 

California, and Nevada. The Lake Area (Oregon, California, 

and Nevada) population is the only one described as large and 

loosely connected (Connelly and others, 2004). Washington is 

the only State with populations of sage-grouse in the Columbia Basin (MZ VI). Only two populations exist in this entire 

MZ (Moses Coulee and Yakima, Wash.), and both populations 

are isolated and far removed from the rest of the sage-grouse 

range (Connelly and others, 2004). These populations are not 

covered by this report, although similarities and information 

overlap may exist. The Colorado Plateau (MZ VII) is made up 

of six populations of sage-grouse in Utah and Colorado. All 

populations are considered to be small and isolated (Connelly 

and others, 2004). This MZ also includes populations of Gunnison Sage-Grouse. One population (living near Gunnison, 

Utah) is a Greater Sage-Grouse population that was translocated into the range of Gunnison Sage-Grouse. The MZ VII 

populations are summarized along with populations in MZ II 

for this report because of the limited area and similar attributes 

of the few populations living in northwestern Colorado and 

northeastern Utah.

The highest densities of strutting male sage-grouse occur 

in MZs I, II, IV, and V (fig. 4; Doherty and others, 2010c). 

Management Zone III includes lower densities, and MZ VI 

represents dispersed birds in the Columbia Basin. In the Colorado Plateau (MZ VII), the Gunnison Sage-Grouse persist in 

the south, whereas small populations of Greater Sage-Grouse 

persist in the north (fig. 4). 

Forty-one discrete populations of sage-grouse (described 

in reference to MZs above) were defined by Connelly and others (2004; fig. 5). Some of these populations cross MZ boundaries and are thus divided into subpopulations for management 

purposes. Detailed descriptions of populations and subpopulations and justification for their definitions were provided in 

the WAFWA Conservation Assessment (Connelly and others, 

2004), and a summary of that information is provided here 

(fig. 5). The most isolated populations occur in Colorado, 

Utah, Nevada, California, and Washington. Of the seven MZs, 

the most populations occur in MZs III and IV.

The species’ range and total population size have 

declined dramatically from historical levels (Hornaday, 1916; 

Crawford, 1982; Drut, 1994; Braun, 1998; Schroeder and 

others, 1999). Analysis of rangewide decline between 1965 

and 2003 revealed an average of 2-percent decline per year 

with the earlier years (1965–1985) declining at a greater rate, 

3.5 percent, than the later years when the rate slowed to 0.37 

percent (Connelly and others, 2004). Two additional analyses found similar rates of decline using different statistical 

techniques and additional years of data (Western Association 

of Fish and Wildlife Agencies, 2008; Garton and others, 2011). 

Connelly and others (2004) also estimated that sage-grouse 

numbers in the 1960s and 1970s were double or triple current 

numbers, an analysis that was corroborated by Garton and 

others (2011). Three analyses of sage-grouse population trends 

within MZs showed long-term population declines in most 

MZs (Connelly and others, 2004; Western Association of Fish 

and Wildlife Agencies, 2008; Garton and others, 2011). Only 

one MZ (VII) has recently demonstrated population trend estimates that were not negative. Estimated trends in populations 

are summarized (table 2) by MZ for each of the three studies 

(U.S. Fish and Wildlife Service, 2010b). Declines in male population estimates (table 3) were considerably larger than effect 

sizes for the total population (table 2). The minimum number 

of male sage-grouse in 2007 was estimated (Garton and others, 

2011b), along with the percent change in number of males per 

lek and percent change in active leks between 1965 and 2007. 

The most male sage-grouse occur in MZ II, and the least are 

in MZ VII. The highest percent change (decline) in number 

of males per lek and the largest percent change in active leks 

both occurred in MZ VI. 

Genetic Diversity, Population Structure, and 

Sustainability 

The spatial organization of populations across a species’ 

range is an important factor influencing its long-term viability. Species that have multiple interconnected populations are 

more likely to persist because the risk of extirpation caused by 

regional events is confined to local populations; connectivity 

among populations ensures that re-colonization can occur following local extirpation assuming that sufficient suitable habitat remains (Gilpin and Hanski, 1991; Hanski and Thomas, 

1994; Hanski, 1998). Thus, movement by individuals within 

this spatial network is expressed through gene flow, one of the 

most critical, yet least understood, processes governing species persistence. For several grouse species, patches of unsuitable/poor habitat above a particular size threshold have been 
Management 

Zones Population Subpopulation Approximate Separation from Adjacent Populations (km) Brief 

1 Dakota (Mont./N. Dakota/S. Dakota) 30–40 Isolated population, fr

Fall River S. Dakota/ Eastern Wyoming 10–20 Small population, fragAlberta/ Southwest Saskatchewan/ Montana 20, narrow corridor Isolated population North Central Montana 20 Large population, isolSouth Central Saskatchewan/ Montana 20–40 Fragmented Central Mont. N.A. Large population, isolEastern Interior Mont./Northeastern Wyoming 10–20 Large population, loo

2 Eastern Tavaputs Plateau, Utah 50 Small population, isol

Eagle/ Southern Routt, Colorado 20–30 and mountains Small population, isolGarfield, Colorado 40 Small population, isolJackson Hole, Wyoming 50 Small population, isolLaramie, Wyoming 30 and mountains Small population, isolMiddle Park, Colorado 20–30 and mountains Isolated Northeastern-Interior, Utah 30–50 Isolated, natural fragmSummit/Morgan, Utah 20–40 and mountains Small population, isolDinosaur, Utah/ Colorado 10–20, narrow corridors Isolated North Park Colorado/ Wyoming 10, narrow corridor Isolated, loosely connSouth Central Mont./North Central Wyoming 10–40 Large population, looSouth Central, Wyoming/North Central, Colorado N.A. Large population, looSouthwestern Wyoming/ Northwestern Colorado/ Northeastern Utah/ Southeastern Idaho N.A. Large population, loo

3

Central Nevada N.A. Large population, natuSoutheastern Nevada/ Southwestern Utah N.A. Large population, natuGunnison Range, Utah 200 Small, translocated poNo. Mono Lake California / Nevada * 20–40 and mountains Isolated

Northwestern Interior Nevada 20–30 Dispersed and isolated Pine Nut, Nevada 50–60 and valleys Small population, isolQuinn Canyon Range, Nevada 50–80 and valleys Small population, isolS Mono Lake, California * 20–50 and mountains Small population, isolS White River, Utah 40–50 Small population, isolSanpete/Emery, Utah 50–60 Small population, isolS-Central, Utah 50–70 and mountains Small population, isolTooele/Juab, Utah 40 Small population, isolWhite Mountains, Nevada/ California * 50 and mountains Small population, isol

Table 1. Recognized populations and subpopulations of sage-grouse included in this analysis. 
Management 

Zones Population Subpopulation Approximate Separation from Adjacent Populations (km) Brief 

4

Baker, Oregon 30 Small population, isol

Bannack, Mont. 30–50 and Continental Divide Small population, isolBelt Mountains, Mont. 70, narrow corridor Small population, isolE-Central, Idaho 30–50 IsolatedRed Rock, Mont. 20–40 and mountains Small population, isolSawtooth, Idaho 70–80 Small population, isolBig Lost, Idaho 10, narrow corridors Loosely connectedLemhi-Birch, Idaho 20 and topography IsolatedLittle Lost, Idaho 20 and narrow corridors Loosely connectedN Side Snake 10–30 Large population, looUpper Snake 20–40 and mountains IsolatedTwin Bridges, Montana 60 Small population, isolWeiser, Idaho 20 Small population, isolWisdom, Montana 4–60 Small population, isol

5

E-Central Oregon 10–30 Loosely connected

Lake Area Oregon/ Northeastern California/ Northwestern Nevada 20–50 Large population, looSouth Central Oregon/North Central Nevada 20–30 Several connected subNortheastern Nevada/South Central Idaho/Northwestern Utah 10–20 Large population, looNorth Central Nevada/ Southeastern Oregon/ Southwestern Idaho 10–20 Several connected subCentral Oregon 30 Isolated and fragmentKlamath, Oregon/ California 50 Small population, fragWarm Springs Valley, Nevada 30–60 and valleys Small population, isol

6 * Moses Coulee, Washington * 50 and Columbia R. Isolated

Yakima, Washington * 50 and Columbia R. Isolated

7 (2) Piceance, Colorado 30–40 Small population, isol

White River, Colorado 30–40 and mountains Small population, isol

*Recognized populations which are not part of this assessment.

(Adapted from Connelly and others, 2004.)

Table 1. Recognized populations and subpopulations of sage-grouse included in this analysis.—Continued 
14 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 4. Concentrations of strutting males at leks, an indication of the distribution of individuals, populations, and reproductive effort 

across Management Zones (MZ). 
II. Populations, Distributions, Trends, and Natural History 15

Figure 5. Greater Sage-Grouse populations and subpopulations. MZ, Management Zone.
16 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

MZ State and Provinces 

Included

Population Trend Estimates 

1965–2003* (Connelly 

and others, 2004)

Population Trend Estimates 

Based on Annual Rates 

of Change (%) 1965–2007 

(WAFWA 2008)

Population Trend 

Estimates Based on 

Annual Rates of Change 

(%) 1965–2007 (Garton 

and others, 2011)

I MT, WY, ND, SD,

SK, AL

Long-term decline –2.9 –2.9

II ID, WY, UT, CO Long-term decline –2.7 –3.5

III UT, NV, CA Long-term decline –2.2 –10**

IV ID, UT, NV, OR Long-term decline –3.8 –4**

V OR, CA, NV Change statistically undetectable –3.3 –2**

VI WA Long-term decline –5.1 –6.5

VII CO, UT Change statistically undetectable No detectable trend +34**

*

Average annual rate of change was not reported.

**Due to sample inadequacies for the statistical analyses used, only data from 1995 to 2007 could be used.

(Adapted from USFWS, 2010, table 5.)

Table 2. Estimated trends in population size for each sagebrush Management Zone (MZ).

MZ

Minimum Population 

Estimate in 2007 

(number of males)

Percent Change in

Number of Males per 

Lek (1965–2007)

Percent Change of 

Active Leks

(1965–2007)

I 14,814 –17 –22

II 42,429 –30 –7

III 6,851 –24 –16 ***

IV 15,761 –54 –11***

V 6,925 –17** –21**

VI 315 –76 –57

VII 241 –13 –39*

*

1995 to 2007—due to sample sizes, only data from this time period were used.

**1985 to 2007—due to sample sizes, only data from this time period were used.

***1975 to 2007—due to sample sizes, only data from this time period were used.

(Adapted from Garton and others, 2011.)

Table 3. Male sage-grouse minimum population estimates (2007), percent change in number of males per lek, and percent change in 

number of active leks 1965–2007 by Management Zone (MZ).
II. Populations, Distributions, Trends, and Natural History 17

shown to prevent successful movement of individuals between 

populations (Piertney and others, 1998; Oyler-McCance and 

others, 2005a; Fedy and others, 2008).

The rangewide extent of almost all species, including 

sage-grouse, is orders of magnitude larger than the dispersal 

distance of any single individual. In addition, heterogeneity 

in habitat quantity, configuration, and quality creates spatial 

discontinuities in population densities. Consequently, species 

distributions do not consist of a single panmictic population but instead can be best described by a meta-population 

structure having hierarchical levels of connectivity (Weins 

and others, 1993). At larger ecological scales, less frequent 

but longer movements by individuals between populations 

influence rangewide connectivity and are essential for population persistence. The probability that an individual will move 

from one population to another is influenced by the species’ 

life-history strategies, relative densities among populations, 

and the cost to movement. At smaller ecological scales, short 

dispersals characteristic of most individuals result in the 

majority of breeding occurring within a relatively distinct and 

confined area characterized by extensive internal connectivity. 

Importantly, sage-grouse have demonstrated strong site fidelity 

suggesting resistance of individuals to adjust to changing habitat conditions (Berry and Eng, 1985; Fischer and others, 1993; 

Schroeder and Robb, 2003; Holloran and Anderson, 2005; 

Moynahan and others, 2007; Baxter and others, 2008; Doherty 

and others, 2010a; Holloran and others, 2010). Identification 

of these demographically independent populations and defining their boundaries is a fundamental component to managing 

any wildlife species.

In addition to population connectivity, maintaining sufficient levels of genetic diversity is also important for population viability and persistence. Observations of inbreeding 

depression in captive (Lacy and others, 1996) and field populations (Jimenez and others, 1994; Keller and others, 1994; 

Keller and Waller, 2002) and studies of heterozygosity-fitness 

relations (Reed and Frankham, 2003) have led to the realization that loss of genetic variation could affect population 

viability (Gilpin and Soule, 1986; Lacy, 1997). Furthermore, 

observations of wildlife populations that have experienced 

loss of genetic variation due to bottlenecks also support the 

conclusion that such losses can affect population productivity, particularly in lek-breeding birds (Bouzat and others, 

1998) such as sage-grouse. Practices that lead to reduced 

genetic variation, such as establishing populations with only a 

few individuals or allowing populations to remain small and 

fragmented, might have serious consequences for population 

viability. Concerns about effects of inbreeding on demography 

relate to time scales that are relevant to management activities 

(Westemeier and others, 1998; Johnson and Dunn, 2006). On 

a longer time scale, managers must be concerned about loss 

of allelic variation that can affect the ability of populations to 

adapt to new environmental challenges (Allendorf and Leary, 

1986; Frankham, 1995), including enhanced susceptibility 

to parasitic agents or infectious disease such as West Nile 

virus, which has been shown to be a significant threat for 

sage-grouse (Naugle and others, 2004).

Most conservation geneticists promote maintaining large 

effective sizes of well-connected populations to prevent loss of 

genetic variation and possible associated reductions in population viability. Recommendations concerning population sizes 

necessary to prevent adverse genetic consequences vary considerably; there is no general agreement on what appropriate 

minimum numbers are acceptable for long-term management 

goals (Gilpin and Soule, 1986; Simberloff, 1988; Hedrick 

and Kalinowski, 2000; Reed and Bryant, 2000). Most published recommendations of minimum population size are in 

terms of minimum effective size, and these recommendations 

indicate that the number of breeding-age individuals in most 

populations should be at least two to four times larger than the 

minimum effective size. This is particularly relevant for sagegrouse whose effective population size may be much less than 

census size due to their highly skewed mating system.

Sage-grouse need vast expanses of sagebrush habitat 

to meet their seasonal habitat needs (Connelly and others, 

2004; Connelly and others, 2011d). Fundamental to developing conservation objectives for sage-grouse is to identify and 

subsequently design strategies to maintain a set of viable and 

connected populations. Therefore, it is important to know 

(1) the spatial delineation of breeding populations of sagegrouse, (2) how primary populations are interconnected across 

regions of lower population densities and less suitable habitat, 

and (3) the spatial scale and relative importance of landscape 

features that influence gene flow. Currently, an understanding 

of how populations are spatially structured for sage-grouse 

is somewhat limited. The characteristics of gene flow within 

and among populations and what landscape features represent 

barriers to sage-grouse dispersal that are significant enough to 

fragment or isolate populations are largely unknown. Distance, 

topography, or large blocks of unsuitable habitat all potentially 

influence dispersal at local and regional scales. Few studies 

using conventional radio-telemetry techniques or recaptures of 

marked individuals have documented either dispersal distances or landscape features that influence dispersal patterns. 

Considerable money and effort has been spent tracking the 

movement of animals using radio-telemetry and band recoveries for sage-grouse. Although these methods are effective, they 

are limited in the spatial and temporal scale of the questions 

they can address.

A recent model of the rangewide spatial structure of 

sage-grouse based on the mapped distribution of leks delineated numerous small populations interspersed between a 

few large populations and around the periphery of the range 

by clustering leks interconnected within an 18 km (11 mi) 

dispersal distance (fig. 6; Knick and Hanser, 2011). Concern 

over the degree of isolation of the small populations is warranted. Current sagebrush habitats were relatively intact within 

the large populations. Nonetheless, additional habitat loss 

caused by natural or human disturbance could fragment and 

divide these large populations as well as further isolate small 
18 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 6. Spatial connectivity within sage-grouse population structure across the current species’ range. MZ, Management Zone.

18 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse
II. Populations, Distributions, Trends, and Natural History 19

populations whose viability may depend on dispersal from 

neighboring populations. 

A complementary approach to understanding population 

boundaries and movement among populations uses genetic 

methods that allow for assessment over broad spatial extents 

and the measurement of the actual breeding consequences of 

animal movement. In addition to defining populations and 

measuring connectivity, genetic approaches also address many 

other relevant questions including the conservation of genetic 

diversity, the impacts of inbreeding, and the association 

between habitats and genetics. Previous genetic work has provided a coarse-scale examination of the distribution of genetic 

variation across the entire range of sage-grouse using both 

mitochondrial DNA (mtDNA) sequence data and data from 

nuclear microsatellites (Oyler-McCance and others, 2005b). In 

this study, 1,080 samples were collected from 46 populations 

from all U.S. States with populations of sage-grouse and one 

Canadian province (Alberta) spanning the entire range of the 

species (Oyler-McCance and others, 2005b). Overall, OylerMcCance and others (2005b) found the distribution of genetic 

variation showed a gradual shift across the range in both mitochondrial and nuclear datasets. This pattern suggests localized 

gene flow with isolation by distance, for example movements 

common among neighboring populations yet highly unlikely 

across distant portions of the range. A genetic-clustering 

analysis (fig. 7; Oyler-McCance and others, 2005b) revealed 

that unique genetic clusters were comprised of populations 

geographically adjacent to one another, and though most 

genetic clusters consisted of many populations, the smaller, 

more fragmented populations on the periphery of the range (in 

Colorado, Utah, Bi-State in Nevada/California, and Washington) comprised their own clusters, suggesting lower amounts 

of gene flow in these areas (peripheral isolates). These data 

are consistent with previous research on dispersal (Dunn and 

Braun, 1985), suggesting that gene flow is likely limited to 

the movement of individuals between neighboring populations and not likely the result of long-distance movements of 

individuals (across large portions of the range). Their data suggest linkages among neighboring populations and differences 

among distant populations. This raises the possibility that local 

adaptations may exist, and therefore, translocations involving 

neighboring populations rather than geographically distant 

populations are more likely to succeed. 

In addition to estimating levels of connectivity among 

populations, genetic analysis can compare levels of genetic 

diversity and document genetically unique populations. Similar to previous findings, (Benedict and others, 2003), recent 

analyses by Oyler-McCance and others (2005b) revealed 

that the least amount of genetic diversity occurred in the two 

Washington populations (MZ VI), which was likely caused by 

prior habitat loss, isolation and subsequent population decline. 

One population sampled in Utah, Strawberry Valley, was also 

found to have low genetic diversity, likely due to a severe 

genetic bottleneck caused by unnaturally high predation. The 

Bi-State population (MZ III) was found to be genetically 

unique compared to all other populations, and the difference 

was striking. Most individuals (93 percent) in the Bi-State 

population contained novel mtDNA haplotypes not found 

elsewhere across the range. The genetic diversity present in 

the Bi-State population, however, was comparable to (if not 

higher than) most other populations, suggesting the differences 

were not due to a genetic bottleneck or founder event. Nuclear 

data corroborated these data as the Bi-State population was 

significantly different from all other populations and was the 

only population forming its own unique genetic cluster (fig. 7). 

Under the National Greater Sage-Grouse Land Use Planning Strategy, BLM and USFS are designing management 

actions for sage-grouse based on identifying priority areas 

containing the highest densities of breeding birds and their 

seasonal and annual habitats. This approach is intended to 

reduce threats to priority habitat and focus limited conservation resources in regions that have the greatest potential to 

benefit the largest proportion of sage-grouse (Doherty and 

others, 2011c). Complementary to the priority areas, general 

habitat areas will also be identified with objectives related to 

maintaining connectivity, movement, and genetic diversity 

(Bureau of Land Management, 2011a). As a trade-off, energy 

and other development may be proposed within general 

habitat under less restrictive stipulations. However, meeting 

the overall goals for sage-grouse in this approach will rely on 

avoiding the unintended consequence of isolating sage-grouse 

populations within priority areas. Therefore, it is important to 

understand how sage-grouse populations are structured, the 

relation of breeding populations to delineated core areas, and 

how landscape features influence dispersal among core areas. 

The concepts of structural and functional connectivity are 

critical components for guiding conservation actions emphasizing priority areas coupled with identifying and maintaining corridors to facilitate gene flow through general habitat. 

Structural connectivity, the spatial arrangement of habitat and 

environmental variables, is an important first step and is the 

foundation for delineating priority areas. Recent rangewide 

assessments (Connelly and others, 2004; Rowland and others, 

2006; Knick and Connelly, 2011b) have provided extensive 

spatial information on habitats, threats, and conservation 

actions that is necessary for understanding the structural connectivity of habitats (Tischendorf and Fahrig, 2000). These 

data help delineate the spatial patterns of important ecological components for sage-grouse. Ongoing genetic studies that 

incorporate landscape data are attempting to better understand 

functional connectivity, which is based on interpreting the 

spatial arrangement of habitats from a species’ perspective 

(Wiens, 2002). Functional connectivity is far more challenging to study than structural connectivity, but it provides 

information on the processes underlying the patterns. State 

and Federal agencies have the opportunity to influence the 

future form and function of sagebrush landscapes across broad 

regions through resource planning, and sage-grouse population and habitat connectivity are an important consideration 

for this process. Landscape-genetics concepts provide keys to 

developing conservation strategies by identifying population 

strongholds, habitat connectivity, and movement corridors that 
20 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 7. Map of sampling sites for the microsatellite analysis assigned by ‘Structure’ analysis; genetic similarity is implied for 

subpopulations with similar color coding. MZ, Management Zone.
II. Populations, Distributions, Trends, and Natural History 21

facilitate dispersal and gene flow and are, therefore, important 

to sustain population viability. 

Habitat Characteristics and Ecosystem 

Associations 

Sage-grouse is a sagebrush-obligate species that relies on 

a variety of sagebrush dominated communities to meet various needs throughout their life cycle (Patterson, 1952; Braun 

and others, 1976; Connelly and others, 2004; Connelly, 2005; 

Miller and others, 2011). Sage-grouse are closely tied to sagebrush communities and the range of sage-grouse includes at 

least eleven species, or subspecies (as many as 20 identified in 

some States), of sagebrush (Artemisia spp.) that differ in their 

associated plant communities, productivity, resilience, and 

ability to resist disturbance (Miller and Eddleman, 2000; West 

and Young, 2000; Connelly and others, 2004; Knick and Connelly, 2011a). Sagebrush communities comprise diverse plant 

communities that include perennial grasses and forb species 

with composition, structure, and productivity influenced by 

abiotic conditions such as topography, elevation, precipitation, 

and soil (Miller and Eddleman, 2000; Connelly and others, 

2004). The species of sagebrush most commonly associated 

with sage-grouse include Artemisia tridentata ssp. wyomingensis (Wyoming big sagebrush), A. t. ssp. vaseyana (mountain big sagebrush), A.t. tridentata (basin big sagebrush), A. 

arbuscula (low sagebrush), A. nova (black sagebrush), A. 

frigida (fringed sagebrush), and A. cana (silver sagebrush; 

Schroeder and others, 1999; Connelly and others, 2004). The 

distribution of sage-grouse is highly correlated with the distribution of sagebrush across its distribution in North America 

(Schroeder and others, 2004). 

In the spring, during the breeding season, sage-grouse 

males seek out lek sites that are open areas of bare soil, short 

grass steppe, windswept ridges, or exposed knolls in which to 

gather and perform their ritualized mating displays (Patterson, 

1952; Connelly and others, 2004) in order to attract females 

for breeding. The location of active leks is generally known, 

and this information has been used to define MZs, planning 

units, and research designs as discussed throughout this report. 

The timing of lek attendance varies considerably depending 

on snow depth, elevation, weather, and geographic region 

with first attendance ranging from the end of February to early 

April and ending in late May or early June (Eng, 1963; Schroeder and others, 1999; Aldridge, 2000; Hausleitner, 2003; 

Connelly and others, 2004). Such lek sites are typically open 

areas (low-shrub cover) located in the midst of denser shrub 

stands, which together provide the necessary combination of 

visibility, protection, food, and thermal regulation (Connelly 

and others, 1981; Connelly and others, 2000b; Connelly and 

others, 2011b). Females visit leks for copulation and then can 

travel more than 20 km (12.5 mi) for nesting afterward (Connelly and others, 2000c), yet distances from the lek to nesting 

areas are highly variable. Five studies that included 301 nest 

locations revealed that the distance from lek of capture to 

nesting areas averaged from 3.4 km to 7.8 km (2.1–4.8 mi; 

Schroeder and others, 1999). Nesting areas tend to be surrounded by sagebrush with an understory of native grasses and 

forbs with ample vertical and horizontal structure to support a 

diversity of insect prey, provide cover, as well as herbaceous 

forage for pre-laying and nesting hens (Gregg, 1991; Schroeder and others, 1999; Connelly and others, 2000b; Connelly 

and others, 2004; Connelly and others, 2011b). Vegetation 

characteristics of successful nesting areas have been described 

with details not provided here (Connelly and others, 2000c). 

Egg laying and incubation typically occur 3–4 weeks 

after peak lek attendance followed by brood-rearing in late 

spring and early summer (Schroeder, 1997; Aldridge and 

Brigham, 2003b; Hausleitner, 2003; Connelly and others, 

2004). Broods are typically found in areas near nest sites for 

the first 2–3 weeks after hatching (Connelly and others, 2004). 

Such habitat needs to provide adequate cover and areas with 

sufficient forbs and insects to ensure chick survival in this life 

stage (Connelly and others, 2004). As the chicks get older, 

sage-grouse tend to move into more moist areas (streambeds 

or wet meadows) because as herbaceous vegetation dries 

out, wetter areas provide more forbs and insects for hens and 

their chicks (Schroeder and others, 1999; Connelly and others, 2000a). Hens without broods and male sage-grouse use 

wetter areas that are close to sagebrush cover in late summer 

(Connelly and others, 2004).

Beginning at the end of summer, and extending into fall 

and winter, the diet of sage-grouse shifts to one comprised 

solely of sagebrush (Schroeder and others, 1999). During this 

time, sage-grouse also depend on sagebrush for cover. Habitat 

selection at the sagebrush-stand level during winter months is 

driven by the depth of snow (Patterson, 1952; Hupp, 1989), 

the availability of sagebrush above the snow (Connelly and 

others, 2004), and topographic patterns (Beck, 1977; Crawford 

and others, 2004) that create localized habitats providing cover 

and forage. Because use and availability of these seasonal 

habitats are spread across a given landscape, sage-grouse 

require vast areas of contiguous sagebrush to meet their needs 

on an annual basis (Patterson, 1952; Connelly and others, 

2004; Connelly and others, 2011d; Wisdom and others, 2011). 

Sagebrush-vegetation types are strongly determined by 

environmental limitations and gradients driven primarily by 

temperature and precipitation patterns (Miller and others, 

2011). The sagebrush-steppe occurs in the northern portion 

of the range of sage-grouse from British Columbia and the 

Columbian Basin in the northwest; south through the northern 

Great Basin and Snake River Plain; and east into southwestern 

Montana, the Wyoming Basin, and northern Colorado Plateau 

(fig. 8). In this type, sagebrush typically co-dominates with 

perennial bunchgrasses (Miller and others, 2011). The second 

major type, Great Basin sagebrush, is found south (and west) 

below the polar-front gradient where the herbaceous component contributes a smaller portion of the total plant cover 

(Miller and Eddleman, 2000) due to hydrologic patterns. Thus, 

in this type, sagebrush is frequently the canopy dominant with 

little understory (Miller and others, 2011). The Great Basin 
22 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 8. Seven major sagebrush biomes, including the southern Great Basin types (Southern, Northern, and Colorado 

Plateau), northern sagebrush-steppe (Snake River Plain, Wyoming Basin, and Columbia Basin) and northern mixed prairies. 

MZ, Management Zone.
III. Characterization of Important Threats and Issues 23

sagebrush community type extends from the Colorado Plateau 

west across Nevada and Utah and into California (Miller and 

others, 2011). A third major sagebrush-vegetation type, the 

mixed shrubland, occurs in the Bighorn Basin in north-central 

Wyoming. A fourth type includes the mixed big sagebrush and 

silver sagebrush-grasslands (including portions of the Northern Prairies) that are found in eastern Montana and Wyoming 

(Miller and others, 2011); these support sage-grouse populations primarily within A. cana and A. filifolia associations.

Multiscale Habitat Selection 

Sage-grouse are currently estimated to occupy 165 million acres (668,000 km2

) across the Western United States 

and Canada (Knick and Connelly, 2011a), and this range 

encompasses tremendous variability in habitat conditions, 

anthropogenic activities, and grouse populations. Development of comprehensive monitoring approaches lead to formal 

recognition that habitat selection assessments are needed to 

utilize approaches that address multiple spatial scales to represent selection processes of the animals (Connelly and others, 

2003b; Connelly and others, 2011d; Stiver and others, 2010). 

The first-order (1) is the geographic range and defines the 

sage-grouse population of interest, and within this geographic 

range (2) characterization of the second-order hinges on large, 

relatively intact regions of habitat identified using subpopulation distributions (for example, geographic connections among 

leks or regional population connectivity using genetics) to link 

habitats to use. The third-order (3) requires refinement from 

broad habitat delineations by specifying seasonal habitats (for 

example, nesting habitat), patch selection, and migration habitats. Finally, assessment can be made of fourth-order selection 

(for example, daily site selection and behavioral observations) 

by (4) quantifying food and cover attributes and foraging 

behavior at particular sites. In practice, selection of food items 

is nested within selection of feeding site because selection of 

a particular site determines the array of food items available 

to be selected; importantly, habitat value and use will best be 

determined using a combination of these characteristics (not 

one alone). To accurately characterize sage-grouse habitat 

selection for a given population at the first- and second-orders, 

or landscape spatial scales, the migratory nature (seasonal 

movements) of the population must be well understood (see 

Connelly and others, 2000), and this may include very large 

areas on an annual basis. It has been suggested that migratory populations may range across hundreds of square miles 

(Connelly and others, 2003b) with individual movements up to 

145 km (90 mi; Smith 2012). 

The relative importance of a particular seasonal habitat may be dictated by quantity (for example, critical winter 

habitat may represent a small proportion of the available 

sagebrush habitats in the area), quality (this may be realized 

when potential early brood-rearing habitats are widespread, 

for example, but suboptimal herbaceous cover reduces value 

and use of some areas), and juxtaposition (as an indication of 

the necessary proximity of suitable early brood-rearing sites 

and suitable nesting sites), which together describe relevant 

local-scale spatial heterogeneity within broadly suitable and 

available habitats. It is also likely that movement corridors 

between seasonal sites have particular value for sage-grouse 

as seasonal habitats (distinct from origination and destination habitats), especially for migratory populations moving 

long distances between seasons (Connelly and others, 2003). 

Although the optimal proportions of distinct seasonal habitats 

required on a landscape for productive sage-grouse populations are unknown, sage-grouse productivity is generally 

increased if individuals are able to space themselves widely 

across the available landscape allowing them full advantage 

of variations in land and habitat to satisfy their cover, forage, 

solitude, and migratory needs (Holloran and Anderson, 2005).

III. Characterization of Important

Threats and Issues 

The USFWS 12-month finding, in agreement with recent 

reviews, research, and analyses provided by the science and 

management communities (Federal Register 50 CFR Part 

17; FWS-R6-ES-2010-0018; Connelly and others, 2004; 

Knick and Connelly, 2011b), recognized a range of important 

influences on sage-grouse populations and their successful 

conservation. These common threats and issues fall into five 

main categories, which were recognized by USFWS in the 

published findings—habitat change (Factor A), over-utilization 

(Factor B), disease and predation (Factor C), chemical poisoning (Factor E), and policy and land use (Factor D)—which 

may vary in relative importance among MZs but are inclusive 

and representative of the suite of threats and issues across the 

species’ range. (Factors A-E were originally characterized in 

the USFWS findings report; we reorganized our treatment 

of these topics [Factors A, B, C, E, then D] to consolidate 

conceptually related topics. The organization in this document 

does not exactly parallel the USFWS Federal Register document, but all topics in the findings report are addressed here.) 

Each of these topics are addressed in the following pages, with 

particular attention paid to issues identified by USFWS and 

others that contribute to direct or indirect impacts on sagegrouse populations. With this broad outlook, it is important to 

recognize that though over-utilization, disease and predation, 

and chemical poisoning are recognized as having direct effects 

(such as mortality) on sage-grouse populations—and the 

effects of these factors may be the principal cause of population declines in local areas during specific years, for example 

West Nile virus outbreaks—the impact of these factors on 

rangewide population sustainability are considered relatively 

small compared to indirect effects on populations via habitat 

degradation, policy limitations, and competing land uses. 

Habitat change (Factor A), which represents a suite of changes 

in both local conditions (implications for forage, cover and 

nest quality, for example) as well as regional landscape patterns (implications for habitat availability, connectivity, and 
24 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

isolation, for example), includes the bulk of factors identified 

in previous research and litigation as affecting sage-grouse 

populations. Despite research and expertise that address the 

role of these factors in habitat condition and function of the 

sagebrush ecosystem, causal connections that precisely relate 

these factors to population responses are not known in many 

cases (and likely cannot be consistently and accurately translated as simple causal mechanisms); this is often the case with 

complicated relations. Thus, many of the following sections 

outline connections between activities, patterns, and processes 

recognized as threats to the condition (measured, theoretical, 

and desired) of the sagebrush ecosystem and the likely, or 

expected, response of local sage-grouse populations to these 

influences, as presented in the literature. These discussions and 

diagnoses may recognize local population details; however, 

detailed local distinctions are largely beyond the scope of this 

effort. The broad-scale patterns and associations occurring 

rangewide and regionally, which are summarized here, will 

benefit from incorporation with detailed knowledge of local 

managers, including unpublished reports and similar locally 

explicit references, when translating these regional patterns 

into local conservation planning. Therefore, this summary and 

spatial analysis will inform and enhance local understanding 

by providing broad-scale data summary and interpretation 

helping to put local conditions and issues into context and 

thereby informing the process of developing complete and 

comprehensive land and resource management planning. 

This distinction (local detail versus regional perspective) 

is consistent with the multiple-scale approach to management 

and conservation being applied here. This report is focused 

on providing “global” (first order) and “regional” perspectives (second order); much of the information provided herein 

is summarized from research on individuals and populations 

(third and fourth order). Local data, and associated local decisions, are critically important to conservation and management success, but they cannot be accurately represented here 

(without expanding the scope and effort); local perspectives 

and decisions need to be informed by local professionals. 

Information on sage-grouse has been accumulated from many 

different populations residing in different habitats, and current 

knowledge is based on combining these disparate sources and 

extrapolating understanding derived from specific populations and circumstances to establish rangewide consistencies 

(Crawford and others, 2004). Confounding factors across all 

populations and analytical units include different causes of 

mortality in different areas, differences between migratory and 

resident populations, temporal and spatial differences in habitat conditions, nuances and variability in population estimates, 

and differences in cycling rates and current position relative to 

long-term and short-term trends (Fedy and Doherty, 2011). 

Recent developments in wildlife conservation have 

included a shift from project-level to landscape-level perspectives in conservation planning. However, effective management of a species of wildlife under this paradigm typically 

requires the consideration of several scales. Sage-grouse are a 

wide-ranging species, and large landscapes need conservation 

to maintain the species (Connelly and others, 2004; Connelly and others, 2011d). However, habitat degradation—one 

of the overriding mechanistic factors resulting in population 

declines—will have to be handled at much smaller scales to 

restore the condition and function of rangelands.

Factor A: Habitat Change 

Sage-grouse populations typically occupy habitats with a 

diversity of species and subspecies of sagebrush interspersed 

with a variety of other habitats (riparian meadows, agricultural 

lands, grasslands, and sagebrush habitats with some conifer 

or deciduous trees); these habitats are usually intermixed in a 

sagebrush-dominated landscape and are often used by sagegrouse during certain times of the year (seasonally) or during 

certain years, for example, a winter with above-normal snowpack (Connelly and others, 2011d). The natural variation in 

vegetation, the dynamic nature of sagebrush habitats, and the 

variation in the habitats selected by sage-grouse across a landscape imply that characterizing habitats using a single value 

or narrow range of values, for example, 15- to 25-percent 

sagebrush-canopy cover in breeding habitat (Connelly and 

others, 2000c), is insufficient to describe sage-grouse habitat 

requirements. The differing seasonal habitat requirements of 

sage-grouse dictate that multiple vegetation attributes, across 

the landscape and in particular sites, are important, reinforcing 

emphasis that combinations of shrub overstory and herbaceous 

understory, which are both important as habitat components 

during different seasons, are important in combination and 

across scales (Connelly and others, 2011d). Although animals 

may have different requirements and selection behaviors in 

different seasons, seasonal habitats may overlap; for example, 

winter habitat may also provide brood-rearing habitat in 

some populations, whereas others may travel great distances 

between seasonal habitats. Interspersion and juxtaposition of 

the differing cover types used by sage-grouse on an annual 

basis within the range of a local population will greatly influence the effectiveness of the landscape to provide quality 

sage-grouse habitat (Connelly and others, 2011d). 

Human alterations, uses, and impacts coupled with 

natural variability (for example, drought) have changed the 

extent, condition, and distribution of sagebrush-steppe and the 

ecosystem services this biome provides (Meinke and others, 

2009). Current sage-grouse range is estimated to be 56 percent 

of historic (pre-European settlement) distribution (Stiver 

and others, 2006a). Disrupted disturbance regimes, degraded 

or depressed native species, and dominance by introduced 

noxious plants have moved many of these systems toward, or 

beyond, critical thresholds from which restoration is difficult 

or excessively time-consuming and expensive (Meinke and 

others, 2009). Three of the fundamental characteristics of the 

sagebrush biome that have been altered from presettlement 

conditions include (1) the total area of sagebrush shrubland 

has been reduced; (2) the composition and structure of the 

vegetation and soils in sagebrush communities have been 
III. Characterization of Important Threats and Issues 25

changed, including increased abundance and performance of 

invasive species and decreased abundance and performance 

of native species; (3) fragmentation created by roads, power 

lines, fences, energy developments, urbanization, and other 

anthropogenic features isolate populations by restricting 

movements or degrading habitat (Connelly and others, 2004). 

For example, 75 percent of the shrub steppe growing on deep 

soils has been converted to agricultural croplands (Connelly 

and others, 2004), and intense historic land use (especially 

livestock grazing) in the late 19th and early 20th centuries 

reduced the dominance of native grasses, trampled microbiotic crusts, and encouraged expansion of Eurasian grasses 

(Anderson and Inouye, 2001; Ponzetti and others, 2007; Root 

and McCune, 2012). Therefore, long-term conservation of the 

species as well as sagebrush habitats may, simply stated, hinge 

on adaptation, reclamation, and recovery of native ecosystems 

from historic land uses and former practices.

The combination of natural variability (for example, 

drought) and a legacy of multiple human land uses with various but widespread impacts has induced changes in the extent, 

condition, and distribution of sagebrush ecosystems and the 

biological services they provide. Currently, few intact sagebrush ecosystems are in the condition they were in historically 

(reference conditions), which influences habitat function, and 

consequentially, the distribution and health of wildlife in the 

region (Connelly and others, 2004). To better address cumulative effects of multiple (different) land uses, and to begin to 

account for indirect impacts (besides direct habitat removal, 

for example), a combination of factors may be combined to 

estimate a “human footprint” providing an index to assess and 

compare levels of use and potential impacts (Leu and Hanser, 

2011). The human-footprint index considered here indicates 

the spatial accumulation of effects due to anthropogenic 

features—including human habitation, highways and roads, 

railroads, power lines, agricultural lands, campgrounds, rest 

stops, landfills, oil and gas developments, and human-induced 

fires—on a landscape expressed on a 1 to 10 scale (Johnson 

and others, 2011; Leu and Hanser, 2011). The human footprint is most intense at low elevations near valley floors and 

may have disproportionate effect on sage-grouse populations 

reliant on these habitats during critical portions of the year 

(Leu and Hanser, 2011). Across the sage-grouse range, lek 

count declines were measurable when human-footprint scores 

exceeded “2” at lek sites and when scores exceeded “3” within 

either 5 km or 18 km (3.1 or 11.2 mi) of a lek (Johnson and 

others, 2011). Notably, these values (2 and 3) are toward the 

low-intensity end of this distribution. In the following pages, 

six sections summarize information regarding contributions 

of the human footprint to sage-grouse habitat conditions: (A1) 

fragmentation and connectivity, (A2) agricultural conversion, 

(A3) urbanization and human habitation, (A4) general infrastructure, including highways and improved surface roads, 

railroads, transmission lines and power lines, communication 

towers, and fences, (A5) energy development and associated 

infrastructure, and (A6) fire.

A1. Habitat Fragmentation and Connectivity

Sage-grouse populations generally rely on large, interconnected expanses of sagebrush to accommodate local 

migrations and access to seasonal habitats distributed within 

their inhabited range (Connelly and others, 2004), and “fragmentation” represents the dissection of large expanses via 

various mechanisms. Conclusive, consistent data establishing 

minimum sizes of sagebrush-dominated landscapes necessary 

to support viable populations of sage-grouse are unavailable 

(Connelly and others, 2011d). However, some quantitative 

indications exist, for example sage-grouse populations in 

Idaho used an annual range of at least 683,000 acres (2,764 

km2

; Leonard and others, 2000). Research in Wyoming and 

Montana suggested that a sagebrush-dominated landscape 

77,600 acres (314 km2

) in size may provide the area necessary to maintain breeding habitat around a given lek (Doherty 

and others, 2008). The size of a landscape needed to support 

breeding habitats of an interspersed population (for example, 

an area with multiple leks spaced less than 6.2 miles [10km] 

apart) may exceed 247,000 acres (1,000 km2

; Doherty and others, 2008). Investigations from Idaho and Wyoming suggest 

that relatively large blocks of sagebrush habitat (>9,900 acres 

[4,000 ha]) are critical to successful reproduction and overwinter survival (Leonard and others, 2000; Walker and others, 

2007a). Mean sagebrush patch size within an 18 km radius 

(250,000 acres [1,018 km2

]) was more than nine times as large 

in occupied versus extirpated sage-grouse range; sagebrush 

patch size in occupied range averaged 10,300 acres (4,173 ha; 

Wisdom and others, 2011). Based on natural geographic patterns, it has been suggested that sage-grouse may have adapted 

to a scale of natural fragmentation in sagebrush habitats 

organized at 2.8–5.6 mi (4.5 to 9 km; Leu and Hanser 2011); 

research on selection behavior indicated similar, emergent 

patterns based on spacing between leks (nearest-neighbor distances of 0.36 mi [5.9 km ]), mean lek to nest movements (3.2 

mi [5.1 km ]), and nest to summer range movements generally 

limited to less than 6.2 mi (10 km; Fedy and others, 2012), 

supporting this contention. 

The scale of the landscape used by sage-grouse changes 

throughout seasons and may differ between populations based 

on available habitats. Strong site fidelity of sage-grouse for 

established nesting habitat (Fischer and others, 1993; Holloran 

and others, 2005; Thompson, 2012) and suggested for other 

seasonal habitats (Berry and Eng, 1985; Thompson, 2012) 

indicates that the “landscape” targeted by an individual female 

during different life-history stages may be relatively small. 

The overall landscape requirements for an individual would 

be the conglomeration of these seasonal habitats combined 

with the necessary migration corridors (the length of these 

corridors will be different between and within populations 

depending on the local landscape as much as on the birds). 

Thus, the landscape required by an individual is a combination of the seasonal habitat requirements on a relatively small 

scale, the spatial distribution of those seasonal habitats, and 

the habitats required to move between those seasonal ranges. 
26 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Distances between consecutive-year nests of 0.46 mi (740 m) 

on average suggest a female will nest (repeatedly) within a 

425-acre (172-ha ) area during its lifetime (Fischer and others, 

1993; Holloran and others, 2005). Additionally, a high degree 

of fidelity of female offspring to their natal home ranges has 

been observed (for example, yearling females nesting close 

to their natal nest) suggesting that family groups of females 

may inhabit relatively distinct areas (Thompson, 2012). Based 

on cumulative mean daily movements of sage-grouse broods 

between hatch and 2-weeks post-hatch (Gregg, U.S. Fish and 

Wildlife Service, unpub. data, May 2000 – July 2003; received 

July 2010), early brood-rearing tends to occur within 2.9 mi 

(4.6 km ) of the nest. Sage-grouse generally move ≤6.2 mi 

(10 km) from nests to summer range—but may travel as far as 

50 mi (82 km; Fedy 2012)—and remain in relatively distinct 

locations upon reaching summer range (Connelly and others, 

2011d). In contrast, a majority of sage-grouse move >6.2 mi 

(10 km) from summer to winter locations with movements of 

up to 90 mi (145 km ) documented (Smith, 2013). Fidelity to a 

specific region does not appear to be as strong for sage-grouse 

during winter, and populations have been documented traveling up to 31 mi (50 km ) in search of exposed sagebrush after 

severe storm events in Wyoming (Smith, 2013). Movements 

from spring to summer range and from summer to winter 

range generally occur along sagebrush-dominated habitats 

(Jensen, 2006; Connelly and others, 2011d; Smith, 2013); 

however, sage-grouse can traverse or circumvent unsuitable 

habitats between seasonal ranges (Bush, 2009). 

In addition to the size of selected habitat patches, lek 

persistence is strongly related to lek connectivity, which is a 

measure of the relation between each lek with the maintenance 

of a regional population network with active dispersal and 

genetic mixing among subpopulations (Knick and Hanser, 

2011). Centrally located, large lek sites have greater importance and metapopulation implications, whereas abandoned 

leks have lower connectivity importance (Knick and Hanser, 

2011). Dispersal distances reported in the literature were 

compiled and combined to establish the connectivity scale; 

reported dispersal distances range from 4.6 to 6.6 mi (7.4-10.6 

km ) for males, 5.5 to 8.1 mi (8.8-13.1 km) for females, and 

distances of 17 mi (27.6 km) are within the range of variation 

(Knick and Hanser, 2011). Gene flow in sage-grouse populations is likely limited to the movement of individuals between 

neighboring populations and not likely the result of longdistance movements of individuals across large portions of 

the species’ range (Oyler-McCance and others, 2005b). Thus, 

regional connectivity among leks represents a fundamental 

source of genetic re-combination and metapopulation structure 

that supports the long-term viability of the species. 

Fragmentation in general results in a landscape that 

consists of remnant areas of native habitats surrounded by 

a matrix of non-native and typically unsuitable habitats, for 

example developed or cultivated lands. Fragmentation generally begins to have significant effects on wildlife when suitable 

habitat becomes less than 30 to 50 percent of the landscape; at 

lower levels of suitable habitat, the distances between remnant 

patches of native habitat increase exponentially, and spatial 

arrangement becomes the critical factor determining success 

of dispersers finding and using suitable areas (Connelly and 

others, 2004). Research on fragmented landscapes has focused 

primarily on the biogeographic consequences of the creation 

of habitat “islands,” which provides little practical value to 

managers (Saunders and others, 1991). According to Saunders 

and others (1991), management of fragmented ecosystems 

has two basic components: (1) management of the internal 

dynamics of remnant habitats, or managing the natural system; 

and (2) management of the external influences of non-native 

areas on these remnant patches. Therefore, management of 

fragmented landscapes requires integration across land ownership with an approach that incorporates several remnant areas 

managed as an inclusive system to provide the habitats and 

resources needed by the sage-grouse population inhabiting 

the area.

A2. Conversion to Agriculture 

One of the fundamental characteristics of western landscapes, which have been altered from pre-settlement conditions, includes a reduction in the total land area dominated 

by sagebrush (Connelly and others, 2004). Development 

of vegetation and soil using clearing, tillage, and irrigation 

(among other practices including seeding, application of 

fertilizers, pesticides, and herbicides) results in long-term 

conversion of native sage-grouse habitats to sustained human 

uses (obviously agriculture, but also subdivisions and exurban 

developments in portions of all MZs). Cultivated agriculture, primarily cropland, covers more than 56.8 million acres 

(230,000 km2

; 11 percent) of the total land area within the 

estimated, historic distribution of sage-grouse, including a 31 

mi (50km ) buffer (Knick and Connelly, 2011a). Agriculture 

is defined as predominantly cropland, or lands that have been 

converted for the production of foods and goods (Knick and 

Connelly, 2011a). The primary agricultural regions in the 

sagebrush biome include central Washington and northern 

Oregon, the Snake River Plains of southern Idaho, northern 

Utah, northern Montana, southern Alberta, southern Saskatchewan, and western North Dakota (Connelly and others, 2004). 

Thus, agricultural lands are widespread across the range of 

sage-grouse (table 4, fig. 9). Approximately 4.4 million acres 

17,800 km2

; 3.04 percent) of designated sage-grouse habitat has been converted to crops throughout the range of the 

species, with approximately 261,400 acres (1,050 km2

; 2.25 

percent) of priority habitats and 3.1 million acres (12,500 km2

; 

8.90 percent) of general habitats converted in MZ I, the MZ 

most influenced by agriculture. Indirect effects to sage-grouse 

of crop lands (estimated as effects on sage-grouse populations 

due to habitat alterations rather than direct mortality) were 

assessed using the spatial foraging scale of sage-grouse avian 

predators, which may be attracted to agricultural lands (6.9 

km [4.3 mi]; Boarman and Heinrich, 1999; Leu and others, 

2008) to summarize the influence area. Based on this estimate, 

agricultural lands influence a majority (approximately 84.2 
Table 4. Summary of the direct and indirect influences of agricultural lands* (crops, tillage, and similar, not open range) across Management Zones 

preliminary priority and preliminary general habitats (PPH and PGH, respectively). 

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

6.9 km Indirect 

Influence1

(acres)

Direct 

Footprint1

(%)

Relative 

Influence2

(%)

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

6.9 km Indirect 

Influence1

(acres)

MZ I–GP 11,636,400 261,400 11,558,300 2.25 99.33 34,663,000 3,084,100 34,619,100 

BLM 2,994,300 6,600 2,944,300 0.22 25 4,524,900 17,700 4,503,800 

Forest Service 292,400 600 292,400 0.21 3 515,300 1,000 515,300 

Tribal and Other Federal 219,700 1,300 219,700 0.59 2 2,427,700 534,900 2,427,800 

Private 7,132,500 247,400 7,113,800 3.47 62 24,682,800 2,436,900 24,664,400 

State 995,600 5,400 986,300 0.54 9 2,498,400 93,300 2,494,100 

Other 1,900 0 1,900 0.00 0 13,900 300 13,900 

MZ II and VII–WB & CP 17,476,000 113,000 14,711,100 0.65 84.18 19,200,200 402,300 15,046,400 

BLM 9,021,200 2,100 7,091,200 0.02 48 9,012,500 3,200 6,324,600 

Forest Service 162,000 0 124,100 0.00 1 452,500 300 407,400 

Tribal and Other Federal 784,000 1,400 701,900 0.18 5 1,354,600 5,200 1,252,100 

Private 6,233,900 106,100 5,627,900 1.70 38 7,394,800 385,900 6,194,900 

State 1,244,800 3,300 1,135,900 0.27 8 979,800 7,700 861,400 

Other 30,100 100 30,100 0.33 0 6,000 0 6,000 

MZ III–SGB 10,028,500 80,000 8,086,800 0.80 80.64 3,970,100 4,600 2,803,800 

BLM 6,309,400 3,800 4,679,000 0.06 58 3,199,800 1,000 2,191,500 

Forest Service 1,236,200 400 1,065,000 0.03 13 356,200 0 243,300 

Tribal and Other Federal 260,800 2,100 246,000 0.81 3 29,100 0 13,000 

Private 1,836,200 72,900 1,720,100 3.97 21 384,800 3,500 355,700 

State 385,900 800 376,500 0.21 5 200 0 200 

MZ IV–SRP 21,930,600 72,300 18,309,700 0.33 83.49 10,958,500 257,400 9,762,400 

BLM 13,710,700 14,800 10,960,600 0.11 60 4,928,200 14,500 4,227,900 

Forest Service 1,613,800 900 1,452,800 0.06 8 1,113,500 1,800 1,009,300 

Tribal and Other Federal 633,600 500 573,300 0.08 3 522,500 1,800 478,200 

Private 4,890,200 55,200 4,404,300 1.13 24 3,516,742 233,600 3,272,000 

State 1,019,373 800 855,800 0.08 5 846,200 4,400 743,600 

Other 62,900 200 62,800 0.32 0 31,400 1,300 31,400 
Table 4. Summary of the direct and indirect influences of agricultural lands* (crops, tillage, and similar, not open range) across Management Zones 

preliminary priority and preliminary general habitats (PPH and PGH, respectively).—Continued Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint1 (acres) 6.9 km Indirect Influence1 (acres) Direct Footprint1 (%) Relative Influence2 (%) SG Habitat (acres) Direct Footprint1 (acres) 6.9 km Indirect Influence1 (acres) 

MZ V–NGB 7,097,200 6,300 4,711,300 0.09 66.38 5,808,000 58,300 4,948,800 

BLM 5,117,500 300 3,333,900 0.01 71 4,196,700 700 3,435,400 

Forest Service 62,200 0 60,800 0.00 1 114,900 0 104,700 

Tribal and Other Federal 717,100 0 223,400 0.00 5 101,800 300 76,900 

Private 798,000 3,000 696,300 0.38 15 1,199,000 55,700 1,155,900 

State 64,900 0 60,200 0.00 1 115,800 400 96,100 

Other 337,500 2,900 336,700 0.86 7 79,800 1,200 79,800 

*Data Source: National Agriculture Statistics Service Cropland Data Layer 2012. 1Direct footprint is the co-location of agricultural lands within the designated habitat boundaries, and indirect influence is inferred by applying an effect buffer to the features a

Indirect influence distance derived from foraging distances of predators (Boarman and Heinrich, 1999; Leu and others, 2008). 2For each MZ, these were calculated as the percent of the particular sage-grouse habitat type influenced by the indirect impact of the threat. For management entities within a calculated as the percent of the total indirect impact in the management zone represented by that management entity; that is, the relative area of indirect influence among manage
III. Characterization of Important Threats and Issues 29

Figure 9. Overlap of agricultural land development, potential indirect effects of agriculture, and preliminary priority habitats (PPH) and 

preliminary general habitats (PGH) for sage-grouse. MZ, Management Zone.
30 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

percent) of priority habitats throughout the species’ range. 

Although little BLM land has been directly converted, this 

approach suggests that BLM administers approximately 50 

percent of the priority habitats influenced by agriculture. Areas 

converted to croplands are generally those with deeper, loamy 

soils that are able to be irrigated while sagebrush remains in 

arid areas where soils and topography are limiting to crops; 

agriculture has replaced 75 percent of the shrub steppe in deep 

soils but only 15 percent in shallow soils (Connelly and others, 

2004). Summary analyses indicate that though agricultural 

conversion is widespread across and within MZs, current overlap with PPH and PGH designations vary among MZs, which 

will help differentiate priorities among management entities 

within each MZ (table 4).

Conversion of sagebrush to agriculture can influence the 

ability of sagebrush-dominated landscapes to support sagegrouse through habitat loss and fragmentation (Connelly and 

others, 2004). Isolation of shrub steppe habitats increased, 

mean patch size decreased, and number of patches increased 

with habitat conversion to agriculture in Washington (Connelly and others, 2004). Agricultural development can also 

influence sage-grouse by providing access to sagebrush habitats for predators such as domestic cats, red fox, and corvids 

(Connelly and others, 2004).

In a comparison of currently occupied versus unoccupied 

sage-grouse range (see Schroeder and others, 2004), estimates 

indicated that sage-grouse were extirpated from areas of their 

range when the proportion of a 735,000 acre (2,975 km2

) 

area in cropland exceeded 25 percent (Aldridge and others, 

2008). A similar analysis of occupied versus unoccupied range 

reported areas where sagebrush cover was <27 percent (within 

a 251,500 acre [1,018 km2

] search area) had a high probability 

of sage-grouse extirpation. Areas with >50 percent sagebrush 

cover had high probabilities of sage-grouse persistence, and 

extirpated range contained approximately three times more 

area in agriculture compared to occupied range (Wisdom and 

others, 2011). In Idaho between 1975 and 1992, declines in 

the mean number of males per lek were strongly correlated to 

increases in the amount of land converted to agriculture, which 

increased 74 percent in the region during this period. The 

proportion of sagebrush habitat (positive effect) and the proportion of tillage agriculture (negative effect) within 4 mi (6.4 

km ) best explained lek persistence in northeastern Wyoming 

(Walker and others, 2007a). The percentage of cultivated land 

within 2.5 mi (4 km ) of active leks in North Dakota was lower 

than that around inactive leks, and the proportion of cultivated 

land (area of cultivated/area of noncultivated) was greater 

within a region of the State historically occupied, but currently 

not occupied, compared to a region where sage-grouse still 

occurred (Smith and others, 2005).

A comparison of treatments in Wyoming, Montana, and 

Colorado found that eliminating ≥16 percent of the sagebrushdominated area in a landscape closely associated with a group 

of leks either through plowing or herbicide spraying was 

correlated with a 50 to 100 percent reduction in the number 

of males occupying the leks (Swenson and others, 1987). 

A similar study suggested greater sensitivity with observed 

reduction in rangewide sage-grouse lek trends when agricultural land use exceeded 2.5 percent of the area within a 3.1 

mi (5 km radius (or 1.5 percent of the area within an 11.2 mi 

[18 km] radius); trends in lek counts stabilized as the percent 

of agricultural land increased beyond these proportions, but 

few leks occurred in areas where the proportion of agricultural 

land exceeded 50 percent (Johnson and others, 2011). Conversion of 30 percent of the sagebrush-dominated winter habitats 

within a focused 50,000 acres (202 km2

) area in Montana by 

plowing and conversion to cropland resulted in a 73 percent 

decline in the number of breeding-male sage-grouse on leks 

in the area relative to controls (Swenson and others, 1987). 

In southern Canada, nesting sage-grouse avoided areas with a 

high proportion of anthropogenic-edge habitats (borders with a 

non-natural edge, such as cropland), and broods avoided areas 

close to cultivated cropland (Aldridge and Boyce, 2007).

The sage-grouse habitat management guidelines (Connelly and others, 2000c) recommend that a minimum of 80 

percent of nesting, early brood-rearing, and winter habitats 

are dominated by a sagebrush overstory; for example, if 20 

percent of the sagebrush habitats used by a population of sagegrouse are eliminated through a prescribed fire, these areas 

need to regrow and provide sagebrush cover useful for sagegrouse prior to additional treatments. The research presented 

here suggests that this guideline may be most appropriate for 

short-term habitat treatments (for example, vegetation and 

fuel treatments). Available research suggests (1) sage-grouse 

populations may become extirpated when the proportion of a 

landscape permanently converted from sagebrush to agriculture exceeds 25 to 27 percent, (2) substantial declines in lek 

counts may occur when this proportion exceeds 16 percent, 

and (3) lek-count declines may occur when the proportion is 

as low as 1.5 to 2.5 percent of the landscape. 

A3. Urbanization 

Low densities of indigenous peoples in western North 

America (estimated range from one person per 1,500 acres 

[6 km2

] to as low as one person per every 22,000 acres [90 

km2

] in the Great Basin) probably limited their impact on the 

biophysical landscape, although their activities for hunting, 

gathering, and burning may have been significant locally 

(Connelly and others, 2004). Ultimately, settlement by 

Europeans in sagebrush habitats had a much greater effect on 

transforming or converting habitats and altering disturbance 

regimes and animal communities than behaviors exerted by 

the low densities of indigenous people (Connelly and others, 

2004). Human populations have grown and expanded during the past century, primarily in the western portion of the 

sagebrush biome. Human populations in sagebrush habitats 

increased between 166 and 666 percent between 1920 and 

2000 and between 19 and 31 percent between 1990 and 2000; 

the amount of uninhabited area (0 residents/km2

) within the 

Great Basin decreased from 22.2 million acres (90,000 km2

) 

in 1990 to <3 million acres (12,000 km2

 ) in 2004 (Knick and 
III. Characterization of Important Threats and Issues 31

Connelly, 2011a). Although urbanized areas occur throughout 

the range of sage-grouse, the direct footprint is relatively small 

with approximately 792,700 acres (3,200 km2

; 0.56 percent) 

of sage-grouse habitat directly converted to urbanized areas 

(table 5, fig. 10). Preliminary priority habitats in Utah in 

particular, and to a lesser degree priority habitat in MZs II and 

VII, have a higher urbanized footprint than the remainder of 

the species’ range. Indirect impacts of urban areas—estimated 

as the spatial foraging scale of avian predators that may be 

attracted to urban areas (4.3 mi [6.9 km]; Boarman and Heinrich, 1999; Leu and others, 2008)—influence a relatively small 

percentage (approximately 5.7 percent) of priority habitats 

throughout the species’ range suggesting localized potential 

impacts (versus widespread potential impacts such as with 

agriculture). BLM lands account for approximately 38 percent 

of the priority habitats influenced by urban areas, according to 

our estimates. Rural areas have also been developed throughout the sagebrush region, particularly around urban centers 

and major highways (Knick and Connelly, 2011a). Although 

many urban developments in rural areas continue to provide 

some sagebrush habitat in contrast to total urban conversion, 

habitat fragmentation and disturbance from human dwellings 

and activities probably render much of the area inhospitable 

to sage-grouse (Connelly and others, 2004). Comparison of 

currently occupied to historically occupied (presumed extirpated) sage-grouse range determined that mean human density 

(circa 1950 and 2000) was up to 26 times lower in currently 

occupied range (Aldridge and others, 2008; Wisdom and 

others, 2011).

There is little information directly assessing the response 

of sage-grouse to urbanization. Research in Canada revealed 

that brood-rearing females avoided habitats associated with 

a high density of urban developments (Aldridge and Boyce, 

2007). Urban areas by themselves remove habitat and present 

inhospitable environments for sage-grouse, but the physical 

boundaries of cities are small relative to the total sagebrush 

area. The roads, railways, power lines and communications 

corridors connecting urban centers may exert a greater influence on sagebrush habitats than that exerted by the actual city 

(Connelly and others, 2004). Additionally, recreation, including hiking, hunting and fishing, and OHV use in areas surrounding urban centers can negatively influence sage-grouse 

through habitat loss and fragmentation, facilitation of exotic 

plant spread, animal displacement or avoidance, establishment 

of population barriers, or increased human-wildlife encounters that increase wildlife mortality (Connelly and others, 

2004). Recreation on lands managed by the BLM remains 

a significant land use with potential impacts to range conditions and sage-grouse populations (Connelly and others, 2004; 

also see Section III. A12. Other Land Uses). The cumulative nature of changes to the sagebrush biome as a result of 

human encroachment needs to be considered when managing 

sage-grouse. Potential synergistic effects of the components 

of urbanization—including the stresses in habitats surrounding urban centers—may influence sage-grouse habitat use and 

demography making growth and mitigation of urban areas and 

effects an important consideration in many MZs. For example, 

the development of an energy field (discussed at length below) 

involves more than the infrastructure required to extract the 

resource. Urban centers near the developing field will expand 

with the increased human population in the area, communication towers and power lines will be erected, traffic on highways will increase, recreational use of areas surrounding urban 

centers will increase, and all these factors individually and in 

combination may influence sage-grouse populations (Johnson 

and others, 2011).

A4. Infrastructure 

Interstates and major highways are ubiquitous throughout 

the range of sage-grouse directly influencing 1,338,200 acres 

(5,400 km2

; 2 percent) of sage-grouse PPH habitat and more 

than 3 million acres (12,100 km2

) of PPH and PGH combined, 

with indirect influences (impacts beyond habitat loss and 

immediate threats of mortality such as via collision) estimated 

on more than 139 million acres (565,800 km2

) across the range 

of the species (table 6, fig. 11). Secondary paved roads exist 

in most sagebrush regions in densities >1.25 mi/100acres (≈5 

km/km2 ), less than 5 percent of the sage-grouse range is more 

than 1.5 mi (2.5 km ) from a paved road, and almost no area 

of sagebrush is more than 4.3 mi (6.9 km ) from a paved road 

(Knick and Connelly, 2011a). Indirect influences such as aversions to noise and activities were assessed using 4.6 mi (7.5 

km ) buffers for interstates and 1.9 mi (3 km ) buffers for highways, primary, and secondary routes. Based on indirect effects 

estimates, interstates and major highways potentially affect 

the habitat quality of more than 95 percent of priority habitats 

throughout the range of the species. A large proportion of these 

roads exist as rights-of-way on public lands, including 55 percent of BLM-managed PPH and 5 percent of USFS-managed 

PPH (52 percent and 5 percent of PGH, respectively; table 6). 

In contrast to roads, major railroads are not as widespread 

throughout the range of sage-grouse and directly influence 

(including abandoned rail-lines) only 32,500 acres (132 km2

; 

0.02 percent) of sage-grouse habitat (PPH and PGH) across 

the range of the species (table 7, fig. 12). Railroads are slightly 

more widespread in MZ I and in Wyoming portions of MZs II 

and VII; additionally, railroads may have a relatively important influence in some priority habitats in central Utah. Indirect 

effects of non-abandoned railroads (similarly to roads, indirect 

effects are considered impacts besides immediate habitat loss 

or mortality due to collision) were assessed using estimated 

contributions to spread of exotic plant species (1.9 mi [3 km]), 

which potentially influence approximately 4 percent of priority 

sage-grouse habitats across the range. 

Transmission lines and local distribution lines (collectively power lines) are widespread throughout the range of 

sage-grouse and are especially prevalent in MZ II and in priority habitats in portions of MZs III and IV (table 8, fig. 13A). 

Major power lines directly influence approximately 3,896,400 

acres (276,000 km2

; 2.7 percent) of sage-grouse habitats 

throughout the range of the species, including approximately 
Table 5. Summary of the direct and indirect influences of urban areas* across Management Zones (MZ) by acres of preliminary priority and prelimin

(PPH and PGH, respectively). Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint1 (acres) 6.9 km Indirect Influence1 (acres) Direct Footprint1 (%) Relative Influence2 (%) SG Habitat (acres) Direct Footprint1 (acres) 6.9 km Indirect Influence1 (acres) 

MZ I–GP 11,636,400 5,000 436,600 0.04 3.75 34,663,000 130,100 2,733,300 

BLM 2,994,300 100 34,600 0.00 8 4,524,900 9,300 190,300 

Forest Service 292,400 100 9,600 0.03 2 515,300 0 32,400 

Tribal and Other Federal 219,700 0 400 0.00 0 2,427,700 200 100,700 

Private 7,132,500 4,100 331,800 0.06 76 24,682,800 113,200 2,188,300 State 995,600 800 59,800 0.08 14 2,498,400 7,300 219,000 

Other 1,900 0 300 0.00 0 13,900 0 2,600 

MZ II and VII–WB & CP 17,476,000 155,700 1,875,000 0.89 10.73 19,200,200 353,400 3,841,800 

BLM 9,021,200 37,400 820,900 0.41 44 9,012,500 106,200 1,431,100 

Forest Service 162,000 0 3,500 0.00 0 452,500 24,600 80,500 

Tribal and Other Federal 784,000 32,400 86,000 4.13 5 1,354,600 2,500 145,000 

Private 6,233,900 79,100 833,600 1.27 44 7,394,800 209,300 2,008,500 

State 1,244,800 6,800 126,300 0.55 7 979,800 10,900 175,800 

Other 30,100 0 4,700 0.00 0 6,000 0 800 

MZ III–SGB 10,028,500 57,200 909,800 0.57 9.07 3,970,100 14,500 144,900 

BLM 6,309,400 4,100 226,500 0.06 25 3,199,800 2,200 81,000 

Forest Service 1,236,200 0 50,400 0.00 6 356,200 0 2,400 

Tribal and Other Federal 260,800 100 50,400 0.04 6 29,100 0 3,700 

Private 1,836,200 51,500 527,500 2.80 58 384,800 12,300 57,700 

State 385,900 1,500 54,900 0.39 6 200 0 100 

MZ IV–SRP 21,930,600 5,200 635,900 0.02 2.90 10,958,500 66,700 937,800 

BLM 13,710,700 1,100 386,600 0.01 61 4,928,200 19,700 277,700 

Forest Service 1,613,800 0 48,000 0.00 8 1,113,500 700 39,200 

Tribal and Other Federal 633,600 4,100 20,700 0.65 3 522,500 100 28,200 

Private 4,890,200 0 153,400 0.00 24 3,516,742 43,400 535,500 

State 1,019,373 0 26,900 0.00 4 846,200 2,800 56,800 

Other 62,900 0 400 0.00 0 31,400 0 300 
Table 5. Summary of the direct and indirect influences of urban areas* across Management Zones (MZ) by acres of preliminary priority and prelimin

and PGH, respectively).—Continued

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

6.9 km Indirect 

Influence1

(acres)

Direct 

Footprint1

(%)

Relative 

Influence2

(%)

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

6.9 km Indirect 

Influence1

(acres)

MZ V–NGB 7,097,200 300 17,000 0.00 0.24 5,808,000 4,600 92,200 

BLM 5,117,500 0 3,900 0.00 23 4,196,700 0 19,700 

Forest Service 62,200 0 0 0.00 0 114,900 0 1,800 Tribal and Other Federal 717,100 0 0 0.00 0 101,800 100 400 

Private 798,000 300 13,000 0.04 76 1,199,000 4,500 65,300 

State 64,900 0 0 0.00 0 115,800 0 0 Other 337,500 0 0 0.00 0 79,800 0 5,000 

*Data Source: Tele Atlas ESRI Street Map Premium for ArcGIS v 9.0, 20081Direct footprint is the co-location of urban areas within the designated habitat boundaries, and indirect influence is inferred by applying an effect buffer to the features and es

Indirect influence distance derived from foraging distances of predators (Boarman and Heinrich, 1999; Leu and others, 2008).

2For each MZ these were calculated as the percent of the particular sage-grouse habitat type influenced by the indirect impact of the threat. For management entities within a m

calculated as the percent of the total indirect impact in the management zone represented by that management entity, that is, the relative area of indirect influence among manage

between individual entity totals and MZ summary values may exist due to rounding of acre estimates during calculations.
34 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 10. Overlap of urbanized areas, potential indirect influences of urbanization, and sage-grouse preliminary priority and general 

habitats (PPH and PGH, respectively).
Table 6. Summary of the direct and indirect influences of roads* across Management Zones (MZ) by acres of preliminary priority and preliminary ge

PGH, respectively). 

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

 Indirect 

Influence1

(acres)

Direct 

Footprint1

(%)

Relative 

Influence2

(%)

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

Indirect 

Influence1

(acres)

MZ I–GP 11,636,400 255,300 11,602,600 2.19 100 34,663,000 887,300 34,604,700 

BLM 2,994,300 48,200 2,971,300 1.61 26 4,524,900 79,600 4,511,000 

Forest Service 292,400 7,200 292,400 2.46 3 515,300 12,300 515,100 

Tribal and Other Federal 219,700 3,300 218,100 1.50 2 2,427,700 61,500 2,418,200 

Private 7,132,500 176,200 7,127,900 2.47 61 24,682,800 675,000 24,653,700 

State 995,600 20,300 991,200 2.04 9 2,498,400 58,600 2,492,700 

Other 1,900 0 1,800 0.00 0 13,900 300 13,900 

MZ II and VII–WB & CP 17,476,000 431,400 17,395,000 2.47 100 19,200,200 483,200 19,062,400 

BLM 9,021,200 209,600 8,993,500 2.32 52 9,012,500 188,800 8,948,200 

Forest Service 162,000 2,900 160,700 1.79 1 452,500 5,600 420,300 

Tribal and Other Federal 784,000 17,100 769,100 2.18 4 1,354,600 28,600 1,341,700 

Private 6,233,900 170,800 6,200,300 2.74 36 7,394,800 236,700 7,370,400 

State 1,244,800 30,200 1,241,300 2.43 7 979,800 23,400 975,800 

Other 30,100 900 30,100 2.99 0 6,000 200 6,000 

MZ III–SGB 10,028,500 211,700 9,599,100 2.11 96 3,970,100 71,700 3,772,500 

BLM 6,309,400 115,700 6,003,000 1.83 63 3,199,800 56,900 3,061,200 

Forest Service 1,236,200 20,900 1,180,700 1.69 12 356,200 4,400 331,100 

Tribal and Other Federal 260,800 8,800 260,600 3.37 3 29,100 600 28,000 

Private 1,836,200 56,800 1,774,400 3.09 18 384,800 9,800 352,000 

State 385,900 9,400 380,200 2.44 4 200 0 200 

MZ IV–SRP 21,930,600 351,700 20,890,500 1.60 95 10,958,500 187,900 10,638,900 

BLM 13,710,700 199,400 13,075,200 1.45 63 4,928,200 68,500 4,799,300 

Forest Service 1,613,800 20,100 1,479,200 1.25 7 1,113,500 12,900 1,047,800 

Tribal and Other Federal 633,600 11,200 628,200 1.77 3 522,500 8,000 449,300 

Private 4,890,200 100,900 4,643,900 2.06 22 3,516,700 83,500 3,485,800 

State 1,019,400 18,800 1,001,100 1.84 5 846,200 14,100 825,300 

Other 62,900 1,200 62,900 1.91 0 31,400 800 31,400 
Table 6. Summary of the direct and indirect influences of roads* across Management Zones (MZ) by acres of preliminary priority and preliminary ge

PGH, respectively).—Continued Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint1 (acres) Indirect Influence1 (acres) Direct Footprint1 (%) Relative Influence2 (%) SG Habitat (acres) Direct Footprint1 (acres) Indirect Influence1 (acres) 

MZ V–NGB 7,097,200 88,100 6,608,800 1.24 93 5,808,000 99,100 5,636,800 

BLM 5,117,500 54,300 4,724,400 1.06 71 4,196,700 59,900 4,034,200 

Forest Service 62,200 2,000 62,200 3.22 1 114,900 3,600 114,900 Tribal and Other Federal 717,100 6,900 639,800 0.96 10 101,800 2,200 99,500 

Private 798,000 17,400 788,600 2.18 12 1,199,000 29,400 1,194,600 

State 64,900 1,300 64,200 2.00 1 115,800 2,100 115,600 Other 337,500 6,200 329,500 1.84 5 79,800 1,900 77,900 

*Data Source: Tele Atlas ESRI StreetMap Premium for ArcGIS v 9.0, 2008 1Direct footprint is the co-location of roads within the designated habitat boundaries, and indirect influence is inferred by applying an effect buffer to the features and estimatin

influence of roads was calculated using 7.5 km for interstates and 3km for highways, primary routes, and secondary routes. (Connelly and others, 2004, Holloran, 2005; Lyon, 2

2For each MZ, calculated as the percent of the particular sage-grouse habitat type influenced by the indirect impact of the threat. For management entities within a manageme

of the total indirect impact in the management zone represented by that management entity; that is, the relative area of indirect influence among management entities. Small diffetotals and MZ summary values may exist due to rounding of acre estimates during calculations.
III. Characterization of Important Threats and Issues 37

Figure 11. Overlap of roads and potential indirect influences of roads and sage-grouse preliminary priority and general habitats 

(PPH and PGH, respectively). MZ, Management Zone.
Table 7. Summary of the direct influences of abandoned and non-abandoned, railroads* and indirect influences of non-abandoned railroads across 

acres of preliminary priority and preliminary general habitats (PPH and PGH, respectively). Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint1 (acres) 3 km Indirect Influence1 (acres) Direct Footprint1 (%) Relative Influence2 (%) SG Habitat (acres) Direct Footprint1 (acres) 3 km Indirect Influence1 (acres) 

F

MZ I–GP 11,636,400 1,500 235,400 0.01 2.02 34,663,000 11,800 2,493,800 

BLM 2,994,300 100 14,300 0.00 6 4,524,900 400 130,500 

Forest Service 292,400 0 3,000 0.00 1 515,300 200 63,900 

Tribal and Other Federal 219,700 0 0 0.00 0 2,427,700 600 165,000 

Private 7,132,500 1,300 200,100 0.02 85 24,682,800 9,900 1,983,500 

State 995,600 100 17,900 0.01 8 2,498,400 700 149,500 

Other 1,900 0 100 0.00 0 13,900 0 1,400 

MZ II and VII–WB & CP 17,476,000 3,100 586,500 0.02 3.36 19,200,200 7,800 1,718,200 

BLM 9,021,200 900 202,600 0.01 35 9,012,500 1,700 539,100 

Forest Service 162,000 0 200 0.00 0 452,500 0 300 

Tribal and Other Federal 784,000 100 6,800 0.01 1 1,354,600 300 69,900 

Private 6,233,900 1,900 339,000 0.03 58 7,394,800 5,500 1,022,800 

State 1,244,800 200 33,000 0.02 6 979,800 400 86,100 

Other 30,100 0 5,000 0.00 1 6,000 0 0 

MZ III–SGB 10,028,500 2,300 408,700 0.02 4.08 3,970,100 200 61,000 

BLM 6,309,400 500 149,700 0.01 37 3,199,800 200 43,200 

Forest Service 1,236,200 0 10,000 0.00 2 356,200 0 0 

Tribal and Other Federal 260,800 400 37,000 0.15 9 29,100 0 0 

Private 1,836,200 1,100 174,100 0.06 43 384,800 100 17,800 

State 385,900 200 37,900 0.05 9 200 0 0 

MZ IV–SRP 21,930,600 2,100 316,600 0.01 1.44 10,958,500 3,000 436,300 

BLM 13,710,700 1,000 138,500 0.01 44 4,928,200 900 175,800 

Forest Service 1,613,800 100 17,000 0.01 5 1,113,500 0 4,600 

Tribal and Other Federal 633,600 100 36,500 0.02 12 522,500 100 10,400 

Private 4,890,200 800 114,500 0.02 36 3,516,742 1,900 223,000 

State 1,019,373 100 10,000 0.01 3 846,200 100 22,400 

Other 62,900 0 100 0.00 0 31,400 0 100 
Table 7. Summary of the direct influences of abandoned and non-abandoned, railroads* and indirect influences of non-abandoned railroads across 

acres of preliminary priority and preliminary general habitats (PPH and PGH, respectively).—Continued

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

3 km Indirect 

Influence1

(acres)

Direct 

Footprint1

 (%)

Relative 

Influence2

(%)

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

3 km Indirect 

Influence1

(acres)

F

MZ V–NGB 7,097,200 500 6,800 0.01 0.10 5,808,000 200 14,000 

BLM 5,117,500 200 2,400 0.00 35 4,196,700 0 7,500 

Forest Service 62,200 0 0 0.00 0 114,900 0 0 

Tribal and Other Federal 717,100 0 4,100 0.00 60 101,800 0 100 

Private 798,000 0 100 0.00 1 1,199,000 100 4,500 

State 64,900 0 0 0.00 0 115,800 0 0 

Other 337,500 200 300 0.06 4 79,800 0 1,900 

*Data Source: Federal Railroad Administration (FRA) Rail Lines of the of the U.S.A., 2001.

1Direct footprint is the co-location of rail lines (abandoned and non-abandoned) within the designated habitat boundaries, and indirect influence is inferred by applying an effe

estimating the area affected. Indirect influence distance derived from estimated spread of exotic plants (Knick and others, 2011).

2For each MZ, these were calculated as the percent of the particular sage-grouse habitat type influenced by the indirect impact of the threat. For management entities within a 

calculated as the percent of the total indirect impact in the management zone represented by that management entity; that is, the relative area of indirect influence among managebetween individual entity totals and MZ summary values may exist due to rounding of acre estimates during calculations.
40 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 12. Overlap of abandoned and non-abandoned railroads, potential indirect influences of non-abandoned railroads, and sagegrouse preliminary priority and general habitats (PPH and PGH, respectively). MZ, Management Zone.
PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

6.9 km Indirect 

Influence1

(acres)

Direct 

Footprint1

 (%)

Relative 

Influence2

(%)

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

6.9 km Indirec

Influence1

(acres)

MZ I–GP 11,636,400 128,700 3,348,700 1.11 28.78 34,663,000 1,082,400 16,029,400 

BLM 2,994,300 18,600 601,600 0.62 18 4,524,900 71,300 1,482,800 Forest Service 292,400 3,800 136,300 1.30 4 515,300 16,700 270,100 

Tribal and Other Federal 219,700 1,000 34,600 0.46 1 2,427,700 90,600 1,459,500 

Private 7,132,500 92,100 2,280,300 1.29 68 24,682,800 831,100 11,655,300 

State 995,600 13,200 295,600 1.33 9 2,498,400 71,400 1,156,600 

Other 1,900 0 300 0.00 0 13,900 1,300 5,000 

MZ II and VII–WB & CP 17,476,000 673,800 10,480,800 3.86 59.97 19,200,200 961,700 12,051,000 

BLM 9,021,200 320,500 5,286,400 3.55 50 9,012,500 392,800 5,430,900 Forest Service 162,000 5,300 91,900 3.27 1 452,500 7,100 137,400 Tribal and Other Federal 784,000 13,000 339,900 1.66 3 1,354,600 62,100 760,700 Private 6,233,900 284,400 4,033,300 4.56 38 7,394,800 454,900 5,120,900 State 1,244,800 48,100 711,200 3.86 7 979,800 44,700 597,900 

Other 30,100 2,400 18,100 7.97 0 6,000 200 3,200 

MZ III–SGB 10,028,500 181,700 3,346,700 1.81 33.37 3,970,100 43,200 1,001,500 

BLM 6,309,400 84,500 1,775,800 1.34 53 3,199,800 36,900 801,500 Forest Service 1,236,200 5,500 211,700 0.44 6 356,200 800 46,500 

Tribal and Other Federal 260,800 1,300 92,100 0.50 3 29,100 0 1,700 Private 1,836,200 80,100 1,074,900 4.36 32 384,800 5,500 151,600 State 385,900 10,200 192,100 2.64 6 200 0 200 

MZ IV–SRP 21,930,600 392,600 8,015,200 1.79 36.55 10,958,500 266,300 4,204,300 

BLM 13,710,700 234,900 4,973,200 1.71 62 4,928,200 112,200 1,795,300 Forest Service 1,613,800 13,000 400,700 0.81 5 1,113,500 7,900 313,000 Tribal and Other Federal 633,600 17,400 245,500 2.75 3 522,500 7,900 149,000 Private 4,890,200 106,700 2,035,600 2.18 25 3,516,742 116,200 1,619,700 State 1,019,373 15,900 301,900 1.56 4 846,200 20,500 302,300 Other 62,900 4,800 58,200 7.63 1 31,400 1,700 24,900 

Table 8. Summary of the distribution of power transmission lines (>115 kilovolt)* across sage-grouse habitats (PPH and PGH) by Management Zone (Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G
Table 8. Summary of the distribution of power transmission lines (>115 kilovolt)* across sage-grouse habitats (PPH and PGH) by Management Zone (Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint1 (acres) 6.9 km Indirect Influence1 (acres) Direct Footprint1 (%) Relative Influence2 (%) SG Habitat (acres) Direct Footprint1 (acres) 6.9 km Indirec

Influence1 (acres) 

MZ V–NGB 7,097,200 77,100 1,814,200 1.09 25.56 5,808,000 88,900 1,922,400 

BLM 5,117,500 59,500 1,403,800 1.16 77 4,196,700 60,000 1,237,000 

Forest Service 62,200 200 15,400 0.32 1 114,900 2,100 45,800 Tribal and Other Federal 717,100 0 10,500 0.00 1 101,800 900 24,800 Private 798,000 12,600 238,700 1.58 13 1,199,000 21,500 521,300 

State 64,900 300 31,700 0.46 2 115,800 3,200 67,600 Other 337,500 4,500 114,100 1.33 6 79,800 1,300 25,800 

*Data Source: EV Energy Map, Platts/Global Energy, 2005 ICBEMP Existing Utility Corridors, 2003. 1Direct footprint is the co-location of power lines within the designated habitat boundaries, and indirect influence is inferred by applying an effect buffer to the features and es

Indirect influence distance derived from foraging distances of predators (Boarman and Heinrich, 1999; Leu and others, 2008). 2For each MZ, these were calculated as the percent of the particular sage-grouse habitat type influenced by the indirect impact of the threat. For management entities within a m

as the percent of the total indirect impact in the management zone represented by that management entity; that is, the relative area of indirect influence among management entitindividual entity totals and MZ summary values may exist due to rounding of acre estimates during calculations.
III. Characterization of Important Threats and Issues 43

Figure 13A. Overlap of major power lines and associated infrastructure, indirect influences of these structures, and preliminary 

priority and preliminary general habitats (PPH and PGH, respectively). MZ, Management Zone.
44 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

673,800 acres (2,725 km2; 3.9 percent) of priority habitats 

and 961,700 acres (3,900 km2

; 5.0 percent) of general habitats directly influenced in MZs II and VII—the largest among 

MZs. Indirect impacts of power lines—estimated using 

the spatial foraging scale of avian predators, which may be 

attracted to power lines (4.3 mi [6.9 km])—are estimated to 

influence approximately 44 percent of priority and general 

habitats throughout the species’ range, and approximately 60 

percent of priority habitats in MZs II and VII. Collectively, 

BLM lands account for approximately 48 percent of the 

priority habitats indirectly influenced by major power lines. 

Nonwind-power-related vertical structures are widespread and directly influence approximately 15,200 acres 

(61 km2

; 0.01 percent) of sage-grouse habitat throughout the 

range of the species (table 9; fig. 13B). A minimum of 10,182 

communication towers exist in or within 50 km (30 mi) of current sage-grouse range (Knick and Connelly, 2011a). Indirect 

effects of vertical structures—similarly, estimated using the 

spatial-foraging scale of sage-grouse avian predators, which 

may be attracted to these structures (6.9 km [4.3 mi]; Boarman and Heinrich, 1999; Leu and others, 2008)—influence 

approximately 33.4 percent of priority habitats throughout the 

range of the species, so the potential indirect effects of vertical structures are not insignificant (table 9, fig. 13B). BLM 

lands account for approximately 45 percent of the priority 

habitats indirectly influenced by vertical structures. Fences are 

ubiquitous throughout sage-grouse range (fig. 13C), with areas 

having fence densities exceeding 4 mi/1,000 acres (1.5 km/

km2

 ) in all MZs except western portions of MZ III (Knick and 

Connelly, 2011a). Approximately 167,700 mi (270,000 km) of 

fence are present within BLM- and USFS-managed allotment 

and pasture boundaries on sage-grouse habitats, with approximately 78,300 mi (126,000 km) of fence present on these 

public lands, in priority habitats (table 10; fig. 13C). These 

estimates of fence densities across the range of the species are 

approximately 0.75 miles per section (one section equals one 

square mile) and exceed 1 mi/section (1.2 km/2.6 km2

) in priority habitats in MZ I, without accounting for similar fencing 

on private lands.

Compared to occupied range, extirpated sage-grouse 

range was 60 percent closer to highways and had 25 percent 

higher densities of roads compared to occupied range (Wisdom and others, 2011). Mean distance to transmission lines 

was more than two times farther in occupied range than in 

extirpated range, and the distance to communication towers 

averaged almost two times as far in occupied versus extirpated 

range (Wisdom and others, 2011). Although relatively few leks 

across the range of the species had interstate highways nearby, 

declines in the numbers of males on leks closer to interstates were slightly less than those farther from interstates; 

nonetheless, there was a consistent downward trend in sagegrouse numbers as the length of interstate within 3.1 mi (5 

km) increased (Johnson and others, 2011). Similarly, despite 

low numbers of communication towers across the sagebrush 

biome, sage-grouse lek trends across the range of the species generally increased with distance from nearest tower and 

generally decreased with increasing numbers of towers within 

5 km (3.1 mi) and 18 km (11.2 mi) of leks (Johnson and 

others, 2011). Sage-grouse population response to a human 

footprint metric (see Section III.A) indicated that sage-grouse 

generally respond negatively to increased anthropogenic 

infrastructures located in sagebrush habitats. Roads and power 

lines are especially widespread throughout the range of the 

species, and communication towers are becoming increasingly 

prevalent. Although the response of sage-grouse to communication towers may be correlated with human development 

in general (towers are often concentrated along major roadways and around urban centers; Johnson and others, 2011), 

an extensive rural network exists, and with potential for an 

increase in these types of structures throughout the sagebrush 

biome with ongoing development (for example, meteorological towers at proposed wind developments), the accumulation 

of factors (traffic, predator accessibility, and invasive species) 

is likely to have effects on sage-grouse habitat quality. 

Lekking and nesting sage-grouse appear to avoid road 

infrastructure and related activities (especially traffic). Along 

Interstate 80 in Wyoming and Utah between 1970 and 2003, 

observers found no leks within 2 km (1.25 mi) of the interstate 

and fewer birds on leks within 7.5 km (4.7 mi) than within 

7.5–15 km (4.7–9.3 mi) beyond the interstate (Connelly 

and others, 2004). Additionally, there were higher rates of 

decline in lek counts within 7.5 km than beyond 7.5 km of the 

interstate. Negative relations between the length of road segments within 3.2 km (2 mi) of leks and the probability of lek 

occurrence were found in Montana and southern Canada with 

the impacts of increasing road lengths (implying larger roads) 

being greatest for larger leks (>25 males); the probability of 

occurrence of a large lek approached 0 percent as the length of 

road segments within 3.2 km (2 mi) of a lek exceeded 100 km 

(62 mi; Tack 2009). 

Generally, road-effect distances (the distance from a road 

at which a population density decrease is detected) are positively correlated with increased traffic density and speed (Forman and Alexander, 1998). The upgrade of haul roads associated with surface coal mining activity in Colorado resulted 

in increased traffic levels and was correlated with declines in 

the number of displaying males on sage-grouse leks situated 

within 2 km (1.25 mi) of the road (Remington and Braun, 

1991). Rates of decline in sage-grouse male lek attendance 

increased as traffic volumes on roads near leks increased, 

and vehicle activity on roads during the daily strutting period 

(that is, early morning) had a greater influence on male lek 

attendance compared to roads with no vehicle activity during 

early morning in southwestern Wyoming (Holloran, 2005). In 

central Wyoming, peak male attendance (that is, abundance) 

at leks experimentally treated with noise recorded at roads 

in a gas field decreased 73 percent relative to paired controls 

(Blickley, 2012).

Sage-grouse avoided nesting and summering near major 

roads (for example, paved secondary highways) in southcentral Wyoming (LeBeau, 2012), and traffic disturbance 

(1 to 12 vehicles/day) within 3 km (1.9 mi) of leks during the 
Table 9. Summary of the direct and indirect influences of communication towers and other (non-wind) vertical structures* across preliminary prior

general habitat.

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

6.9 km Indirect 

Influence1

(acres)

Direct 

Footprint1

 (%)

Relative 

Influence2

(%)

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

6.9 km Indire

Influence1

(acres)

MZ I–GP 11,636,400 400 3,969,600 0.00 34 34,663,000 5,700 19,294,600 

BLM 2,994,300 0 665,300 0.00 17 4,524,900 200 1,891,000 

Forest Service 292,400 0 104,500 0.00 3 515,300 100 279,300 

Tribal and Other Federal 219,700 0 18,800 0.00 0 2,427,700 400 1,596,300 

Private 7,132,500 300 2,881,200 0.00 73 24,682,800 4,700 14,125,500 

State 995,600 0 299,300 0.00 8 2,498,400 200 1,397,000 

Other 1,900 0 400 0.00 0 13,900 0 5,300 

MZ II and VII–WB & CP 17,476,000 1,500 7,395,100 0.01 42 19,200,200 4,600 10,775,800 

BLM 9,021,200 500 3,309,100 0.01 45 9,012,500 1,100 4,540,700 

Forest Service 162,000 0 67,400 0.00 1 452,500 0 177,700 

Tribal and Other Federal 784,000 100 322,200 0.01 4 1,354,600 100 685,500 

Private 6,233,900 700 3,176,100 0.01 43 7,394,800 3,100 4,828,200 

State 1,244,800 100 507,100 0.01 7 979,800 200 541,600 

Other 30,100 0 13,100 0.00 0 6,000 0 2,200 

MZ III–SGB 10,028,500 800 3,420,700 0.01 34 3,970,100 200 1,073,500 

BLM 6,309,400 200 1,595,600 0.00 47 3,199,800 100 756,000 

Forest Service 1,236,200 100 377,500 0.01 11 356,200 0 68,900 

Tribal and Other Federal 260,800 0 121,300 0.00 4 29,100 0 9,800 

Private 1,836,200 500 1,154,200 0.03 34 384,800 100 238,600 

State 385,900 0 172,000 0.00 5 200 0 200 

MZ IV–SRP 21,930,600 800 6,818,700 0.00 31 10,958,500 900 4,544,900 

BLM 13,710,700 400 3,876,700 0.00 57 4,928,200 300 1,551,000 

Forest Service 1,613,800 0 460,400 0.00 7 1,113,500 100 359,500 

Tribal and Other Federal 633,600 0 280,400 0.00 4 522,500 100 153,000 

Private 4,890,200 300 1,859,100 0.01 27 3,516,742 400 2,078,800 

State 1,019,373 0 326,300 0.00 5 846,200 100 385,100 

Other 62,900 0 15,800 0.00 0 31,400 0 17,500 
Table 9. Summary of the direct and indirect influences of communication towers and other (non-wind) vertical structures* across Management Zon

and PGH.—Continued Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint1 (acres) 6.9 km Indirect Influence1 (acres) Direct Footprint1 (%) Relative Influence2 (%) SG Habitat (acres) Direct Footprint1 (acres) 6.9 km Indire

Influence1 (acres) 

MZ V–NGB 7,097,200 100 1,164,400 0.00 16 5,808,000 200 1,224,900 

BLM 5,117,500 100 727,000 0.00 62 4,196,700 100 705,100 

Forest Service 62,200 0 6,800 0.00 1 114,900 0 46,100 

Tribal and Other Federal 717,100 0 45,800 0.00 4 101,800 0 17,600 

Private 798,000 0 217,300 0.00 19 1,199,000 100 412,000 

State 64,900 0 11,600 0.00 1 115,800 0 10,700 

Other 337,500 0 155,900 0.00 13 79,800 0 33,400 

*Data Source: Federal Communications Commission, 2009; Federal Aviation Administration Digital Obstacles File, 2011. 1Direct footprint is the co-location of communication towers within the designated habitat boundaries, and indirect influence is inferred by applying an effect buffer to the feat

affected. Indirect influence distance derived from foraging distances of predators (Boarman and Heinrich, 1999; Leu and others, 2008). 2For each MZ, calculated as the percent of the particular sage-grouse habitat type influenced by the indirect impact of the threat. For management entities within a managemen

as the percent of the total indirect impact in the management zone represented by that management entity; that is, the relative area of indirect influence among management entitindividual entity totals and MZ summary values may exist due to rounding of acre estimates during calculations.
III. Characterization of Important Threats and Issues 47

Figure 13B. Overlap of communication towers and other vertical structures (non-wind), potential indirect influences of these 

structures, and sage-grouse preliminary priority and preliminary general habitats (PPH and PGH, respectively). MZ, Management Zone.
48 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Table 10. Summary of the influence of fences* across Management Zones (MZ) by miles within preliminary priority and preliminary 

general habitats (PPH and PGH, respectively) using Bureau of Land Management and U.S. Forest Service allotment and pasture 

boundaries as a surrogate for fence locations.

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; 

NGB, Northern Great Basin.

 PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint 

(miles)

Average 

miles per 

section

SG Habitat 

(acres)

Direct 

Footprint 

(miles)

Average 

miles per 

section

MZ I–GP 11,636,400 18,700 1.03 34,663,000 48,200 0.89

BLM 2,994,300 6,100 1.30 4,524,900 11,300 1.60

Forest Service 292,400 500 1.09 515,300 900 1.12

Tribal and Other Federal 219,700 100 0.29 2,427,700 500 0.13

Private 7,132,500 10,700 0.96 24,682,800 32,100 0.83

State 995,600 1,400 0.90 2,498,400 3,300 0.85

Other 1,900 0 0.00 13,900 0 0.00

MZ II and VII–WB & CP 17,476,000 18,300 0.67 19,200,200 18,900 0.63

BLM 9,021,200 9,300 0.66 9,012,500 8,800 0.62

Forest Service 162,000 500 1.98 452,500 1,100 1.56

Tribal and Other Federal 784,000 400 0.33 1,354,600 500 0.24

Private 6,233,900 6,700 0.69 7,394,800 7,400 0.64

State 1,244,800 1,300 0.67 979,800 1,100 0.72

Other 30,100 0 0.00 6,000 0 0.00

MZ III–SGB 10,028,500 7,800 0.50 3,970,100 3,000 0.48

BLM 6,309,400 4,700 0.48 3,199,800 2,000 0.40

Forest Service 1,236,200 1,700 0.88 356,200 600 1.08

Tribal and Other Federal 260,800 100 0.25 29,100 0 0.00

Private 1,836,200 1,100 0.38 384,800 300 0.50

State 385,900 300 0.50 200 0 0.00

MZ IV–SRP 21,930,600 27,900 0.81 10,958,500 13,900 0.81

BLM 13,710,700 16,100 0.75 4,928,200 7,200 0.94

Forest Service 1,613,800 2,800 1.11 1,113,500 1,900 1.09

Tribal and Other Federal 633,600 400 0.40 522,500 400 0.49

Private 4,890,200 7,400 0.97 3,516,742 3,900 0.71

State 1,019,373 1,200 0.75 846,200 500 0.38

Other 62,900 0 0.00 31,400 0 0.00

MZ V–NGB 7,097,200 5,600 0.50 5,808,000 5,400 0.60

BLM 5,117,500 4,000 0.50 4,196,700 3,600 0.55

Forest Service 62,200 100 1.03 114,900 200 1.11

Tribal and Other Federal 717,100 100 0.09 101,800 100 0.63

Private 798,000 1,000 0.80 1,199,000 1,400 0.75

State 64,900 100 0.99 115,800 100 0.55

Other 337,500 300 0.57 79,800 100 0.80

*

Data Source: BLM GSSP grazing allotments and pastures, 2012; USFS Enterprise Data Warehouse, 2012. Small differences between individual entity 

totals and MZ summary values may exist due to rounding of acre estimates during calculations. 
III. Characterization of Important Threats and Issues 49

Figure 13C. Distribution of fences associated with Federally managed allotments across the sage-grouse study area, estimated from 

Bureau of Land Management and U.S. Forest Service pasture and allotment boundaries.
50 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

breeding season reduced nest-initiation rates and increased 

distances moved from leks during nest-site selection of female 

sage-grouse in southwestern Wyoming (Lyon and Anderson, 

2003). Nesting propensity (that is, nest initiation rates) was 

24 percent lower for females breeding on road-disturbed leks 

compared to undisturbed females. Fifty-six (56) percent of 

females breeding on disturbed leks initiated nests in consecutive years compared to 82 percent of females breeding on 

undisturbed leks; and females moved twice as far from leks to 

nest locations if breeding on disturbed leks (Lyon and Anderson 2003). Roads within 3 km (1.9 mi) of leks also negatively 

influence female habitat selection and fecundity. In summary, 

research suggests that roads within 7.5 km (4.7 mi) of leks 

negatively influence male lek attendance. Increased size of 

road, increased traffic levels on roads, and traffic activity 

during the early morning on roads within approximately 3 

km (1.9 mi) of leks negatively influence male lek attendance 

as well as female behavior, nest-initiation, and nest success. 

Although minimal traffic volumes ( <12 vehicles/day) on these 

roads negatively influence sage-grouse, higher traffic volumes 

appear to have a greater effect. The intermittent noise characteristic of traffic has been connected to declines in male lek 

attendance; however, details of causal relations have not been 

experimentally examined. 

Transmission- and distribution-line construction (power 

lines) may result in substantial indirect habitat loss (that is, 

avoidance) due to sage-grouse avoidance of vertical structures, potentially because of changes in raptor concentrations 

and raptor species’ composition relative to perches on flat 

landscapes. Additionally, the tendency of sage-grouse to fly 

relatively low, and in low light or when harried, may put them 

at a particularly high risk of collision with lines. Transmission 

lines generally refer to the high-voltage lines transferring electricity to substations, whereas distribution lines refer to lower 

voltage, smaller lines carrying electricity to consumers (we use 

“power lines” to refer to them collectively). The erection of 

a transmission line located within 650 ft (200 m) of an active 

sage-grouse lek, and between the lek and day-use areas, in 

northeastern Utah resulted in a 72 percent decline in the mean 

number of displaying males and an alteration in daily dispersal patterns during the breeding season within 2 years (Ellis, 

1985). This project also reported that the frequency of raptor–

sage-grouse interactions during the breeding season increased 

65 percent and golden eagle interactions alone increased 47 

percent between pre- and post-transmission line comparisons 

(Ellis, 1985). Negative effects of power lines on lek persistence were documented in northeastern Wyoming; the probability of lek persistence decreased with proximity to power 

lines and with increasing proportion of power lines within a 4 

mi (6.4 km) window around leks (Walker and others, 2007a). 

Braun (1998b) reported that use of areas near transmission 

lines by sage-grouse increased as distance from transmission 

lines increased up to 1970 ft (600 m). Sage-grouse avoided 

brood-rearing habitats within 2.9 mi (4.7 km) of transmission 

lines in south-central Wyoming (LeBeau, 2012). Power line 

collisions accounted for 33 percent of juvenile (1st winter) 

mortality in low-elevation areas in Idaho (Beck and others, 

2006). In general, it appears sage-grouse may avoid habitats 

within 0.4–2.9 mi (0.6–4.7 km) of a transmission line, and 

erection of a transmission line close to a lek will negatively 

influence sage-grouse lek attendance and breeding-season 

behavior. Additionally, higher densities of power lines within 4 

mi (6.4 km) of a lek may negatively influence lek persistence. 

Power lines may be locally significant causes of mortality due 

to collisions. Potentially more important, poles and towers 

associated with transmission lines have been shown to influence raptor and corvid distributions and hunting efficiency 

resulting in increased predation on sage-grouse (Steenhof and 

others, 1993; Connelly and others, 2004). Foraging distances 

of avian, sage-grouse predators have been estimated at 4.3 mi 

(6.9 km; Knick and Connelly, 2011a), suggesting that transmission and power lines may influence sage-grouse at large 

spatial scales (Connelly and others, 2004; Cresswell and others, 2010). Based on these data, the direct footprint within any 

given MZ is relatively small (1.1–5.0 percent; table 8), but the 

area of relative influence is more extensive (25.2–62.8 percent 

PGH; table 8). Whereas theoretical effects are clear and logical, information relating sage-grouse response to transmission 

lines and distribution lines, or the effects of these lines on 

sage-grouse demographics, is not extensive.

Fences represent potential movement barriers (especially 

woven-wire fences), predator perches, or travel corridors and 

are a potential cause of direct mortality to sage-grouse (Braun, 

1998). Theoretically, not every fence is a problem, and those 

that tend to cause problems typically include one or more 

of the following characteristics: (1) constructed with steel 

t-posts, (2) constructed near leks, (3) bisect winter concentration areas, or (4) border riparian areas (Christiansen, 2009). 

Areas of greater topographic relief (roughness) appear to have 

lower incidence of collisions apparently because the birds 

have to fly higher to avoid the ground (Christiansen, 2009). At 

broad spatial scales during the breeding season, fence collision risk was lower in areas with high topographic ruggedness, 

higher in areas with increased fence density on the landscape, 

decreased with increasing distance to nearest lek (impacts 

detected within approximately 2 km [1.25 mi] of leks), and 

increased with increasing lek size (Stevens and others, 2011; 

Stevens and others, 2012). Visibility of fences also influences 

collision rates, with greater rates associated with less visible 

fences, for example, those constructed using only steel t-posts 

(without wooden posts) and wider segment widths (more than 

4 m (13 ft)) between posts (Stevens and others, 2011). Marking both sides of the top fence strand at 1 m intervals with 

reflective materials reduced collision frequency between 61 

and 83 percent (Christiansen, 2009; Stevens and others, 2012). 

Decisions on the best design or treatment to mitigate collision 

risk must consider tradeoffs; for example, although wooden 

posts are more visible, they may provide better raptor perches 

than t-posts. 
III. Characterization of Important Threats and Issues 51

A5. Energy Development 

Oil and gas development in habitats used by sage-grouse 

and construction of accompanying power lines, roads, and 

pipelines began in the late 1800s with the discovery of oil 

in the Interior West (Connelly and others, 2004). Since the 

1960s, development of natural gas resources in this region 

has dominated the industry (Connelly and others, 2004). The 

United States National Energy Policy projects an increase in 

oil consumption by 33 percent, in natural gas consumption by 

>50 percent, and in electricity by 45 percent by 2025 (Connelly and others, 2004). Development of oil and gas resources 

requires construction (well pads, access roads, and ancillary 

infrastructure including flow lines, other roads, compressor 

stations, pumping stations, and electrical facilities), drilling 

and extraction, and transport of oil and gas (Connelly and 

others, 2004). The expected economic production life of coal 

bed methane wells is 12–18 years and of oil and deep-seam 

gas wells is 20–100 years with advanced technology (Connelly and others, 2004). Gas and oil wells are widespread 

throughout priority and general habitats with concentrated 

development areas exceeding 10 wells/section (1 mi2

 [2.6 

km2

]) common throughout MZs I and II and the far eastern 

portions of MZ III (table 11, fig. 14), whereas current oil shale 

developments are concentrated solely in MZ VII (see Oil 

Shale Section, below). Despite significant closures of public 

lands to oil and gas leasing within PPH and PGH (table 12, 

fig. 15), current leases, including those leased but not yet 

developed, are substantial across sage-grouse ranges in MZs 

I and II (table 13, fig. 16A). Locations of geologic fields for 

traditional oil and gas (Copeland and others, 2011; fig. 16B) 

suggest potential development across eastern portions of the 

range (MZs I, II, VII, and eastern parts III); the potential for 

oil shale development is concentrated in MZs II and VII (see 

Oil Shale Section, below). It has been predicted that currently 

proposed and existing energy developments could affect more 

than 41 million hectares (24 percent) of shrubland habitats in 

the Western United States and Canada (Copeland and others, 

2011). This may be a conservative estimate of impact for species sensitive to anthropogenic activity where the development 

of energy resources results in large-scale indirect habitat loss.

Notably, most research on the effects of energy development on sage-grouse has been focused in MZs I and II 

(Wyoming, Montana, Dakotas, and southern Canada) where 

development is concentrated. The relative consistency of 

distance and density effects of the infrastructure of gas and oil 

developments on sage-grouse across different development 

types—including shallow coal bed methane and deep gas and 

oil development (Naugle and others, 2011)—suggests results 

from these studies should be applicable elsewhere in the 

range. In 2011, fourteen studies were conducted investigating 

impacts of energy development on sage-grouse; all reported 

negative effects, whereas none reported a positive influence of 

development on populations or habitats (Naugle and others, 

2011). Studies consistently reported that breeding populations of sage-grouse were negatively impacted at conventional 

well-pad densities of four and eight well pads/2.6 km2

 (1-mi2

section), with declines in lek attendance by male sage-grouse 

ranging from 13 to 79 percent associated with these well 

densities (Harju and others, 2010; Naugle and others, 2011). 

Lek attendance declines have consistently been reported when 

well-pad densities exceed 1 pad/section (2.6 km2

 [1 mi2]) 

within approximately 3.2 km (2 mi) of a lek (Naugle and others, 2011). Well-pad densities exceeding approximately 0.4 

pads/section within 18 km (11 mi) of leks negatively influenced lek trends rangewide (Johnson and others, 2011), and 

larger leks (>25 males) did not occur in areas where well-pad 

densities exceeded 2.5 pads/section within 12.3 km (7.6 mi) of 

a lek (Tack, 2009). A recent study reported that the probability 

of lek persistence (that is, leks remaining active) approached 0 

percent when well-pad densities exceeded approximately 6.5 

pads/section (Hess and Beck, 2012). 

A recent summary of studies investigating sage-grouse 

response to natural gas development reported that impacts to 

leks were most severe when infrastructure occurred near leks 

and were discernible out to distances of 6.2–6.4 km (3.8–4 

mi; Naugle and others, 2011). However, negative impacts to 

male counts were observed as far as 12.3 km (7.6 mi) on large 

leks (>25 males) with additional impacts as far as 11 mi (18 

km; the largest scale evaluated in literature, Naugle and others, 2011). Government imposed stipulations often restricted 

surface occupancy within 0.4 km (0.25 mi) of a lek during the 

time most studies were conducted, and leks that had ≥1 pad 

within this radius had 35 to 92 percent fewer attending males 

than did leks with zero wells within this distance (Harju and 

others, 2010; Naugle and others, 2011). It is also notable that a 

1-km (0.6-mi) restricted-surface-occupancy buffer is currently 

applied during development of many energy fields. However 

excluding infrastructure within a 0.6-mi buffer may be ineffective for successful conservation because a negative response 

is still estimated with this density of development. These 

patterns were apparent when comparing developed areas in 

Wyoming, whereby gas and oil infrastructure encircling leks 

within smaller radii (≤1.6–2 km [1–1.25 mi]) had fewer sagegrouse compared to leks at which no infrastructure occurred 

within this distance (Harju and others, 2010). Additionally, 

there was a strong negative effect of natural gas development 

within 0.8–3.2 km (0.5–2 mi) on lek persistence in northwestern Wyoming (Walker and others, 2007a). Rates of decline in 

numbers of males occupying leks increased on leks located 

relatively centrally within a developing gas field—that is, 

leks surrounded by producing wells in three or more directions (Holloran, 2005). Peak male attendance (a surrogate for 

abundance) at leks experimentally treated with noise from 

natural gas drilling decreased 29 percent relative to paired 

controls (Blickley and others, 2012). Additionally, changes 

in the number of males occupying leks situated downwind of 

drilling rigs were more negative than those witnessed on leks 

upwind of drilling rigs, supporting evidence that increased 

noise intensity negatively influences male lek attendance 

(Holloran, 2005). A time lag—or a delay between activity 

associated with energy development and its measurable effects 
Table 11. Summary of the direct influence of active and abandoned well sites and indirect influence of active oil and natural gas development-relate

Management Zones (MZ) by acres of preliminary priority and preliminary general habitats (PPH and PGH, respectively). Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint1 (acres) 19 km Indirect Influence1 (acres) Direct Footprint1 (%) Relative Influence2 (%) SG Habitat (acres) Direct Footprint1 (acres) 19 km Indirect Influence1 (acres) 

MZ I–GP 11,636,400 11,100 6,939,400 0.10 59.64 34,663,000 119,500 20,621,100 

BLM 2,994,300 2,000 1,528,400 0.07 22 4,524,900 18,200 2,402,800 

Forest Service 292,400 400 276,600 0.14 4 515,300 1,000 370,200 

Tribal and Other Federal 219,700 0 58,400 0.00 1 2,427,700 2,700 1,442,900 

Private 7,132,500 8,000 4,479,200 0.11 65 24,682,800 88,800 14,874,800 

State 995,600 600 595,800 0.06 9 2,498,400 8,800 1,521,100 

Other 1,900 0 1,000 0.00 0 13,900 0 9,300 

MZ II and VII–WB & CP 17,476,000 10,800 13,558,000 0.06 77.58 19,200,200 53,700 16,072,400 

BLM 9,021,200 6,300 7,375,300 0.07 54 9,012,500 32,000 8,079,600 

Forest Service 162,000 0 41,400 0.00 0 452,500 100 143,100 

Tribal and Other Federal 784,000 800 670,200 0.10 5 1,354,600 2,000 1,093,900 

Private 6,233,900 3,100 4,493,600 0.05 33 7,394,800 16,500 5,974,300 

State 1,244,800 700 952,600 0.06 7 979,800 3,100 775,600 

Other 30,100 0 25,000 0.00 0 6,000 0 6,000 

MZ III–SGB 10,028,500 2,000 1,764,600 0.02 17.60 3,970,100 0 316,400 

BLM 6,309,400 500 663,800 0.01 38 3,199,800 0 252,700 

Forest Service 1,236,200 0 209,400 0.00 12 356,200 0 7,800 

Tribal and Other Federal 260,800 300 139,300 0.12 8 29,100 0 600 

Private 1,836,200 900 697,600 0.05 40 384,800 0 55,200 

State 385,900 300 54,500 0.08 3 200 0 100 

MZ IV–SRP 21,930,600 0 222,100 0.00 1.01 10,958,500 0 32,700 

BLM 13,710,700 0 123,000 0.00 55 4,928,200 0 14,800 

Forest Service 1,613,800 0 0 0.00 0 1,113,500 0 0 

Tribal and Other Federal 633,600 0 0 0.00 0 522,500 0 0 

Private 4,890,200 0 99,100 0.00 45 3,516,700 0 17,900 

State 1,019,400 0 0 0.00 0 846,200 0 0 

Other 62,900 0 0 0.00 0 31,400 0 0 
Table 11. Summary of the direct influence of active and abandoned well sites and indirect influence of active oil and natural gas development-relate

Management Zones (MZ) by acres of preliminary priority and preliminary general habitats (PPH and PGH, respectively).—Continued

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

19 km Indirect 

Influence1

(acres)

Direct 

Footprint1

(%)

Relative 

Influence2

(%)

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

19 km Indirect 

Influence1

(acres)

MZ V–NGB 7,097,200 0 0 0.00 0.00 5,808,000 0 0 

BLM 5,117,500 0 0 0.00 0 4,196,700 0 0 

Forest Service 62,200 0 0 0.00 0 114,900 0 0 

Tribal and Other Federal 717,100 0 0 0.00 0 101,800 0 0 

Private 798,000 0 0 0.00 0 1,199,000 0 0 

State 64,900 0 0 0.00 0 115,800 0 0 

Other 337,500 0 0 0.00 0 79,800 0 0 

*Data Source: BLM Automated Fluid Minerals Support System (AFMSS) Database, 2011, Enerdeq IHS database 2011. Direct and indirect impacts are calculated for the surfa

however, subsurface mineral rights may be severed from surface rights.

1Direct footprint is the co-location of active or plugged and abandoned oil and natural gas wells within the designated habitat boundaries, and indirect influence is inferred by 

the active features and estimating the area affected. Indirect influence of active (non-abandoned) wells was estimated using the identified area of demographic impact (Johnson aothers, 2012).

2For each MZ, calculated as the percent of the particular sage-grouse habitat type influenced by the indirect impact of the threat. For management entities within a managemen

percent of the total indirect impact in the management zone represented by that management entity; that is, the relative area of indirect influence among management entities. Smindividual entity totals and MZ summary values may exist due to rounding of acre estimates during calculations.
54 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 14. Density of active wells related to oil and gas development within preliminary priority and preliminary general habitats (PPH 

and PGH, respectively). MZ, Management Zone.
III. Characterization of Important Threats and Issues 55

Table 12. Summary of the areas closed to Federal oil and gas development across Management Zones (MZ) by acres of preliminary 

priority and preliminary general habitats implicated (PPH and PGH, respectively).*

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; 

NGB, Northern Great Basin.

Table 13. Summary of existing Federal oil and gas leases (currently held by production or undeveloped) across Management Zones 

(MZ) by acres of preliminary priority and preliminary general habitats (PPH and PGH, respectively).*

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; 

NGB, Northern Great Basin.

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Federal 

Leases (acres)

Federal Leases 

(% habitat type)

SG Habitat 

(acres)

Federal 

Leases (acres)

Federal Leases 

(% habitat type)

MZ I–GP 11,636,400 1,304,600 11.21 34,663,000 5,016,800 14.47

Leased–Held By Production 388,400 3.34 2,607,900 7.52

Leased–Undeveloped 916,200 7.87 2,408,900 6.95

MZ II and VII–WB & CP 17,476,000 3,161,000 18.09 19,200,200 4,620,200 24.06

Leased–Held By Production 680,500 3.89 2,134,600 11.12

Leased–Undeveloped 2,480,500 14.19 2,485,600 12.95

MZ III – SGB 10,028,500 1,300,600 12.97 3,970,100 513,300 12.93

Leased–Held By Production 39,000 0.39 1,300 0.03

Leased–Undeveloped 1,261,600 12.58 512,000 12.90

MZ IV – SRP 21,930,600 245,900 1.12 10,958,500 100,200 0.91

Leased–Held By Production 0 0.00 0 0.00

Leased–Undeveloped 245,900 1.12 100,200 0.91

MZ V – NGB 7,097,200 0 0.00 5,808,000 0 0.00

*

Data Source: Aggregated from individual Bureau of Land Management State Office Submissions in 2011 and 2012. Leased areas are calculated based on 

Federal subsurface management; however, subsurface mineral rights may be severed from surface rights. Small differences between individual entity totals 

and MZ summary values may exist due to rounding of estimates during calculations.

PPH PGH

Management Zone SG Habitat 

(acres)

Federal 

Closed 

Areas 

(acres)

Federal 

Closed 

Areas (%)

SG Habitat 

(acres)

Federal 

Closed 

Areas 

(acres)

Federal 

Closed Areas 

(%)

MZ I–GP 11,636,400 170,900 1.47 34,663,000 668,300 1.93

MZ II and VII–WB & CP 17,476,000 1,302,400 7.45 19,200,200 1,242,400 6.47

MZ III–SGB 10,028,500 329,700 3.29 3,970,100 241,300 6.08

MZ IV–SRP 21,930,600 1,709,200 7.79 10,958,500 727,400 6.64

MZ V–NGB 7,097,200 744,000 10.48 5,808,000 82,400 1.42

*

Data Source: Aggregated from individual Bureau of Land Management State Office Submissions in 2011 and 2012. Leased areas are calculated based on 

Federal subsurface management; however, subsurface mineral rights may be severed from surface rights. Small differences between individual entity totals 

and MZ summary values may exist due to rounding of estimates during calculations.
56 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 15. Overlap of Federally managed, subsurface acres closed to oil and gas leasing and sage-grouse preliminary priority and 

preliminary general habitats (PPH and PGH, respectively). MZ, Management Zone.
III. Characterization of Important Threats and Issues 57

Figure 16A. Overlap of Federally managed, subsurface acres (held by production and developed leases) and sage-grouse preliminary 

priority and preliminary general habitats (PPH and PGH, respectively). MZ, Management Zone.
58 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 16B. Overlap of oil and gas resource occurrence potential and sage-grouse preliminary priority and preliminary general 

habitats (PPH and PGH, respectively). MZ, Management Zone.
III. Characterization of Important Threats and Issues 59

on lek attendance—of 3 to 4 years between the time infrastructure is placed and lek abandonment has been consistently 

documented (Naugle and others, 2011) making short-term 

observations potentially misleading. Time lags in response to 

infrastructure have been documented as short as 2 years, or as 

long as 10 years (Harju and others, 2010).

In general, the research suggests that sage-grouse are 

negatively affected when well-pad densities within approximately 3.2 km (2 mi) of a lek exceed 1 pad/section and when 

leks become surrounded by infrastructure. Energy development as far as 6.4 km (4 mi) to a lek may negatively influence lek attendance. Anthropogenic noise is a component of 

energy developments causing declines in male lek attendance; 

however, all potential causes of declines resulting from energy 

developments have not been examined empirically. Negative 

effects of energy development to sage-grouse may occur at 

distances approaching 18 km (11 mi), and the ultimate effects 

of infrastructure may not become apparent for up to 10 years 

following the addition of infrastructure to the landscape. 

Sage-grouse population declines resulted from avoidance 

of infrastructure during one or more seasons, reduced productivity, and (or) reduced survival (Naugle and others, 2011). 

A meta-analysis of grouse populations in general (including 

sage-grouse, prairie chickens, sharp-tailed grouse, and black 

grouse) suggested moderate to large displacement effects and 

small to moderate demographic effects of the infrastructure of 

energy developments; the displacement effect varied by feature type with power lines and roads having the largest effects 

(Hagen, 2010). Yearling female sage-grouse avoided nesting within 950 m (0.5 mi) of the infrastructure of natural gas 

fields (Holloran and others, 2010), and visible wells within a 

1 km2

 (247 acres) area negatively influenced female selection 

of nesting habitats (Kirol, 2012). Female early brood-rearing 

(early June to early July) locations were negatively correlated 

with the number of visible wells within a 1 km2

 area, and 

late brood-rearing females (early July through late August) 

avoided habitats when a surface disturbance (well pads and 

improved roads, for example) threshold of approximately 8 

percent of a 5 km2

 (1,200 acres) area was surpassed (Kirol, 

2012). Sage-grouse were 1.3 times more likely to occupy winter habitats within a 4 km2

 (990 acre) area that had not been 

fully developed for energy (eight pads/section) and avoided 

habitats within 1.9 km (1.2 mi) of infrastructure during winter 

(Naugle and others, 2011).

Decline in sage-grouse population growth (21 percent) 

between pre- and post-development was primarily attributed 

to decreased nest success and adult female annual survival; 

treatment effect (proximity to gas field infrastructure) was 

especially noticeable on annual survival of nesting adult 

females (Holloran and others, 2005). Annual survival of individuals reared near gas field infrastructure (yearling females 

and males) was significantly lower than control individuals 

that were not reared near infrastructure (Holloran and others, 2010). The probability that males reared near gas fields 

established a breeding territory was half that of control males 

(Holloran and others, 2010). Fewer females from impacted 

leks (that is, leks within 3 km [1.9 mi] of gas field infrastructure) initiated nests compared to females from non-impacted 

leks (Lyon and Anderson, 2003). The closer a nest was to a 

natural gas well (that existed or was installed in the previous 

year), the more likely it was to fail (Dzialak and others, 2011). 

When a surface disturbance (such as well pads and improved 

roads) threshold of approximately 4 percent of a 1 km2

 (247 

acre) area was surpassed, risk of daily brood loss increased, 

and risk of chick mortality was 1.5 times greater for each additional well site visible within 1 km (0.6 mi) of brood locations 

(Naugle and others, 2011; Kirol, 2012). 

Only one study has empirically examined the response 

of sage-grouse to explicit changes in conventional natural gas 

development protocols. In southwestern Wyoming, differences in reactions of wintering sage-grouse to conventional 

well pads (liquid by-products stored and collected on-site) and 

well pads equipped with liquid gathering systems (liquid byproducts piped off-site eliminating the need for tanker trucks 

to visit the pad) with reduced daily traffic volumes to individual pads from eight to three vehicles/day on average were 

examined (Holloran and others, in press). Sage-grouse avoided 

suitable winter habitats with high well-pad densities regardless of differences in activity levels associated with well pads. 

However, there was consistent suggestion across analyses that 

the distance-effect on sage-grouse of well pads equipped with 

liquid gathering systems may be less than that of conventional 

well pads. There was a strong positive relation between distance to drilling rig and average hours spent in an area.

In general, females selecting habitats near infrastructure have demonstrated lower annual survival (resulting in 

population-level declines in response to development), and 

females influenced by development activity within 3 km 

(1.8 mi) of the lek are less likely to initiate a nest. Nesting 

females avoid areas within approximately 1 km (0.6 mi) of 

infrastructure, and nests closer to infrastructure are at a higher 

risk of nest failure. Brood-rearing females avoid areas within 

approximately 0.5 km (0.3 mi) of infrastructure, broods reared 

within 1 km of infrastructure are less likely to be successful, and yearling male and female survival and yearling male 

fecundity (the probability of establishing a breeding territory) are lower for individuals reared near infrastructure. It is 

worth noting that a meta-analysis of sage-grouse demographic 

rates collected rangewide during a 73-year period suggested 

that female survival, chick survival, and nest success were 

demographics that had the greatest influence on sage-grouse 

population growth (Taylor and others, 2012). Sage-grouse 

during the winter avoid habitats with high well-pad densities 

and avoid areas within 1.9 km (1.2 mi) of a well pad; reduced 

anthropogenic activity levels at well pads may reduce the 

range of indirect (nonmortality effects) effects on sage-grouse 

on winter habitats (for example, reduction of avoidance).

Wind Energy Developments

Federal lands in the Western United States have significant potential to produce energy from wind power (Connelly 
60 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

and others, 2004). Few wind turbines currently exist within the 

range of sage-grouse, which makes assessment of this threat 

challenging; approximately 1,800 acres (0.001 percent) of 

sage-grouse habitat are directly influenced by wind turbines 

throughout the range of the species (table 14, fig. 17). Indirect 

effects to sage-grouse from wind energy developments were 

also assessed using the spatial foraging behaviors of avian 

predators that have an estimated range of 4.3 mi (6.9 km) from 

perching locations. This estimate suggests that current wind 

energy developments influence approximately 0.31 percent 

of priority habitats throughout the species’ range. Private 

lands account for most (approximately 72 percent) of the 

priority habitats indirectly influenced by wind turbines; BLM 

lands account for approximately 21 percent of these habitats 

indirectly influenced by turbines. Though largely unspecified 

(most Federal lands are not currently leased or developed), 

the coincidence of wind potential (for energy production) and 

sage-grouse habitats, including PPH and PGH, is high across 

sage-grouse range, and is especially widespread in MZs I and 

II (fig. 18A). Estimating development potential also includes 

location and proximity of transmission infrastructure and markets as well as market trends (energy prices); therefore, wind 

potential is only one of several indications of potential and 

all are not considered here. However, current development is 

greatest where rights of way leases have been issued, suggesting wind energy development potential in the near future will 

increase if in close proximity to available transmission. Thus 

areas with suboptimal wind speeds may be developed before 

those with better resources if near available transmission. For 

example, although wind potential for energy production is not 

high in MZ IV, significant wind energy transmission Rights 

of Way overlap PPH in MZ IV suggesting habitats in this MZ 

may be developed (fig. 18B). Concerns surrounding wind 

energy development and sage-grouse include noise produced 

by the rotor blades, sage-grouse avoidance of structure, and 

mortality to sage-grouse flying into rotors; however, the 

greater influence on sagebrush ecosystems will likely result 

from the roads and power lines that are necessary to construct 

and maintain sites used for wind energy (Connelly and others, 

2004). These effects are discussed at length in the previous 

section (also see Section III. A4. Infrastructure). The only 

study on specific effects of wind development on sage-grouse 

was recently completed in south-central Wyoming (LeBeau, 2012). The relative probabilities of a sage-grouse nest 

and brood failing (all chicks lost between hatch and 35-days 

post-hatch) increased with proximity to nearest wind turbine. 

Notably, this study investigated the short-term response of 

sage-grouse to a wind energy facility; the impacts of a facility 

may not be realized within 2 to 4 years of the addition of wind 

turbines due to the time lags associated with responses of 

sage-grouse breeding populations to infrastructure.

In Situ Uranium

According to the World Nuclear Association (London, 

United Kingdom; www.world-nuclear.org), in situ recovery 

(ISR) of uranium in North America involves recovering the 

minerals from an ore body by injecting solution to dissolve 

the uranium, pumping the pregnant solution to the surface, 

and removing the uranium from solution at a processing plant. 

Several projects are currently licensed to operate in the United 

States including several producing and proposed mines in 

Wyoming; most of the operating mines date from the 1990s. 

Uranium deposits are found predominantly in southeastern 

portions of MZ I (Powder River Basin), throughout MZ II, 

and in eastern MZ III and western MZ VII (Finch, 1996). The 

design of ISR-well fields varies depending on local conditions 

such as permeability, sand thickness, deposit type, ore grade, 

and ore distribution. However, whatever the well-field design 

used, there is a mixture of injection wells (to introduce the 

leach solution to the ore body) and extraction wells with submersible pumps used to deliver pregnant solution via pipeline 

to the processing plant. Wells with a common purpose (injection or extraction) are generally spaced 65 to 200 ft (20 to 60 

m) apart. Wells are typically the same size as water-well bores, 

and the processing plant is generally situated on-site creating 

basic infrastructure of wells, pipelines, and a processing plant 

within a geologically defined area.

The largest environmental risk with an ISR uranium 

facility is the potential impacts to groundwater resulting from 

(1) residual constituent concentrations in excess of baseline 

concentrations after the restoration of the production aquifer, 

(2) a migration of production liquids from the production 

aquifer to the surrounding aquifers during operation, (3) a 

mechanical failure of the subsurface-well materials releasing 

production fluids into the overlying aquifers, (4) movement 

of constituents to groundwater outside the licensed area, and 

(5) excessive consumption of groundwater (School of Energy 

Resources, University of Wyoming, Laramie, Wyo.; www.

uwyo.edu/ser/). A detailed description of surface disturbance 

associated with an in situ uranium mine could not be found; 

however, based on pictures provided by Ur-Energy (Littleton, 

Colo.), a company developing in situ uranium mines in Wyoming, surface disturbance most closely aligns with that found 

in a coal bed natural gas field at a localized scale (for example, 

wells not distributed across a large landscape but focused on 

discrete ore deposits) without overhead utilities and substantial 

water discharge. Beyond potential impacts of water contamination, potential disturbance to sage-grouse could occur during 

drilling phases of development, from the processing plant, 

and from traffic on roads accessing well fields (an intensively 

developed region) and the processing plant. Minimal surface 

disturbance appears to occur within the well field.

Oil Shale and Tar Sands

Oil shale (also referred to as tar sands) is fine-grained 

sedimentary rock that contains relatively large amounts of 

kerogen, which can be converted into liquid and gaseous 

hydrocarbons (petroleum liquids, natural gas liquids, and 

methane) by heating the rock. According to the U.S. Energy 

Information Administration (www.eia.gov), the richest U.S. 
Table 14. Summary of the direct and indirect influences of wind turbines* across Management Zones (MZ) by acres of preliminary priority and prelim

habitats (PPH and PGH, respectively). 

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

6.9 km Indirect 

Influence1

(acres)

Direct 

Footprint1

 (%)

Relative 

Innfluence2

(%)

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

6.9 km Indirect 

Influence1

(acres)

MZ I–GP 11,636,400 100 122,100 0.00 1.05 34,663,000 800 243,600 

BLM 2,994,300 0 25,800 0.00 21 4,524,900 0 14,900 

Forest Service 292,400 0 100 0.00 0 515,300 0 0 

Tribal and Other Federal 219,700 0 0 0.00 0 2,427,700 0 0 

Private 7,132,500 100 88,100 0.00 72 24,682,800 700 211,100 

State 995,600 0 8,100 0.00 7 2,498,400 0 17,600 

Other 1,900 0 0 0.00 0 13,900 0 0 

MZ II and VII–WB & CP 17,476,000 0 75,900 0.00 0.43 19,200,200 700 306,700 

BLM 9,021,200 0 16,500 0.00 22 9,012,500 0 65,700 

Forest Service 162,000 0 0 0.00 0 452,500 0 0 

Tribal and Other Federal 784,000 0 0 0.00 0 1,354,600 0 0 

Private 6,233,900 0 52,900 0.00 70 7,394,800 600 223,000 

State 1,244,800 0 6,600 0.00 9 979,800 100 18,000 

Other 30,100 0 0 0.00 0 6,000 0 0 

MZ III–SGB 10,028,500 0 0 0.00 0.00 3,970,100 0 0 

MZ IV–SRP 21,930,600 0 11,500 0.00 0.05 10,958,500 200 93,800 

BLM 13,710,700 0 2,000 0.00 17 4,928,200 0 29,900 

Forest Service 1,613,800 0 0 0.00 0 1,113,500 0 0 

Tribal and Other Federal 633,600 0 0 0.00 0 522,500 0 2,900 

Private 4,890,200 0 9,400 0.00 82 3,516,742 200 57,900 

State 1,019,373 0 100 0.00 1 846,200 0 3,100 

Other 62,900 0 0 0.00 0 31,400 0 0 
PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint1 (acres) 6.9 km Indirect Influence1 (acres) Direct Footprint1 (%) Relative Innfluence2 (%) SG Habitat (acres) Direct Footprint1 (acres) 6.9 km Indirect Influence1 (acres) 

MZ V–NGB 7,097,200 0 0 0.00 0.00 5,808,000 0 0 

*Data Source: Federal Aviation Administration Digital Obstacles File, 2011 1Direct footprint is the co-location of existing wind turbines within the designated habitat boundaries, and indirect influence is inferred by applying an effect buffer to the featu

affected. Indirect influence distance derived from foraging distances of predators (Boarman and Heinrich, 1999; Leu and others, 2008). 2For MZ calculated as the percent of the particular sage-grouse habitat type influenced by the indirect impact of the threat. For management entities within a management zon

total indirect impact in the management zone represented by that management entity; that is, the relative area of indirect influence among management entities. Small difference

and MZ summary values may exist due to rounding of estimates during calculations. Table 14. Summary of the direct and indirect influences of wind turbines* across Management Zones (MZ) by acres of preliminary priority and prelim

habitats (PPH and PGH, respectively).—Continued Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G
III. Characterization of Important Threats and Issues 63

Figure 17. Overlap of wind turbines, potential indirect influences of wind turbines, and preliminary priority and preliminary general 

habitats (PPH and PGH, respectively) across Management Zones (MZ).
64 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 18A. Distribution of wind occurrence potential (based on mean wind speeds) within preliminary priority and preliminary general 

habitats (PPH and PGH, respectively). MZ, Management Zone.
III. Characterization of Important Threats and Issues 65

Figure 18B. Overlap of Federal wind energy right-of-way leases with preliminary priority and preliminary general habitats (PPH and 

PGH, respectively). MZ, Management Zone.
66 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

oil shale deposits are located in northwest Colorado, northeast 

Utah, and southwest Wyoming, and deposits in these regions 

are currently the focus of petroleum industry research and 

potential future production. Current Federal leases for oil shale 

resources within sage-grouse range are limited to 331 km2

(81,800 acres) within MZs II and VII (fig. 19A); a majority of 

these developments are on BLM managed lands (surface) with 

the remaining portion split between private and State lands. 

Development potential extends beyond the current footprint 

with the richest deposits in northwest Colorado overlapping 

sage-grouse populations in MZ VII (fig. 19B) and has been 

subjected to a programmatic analysis considering resource 

potential, technology, and resource management issues (BLM, 

2012b). Given support of technology and market forces, these 

fields may ultimately produce more than 1 million barrels of 

oil equivalent per one acre (2.6 km2

; deposits in Alberta are 

expected to produce about 100,000 barrels per acre [2.6 km2

]) 

suggesting that this may be an important factor in sage-grouse 

habitat conservation in the future.

Techniques for extracting resources from oil shale can be 

generally categorized as direct or indirect recovery: (1) direct 

recovery involves the removal of the oil shale from its formation for ex situ processing and (2) indirect or in situ recovery 

involves some degree of processing of the oil shale while it is 

still in its natural depositional setting, leading ultimately to the 

extraction of just the desired organic fraction. The key steps in 

processing are retorting and pyrolysis. Retorting is a process 

that causes thermal decomposition of the organic fraction 

of the oil shale (kerogen); the recovered organic fraction is 

then distilled, or pyrolyzed, to produce three products: crude 

shale oil, flammable gases (including hydrogen, methane, 

and natural gas), and char (deposited on spent shale). Surface 

mining techniques (strip mining and or pit mining) as well 

as subsurface mining techniques (room-and-pillar mining, 

longwall mining, and other derivatives) have been successfully employed in the recovery of oil shale; however, the BLM 

considers the potential of surface mining in the future low. 

Indirect recovery techniques generally cause decomposition of 

kerogen to liquid and gaseous organic fractions that have sufficient mobility to “flow” through the formation for removal 

by conventional oil and gas recovery techniques. Surface 

disturbance most closely aligns with that found in a natural 

gas field, although well densities may be higher due to the 

requirement of injection (heat) and recovery wells in relative 

close proximity. Therefore, sage-grouse will likely respond to 

in situ oil shale development similarly to conventional natural 

gas development.

In situ recovery processes currently being researched 

are regarded by the U.S. Department of Energy as a promising technology. Although the technical feasibility of in situ 

retorting has been proven, considerable technological development and testing are needed before any commitment can 

be made to a large-scale commercial project. Confirmation of 

the technical feasibility of the processes hinges on the resolution of two major technical issues: controlling groundwater 

during production and preventing subsurface environmental 

problems, including groundwater impacts. Of special concern 

in the arid Western United States is the large amount of water 

required for oil shale processing; currently, oil shale extraction and processing require several barrels of water for each 

barrel of oil produced. The Energy Information Administration estimates that the earliest date for initiating construction 

of a commercial in situ oil shale project is 2017 with the first 

commercial production occurring probably no sooner than 

2023. The information presented in this paragraph as well as a 

detailed discussion of the technology required for the recovery 

(that is, mining), processing (that is, retorting and pyrolysis of 

the hydrocarbon fraction), and upgrading of oil shale resources 

can be found in the Draft Programmatic Environmental Impact 

Statement and Possible Land Use Plan Amendments for Allocation of Oil Shale and Tar Sands Resources on Lands Administered by the Bureau of Land Management in Colorado, Utah, 

and Wyoming (BLM, 2012b).

Solar

Solar power generation facilities that are likely to be 

developed for utility-scale capture of solar energy (that is, 

≥20 MW [megawatts] electricity that will be delivered into 

the electricity transmission grid) in the United States during 

the next 20 years include concentrating solar power—which 

includes parabolic trough, power tower, and dish engine 

systems—and photovoltaic arrays. The main component that 

all these technologies have in common is a large solar field 

where solar collectors capture the sun’s energy. In the parabolic trough and power tower systems, the energy is concentrated in a heat transfer fluid and transferred to a power block 

where steam-powered turbine systems generate electricity 

using similar technology to that used in fossil-fuel-fired power 

plants. In contrast, the dish engine and photovoltaic systems 

are composed of many individual units or modules that generate electricity directly and whose output is combined; these 

systems do not use a central power block. Solar facilities are 

likely to have an operational lifetime of 30 years or more, representing long-term effects on habitats where they co-occur. 

Although no current facilities affect sage-grouse range measurably (the USFWS listing decision identified small developments in Wyoming and California), the southern portion of 

sage-grouse range includes higher yields per unit area of solar 

potential indicating that, given technological developments, 

transmission infrastructure, and market forces, many of these 

lands could be targeted for solar energy facilities in the future 

(fig. 20; BLM, 2012c).

The primary environmental concerns associated with 

solar power generation include the large land area required for 

solar facilities and water consumption. Concentrating solar 

power systems generally require 5–10 acres (2 ha–4 ha) to 

produce 1 MW, and photovoltaic systems require around 10 

acres (4 ha) per MW. Additional impacts will include access 

roads and transmission lines. Although solar developments 

themselves are not similar to the infrastructure of energy 

developments discussed above, impacts to sage-grouse from 
III. Characterization of Important Threats and Issues 67

Figure 19A. Overlap of Federal oil shale leases and sage-grouse preliminary priority and preliminary general habitats (PPH and PGH). 

MZ, Management Zone.
68 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 19B. Overlap of the most likely geological prospects for oil shale and tar sands development and sage-grouse preliminary 

priority and preliminary general habitats (PPH and PGH, respectively). MZ, Management Zone.
III. Characterization of Important Threats and Issues 69

Figure 20. Overlap of photovoltaic-based estimates of solar power potential and sage-grouse preliminary priority and preliminary 

general habitats (PPH and PGH, respectively). MZ, Management Zone; KWh/M2/day, kilowatt hours per square meter per day.
70 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

direct habitat loss, habitat fragmentation via roads and transmission lines, noise, and increased human presence (Connelly 

and others, 2004) may be similar to those discussed for nonrenewable energy development. The information presented in 

this section as well as a detailed discussion of the technology 

required for generation of solar-based electricity can be found 

in the Programmatic Environmental Impact Statement (PEIS) 

for Solar Energy Development in Six Southwestern States 

(BLM, 2012c).

Geothermal

According to the Geothermal Energy Association (see 

Web site at geo-energy.org), geothermal energy is defined 

as heat from the Earth; heat continuously flowing from the 

Earth’s interior is estimated to be equivalent to 42 MW of 

power. Geothermal energy production within the range of 

sage-grouse is primarily within the Southern and Northern 

Great Basins MZs. As of 2011, approximately 2,000 km2

(494,200 acres) of sagebrush habitat has been leased for this 

purpose and an additional 1,140 km2

 (281,700 acres) are 

pending (Knick and others, 2011). The only type of geothermal energy that has been widely developed, currently, 

is hydrothermal energy, which consists of trapped hot water 

or steam, however technologies are evolving such that these 

developments may become an important consideration in the 

near future.

Impacts to sage-grouse associated with geothermal 

energy development have not been assessed because the development has been too recent to identify any immediate or lag 

effects (Knick and others, 2011), but geothermal power plants 

are similar to fossil-fuel-fired power plants in that resources 

are exploited in a highly centralized fashion, thus surface 

impacts could include the footprint of the power plant itself, 

access roads, and transmission lines. Extraction of geothermal 

fluids (gases, steam, and water) for power generation generally 

requires many of the same infrastructure features for construction and operation as do traditional nonrenewable energy 

resources. As such, impacts of geothermal developments to 

sage-grouse from direct habitat loss, habitat fragmentation 

via roads and transmission lines, noise, and increased human 

presence (Connelly and others, 2004) may be similar to those 

discussed for nonrenewable energy development with comparable effects on local sage-grouse populations also anticipated. 

Although geothermal development occurs throughout 

MZs III, IV, and V, the direct footprint is relatively small with 

approximately 141,800 acres (0.38 percent) of sage-grouse 

habitat directly impacted by geothermal leases in these MZs 

(table 15, fig. 21A). Geothermal developments are widespread 

in priority habitats in western portions of MZ III in particular. 

No geothermal development currently occurs in MZs I and 

II. However, geothermal development potential is distributed 

across a majority of priority and general habitats throughout 

the range of sage-grouse (fig. 21B).

Air and water pollution, disposal of hazardous waste, 

siting, and land subsidence are environmental concerns related 

to geothermal electricity generation; however, many of the air 

and water concerns are eliminated in closed-loop systems. In 

addition to these impacts, geothermal energy extraction may 

cause the release of toxic gases (carbon dioxide and hydrogen sulfide) and elements (arsenic) into the environment. The 

form, and subsequent effects, of these substances depends on 

the geological formation from which energy is being extracted. 

Large quantities of water may also be required for drilling and 

condenser cooling (Suter Ii, 1978), and if the water used for 

these purposes depletes the water resources of the surrounding 

habitat, riparian and brood-rearing habitats may be affected 

by water-table changes. On-site water storage may increase 

potential WNv (West Nile virus) exposure in the area (Friend, 

2001; Zou and others, 2006; Walker and others, 2007a; Walker 

and Naugle, 2011).

Hydrothermal energy, based on trapped water or steam, 

is the only type of geothermal energy that has been widely 

developed at this time. However, new technologies are being 

developed to exploit hot dry rock (accessed by drilling deep 

into rock), geopressured resources (pressurized brine mixed 

with methane), and magma (see Union of Concerned Scientists Web site at www.ucsusa.org) making these developments 

potentially important considerations for the near future and 

making direct and indirect effects on sage-grouse anticipated 

and logical, but speculative.

Mining

Besides oil and natural gas development, the major 

mining activity within sage-grouse habitats has been for coal 

(Braun, 1998). However, mining for other substances—especially bentonite, trona, and gravel—occurs throughout the 

range of the species, and mining and exploration for rare 

minerals (such as, gold, silver, and copper) has recently 

become more common and may influence sage-grouse habitats 

extensively in some regions. Coal mines are widespread, but 

discretely located in sage-grouse habitats MZ I and southern 

portions of MZs II and VII, and Federal leases developed 

through surface extraction directly influence approximately 

22,100 acres (89 km2

; <0.1 percent) of these MZs (table 16, 

fig. 22). There is potential for additional coal mining in large 

portions of priority and general habitats in MZs I, II, and VII 

(fig. 23). Indirect effects of surface coal mines with Federal 

leases were estimated using a 19-km (11.8-mi) effects buffer 

based on observations of industrial infrastructure effects on 

sage-grouse, which suggests influence over approximately 8 

percent of priority sage-grouse habitats across the range of 

the species and approximately 5 percent of priority habitats 

in MZs I, II, and VII. Approximately 36 percent of priority 

habitats that are indirectly influenced by coal mines across the 

species’ range are managed by BLM. Surface mining accounts 

for about 67 percent of production in the United States; large 

opencast mines can cover an area of many square kilometers. Coal mining and the use of coal to produce electricity 

raises a number of environmental challenges including soil 

erosion, dust, noise, water pollution, acid-mine drainage, and 
III. Characterization of Important Threats and Issues 71

Table 15. Summary of geothermal leases* across Management Zones (MZ) by acres of sage-grouse preliminary priority and 

preliminary general habitats (PPH and PGH, respectively).

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; 

NGB, Northern Great Basin.

air emissions in addition to impacts on local species. Burning 

coal releases oxides (especially of sulfur [SOx

] and nitrogen 

[NOx

]), trace elements (mercury, for example), and particulate 

matter into the atmosphere with potential effects on local, and 

global, habitat conditions. 

Other forms of mining (for example, bentonite, gravel, 

potash, and trona) can also influence sage-grouse habitats. The 

magnitude of the impacts of mining activities on sage-grouse 

and sagebrush habitats is largely unknown (Braun, 1998), 

but mining of various Federal mineral resources (locatable 

and saleable) currently affects approximately 3.6 percent of 

potential sage-grouse habitat directly (across all MZs) with 

indirect effects potentially affecting large portions (5–32 

percent) of some MZs (table 17A). In addition, existing leases 

for development of non-energy, leasable minerals represent a 

relatively small threat (spatially) but may ultimately be developed to their full, spatial extent based on existing agreements 

(table 17B).

Development of surface mines and associated infrastructure (such as, roads and power lines), noise, and human activity may negatively impact sage-grouse numbers in the short 

term (Braun, 1998), and a variety of mineral claims could 

result in industrial activities that would disrupt the habitat and 

life-cycle of sage-grouse (fig. 24). The number of displaying 

sage-grouse on 2 leks within 2 km (1.25 mi) of active mines 

in northern Colorado declined by approximately 94 percent 

during a 5-year period following an increase in mining activity (Remington and Braun, 1991). However, Braun (1998) 

reported recovery of populations in Montana, Wyoming, and 

Colorado may occur after initial development and subsequent 

reclamation of mine sites, although populations do not recover 

to pre-development sizes. Additionally, population re-establishment may take as long as 30 years (Braun, 1998).

A6. Fire 

Although large fires play an important role in landscape 

ecology for most of the Western United States, fire is much 

less important in the function of sagebrush-bunchgrass ecosystems than most forested systems (Keane and others, 2008). 

Given the suite of contributing disturbances, fire currently has 

largely negative effects on sage-grouse by directly affecting 

the distribution and condition of available sagebrush habitats 

(Nelle and others, 2000; Beck and others, 2009; Rhodes and 

others, 2010; Baker, 2011). Sage-grouse require the cover and 

forage provided by mature sagebrush and healthy herbaceous 

communities, and habitat selection research indicates strong 

selection at multiple scales and increased nesting success in 

areas with greater cover (Sveum and others, 1998a; Connelly 

and others, 2000c; Holloran and others, 2005; Aldridge and 

Boyce, 2007; Hagen and others, 2007; Yost and others, 2008; 

Kolada and others, 2009; Atamian and others, 2010; Carpenter and others, 2010; Doherty and others, 2010b; Bruce and 

others, 2011; Doherty and others, 2011a; Hagen and others, 

2011; Aldridge and others, 2012; Kirol and others, 2012; 

Tack and others, 2012). Wildfire and prescribed fires typically 

kill sagebrush thereby reducing cover and forage in the short 

term. However, fire is also associated with natural dynamics and spatial heterogeneity of many sagebrush ecosystems, 

suggesting that not all fires (wildfire or prescribed) in sagebrush communities have net-negative effects on sage-grouse 

populations and habitats. On the contrary, whereas vegetation 

and fuel management will likely preclude use of fire in some 

areas (for example, winter habitats or Wyoming big sagebrush 

habitats), the need to reduce tree cover (especially juniper) and 

fuel continuity (in mountain sagebrush communities of MZs 

II, IV, and V, for example) means that prescribed fire may be 

an important management option in other areas. If landscapescale habitat patterns stabilize and local populations are not 

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint 

(acres)

Direct 

Footprint 

(%)

SG Habitat 

(acres)

Direct 

Footprint 

(acres)

Direct 

Footprint 

(%)

MZ I–GP 11,636,400 0 0.00 34,663,000 0 0.00

MZ II and VII–WB & CP 17,476,000 0 0.00 19,200,200 0 0.00

MZ III–SGB 10,028,500 72,900 0.73 3,970,100 52,700 1.33

MZ IV–SRP 21,930,600 58,000 0.26 10,958,500 17,900 0.16

MZ V–NGB 7,097,200 10,900 0.15 5,808,000 31,800 0.55

*

Data Source: Aggregated from individual BLM State Office Submissions in 2011 and 2012.
72 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 21A. Overlap of Federal geothermal leases with sage-grouse preliminary priority and preliminary general habitats (PPH and 

PGH, respectively). MZ, Management Zone.
III. Characterization of Important Threats and Issues 73

Figure 21B. Overlap of geothermal occurrence potential in sage-grouse preliminary priority and preliminary general habitats (PPH and 

PGH, respectively). MZ, Management Zone.
Table 16. Summary of the direct and indirect influences of Federal surface coal leases* across Management Zones (MZ) by acres of preliminary prio

habitats (PPH and PGH, respectively). Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint1 (acres) 19 km Indirect Influence1 (acres) Direct Footprint1 (%) Relative Influence2 (%) SG Habitat (acres) Direct Footprint1 (acres) 19 km Indirect Influence1 (acres) 

F

MZ I–GP 11,636,400 5,700 335,900 0.05 2.89 34,663,000 202,600 2,685,600 

BLM 2,994,300 600 28,200 0.02 8 4,524,900 2,600 104,400 

Forest Service 292,400 0 53,800 0.00 16 515,300 32,900 189,000 

Tribal and Other Federal 219,700 0 100 0.00 0 2,427,700 0 14,100 

Private 7,132,500 5,100 229,800 0.07 68 24,682,800 164,500 2,203,400 

State 995,600 0 24,000 0.00 7 2,498,400 2,500 172,000 

Other 1,900 0 0 0.00 0 13,900 0 2,700 

MZ II and VII–WB & CP 17,476,000 16,400 1,325,000 0.09 7.58 19,200,200 35,700 1,873,200 

BLM 9,021,200 12,200 567,300 0.14 43 9,012,500 28,100 706,600 

Forest Service 162,000 0 0 0.00 0 452,500 0 1,400 

Tribal and Other Federal 784,000 2,400 31,000 0.31 2 1,354,600 0 5,700 

Private 6,233,900 1,200 663,200 0.02 50 7,394,800 7,500 1,074,400 

State 1,244,800 600 63,100 0.05 5 979,800 100 85,000 

Other 30,100 0 300 0.00 0 6,000 0 100 

MZ III–SGB 10,028,500 1,500 63,300 0.01 0.63 3,970,100 0 0 

BLM 6,309,400 1,100 22,900 0.02 36 3,199,800 0 0 

Forest Service 1,236,200 0 400 0.00 1 356,200 0 0 

Tribal and Other Federal 260,800 0 0 0.00 0 29,100 0 0 

Private 1,836,200 400 30,800 0.02 49 384,800 0 0 

State 385,900 0 9,300 0.00 15 200 0 0 

MZ IV–SRP 21,930,600 0 0 0.00 0.00 10,958,500 0 0 

MZ V–NGB 7,097,200 0 0 0.00 0.00 5,808,000 0 0 

*Data Source: Aggregated from individual BLM State Office Submissions in 2011 and 2012. Direct and indirect impacts are calculated for the surface management entity; how

may be severed from surface rights.

1Direct footprint is the co-location of surface coal mines within the designated habitat boundaries, and indirect influence is inferred by applying an effect buffer to the features 

be fully developed) and estimating the area affected. Indirect influence distance derived from area of identified demographic impact (Johnson and others, 2011; Taylor and other

2For each MZ, calculated as the percent of the particular sage-grouse habitat type influenced by the indirect impact of the threat. For management entities within each manage

percent of the total indirect impact in the management zone represented by that management entity, that is, the relative area of indirect influence among management entities. Smindividual entity totals and MZ summary values may exist due to rounding of estimates during calculations.
III. Characterization of Important Threats and Issues 75

Figure 22. Overlap of Federally managed surface coal leases, potential indirect influences of these leases, and preliminary priority and 

preliminary general habitats (PPH and PGH, respectively). MZ, Management Zone.
76 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 23. Overlap of coal occurrence and sage-grouse preliminary priority and preliminary general habitats (PPH and PGH, 

respectively). MZ, Management Zone.
Table 17A. Summary of the direct and indirect influences of mining and mineral materials disposal sites* (not including minerals mined as energy so

Zones (MZ) by acres of preliminary priority and preliminary general habitats (PPH and PGH, respectively).

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint1

(acres)

2.5 km 

Indirect 

Influence1

(acres)

Direct 

Footprint1

 (%)

Relative 

Influence2

(%)

SG 

Habitat 

(acres)

Direct 

Footprint1

(acres)

2.5 km 

Indirect 

Influence1

(acres)

F

MZ I–GP 11,636,400 122,900 687,500 1.06 5.91 34,663,000 504,000 1,994,700 

BLM 2,994,300 65,000 261,000 2.17 38 4,524,900 64,500 226,200 Forest Service 292,400 0 300 0.00 0 515,3 1,200 17,300 

Tribal and Other Federal 219,700 0 1,100 0.00 0 2,427,700 0 800 

Private 7,132,500 49,000 364,100 0.69 53 24,682,800 430,500 1,602,600 

State 995,600 8,900 61,100 0.89 9 2,498,400 7,800 147,800 

Other 1,900 0 0 0.00 0 13,900 0 0 

MZ II and VII–WB & CP 17,476,000 582,100 2,947,000 3.33 16.86 19,200,200 445,400 2,177,700 

BLM 9,021,200 484,400 1,922,300 5.37 65 9,012,500 362,200 1,301,300 

Forest Service 162,000 2,400 22,900 1.48 1 452,500 700 6,000 

Tribal and Other Federal 784,000 0 7,200 0.00 0 1,354,600 2,200 43,200 

Private 6,233,900 73,200 754,000 1.17 26 7,394,800 72,500 695,200 

State 1,244,800 22,000 238,600 1.77 8 979,800 7,800 132,000 

Other 30,100 100 2,000 0.33 0 6,000 0 0 

MZ III–SGB 10,028,500 914,800 3,263,700 9.12 32.54 3,970,100 478,800 1,620,600 

BLM 6,309,400 762,500 2,502,800 12.09 77 3,199,800 377,700 1,285,300 

Forest Service 1,236,200 42,400 250,300 3.43 8 356,200 44,200 144,400 

Tribal and Other Federal 260,800 100 14,000 0.04 0 29,100 0 6,100 

Private 1,836,200 106,400 437,500 5.79 13 384,800 56,900 184,600 

State 385,900 3,400 59,100 0.88 2 200 0 200 

MZ IV–SRP 21,930,600 719,100 4,320,800 3.28 19.70 10,958,500 330,500 1,872,400 

BLM 13,710,700 462,100 2,620,800 3.37 61 4,928,200 189,900 899,900 

Forest Service 1,613,800 113,700 427,000 7.05 10 1,113,500 56,500 239,900 Tribal and Other Federal 633,600 500 27,900 0.08 1 522,500 400 11,700 

Private 4,890,200 139,200 1,115,900 2.85 26 3,516,742 80,200 629,100 

State 1,019,373 3,600 127,600 0.35 3 846,200 3,400 91,200 

Other 62,900 0 1,500 0.00 0 31,400 0 600 
PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint1 (acres) 2.5 km Indirect Influence1 (acres) Direct Footprint1 (%) Relative Influence2 (%) SG Habitat (acres) Direct Footprint1 (acres) 2.5 km Indirect Influence1 (acres) 

F

MZ V–NGB 7,097,200 75,900 549,400 1.07 7.74 5,808,000 43,400 469,200 

BLM 5,117,500 71,500 452,800 1.40 82 4,196,700 39,900 348,100 

Forest Service 62,200 0 900 0.00 0 114,900 0 800 Tribal and Other Federal 717,100 900 27,100 0.13 5 101,800 300 10,200 

Private 798,000 3,500 44,600 0.44 8 1,199,000 3,000 93,600 

State 64,900 0 2,600 0.00 0 115,800 100 7,300 

Other 337,500 0 21,300 0.00 4 79,800 100 9,200 

*Data Source: Aggregated from individual BLM State Office Submissions in 2011 and 2012. Direct and indirect impacts are calculated for the surface management entity; how

may be severed from surface rights. 1Direct footprint is the co-location of surface mining activities within the designated habitat boundaries, and indirect influence is inferred by applying an effect buffer to the fe

affected. Indirect influence distance derived from estimated spread of exotic plants (Bradley and Mustard, 2006). 2For each MZ, calculated as the percent of the particular sage-grouse habitat type influenced by the indirect impact of the threat. For management entities within management 

of the total indirect impact in the management zone represented by that management entity, that is, the relative area of indirect influence among management entities. Table 17A. Summary of the direct and indirect influences of mining and mineral materials disposal sites* (not including minerals mined as energy so

Zones (MZ) by acres of preliminary priority and preliminary general habitats (PPH and PGH, respectively).—Continued Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G
III. Characterization of Important Threats and Issues 79

Table 17B. Summary of existing Federal mineral prospecting permits for non-energy, leasable resources* within preliminary priority 

and preliminary general sage-grouse habitats (PPH and PGH, respectively) by Management Zone (MZ).

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; 

NGB, Northern Great Basin.

perceived to be under direct threat from habitat loss, the ecological role of fire in releasing canopy dominance of sagebrush 

and stimulating systemic regeneration may justify the use of 

fire for management. 

The historical role of fire in sagebrush ecosystems has 

been difficult to estimate accurately, yet this information is 

important for guiding fuel and habitat treatments. Sagebrush 

generally does not provide direct evidence of previous fires 

(such as scarred wood on surviving individuals), so historic 

estimates were based on neighboring ecosystems and approximation. Early estimates indicated a range of possible return 

intervals ranging from as few as 13 to 100 years (Brown, 

1982; Wrobleski and Kauffman, 2003; Connelly and others, 2004; Crawford and others, 2004), but broad estimates 

extrapolated from local perspectives hide the complexity of 

this process within the sagebrush ecosystem. Using a robust 

approach to consider landscape heterogeneity and biotic 

potential along with evidence of previous disturbances, Baker 

(2011) described 200–350 year fire-return intervals in Wyoming sagebrush (Art. tri. wyomingensis), 150–300 years in 

mountain big sagebrush (Art. tri. ssp. vaseyana), and more 

than 200 years for little sagebrush (Art. tri. arbuscula). These 

values capture differences among sagebrush types and provide 

approximate time frames that support the juxtaposition of 

disturbance (fire) and recovery (in this case, re-colonization 

by sagebrush); additional information on fire and fire-return 

intervals, especially relating to particular ecological types and 

(or) conditions, is available in the literature (Nelle and others, 2000; Miller, 2001; West and Yorks, 2002; Mensing and 

others, 2006; Lesica and others, 2007; Miller and Heyerdahl, 

2008), and consideration of these and other local details may 

be necessary for comprehensive planning and mitigation. 

Fire regimes are complex and vary tremendously across 

the sagebrush region and through time; furthermore, the 

ecological role of fire has changed dramatically since the 

European settlement era (circa 1850) due to changing fuel 

and habitat patterns (Crawford and others, 2004). Though the 

presence and distribution of suitable sagebrush habitats is limited at landscape scales, precluding the need for disturbances 

to intact sagebrush communities (Beck and others, 2009), 

maintenance of healthy sagebrush communities includes some 

localized disturbances in many regions. Because of the slow 

recovery time of most sagebrush species (none of the native 

big sagebrush species truly sprout, although reproduction by 

layering [akin to sprouting] from the root-crown has been 

described in the mountain variety, Art. tri. ssp. vaseyana; Winward, 2004), patterns of fire-free periods within a region are 

very important in determining landscape composition, habitat 

structure, and fire behavior. Three-tip (Art. tripartita) may 

increase after fire because it sprouts; however, three-tip is less 

preferred by nesting grouse (Lowe and others, 2009). In some 

higher elevation habitats, where mountain big-sagebrush is the 

canopy dominant, rapid regeneration due to site potential, seed 

production, and layering can produce 25 percent cover within 

20 years (Winward, 2004). 

Information on the variability of fire and fire-free periods 

across this landscape over time is limited, but the vast sea of 

sagebrush described by trappers, early European settlers, and 

official surveys would not have been possible under highfrequency fire regimes (Baker, 2011). There is little evidence 

that fire will enhance sage-grouse habitat in Wyoming big 

sagebrush communities, especially where there is already a 

balance of native shrubs, perennial grasses, and forbs (Crawford and others, 2004).There is a growing body of evidence 

that suggests that on the current landscape even prescribed 

fire designed to enhance brood-rearing habitat values does not 

have positive effect on herbaceous habitat conditions and can 

cause demonstrable decline in valuable sagebrush cover (Beck 

and others, 2009). Therefore, use of fire is not recommended 

strictly for sagebrush habitat enhancement (Baker, 2006; Beck 

and others, 2009). 

Due to increased fuel potentials caused by annual grasses 

(Bromus tectorum, Taenatherum asperum) and landscape-scale 

decrease in intact sagebrush habitats (fragmentation), wildfire 

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Direct 

Footprint 

(acres)

Direct 

Footprint 

(%)

SG Habitat 

(acres)

Direct 

Footprint 

(acres)

Direct 

Footprint 

(%)

MZ I–GP 11,636,400 10,400 0.09 34,663,000 28,200 0.08

MZ II and VII–WB & CP 17,476,000 378,400 2.17 19,200,200 557,100 2.90

MZ III–SGB 10,028,500 33,900 0.34 3,970,100 23,500 0.59

MZ IV–SRP 21,930,600 7,100 0.03 10,958,500 4,900 0.04

MZ V–NGB 7,097,200 0 0.00 5,808,000 0 0.00

*

Aggregated from individual BLM State Office Submissions in 2011 and 2012. Overall acres for the valid existing right are reported for the MZ, 

however, note that subsurface mineral rights may be severed from surface rights.
80 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 24. Overlap of Federal mining- and mineral-material disposal sites, potential indirect influences of these areas, and sagegrouse preliminary priority and preliminary general habitats (PPH and PGH, respectively). MZ, Management Zone.
III. Characterization of Important Threats and Issues 81

represents an important threat to habitat conservation and 

population stability (U.S. Fish and Wildlife Service, 2010b). 

Recent estimates indicate that the fire suppression era has had 

little effect on sagebrush ecosystem conditions due to the naturally long fire-return intervals (Baker, 2011); however, accumulation of fuels and volatile weather conditions may increase 

the importance of fuel breaks and related defense strategies for 

protecting priority habitats from wildfires. Current sage-grouse 

populations are limited by the distribution of suitable habitats, 

and near-term detrimental effects of fire on habitat suitability 

indicate a need to control fire in important sagebrush ecosystems. Ironically, the strategic use of fire to control fuels, as 

well as woodland expansion, may be warranted.

Assessment of fires reported to the National Interagency 

Fire Center (NIFC) occurring within designated habitats (PPH 

and PGH) from 2000–2012 (the years where reporting is considered to be mostly complete for fire perimeters rather than 

point locations for the study area) indicates that annual losses 

within most MZs have been minimal (2 percent or less); however, nearly 14 percent of PPH and 17 percent of PGH burned 

in MZ IV, 17 percent and 6 percent in MZ V (PPH and PGH, 

respectively), and 1.7 and 5.7 percent of MZ III (PPH and 

PGH, respectively) in recent years (2000–2012; table 18 and 

fig. 25). Wildfires in 2012 directly affected sagebrush habitats 

with sage-grouse populations in Nevada, California, Oregon, 

and Wyoming. Clearly, this time frame (one decade) is insufficient to assess the accumulation of fire and fire effects across 

the sagebrush landscape; however, this perspective is provided 

as a spatially consistent summary of recent fire occurrence that 

should be supplemented by additional data where available. 

Because the typical recovery time for sagebrush communities 

impacted by fire is several decades, the reporting period used 

here underrepresents some recent events that continue to affect 

habitat conditions, such as the large fires in the Great Basin 

during the late 1990s (BLM, 1999). Challenges related to fire 

and fuels management have become pronounced and sometimes extreme in the Great Basin (MZs III and V) and parts of 

the Snake River Plain (MZ IV) where cheatgrass has invaded, 

changed fuel profiles, and subsequently enhanced fire behavior 

by increasing surface intensity and decreasing return intervals 

(Knapp, 1996; Epanchin-Niell and others, 2009; Shinneman 

and Baker, 2009; Rowland and others, 2010; Baker, 2011; 

Condon and others, 2011). Minimizing disturbance within 

remnant sagebrush communities deemed important for sagegrouse conservation might include a combination of wildfire 

control as well as adjusting use standards (for example, grazing, energy development, and recreation) to avoid treatments 

and activities that remove sagebrush, degrade native herbaceous species, and (or) promote cheatgrass expansion. In 

areas with widespread loss of sagebrush and replacement with 

cheatgrass, active restoration may be required (see section III. 

A11. Habitat Treatments and Vegetation Management). Revegetation following fire is expensive compared to letting “natural 

regeneration processes” run their course, but the opportunity 

to reduce fire potential, increase forage quality, and increase 

habitat quality based on intensive revegetation efforts may 

justify these actions in some habitats (Epanchin-Niell and others, 2009). For example, stabilization of surface soils, prevention of noxious weed infestations, and re-establishment of 

native species are important vegetation management priorities, 

which may benefit from post-fire rehabilitation. Research and 

development of cheatgrass control strategies are ongoing, but 

management of the fire-return interval and fuel profile created 

by cheatgrass is recognized as a fundamental component of 

cheatgrass control efforts. Further, support and enhancement 

of deep-rooted, native, perennial plants may be important in 

the control of cheatgrass and post-disturbance response of the 

community (Balch and others, 2012). 

Although precise occurrence of future fire is impossible 

to determine due to complicated interactions of weather, vegetation, and ignition, the distribution of fuel profiles have been 

used to estimate probability for development of large fires (see 

National Interagency Fire Center Geographic Area Coordination Centers Web site at http://gacc.nifc.gov/rmcc/predictive/

firedngr.htm). Fuel models indicate vast acreages in all MZs, 

which are susceptible to fire with the most dramatic numbers 

occurring in MZs III, IV and V (63 percent, 84 percent, and 68 

percent of PPH, and 60 percent, 76 percent, and 64 percent of 

PGH, respectively; table 19 and fig. 26)

In contrast, lack of fire at higher elevations, where 

moisture and productivity are greater than neighboring communities at lower elevations, has contributed to an increase in 

juniper cover (Miller and Rose, 1995; Miller and others, 2000; 

Miller and Heyerdahl, 2008; Sankey and Germino, 2008; 

Shinneman and others, 2008; Bradley, 2010). In these areas, 

active restoration using fire or “fire-mimic” (mechanical) 

treatments may be needed to maintain sage-grouse habitats by 

reducing juniper cover (Bradley, 2010; Rowland and others, 

2010). Importantly, all sites do not have equal restoration 

potential, with the greatest potential being in the least altered 

locations where vegetation and soils can readily recover 

(Shinneman and others, 2008), but recovery processes may be 

supported and enhanced through methods and timing of application (Bates and others, 2011; Rau and others, 2011).

Because of the important value of sagebrush canopies 

and tall grasses for nesting cover (Holloran and others, 2005; 

Beck and others, 2009), wildfires and prescribed fires (and 

treatments with similar effects on vegetation) that reduce 

these values are likely detrimental for sage-grouse. On the 

other hand, fire control and mitigation represents an important 

component of modern habitat management due to the recently 

perceived (circa 50 years) threat of wildfire in many areas, 

including sage-grouse habitats (fig. 26). Particular caution and 

concern is warranted when noxious invasive species (notably, 

but not limited to, cheatgrass) are present in the pre-disturbance community because these species may have lasting, 

detrimental effects on post-disturbance habitat conditions. The 

threat of large wildfires in priority habitats, potentially resulting in removal of large stands of mature sagebrush, remains 

one of the most important and difficult to control obstacles to 

sage-grouse conservation.
Table 18. Summary of fires reported* to National Interagency Fire Center between 2000–2012, across Management Zones (MZ) by acres within preli

preliminary general habitats (PPH and PGH, respectively). Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Yearly Max Area Burned (acres) Yearly Min Area Burned Average Area Burned (acres/yr) Area Burned 2000–2012 (%) Relative Influence1 (%) SG Habitat (acres) Yearly Max Area Burned (acres) Yearly Min Area Burned A

B

(ac

MZ I–GP 11,636,400 70,900 100 14,329 1.6 34,663,000 279,700 100 6

BLM 2,994,300 10,800 0 2,212 1.0 15 4,524,900 24,600 0 

Forest Service 292,400 1,000 0 136 0.6 1 515,300 34,600 0 

Tribal and Other Federal 219,700 22,100 0 1,702 10.1 12 2,427,700 29,500 0 

Private 7,132,500 55,500 0 8,990 1.6 63 24,682,800 189,300 0 4

State 995,600 6,100 0 1,289 1.7 9 2,498,400 19,400 0 

Other 1,900 0 0 0 0.0 0 13,900 0 0 

MZ II and VII–WB & CP 17,476,000 27,100 200 7,661 0.6 19,200,200 161,100 400 2

BLM 9,021,200 8,100 0 2,943 0.4 38 9,012,500 25,500 200 

Forest Service 162,000 8,800 0 966 7.7 13 452,500 6,800 0 

Tribal and Other Federal 784,000 13,600 0 1,388 2.3 18 1,354,600 126,000 0 1

Private 6,233,900 4,500 100 1,411 0.3 18 7,394,800 34,200 100 State 1,244,800 8,100 0 953 1.0 12 979,800 4,800 0 

Other 30,100 0 0 0 0.0 0 6,000 0 0 

MZ III–SGB 10,028,500 55,900 0 13,500 1.8 3,970,100 55,000 0 1

BLM 6,309,400 44,700 0 9,397 1.9 70 3,199,800 30,900 0 

Forest Service 1,236,200 3,100 0 527 0.6 4 356,200 4,600 0 

Tribal and Other Federal 260,800 1,100 0 129 0.6 1 29,100 900 0 

Private 1,836,200 9,300 0 2,559 1.8 19 384,800 26,800 0 

State 385,900 4,300 0 888 3.0 7 200 0 0 
Table 18. Summary of fires reported* to National Interagency Fire Center between 2000–2012, across Management Zones (MZ) by acres within preli

preliminary general habitats (PPH and PGH, respectively).—Continued

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG 

Habitat 

(acres)

Yearly 

Max 

Area 

Burned 

(acres)

Yearly 

Min 

Area 

Burned

Average 

Area 

Burned 

(acres/yr)

Area 

Burned 

2000–2012 

(%)

Relative 

Influence1

(%)

SG 

Habitat 

(acres)

Yearly 

Max 

Area 

Burned 

(acres)

Yearly 

Min 

Area 

Burned

A

B

(ac

MZ IV–SRP 21,930,600 1,030,400 0 239,769 14.2 10,958,500 442,900 0 14

BLM 13,710,700 790,600 0 181,646 17.2 76 4,928,200 361,000 0 10

Forest Service 1,613,800 89,700 0 9,509 7.7 4 1,113,500 117,500 0 1

Tribal and Other Federal 633,600 53,000 0 5,407 11.1 2 522,500 64,200 0 

Private 4,890,200 189,000 0 37,313 9.9 16 3,516,742 69,400 0 1

State 1,019,373 30,500 0 4,954 6.3 2 846,200 12,600 0 

Other 62,900 11,500 0 940 19.4 0 31,400 1,400 0 

MZ V–NGB 7,097,200 950,500 0 95,441 17.5 5,808,000 136,000 0 2

BLM 5,117,500 877,700 0 83,677 21.3 88 4,196,700 124,300 0 2

Forest Service 62,200 2,000 0 199 4.2 0 114,900 7,700 0 

Tribal and Other Federal 717,100 7,500 0 1,082 2.0 1 101,800 800 0 

Private 798,000 45,600 0 7,091 11.6 7 1,199,000 9,700 0 

State 64,900 4,100 0 411 8.2 0 115,800 2,500 0 

Other 337,500 22,900 0 2,981 11.5 3 79,800 900 0 

*Data Source: Geospatial Multi-Agency Coordination (GeoMAC) Group, 2012.1For management entities within a Management Zone, calculated as the percent of the total acres burned during the time period within the management zone represented by th

the relative area of direct influence among management entities. Small differences between individual entity totals and MZ summary values may exist due to rounding of estimaaverages were calculated independently from entity estimates; therefore, items in columns with averages may not sum equivalently.
84 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 25. Overlap of fires reported to National Interagency Fire Center between 2000–2012 and preliminary priority and preliminary 

general habitats (PPH and PGH, respectively). MZ, Management Zone.
PPH PGH

Management Zone

Entity

SG Habitat 

(acres)

High Burn 

Probability 

(acres)

High Burn 

Probability 

(%)

Relative 

Influence1

(%)

SG Habitat 

(acres)

High Burn 

Probability 

(acres)

Hig

Pro

MZ I–GP 11,636,400 1,921,000 16.5 34,663,000 6,140,700 

BLM 2,994,300 299,200 10.0 16 4,524,900 718,800 

Forest Service 292,400 124,900 42.7 7 515,300 208,800 

Tribal and Other Federal 219,700 39,600 18.0 2 2,427,700 67,800 

Private 7,132,500 1,271,600 17.8 66 24,682,800 4,621,600 

State 995,600 185,800 18.7 10 2,498,400 523,700 

Other 1,900 0 0.0 0 13,900 0 

MZ II and VII–WB & CP 17,476,000 2,104,300 12.0 19,200,200 1,678,400 

BLM 9,021,200 862,000 9.6 41 9,012,500 402,600 

Forest Service 162,000 31,100 19.2 1 452,500 182,700 

Tribal and Other Federal 784,000 180,100 23.0 9 1,354,600 435,900 

Private 6,233,900 871,200 14.0 41 7,394,800 593,300 

State 1,244,800 151,600 12.2 7 979,800 62,700 

Other 30,100 8,400 27.9 0 6,000 1,300 

MZ III–SGB 10,028,500 6,312,300 62.9 3,970,100 2,391,600 

BLM 6,309,400 4,583,100 72.6 73 3,199,800 1,990,900 

Forest Service 1,236,200 280,500 22.7 4 356,200 78,900 

Tribal and Other Federal 260,800 120,000 46.0 2 29,100 6,500 

Private 1,836,200 1,137,600 62.0 18 384,800 315,200 

State 385,900 191,000 49.5 3 200 100 

MZ IV–SRP 21,930,600 18,423,300 84.0 10,958,500 8,305,700 

BLM 13,710,700 11,904,200 86.8 65 4,928,200 4,438,100 

Forest Service 1,613,800 1,163,200 72.1 6 1,113,500 621,400 

Tribal and Other Federal 633,600 487,200 76.9 3 522,500 301,900 

Private 4,890,200 4,068,100 83.2 22 3,516,742 2,268,400 

State 1,019,373 738,700 72.5 4 846,200 649,700 

Other 62,900 62,000 98.6 0 31,400 26,300 

Table 19. Summary of areas with fuel models* that project a high probability of developing large fires across each management Zone (MZ) by acres 

preliminary general habitats (PPH and PGH, respectively). 

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G
Table 19. Summary of areas with fuel models* that project a high probability of developing large fires across each Management Zone (MZ) by acres 

preliminary general habitats (PPH and PGH, respectively).—Continued Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) High Burn Probability (acres) High Burn Probability (%) Relative Influence1 (%) SG Habitat (acres) High Burn Probability (acres) Hig

Pro

MZ V–NGB 7,097,200 4,858,900 68.5 5,808,000 3,729,300 

BLM 5,117,500 3,545,800 69.3 73 4,196,700 2,801,300 Forest Service 62,200 29,900 48.1 1 114,900 40,300 Tribal and Other Federal 717,100 351,100 49.0 7 101,800 77,000 Private 798,000 589,400 73.9 12 1,199,000 689,500 State 64,900 49,300 76.0 1 115,800 74,200 Other 337,500 293,200 86.9 6 79,800 47,100 

*Data Source: National Interagency Fire Center (NIFC) 2012, Geographic Area Coordination Centers, available at http://gacc.nifc.gov/rmcc/predictive/firedngr.htm. 1For management entities within a Management Zone, calculated as the percent of the total direct impact in the management zone represented by that management entity that 

influence among management entities. Small differences between individual entity totals and MZ summary values may exist due to rounding of estimates during calculations.
III. Characterization of Important Threats and Issues 87

Figure 26. Overlap of areas modeled with a high probability for occurrence of large fires and preliminary priority and preliminary 

general habitats (PPH and PGH, respectively). MZ, Management Zone.
88 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

A7. Invasive Plants 

Because of the strong interactions between disturbance, 

niche availability, and the “colonist” nature of most invasive 

species, presence of invasive species is a mechanism whereby 

a disturbance holds the potential for a strong, negative effect 

on habitat quality due to the post-disturbance response (Crawford and others, 2004). In Wyoming big sagebrush types, 

especially in the Great Basin (all or part of MZs III, IV, and 

V), the invasion by exotic annuals has resulted in dramatic 

increases in number and frequency of fires with widespread, 

detrimental effects on habitat conditions (Young and Evans, 

1978; West and Young, 2000; West and Yorks, 2002; Connelly 

and others, 2004). For example, big sagebrush communities invaded by cheatgrass have estimated mean fire-return 

intervals of less than 10 years in many areas (Connelly and 

others, 2004), whereas the natural regime is estimated (conservatively) to be 10 to 20 times longer. Increased fire frequency 

or intense fire behavior typically results in removal of the 

sagebrush canopy in affected areas and often with replacement by annual species that provide little, to no, habitat value 

(Knapp, 1996; Epanchin-Niell and others, 2009; Rowland and 

others, 2010; Baker, 2011; Condon and others, 2011). Presumably cheatgrass (Bromus tectorum) was able to thrive in 

this region, in part because there was no pre-existing (native) 

dominant annual plant species. As this optimal colonist species established, chronic grazing by cattle, sheep, and horses 

combined with drought and fire to increase the distribution 

and frequency of disturbance and further optimize this region 

for dominance by an annual grass (Knapp, 1996). Importantly, 

research in sagebrush ecosystems has revealed an inverse 

relation between cheatgrass dominance and native perennial 

herbs, especially grasses (West and Yorks, 2002). Further, the 

post-disturbance response of sagebrush communities to fire 

and similar disturbances is strongly affected by the condition 

and composition before disturbance, the presence of propagules, and sprouting of native species (West and Yorks, 2002; 

Beck and others, 2009; Epanchin-Niell and others, 2009; 

Condon and others, 2011). Cheatgrass competes with native 

grasses and forbs that are important components of sagegrouse habitat. Cheatgrass abundance is negatively correlated 

with habitat selection by sage-grouse (Kirol and others, 2012) 

indicating that changes in composition and structure associated with cheatgrass specifically degrade sage-grouse habitat. 

Invasion by Medusahead (Taeniatherum caput-medusae), 

which can replace cheatgrass in some circumstances, may be 

even worse as it also reduces perennial productivity, degrades 

wildlife habitat, supports high-frequency fire-return intervals, 

and requires intensive treatment for restoration (Davies, 2010). 

Infestation of these species, and others, cause direct degradation of sagebrush habitats resulting in (indirect) effects on 

local sage-grouse populations by affecting forage and cover 

quality with potential to cause complete avoidance (funtional 

habitat loss).

In southern habitats (MZs III, IV, V, and VII), cheatgrass 

is found primarily at elevations between 5250 and 6550 ft 

(1,600–2,000 m), compared to 1950 to 5900 ft (600–1,800 

m) in the sagebrush-steppe of Idaho and has been expanding 

in habitats below to 3900 ft (1,200 m; Connelly and others, 2004). Large-scale restoration is needed in many areas, 

making minimally invaded areas highly valuable for habitat 

conservation. In the sagebrush-steppe of northern habitats 

(all or parts of MZs I, II, IV, V, and VI), cheatgrass is less 

ubiquitous but demonstrates increased dominance, productivity, and elevation range on south-facing slopes (Connelly 

and others, 2004), which indicates the need for careful local 

considerations and best-practices that minimize disturbance 

in areas with a threat (presence) of cheatgrass expansion. 

Potential for cheatgrass occurrence has been modeled in the 

Great Basin region based on environmental correlations, 

which can help discern locations and habitats that have the 

greatest risk, either because cheatgrass is already on those 

landscapes (some of the risk has been realized) or the conditions are right to support cheatgrass (fig. 27A). Summary data 

indicate that invasion potential is widespread and similar 

among assessed MZs (table 20). Although the distribution of 

cheatgrass, and other annual invaders such as Japanese brome 

(Bromus arvensis), has been documented across shrub and 

grasslands of Colorado, Wyoming, and Montana, the currently 

available model was only parameterized for the Great Basin, 

therefore only MZs III, IV and V are described here (table 20, 

fig. 27A). Similar information is being developed rangewide, 

as well as with subregional details. Due to the emerging nature 

of invasive plants, especially cheatgrass, information and 

rapid changes in species’ distributions, details of invasion, 

control, and risks will be best provided by local information 

and subregional to regional-scale models. Data presented here 

demonstrate the potential risk to priority habitats within the 

Great Basin and Snake River Plain based on a spatial model 

developed using field observations and geographic information system (GIS) representation of dominant environmental patterns (that predict and [or] restrict the distribution of 

the species). Model results suggest the most serious risk of 

cheatgrass invasion (in these analytical units) lies in the Snake 

River Plain where more than 50 percent of PPH and PGH 

are projected to be at risk of cheatgrass invasion (table 20). 

Assessment of regional habitat management issues by Wisdom 

and others (2005) highlighted concerns regarding expansion 

risk for cheatgrass and further specified the need for active 

restoration methods to improve sagebrush habitat conditions 

where fire and invasive species represent an interactive threat. 

The northern Great Basin follows this pattern closely with 

nearly 50 percent of preliminary priority habitats (PPH) and 

36 percent of preliminary general habitats (PGH) threatened 

according to this independent, non-overlapping estimate, and 

similarly 31 percent and 43 percent of PPH and PGH, respectively, of the southern Great Basin MZ III is projected to share 

this level of risk. Importantly, most (more than 50 percent) of 

the affected lands in each MZ are managed by BLM and < 2% 

of the affected areas are USFS managed shrublands according 

to these data (table 20).
III. Characterization of Important Threats and Issues 89

Figure 27A. Overlap of moderate to high probability of cheatgrass occurrence and preliminary priority and preliminary general habitats 

(PPH and PGH, respectively) in Management Zones III, IV and V (Great Basin) from logistic regression models. MZ, Management Zone.
Table 20. Summary of lands with moderate to high probability for cheatgrass occurrence* across Management Zones (MZ) by acres of preliminary p

general habitats (PPH and PGH, respectively). Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint (acres) Direct Footprint (%) Relative Influence1 (%) SG Habitat (acres) Direct Footprint (acres) D

Fo

MZ I–GP 11,636,400 n/a n/a n/a 34,663,000 n/a 

MZ II and VII–WB & CP 17,476,000 n/a n/a n/a 19,200,200 n/a MZ III – SGB 10,028,500 3,143,000 31.3 3,970,100 1,716,800 

BLM 6,309,400 2,154,300 34.1 69 3,199,800 1,400,200 Forest Service 1,236,200 72,500 5.9 2 356,200 33,900 Tribal and Other Federal 260,800 90,500 34.7 3 29,100 8,800 Private 1,836,200 723,600 39.4 23 384,800 273,900 State 385,900 102,000 26.4 3 200 0 

MZ IV–SRP 21,930,600 11,657,100 53.2 10,958,500 6,401,100 

BLM 13,710,700 7,796,700 56.9 67 4,928,200 3,542,300 Forest Service 1,613,800 176,000 10.9 2 1,113,500 140,800 

Tribal and Other Federal 633,600 458,900 72.4 4 522,500 304,900 Private 4,890,200 2,732,800 55.9 23 3,516,742 1,909,500 State 1,019,373 459,700 45.1 4 846,200 474,100 Other 62,900 33,000 52.5 0 31,400 29,500 

MZ V–NGB 7,097,200 3,521,300 49.6 5,808,000 2,096,700 

BLM 5,117,500 2,590,200 50.6 74 4,196,700 1,483,600 Forest Service 62,200 23,200 37.3 1 114,900 11,700 

Tribal and Other Federal 717,100 625,900 87.3 18 101,800 40,100 Private 798,000 176,100 22.1 5 1,199,000 502,100 

State 64,900 17,700 27.3 1 115,800 33,600 

Other 337,500 88,200 26.1 3 79,800 25,500 

*Data Source: Meinke, C.W., S.T. Knick, and D.A. Pyke (2009). A spatial model to prioritize sagebrush landscapes in the intermountain west (U.S.A.) for restoration. Restora1For management entities within a Management Zone, these were calculated as the percent of the total direct impact in the management zone represented by that management 

of direct influence among management entities. Small differences between individual entity totals and MZ summary values may exist due to rounding of estimates during calcul
III. Characterization of Important Threats and Issues 91

Because of ecological and morphological characteristics, 

cheatgrass can often out-compete native perennial plants and 

promote rapid fire-return intervals (Klemmedson and Smith, 

1964; Connelly and others, 2004). The positive feedback 

cycle connecting fire, sagebrush loss, and cheatgrass dominance has resulted in entire landscapes being converted to 

annual grasslands (D’Antonio and others, 2009), and these 

areas typically require active restoration, including costs and 

effort, associated with eradication of weeds and reseeding of 

native species, if local priorities indicate important potential 

habitat value for restored lands. Based on the scale of such 

efforts, locally planned and implemented sagebrush restoration efforts will likely benefit from planning and perspectives 

provided by regional scales to strategically combat the spread 

and dominance of invasive annuals in priority habitats and 

connected areas. 

Invasive plants are thought to alter plant community 

structure and composition, productivity, nutrient cycling, and 

hydrology (Vitousek, 1990) and may competitively exclude 

native plant populations (Mooney and Cleland, 2001). In 

particular, invasive plants can reduce and eliminate vegetation 

that sage-grouse use for food and cover resulting in habitat 

loss and fragmentation. An assortment of nonnative annuals and perennials and native conifers are currently invading 

sagebrush ecosystems. Many areas throughout the range of 

sage-grouse are at high risk from invasive plants, yet the most 

concentrated areas of risk include the Intermountain West 

and Great Basin (MZs III, IV, V, and VI). Much of the Great 

Basin is at risk for invasion by cheatgrass or pinyon-juniper 

encroachment within the next 30 years (Wisdom and others, 

2005; Leu and others, 2008; Doherty and others, 2008), and 

where cheatgrass has invaded, there has typically been an 

increase in fire frequency resulting in further degradation of 

sage-grouse habitats by removing and excluding sagebrush 

(Knapp, 1996; Epanchin-Niell and others, 2009; Rowland and 

others, 2010; Baker, 2011; Condon and others, 2011). Regions 

that are currently invaded or predicted by distribution models 

to be highly susceptible may benefit from explicit guidance 

and practices that avoid, eliminate, or mitigate feedbacks in 

this cycle, including natural disturbances, over-grazing, treatments, new roads, and industrial developments that disrupt 

native vegetation cover and destabilize soils. Disrupting 

the processes that generate chronic disturbance and thereby 

facilitate dominance of annual plants is a necessary first step 

in the restoration and conservation process. Even at low levels, 

invasive plants can decrease forage quality and compete with 

native species that provide high-quality habitat values for 

sage-grouse and productive agricultural systems for people. 

This decline can be expected to cause a decrease in secondary productivity (in this case, sage-grouse), but potential for 

infestation, upon disturbance, with more significant implications for conditions must be an important consideration when 

problem species are present. In cases of severe infestation, 

system phenology (timing of green-up), cover and forage quality, and fire regimes are often altered with widespread, severe, 

and detrimental effects on sage-grouse habitat conditions. The 

relation between cheatgrass and fire in degrading sagebrush 

habitats is well documented, and this interaction continues to 

challenge management and restoration efforts—considerable 

research and development effort is needed to reduce this threat 

(Wisdom and others, 2005).

A8. Conifer Woodland Expansion and 

Encroachment 

Expansion of conifer woodlands, especially juniper 

(Juniperus spp.) present a threat to sage-grouse because they 

do not provide suitable habitat, and further, mature trees 

displace shrubs, grasses and forbs through direct competition 

for resources that are important components of sage-grouse 

habitat; juniper expansion is associated with increased bare 

ground and an increased potential for erosion (Petersen and 

others, 2009). Mature trees may offer perch sites for raptors, 

thereby, woodland expansion may also represent expansion 

of raptor predation threat, similar to perches on power lines, 

poles and other structures (also see Section III. C. Predation). 

Although the prolonged drought at the beginning of the 21st 

century (2002–2004) caused significant (55 percent) mortality 

of mature pinyon pine (Clifford and others, 2011), reducing 

the threat attributed to this species in some areas, increased 

pinyon-juniper forest density and distribution continue to be 

documented following the drought period and are recognized 

as a threat to the sagebrush ecosystem in other areas (Romme 

and others, 2009; Bradley, 2010; Rowland and others, 2010). 

Intensive grazing in the late 1800s and early 1900s, coupled 

with climate and fire, have been associated with invasion of 

annual grasses at lower elevations and expansion of juniper 

and pinyon pine at higher elevations (Burkhardt and Tisdale, 

1976; Miller and others, 1994; Provencher and others, 2007; 

Miller and others, 2011). Precipitation and fire are thought 

to drive long-term trends in cover (Clifford and others, 

2011; Miller and others, 2011), and disturbance-free periods 

coupled with grazing that reduced competition and precipitation that supplied moisture for seedlings increased success of 

tree establishment and woodland expansion during the 20th 

century (Miller and Rose, 1995; Strand and others, 2007; 

Miller and others, 2011). In some areas (best documented in 

MZs III, IV, and V, and VI), conifer encroachment is connected to reduced habitat quality in important seasonal ranges 

when woodland development is sufficient to restrict shrub and 

herbaceous production (Connelly and others, 2004). Though 

widespread, this problem affects specific sagebrush habitats 

and sage-grouse populations because of local juniper and 

pinyon-juniper woodland expansions; notably, USFS research 

indicated more than 55 percent of Great Basin sagebrush 

ecosystems (MZs III and V) are at risk of cheatgrass invasion, 

whereas approximately 40 percent of this same landscape was 

at risk of displacement by juniper expansion. The encroachment problem is likely exacerbated by adjacent land uses and 

cheatgrass invasions that have decreased the habitat values in 

nearby, lower elevation big sagebrush communities, thereby 
92 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

increasing the importance of remaining habitats. Thus it may 

be important to consider surrounding land use when prioritizing habitats for treatment to insure that the net result is more 

usable (for example, accessible to local populations) sagegrouse habitat across the local and regional landscape. Further, 

whereas juniper may have negative implications for sagegrouse habitat quality, these areas can provide important winter range for ungulates (Anderson and others, 2012) indicating 

potential interactions among multiple species and habitat 

functions at the sagebrush-forest ecotone. These locations can 

be mapped with reasonable accuracy; therefore, encroachment 

within priority habitats may be specifically targeted. Regional 

modeling efforts suggested that locations within 3280 ft (1,000 

m) of current pinyon-juniper woodlands have the greatest (20 

percent) juniper-expansion risk and locations beyond this distance, 3280 to 6550 ft (1,000–2,000 m), experience one-half 

of this potential (Bradley, 2010). Based on a simple proximity 

modeling approach, whereby sagebrush habitats in close proximity (820 ft [250 m]) to an existing conifer woodland (especially juniper and pinyon pine, but also ponderosa pine and 

Douglas-fir) are recognized as having increased invasion risk 

due to proximity of the seed source, we estimate that 6 to 13 

percent of sage-grouse habitat within all MZs may be at risk 

of conifer expansion. The most pronounced risks are, again, 

across the Great Basin where an estimated 13 percent (both 

PPH and PGH; southern Great Basin) and 10 to 12 percent 

(PGH and PPH, respectively; northern Great Basin) are predicted to be at risk (table 21, fig. 27B). Though substantial, the 

estimated risks in the Snake River Plain (7 to 8 percent PPH 

and PGH, respectively) and Wyoming Basin (6 to 7 percent 

PPH and PGH, respectively) are perceived to be smaller (that 

is, less area projected to be affected). Importantly, the acreage of predicted woodland expansion is one-half of the area 

projected for cheatgrass risk, and not all of these areas will be 

invaded uniformly or completely. In addition, acreage projected to be a “high fire risk” is 2 to 10 times greater (depending on MZ) than the area of projected conifer expansion. 

Although the precise probability and realization of woodland 

expansion will likely vary (from these model results) within 

zones identified, based on local environmental conditions, for 

example, this risk assessment identified large portions of sagegrouse habitat in MZs III, IV, and V as at risk of tree invasion 

based on proximity to seed sources (table 21) making this a 

potentially important consideration for managing habitats in 

those regions.

Prescribed fire is often used as an affordable and 

seminatural means to control woody invasion and restore 

invaded communities (Pyke, 2011). However, it is not clear 

that prescribed fire is the best management option in many 

cases (Rhodes and others, 2010). The best results reported 

were attained using manual treatments that retained cover 

of woody and herbaceous litter post-treatment (Baughman 

and others, 2010). A review of the impacts of treatments and 

grazing on grouse (Beck and Mitchell, 2000) suggested that 

fire be applied cautiously because optimal patterns of burnedunburned habitat and the ideal size(s) for burned patches 

are unknown, suggesting that small treatment areas coupled 

with monitoring of subsequent habitat and use patterns may 

improve restoration success. Research focused on treatment 

effectiveness (Brockway and others, 2002) indicated that 

mechanical tree thinning increased native understory biomass 

by 200 percent; typically, this type of response represents 

improvement of sage-grouse habitat. Additionally, mechanical operations followed by seeding have been used successfully to restore shrub- and tree-dominant states, however 

these are typically the most expensive management actions 

(Provencher and others, 2007). Previous efforts indicate that 

the success of native plant recovery increases with less pinyon 

and juniper cover and increases with improved condition 

of the pre-treatment community (Pyke, 2011). Gradients of 

condition and potential, estimated locally and applied during 

the planning process, coupled with local habitat and restoration priorities, may be a useful combination for guiding 

specific actions (see Section III. A11. Habitat Treatment and 

Vegetation Management).

A9. Grazing 

The effect of livestock grazing on range condition is one 

of the most contentious issues underlying the management and 

use of sagebrush habitats (Crawford and others, 2004). However, livestock grazing is the most widespread land use across 

the sagebrush biome (Connelly and others, 2004), making 

discussion of its role in sagebrush ecosystems and specifically 

sage-grouse population conservation a necessary consideration. Although isolated areas exist that have not been grazed 

by domestic livestock (for example, the kipukas in the Great 

Rift lava fields of southern Idaho), most sagebrush habitats 

have been grazed in the past century (Knick and Connelly, 

2011b). Livestock grazing has been described as a diffuse 

form of biotic disturbance that exerts repeated pressure over 

many years on a system; unlike point-sources of disturbance 

(for example, fires that have acute perturbations from welldefined origins), livestock grazing is characterized as a “press” 

form of disturbance because it exerts repeated pressure across 

the landscape (Knick and Connelly, 2011b). Thus, effects of 

grazing are not likely to be detected as disruptions—except 

in extreme cases as around water sources or mineral-nutrient 

blocks—but rather as differences in the processes and functioning of the sagebrush system (Knick and Connelly, 2011b). 

Importantly, effects of grazing are not distributed evenly, 

because historic practices, management plans and agreements, 

and animal behavior all dictate differential use and therefore 

different effects.

Historically, the numbers of livestock and the area grazed 

increased between 1880 to 1905 and combined with the 

drought that followed in the 1920s and 1930s severely altered 

the condition of western landscapes (Connelly and others, 

2004). Numbers of livestock increased from 4.1 million cattle 

and 4.8 million sheep in 1870 to 19.6 million cattle and 25.1 

million sheep in 1900 (Knick and Connelly, 2011b). Native 

perennial grasses and forbs that were not adapted to heavy 
Table 21. Summary of spatial model describing pinyon pine, juniper, and other conifer encroachment risk* across Management Zones by acres of pr

preliminary general habitats (PPH and PGH, respectively). 

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG 

Habitat 

(acres)

Direct 

Footprint 

(acres)

Direct 

Footprint 

(%)

Relative 

Influence1

(%)

SG 

Habitat 

(acres)

Direct 

Footprint 

(acres)

D

Foo

MZ I–GP 11,636,400 130,600 1.12 34,663,000 894,500 2

BLM 2,994,300 33,100 1.11 25 4,524,900 180,800 4MZ II and VII–WB & CP 292,400 1,100 0.38 1 515,300 20,300 3BLM 219,700 1,700 0.77 1 2,427,700 25,400 1MZ III–SGB 7,132,500 82,800 1.16 63 24,682,800 604,800 2BLM 995,600 12,000 1.21 9 2,498,400 63,100 2MZ IV – SRP 1,900 0 0.00 0 13,900 0 0

MZ II and VII–WB & CP 17,476,000 1,076,300 6.16 19,200,200 1,390,500 7

BLM 9,021,200 499,700 5.54 46 9,012,500 595,500 6Forest Service 162,000 18,200 11.23 2 452,500 62,300 13

Tribal and Other Federal 784,000 77,100 9.83 7 1,354,600 88,400 6Private 6,233,900 373,000 5.98 35 7,394,800 545,800 7State 1,244,800 106,600 8.56 10 979,800 97,800 9Other 30,100 1,700 5.65 0 6,000 700 11

MZ III–SGB 10,028,500 1,292,400 12.89 3,970,100 517,400 13

BLM 6,309,400 751,400 11.91 58 3,199,800 394,000 12

Forest Service 1,236,200 247,000 19.98 19 356,200 86,800 24Tribal and Other Federal 260,800 29,400 11.27 2 29,100 4,600 15

Private 1,836,200 217,400 11.84 17 384,800 32,000 8

State 385,900 47,100 12.21 4 200 0 0

MZ IV–SRP 21,930,600 1,698,500 7.74 10,958,500 918,100 8

BLM 13,710,700 938,700 6.85 55 4,928,200 311,300 6Forest Service 1,613,800 248,200 15.38 15 1,113,500 228,100 20Tribal and Other Federal 633,600 10,000 1.58 1 522,500 11,100 2Private 4,890,200 427,500 8.74 25 3,516,742 295,200 8State 1,019,373 67,700 6.64 4 846,200 69,600 8Other 62,900 6,400 10.17 0 31,400 2,900 9
Table 21. Summary of spatial model describing pinyon pine, juniper, and other conifer encroachment risk* across Management Zones by acres of pr

preliminary general habitats (PPH and PGH, respectively).—Continued Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint (acres) Direct Footprint (%) Relative Influence1 (%) SG Habitat (acres) Direct Footprint (acres) D

Foo

MZ V–NGB 7,097,200 823,500 11.60 5,808,000 533,700 9

BLM 5,117,500 597,500 11.68 73 4,196,700 346,600 8

Forest Service 62,200 11,300 18.17 1 114,900 29,200 25Tribal and Other Federal 717,100 44,000 6.14 5 101,800 8,100 7Private 798,000 106,800 13.38 13 1,199,000 132,300 11State 64,900 2,700 4.16 0 115,800 7,300 6Other 337,500 61,200 18.13 7 79,800 10,100 12

*Data Source: Modeled from National GAP/ReGAP Landcover, National GAP Analysis Program, 2010. Based on occurrence of sagebrush within 120 m of a conifer vegetatio1For management entities within a management zone calculated as the percent of the total direct impact in the Management Zone represented by that management entity, that 

influence among management entities. Small differences between individual entity totals and MZ summary values may exist due to rounding of estimates during calculations.
III. Characterization of Important Threats and Issues 95

Figure 27B. Overlap of pinyon pine, juniper, and other conifer encroachment risk and preliminary priority and preliminary general 

habitats (PPH and PGH, respectively) in Management Zones (MZ) III, IV, and V (Great Basin). 
96 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

grazing pressure were depleted from the vegetative community and replaced in much of the Great Basin, Snake River 

Plain, and surrounding intermountain regions by grazingtolerant grass species, exotic annual grasses, or both. Loss 

of protective vegetation cover in some communities resulted 

in extensive soil disturbance and erosion, and shrub density 

increased (although the total distribution of shrubs across 

the region likely remained similar). Research revealed that 

the decline of palatable forage species and increases in plant 

species of low palatability took only 10 to 15 years at any 

given site under heavy uncontrolled grazing (Knick and Connelly, 2011b). Forage production for livestock dropped to an 

estimated 10 percent of site potential following depletion of 

the vegetation community in some regions. The area required 

to support an animal unit month (AUM; the amount of forage 

required to feed one 1,000-pound cow and her calf, one horse, 

five sheep, or five goats for one month) was estimated at 3 

acres (1.2 ha) prior to European settlement, 9 acres (3.7 ha) in 

the 1930s, and 8 acres (3.2 ha) in the 1970s (Knick and Connelly, 2011b). Implied in this estimate is the assumed relation 

that 3 times the area per AUM is required because current 

primary production is approximately one-third of what it was 

during the first interval, years after severe overgrazing and 

droughts of the early 1900s ended. Current-use patterns vary 

based on local and regional plans and conditions, and grazing 

allotments and pastures on public lands (management units) 

represent the typical planning, leasing, and evaluation units 

used in grazing management across sage-grouse range. Grazing, assessed using Field Office records of grazing allotments, 

suggested that allotments “not meeting wildlife land health 

standards due to livestock grazing” influence sage-grouse 

habitats throughout MZ IV and western portions of MZ III, 

although BLM lands not meeting wildlife land health standards (due to livestock) can be found throughout the range of 

sage-grouse (table 22, fig. 28). Importantly, assessments for 

some lands were not available (some Federal and all State, private, and tribal lands), and conditions have changed since the 

data were gathered (assembled in 2008 using available data), 

so regional-scale comparisons may be misleading (contemporary, local data should supersede this information in most 

cases). Approximately 6.6 million acres (26,700 km2

; 10.42 

percent) of BLM controlled sage-grouse range did not meet 

land health standards, and 17.9 percent of priority habitats in 

MZs III and IV did not meet these standards. 

Livestock grazing can affect soils, vegetation, water, 

and nutrient availability by consuming or altering vegetation, redistributing nutrients and plant seeds, trampling soils 

and vegetation, and disrupting microbiotic crusts (Connelly and others, 2004). At unsustainable levels of grazing, 

these impacts can lead to loss of vegetative cover, reduced 

water infiltration rates, decreased plant litter on soil surface, 

increased bare ground, reduced nutrient cycling, decreased 

water quality, increased soil erosion, and reduced overall 

habitat quality for wildlife including sage-grouse (Wisdom 

and others, 2002; Knick and others, 2011). Ultimately, livestock function as keystone species; domestic grazing does 

not preclude native wildlife and vegetation, but it influences 

ecological pathways and can influence which plant and animal 

species persist (Knick and others, 2011). Thus there are two 

important influences of detrimental grazing on sage-grouse 

habitat: the influence on annual conditions in the near-term 

and the accumulation of selective pressure resulting in altered 

vegetation dominance over time. Prolonged selective pressure 

can affect condition of individual plants, abundance of species, 

inter-specific competition, and ultimately, community composition (Miller and others, 1994; Beck and Mitchell, 2000; 

Wisdom and others, 2002; Erichsen-Arychuk and others, 

2002; Holechek and others, 2003; Connelly and others, 2004; 

and Pyke, 2011). Although specific effects and conditions are 

localized in most cases, the cumulative effect of these transitions across the species’ range may affect the regional condition of sage-grouse habitats. 

There is little scientific data directly linking grazing 

practices to sage-grouse population levels (Knick and others, 

2011). Direct positive and negative effects of livestock grazing 

on sage-grouse reported in the literature include (1) light to 

moderate rest-rotation cattle grazing in mesic upland meadows 

promoted forb growth and availability and sage-grouse use, 

(2) sage-grouse used sheep salting grounds as leks, (3) heavy 

grazing in wet meadows deteriorated hydrology and reduced 

the extent of habitats suitable for summer—these sites were 

avoided by sage-grouse, and (4) sheep and cattle trampled 

nests and caused nest desertions (Beck and Mitchell, 2000). 

To help make the connection between the effects of livestock 

grazing on plant community dynamics in sagebrush ecosystems, the context of state and transition theory (states being 

discrete, observable communities or conditions, and transitions represent the influence of drivers of change that move 

the community among alternative states) has been used to 

describe the observed range of variation of plant communities 

(Pyke, 2011) and frame a discussion of grazing effects on vegetation and habitat conditions, habitat treatments, wild horse 

and burro herds, and water developments. Though differences 

in tolerance and resilience may exist among different communities within the sagebrush ecosystem (for example, eastern 

versus western, northern versus southern), multiple lines of 

evidence indicate the presence of thresholds in the response 

of grasses and other native vegetation, including sagebrush, to 

variations in grazing pressure, which, in turn, have important 

implications for sage-grouse habitat quality in multiple-use 

environments (Beck and Mitchell, 2000; Erichsen-Arychuk 

and others, 2002; Holechek and others, 2003; Connelly and 

others, 2004; Pyke, 2011).

Sage-grouse population persistence has been linked 

to the availability and condition of sagebrush habitat; the 

dependence of the species on sagebrush through all seasonal 

periods has been well documented and cannot be overemphasized (Connelly and others, 2004). Nesting sage-grouse 

consistently select areas with more sagebrush canopy cover 

and taller grasses compared to available habitats (Hagen 

and others, 2007); tall, dense herbaceous cover—including residual grasses—in selected dense sagebrush stands 
III. Characterization of Important Threats and Issues 97

Table 22. Summary of grazing allotments not meeting Land Health Standards for wildlife habitat with grazing as the causal factor* by 

acres of preliminary priority and preliminary general habitats (PPH and PGH, respectively).

PPH PGH

Management Zone

 Entity

SG 

Habitat 

(acres)

Direct 

Footprint 

(acres)

Direct 

Footprint 

(%)

SG 

Habitat 

(acres)

Direct 

Footprint 

(acres)

Direct 

Footprint 

(%)

MZ I–GP

BLM 2,994,300 82,500 2.76 4,524,900 52,100 1.15

MZ II and VII–WB & CP

BLM 9,021,200 286,900 3.18 9,012,500 366,000 4.06

MZ III–SGB

BLM 6,309,400 965,400 15.30 3,199,800 654,600 20.46

MZ IV – SRP

BLM 13,710,700 2,617,200 19.09 4,928,200 968,900 19.66

MZ V–NGB

BLM 5,117,500 417,000 8.15 4,196,700 158,700 3.78

*

Data Source: (Veblen and others, 2011; Assal and others, 2012). Only BLM-managed portions of allotments were evaluated. Data assembled in 2008 from 

available records.

increases the probability of a successful hatch. Thermal cover, 

predator protection, and food availability are important for 

chick survival during the early brood-rearing period with tall 

(>30cm) grasses and sagebrush creating this habitat structure. 

Grazing intensity—including stocking rate, duration, and frequency—has consistently been identified as having impacts on 

ecosystem and rangeland health (Vallentine, 1990; Briske and 

others, 2008; Veblen and others, 2011) including the structure 

required by sage-grouse. Similarly, the timing of grazing relative to plant phenology in particular can influence the sustainability of grazing (Briske and Hendrickson, 1998; Briske and 

others, 2003; Veblen and others, 2011) and compatibility with 

wildlife requirements. Resting pastures from livestock grazing during periods of fastest growth of dominant grasses and 

forbs in intermountain sagebrush-steppe generally enhances 

herbaceous plant growth and reproduction and increases culm 

height, long-term tiller production, and flower and seed production (Pyke, 2011) improving range conditions and habitat. 

Repeated grazing during this time tends to favor sagebrush 

growth (Pyke, 2011) through reduced competitive ability of 

grasses. Seasonal monitoring of range conditions could enable 

removal of livestock when stubble heights required to protect 

nests and broods are reached; however, this information is difficult to attain accurately in a timely way across large regions; 

therefore, surrogate measures or indices of condition would 

likely benefit this effort.

Heavy fall utilization of sagebrush habitats by livestock 

has been deemed detrimental to sagebrush overstories and 

thus may negatively influence sage-grouse habitat suitability 

(Wright, 1970; Owens and Norton, 1990; Angell, 1997; Beck 

and Mitchell, 2000). Trampling by livestock under short-duration or season-long grazing may kill sagebrush, particularly 

seedlings growing in interstitial spaces (Beck and Mitchell, 

2000). Domestic sheep browsing in fall and winter can reduce 

the density and vigor of sagebrush, especially where sagebrush densities are low (Beck and Mitchell, 2000) and may 

require avoidance (rest, removal) in important sage-grouse 

habitats with limited sagebrush cover. Spring grazing may 

benefit sage-grouse winter range because grass reductions can 

increase sagebrush densities (Wright, 1970; Owens and Norton, 1990; Angell, 1997; Beck and Mitchell, 2000) suggesting an opportunity for adaptation of grazing systems to graze 

winter habitats in spring when brood-rearing habitats would be 

avoided, and vice versa.

A study (Van Poolen and Lacey, 1979), compiling results 

from 18 western grazing-system studies reported that adjustments in livestock numbers resulted in increased herbage 

production of approximately 35 percent and 28 percent when 

grazing-use levels were reduced from heavy (60–80 percent) 

to moderate (40–60 percent) and from moderate to light 

(20–40 percent), respectively. The authors concluded that 

livestock stocking intensity was more important than grazing 

system for herbage production (Van Poolen and Lacey, 1979), 

a key habitat feature associated with hatching success of sagegrouse nests and chick survival during early brood-rearing. In 

contrast, others found season of use to influence production: 

grazing heavily during the spring or during spring and fall 

was detrimental to herbaceous understories (Mueggler, 1950; 

Laycock, 1978; Owens and Norton, 1990). Insect diversity and 

density were positively correlated with herbaceous density and 

diversity (Hull and others, 1996; Jamison and others, 2002); 

thus, spring or spring-fall grazing could negatively impact 

nesting sage-grouse and young chick survival during early 

brood-rearing, and avoidance through rotation or rest may 

benefit nesting or brood-rearing success. Grazing during the 

fall had minor effects on herbaceous understories (Mueggler, 
98 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 28. Overlap of grazing allotments not meeting Land Health Standards for wildlife habitat with grazing as the causal factor 

and preliminary priority and preliminary general habitats (PPH and PGH, respectively). Bureau of Land Management (BLM) lands only, 

assembled in 2008. MZ, Management Zone. 
III. Characterization of Important Threats and Issues 99

1950; Laycock, 1978; Owens and Norton, 1990). However, 

grazing during the dormant season (late summer through winter) may influence residual-grass-stubble height (Pyke, 2011), 

which could influence nesting habitat quality for sage-grouse 

the following spring. 

A study conducted in central Wyoming compared vegetative conditions in grazed pastures to conditions selected by 

sage-grouse in the area and found that reduced forage utilization, extended periods of rest, and reduced spring grazing 

provided conditions most suitable for sage-grouse nesting 

and early brood-rearing, even during a drought (precipitation 

68 percent of normal during study, Kuipers, 2004). Grazing 

system (based on rotation period) was less important relative 

to stocking rates and season of use in this study. Long-term 

removal of livestock generated a steady increase in the richness of shrubs, perennial grasses and forbs, and vegetative 

heterogeneity through 45-years post-removal of livestock in 

southwestern Idaho (Anderson and Inouye, 2001). Comparing 

grazed to un-grazed (not grazed for 25 to 40 years) big sagebrush communities in Utah and Idaho, researchers reported 

increased sagebrush canopy cover of 13 to 54 percent (Beck 

and Mitchell, 2000). In contrast, no increases in total herbaceous standing crop after removal of livestock for 13 years 

were reported in Utah (Beck and Mitchell, 2000). Studies 

tracking changes in vegetation after removal of livestock in 

sagebrush systems report that initial proportions of the different growth forms were retained, and that a minimum of 10 to 

15 years was required for seed production, seedling establishment, and growth to occur (Connelly and others, 2004; Pyke, 

2011). Thus, well-prescribed livestock management may 

positively influence sage-grouse habitat suitability especially 

during nesting (spring), early brood-rearing (early summer), 

and winter, but extended rest may be required for areas that 

are currently degraded.

Livestock distribution patterns are directly linked with 

water availability, and this bias has also had relevant, measureable impacts to riparian habitats, which are of primary 

importance for sage-grouse as late brood-rearing and summer habitats. The most direct effect of livestock on riparian 

vegetation is removal of the lower vegetation layers; livestock 

exclusion from riparian habitats resulted in increased sedge 

cover, forb cover, foliage-height diversity, and water-table 

depth along with expansion of riparian vegetation laterally 

from stream channels (Dobkin and others, 1998). High stocking rates in areas with limited water availability were particularly detrimental to forage productivity on lands immediately 

surrounding water sources (Hall and Bryant, 1995; Dobkin 

and others, 1998). Similarly, summer grazing on riparian habitats concentrated livestock on riparian corridors resulting in 

decreased low-vegetative growth (typically the forb communities essential in sage-grouse summer diets) and reduced lateral 

extent of succulent vegetation associated with the riparian 

corridor due to a reduction in the hyporheic zone (that is, the 

region beneath and alongside a water body where there is mixing of groundwater and surface water). However, sage-grouse 

preferred grazed to ungrazed wet meadows where protective 

cover conditions were otherwise equal, and rest-rotation grazing provided the best effects on sage-grouse summer habitat 

through moderate stocking levels and rest of a minimum of 

every 3 years (Neel, 1980) 

Most sagebrush grasslands are in winter-dominated 

precipitation regions, and cool-season plants generally 

dominate the herbaceous layers (Pyke, 2011). Exceptions are 

the Colorado Plateau in southern Utah, eastern Utah, northeastern Colorado, eastern Wyoming, and eastern Montana 

(eastern portions of both MZ I and MZ III) where monsoon 

moisture creates a second peak of predictable moisture in late 

summer; warm-season plants co-dominate with cool-season 

plants in the herbaceous layers of these regions (Pyke, 2011). 

Therefore, the most significant long-term influence of grazing on sage-grouse habitat is the potential for transition from 

an ecological state dominated by sagebrush and early (cool) 

season grasses to a site dominated by sagebrush, grazing-tolerant grasses (increasers), invasive annual grasses and forbs, 

or woodlands (Pyke, 2011) driven by persistent, selective herbivory that can affect composition, dominance, and community structure (Manier and Hobbs, 2007). Importantly, not all 

sagebrush communities are identical. Sagebrush-steppe is one 

of the most widespread and characteristic vegetation types in 

the intermountain west, and it comprises the northern portion 

of the sage-grouse distribution (West, 1988). In these communities, co-dominance of perennial bunchgrasses along with one 

or more of the 12 different species of sagebrush creates a variety of types and conditions that supported moderate species 

diversity and historically some limited populations of large 

herbivores (West, 1988). On eastern portions of the species’ 

range, where the sagebrush-steppe gradates with mixed-grass 

prairie species, rhizomatous grasses often play a prominent 

role in community composition with important implications 

for grazing management (especially in MZ I). Great Basin 

sagebrush characterizes sagebrush communities in the southern and southwestern portions of the sage-grouse range (MZs 

III, IV, V, and VII) , and though there are similarities in composition and structure, these systems have significantly lower 

diversity, productivity, and resilience to disturbance owing to 

greater aridity across these regions (West, 1988). Thus, though 

the northern sagebrush-steppe has proven similar in response 

to disturbance and management to semiarid grasslands, Great 

Basin types are more similar to deserts with islands of fertility 

surrounding shrubs, increased potential for erosion due to limited cover (soil exposure), and seasonal drought and precipitation patterns (West, 1988). Thus, it is probable that the impacts 

of overgrazing are more severe in these arid regions compared 

to northern wetter regions. Further impacts of drought and 

prolonged shifts in precipitation patterns may trigger shifts in 

systemic condition, productivity, and resilience in areas that 

were previously more robust, and this may cause significant 

differences in effects of local grazing practices.

Sage-grouse generally initiate nesting in April, prior to 

production of new herbaceous cover; thus, residual grasses 

left from the previous year represent the initial cover available for nesting sage-grouse (Hausleitner and others, 2005; 
100 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Holloran and others, 2005). With few exceptions, ensuring 

adequate residual herbaceous cover through the nesting 

season (through June in most areas) will provide for longterm resilience with plant communities that include healthy 

bunchgrass understories and adequate residual grass cover and 

height to support annual objectives (Pyke, 2011). The potential 

exists to successfully manage for good sagebrush community 

condition but fail to achieve sage-grouse habitat objectives if 

annual management for sufficient residual vegetation (standing crop) is not considered. According to research conducted 

in sagebrush-steppe, adherence to light-utilization standards is 

the most dependable way to ensure a healthy plant community 

(Cagney and others, 2010). Conclusions from a review of the 

effects of herbivory on bluebunch wheatgrass (Pseudoroegneria spicata), an important sagebrush associate, indicated 

(1) utilization levels of 30 to 40 percent under deferred grazing 

systems is a recommended maximum use-level if maintaining 

the community is desirable; (2) onetime growing season utilization levels of more than 50 percent have long-term (up to a 

decade) impacts on plant vigor and productivity (even if followed by complete protection); and (3) grazing following the 

growing season has little effect, although yield reductions the 

following year may occur if grazed to 2-inch stubble height 

(Anderson, 1991). Annual and seasonal monitoring of production and standing crop, with subsequent removal of livestock 

as range utilization reaches capacity (Holechek and others, 

1989; Thurow and Taylor, 1999) is important for providing 

for habitat quality rangewide and would be facilitated by 

development within local monitoring, planning, and adaptive 

management cycles.

Even though livestock numbers have been considerably 

lower since the implementation of the Taylor Grazing Act in 

1934, and grazing management across the West has steadily 

improved, acres continue to transition away from reference 

(historic, potential, and [or] desired) conditions (Cagney and 

others, 2010). Because of lasting historic impacts (late 1800s–

early 1900s), the reduced numbers of livestock in the modern 

era often do not simply represent reduced grazing effects 

(Knick and others, 2011), but rather, a slower rate of accumulation of effects. Importantly, environmental patterns, historic 

and current uses vary tremendously in space and time, and 

though some generalizations may be made, local conditions 

and appropriate solutions will be based on local understanding 

and adaptations. Thus in some areas, grazing on sage-grouse 

habitat may be a component of both long-term management 

to promote resilient, desirable plant communities and annual 

management of the standing crop to provide residual cover for 

sage-grouse (Cagney and others, 2010; Pyke, 2011). However, if the desired vegetative components are not present 

in a priority site, additional manipulations may be required 

such as addition of desired species through active restoration 

(Pyke, 2011), and because these treatments may be expensive, 

prioritization based on habitat value and site potential may 

be warranted.

Interactions between grazing and recent disturbances can 

have lasting effects on recovery of sage-grouse habitat values 

in the post-disturbance environment. Deferring grazing for 

two growing seasons after disturbance has been recommended 

because it allows the cool season bunchgrasses—which are 

especially vulnerable to grazing after treatment—to capitalize on resource availability created by the disturbance (Knick 

and others, 2011). However, reintroduction of livestock to a 

disturbed area prior to the native or reseeded plant community 

becoming established, regardless of the number of years of 

rest afforded the site, can result in failed rehabilitation efforts 

and increased levels of exotic grasses (Knick and others, 

2011). Although rest is often prescribed, timing, intensity, and 

duration of grazing of treated rangelands may be more important than a specific period of rest after fire (Bates and others, 

2009). Moderate grazing after perennial grass dormancy (that 

is, late season) in the first two summers after fire is not likely 

to reduce the recovery ability of herbaceous communities in 

sagebrush-steppe (Bates and others, 2009) when rest during 

the growing season is permitted. Differences in herbaceous 

cover among burn-ungrazed and burn-grazed areas were not 

observed during the first 6 years after fire, but between 7 and 

18 years post-fire, perennial grass cover in grazed areas was 

less than cover in ungrazed areas (West and Yorks, 2002), 

so long-term post-treatment monitoring may be important. 

Treated areas may draw grazing pressure from all herbivores; 

thus, treatment designs that consider the possibility of an 

unplanned escalation of use by wild horses or elk (Cagney and 

others, 2010) when significant populations of these species 

are present have better chances of meeting productivity and 

habitat targets.

Wild Horses

Free-roaming horses (Equus caballus) and burros (E. 

asinus) have been a component in the dynamics of sagebrush 

and other semiarid communities since they were brought to 

North America at the end of the 16th century (Connelly and 

others, 2004). Approximately 40,000 free-roaming horses 

currently live in ten Western U.S. States; areas managed for 

horses and (or) burros from 1971 to 2007 constitute approximately 18 percent of currently occupied sage-grouse range 

predominantly in Nevada, southwest Wyoming, and southeast 

Oregon (Connelly and others, 2004; Beever and Aldridge, 

2011). Because of physiological differences, a horse consumes 20 to 65 percent more forage than would a cow of 

equivalent body mass (Connelly and others, 2004). Comparing 

horse-removed sites to horse-occupied sites, researchers have 

documented the following equid-induced changes to sagebrush 

communities: (1) reduced total vegetative and grass abundance 

and cover, (2) lower sagebrush canopy cover, (3) increased 

fragmentation of shrub canopies, (4) lower species richness, 

(5) increased compaction in surface soil horizons (Bartmann 

and others, 1987), and (6) increased dominance of unpalatable forbs (Beever and Aldridge, 2011). Additionally, because 

horses separate themselves from cattle by using higher elevations and steeper slopes, horse occupancy of a sagebrush 

ecosystem reduces the occurrence of ungrazed areas (Connelly 
III. Characterization of Important Threats and Issues 101

and others, 2004). Areas managed Federally as wild horse 

and burro range constitute approximately 14.6 million acres 

(5.9 million hectares; 10.24 percent) of sage-grouse habitats across the range of the species (table 23, fig. 29A). Wild 

horse and burrow range coincides with sage-grouse habitat 

predominantly in Nevada, southwest Wyoming, and southeast 

Oregon; in these MZs (III and V and II and VII), 19.9 percent 

of priority habitats are negatively influenced. 

Water Developments

Open water has been suggested as a limiting factor for 

summering sage-grouse. Although water availability may 

influence the species’ summer distribution (Patterson, 1952; 

Autrienth, 1981), movements to summer range are probably in 

response to lack of succulent forbs in an area rather than a lack 

of free water (Connelly and Doughty, 1989). Existing research 

suggests that sage-grouse do not regularly use water developments even during relatively dry years but obtain required 

moisture from consuming succulent vegetation in the vicinity 

(Connelly, 1982; Connelly and Doughty, 1989; Connelly and 

others, 2004). More than 56,500 water development projects 

have been implemented on lands managed by the BLM within 

the current distribution of sage-grouse plus a 50 km (31 mi) 

buffer around this distribution (Connelly and others, 2004; 

fig. 29B). Water developments are generally intended to provide water for livestock or wildlife but may also be designed 

to provide succulent vegetation surrounding the water. 

Artificial water sources may facilitate the spread of West 

Nile virus (WNv) within sage-grouse habitats because these 

water developments support abundant populations of the 

mosquito (Culex tarsalis) longer than natural, ephemeral water 

sources thereby providing habitat for the vector responsible for 

the majority of WNv infections (Walker and Naugle, 2011). 

Additionally, projects that create mesic zones around water 

developments to promote the growth of succulent vegetation 

may inadvertently contribute to the proliferation of WNv as 

Culex tarsalis regularly breed in water-filled hoofprints in 

these areas (Walker and Naugle, 2011). Water developments 

tend to attract other animals and thus may serve as predator 

sinks for sage-grouse (Connelly and Doughty, 1989). Additionally, water developments have substantially influenced the 

movements and distribution of livestock in arid western habitats and have increased the amount of sagebrush area available 

for livestock (Connelly and others, 2004), which—although 

these practices may benefit riparian conditions (sage-grouse 

summer habitats)—may increase the effect of livestock across 

the landscape, expanding impacts to upland areas important 

for sage-grouse during nesting, early brood-rearing, and 

winter seasons. 

A10. Climate Dynamics 

Climate change is a complex process in which interactions among natural and anthropogenic drivers affect 

atmospheric characteristics leading to long-term changes in 

temperature and precipitation (IPCC, 2007; Miller and others, 

2011). Notably, the climate has always been understood as a 

highly dynamic system, and although it has been possible to 

develop understanding and theories using persistent patterns 

(in space and time), the climate has always been changing. 

Modern issues and concerns over climate change are generally focused on rapid warming and associated circulation 

feedbacks that have been linked to human industrial activities. 

Although imprecise, plausible global climate change models 

predict higher temperatures, drier soils in summer with high 

variability, severe weather events (drought and storms), and 

changing moisture regimes across mid-latitude, semiarid 

regions of the American West (Finch, 2012; Friggens and 

others, 2012). 

Sage-grouse population dynamics were strongly related 

to multiple climatic conditions as measured between 2003 

and 2010 in central Nevada (Blomberg and others, 2012). 

Precipitation (annual rainfall, annual precipitation, and 

average winter snow depth) was positively related to annual 

recruitment (higher recruitment in years with high precipitation); the positive relation was strongest with total annual 

rainfall. Additionally, annual rainfall and mean monthly winter 

snowpack were positively related to sage-grouse population 

growth. Annual adult male survival was negatively related to 

maximum summertime temperatures (high survival in years 

with low maximum temperature). Results from this study 

suggest a direct link between sage-grouse population dynamics and several ecological processes expected to be influenced 

by climate change in southern portions of the species’ range 

(for example, decreased precipitation amounts and increased 

temperatures); projected changes to climate are likely to 

negatively influence sage-grouse population dynamics if they 

decrease the productivity of the sagebrush ecosystem (Blomberg and others, 2012). 

Changing climate conditions may render some locations 

less suitable for sagebrush than for other species, creating 

potential shifts in ecosystem distributions (Bradley, 2010). 

Increased temperatures, the trend for decreased snowpack, 

earlier onset and warmer spring periods, and reduced summer 

water flows in the Western United States could exert stresses 

on sagebrush; sagebrush seedling recruitment may be particularly susceptible to these changes in climate (Miller and others, 2011). A substantial increase in temperature could impart 

a competitive advantage to woodland vegetation currently 

dominating the Chihuahuan and Sonoran Deserts, and these 

woodlands may expand northward and displace large areas 

of sagebrush (Miller and others, 2011). Increased levels of 

carbon dioxide may favor exotic annual grasses; in controlled 

laboratory tests, reproductive biomass of cheatgrass doubled 

and time to maturation decreased at elevated levels of carbon 

dioxide (Miller and others, 2011). Under current atmospheric 

carbon dioxide levels, cheatgrass competes successfully 

against native grasses because of earlier maturation, shallow 

root systems preempting water in soils, greater seed production, and the ability to respond quickly to disturbance (Miller 

and others, 2011). Thus, plausible scenarios suggest that an 
Table 23. Summary of Federally managed Wild Horse and Burro Herd Management Areas and Territories* across Management Zones (MZ) by acres 

preliminary general habitats (PPH and PGH, respectively). Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH Management Zone Entity SG Habitat (acres) Direct Footprint (acres) Direct Footprint (%) Relative Influence1 (%) SG Habitat (acres) Direct Footprint (acres) Di

Foot

(%

MZ I–GP 11,636,400 0 0.00 34,663,000 0 0 MZ II and VII–WB & CP 17,476,000 2,217,100 12.69 19,200,200 2,734,700 14.

BLM 9,021,200 1,792,900 19.87 81 9,012,500 2,007,200 22.Forest Service 162,000 0 0.00 0 452,500 0 0.

Tribal and Other Federal 784,000 69,800 8.90 3 1,354,600 50,700 3.Private 6,233,900 271,200 4.35 12 7,394,800 602,400 8.State 1,244,800 83,200 6.68 4 979,800 74,300 7.

Other 30,100 0 0.00 0 6,000 0 0.

MZ III–SGB 10,028,500 2,479,800 24.73 3,970,100 1,635,800 41.

BLM 6,309,400 2,199,200 34.86 89 3,199,800 1,463,200 45.Forest Service 1,236,200 210,100 17.00 8 356,200 136,100 38.

Tribal and Other Federal 260,800 11,700 4.49 0 29,100 14,700 50.

Private 1,836,200 44,500 2.42 2 384,800 21,800 5.

State 385,900 14,300 3.71 1 200 0 0.

MZ IV–SRP 21,930,600 1,244,200 5.67 10,958,500 642,600 5.

BLM 13,710,700 1,177,200 8.59 95 4,928,200 601,400 12.Forest Service 1,613,800 0 0.00 0 1,113,500 0 0.

Tribal and Other Federal 633,600 0 0.00 0 522,500 7,200 1.

Private 4,890,200 51,900 1.06 4 3,516,742 29,100 0.State 1,019,373 15,000 1.47 1 846,200 4,800 0.

Other 62,900 0 0.00 0 31,400 0 0.
Table 23. Summary of Federally managed Wild Horse and Burro Herd Management Areas and Territories* across Management Zones (MZ) by acres 

preliminary general habitats (PPH and PGH, respectively).—Continued

Abbreviations: SG, sage-grouse; GP, Northern Great Plains, WB, Wyoming Basin; CP, Colorado Plateau; SGB, Southern Great Basin; SRP, Snake River Plain; NGB, Northern G

PPH PGH

Management Zone

 Entity

SG 

Habitat 

(acres)

Direct 

Footprint 

(acres)

Direct 

Footprint 

(%)

Relative 

Influence1 (%)

SG 

Habitat 

(acres)

Direct Footprint 

(acres)

Dir

Foot

(%

MZ V–NGB 7,097,200 2,190,000 30.86 5,808,000 1,476,300 25.4

BLM 5,117,500 2,002,900 39.14 91 4,196,700 1,399,600 33.3

Forest Service 62,200 0 0.00 0 114,900 0 0.0Tribal and Other Federal 717,100 4,300 0.60 0 101,800 700 0.6

Private 798,000 73,400 9.20 3 1,199,000 75,000 6.2State 64,900 5,600 8.63 0 115,800 400 0.3Other 337,500 103,800 30.76 5 79,800 600 0.7

*Data Source: BLM (2012), USFS Enterprise Data Warehouse, 2012. Nonfederal lands fall within these areas and the presence of wild horses and burros on those lands is dep

practices, such as, fencing or tolerance of trespass.

1For management entities within a Management Zone, these were calculated as the percent of the total direct impact in the Management Zone represented by that management 

of direct influence among management entities. Small differences between individual entity totals and MZ summary values may exist due to rounding of estimates during calcula
104 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 29A. Overlap of Federally managed Wild Horse and Burro Herd Management Areas and Territories and sage-grouse 

preliminary priority and preliminary general habitats (PPH and PGH, respectively) within each Management Zone (MZ).
III. Characterization of Important Threats and Issues 105

Figure 29B. Distribution of water developments on Bureau of Land Management lands overlapping sage-grouse preliminary priority 

and preliminary general habitats (PPH and PGH, respectively) across each Management Zone (MZ). 
106 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

increase in the competitive advantage of cheatgrass may 

facilitate the species’ spread, exacerbating the cycle of fire and 

cheatgrass-dominance already eliminating substantial acreages 

of sagebrush annually (Miller and others, 2011).

In central Nevada, recruitment of male sage-grouse to 

leks was consistently low in areas with substantial exotic 

grasslands interspersed in the landscape surrounding a lek, 

even during years when climatic conditions resulted in substantial recruitment to leks in the region (Blomberg and others, 

2012). The interactive relation between climate and exotic 

annuals suggests that pulses in the growth of a sage-grouse 

population in response to increased precipitation may be mediated by the presence of areas dominated by exotic annuals 

within key habitats (Blomberg and others, 2012). Therefore, 

changing precipitation patterns and competitive advantages 

cheatgrass has over native vegetation, such as rapid response 

to moisture availability, may act synergistically to negatively 

affect sagebrush ecosystem condition and associated sagegrouse population dynamics. 

Summer precipitation and temperature are the best 

predictors of sagebrush regional distribution suggesting that 

changing summer conditions may have the most impact on 

long-term viability of sagebrush habitats (Bradley, 2010). Climate change risk to sagebrush due to changing summer conditions may be most pronounced in southern portions of the 

species’ range where decreased precipitation and (or) rising 

temperatures may make current habitat climatically unsuitable 

in the future (Bradley, 2010). However, in an experimental 

study where rainout shelters excluded natural rainfall and 

seasonal distribution of precipitation was controlled, Bates 

and others (2006) found that Wyoming big sagebrush (Art. tri. 

wyomingensis) did not respond in terms of cover or density to 

shifts in the timing of precipitation from predominantly winter 

(for example, normal precipitation timing on-site of 75 percent 

occurring between October and April) to spring (80 percent of 

total water applied between April and July) in the short term 

(7 years), suggesting changes to the shrub overstory may take 

decades to materialize. Additionally, increasing summer temperatures have been related to increases in threetip sagebrush 

(Art. tripartita) population growth, a result driven by increased 

survival of this species (Dalgleish, 2011). 

The loss of approximately 12 percent of the current 

distribution of sagebrush was predicted to occur with each 1°C 

increase in temperature, primarily to increasing distributions 

of other woody vegetation (Miller and others, 2011). However, 

most scenarios do not factor in the potential response of exotic 

annual grasses and the consequences these changes may have 

on the distribution of sagebrush habitats; therefore, estimates 

of range contraction may be low. The current distribution of 

sagebrush is predicted to decline by 80 percent under one 

of the most extreme global climate change scenarios of an 

increase of 6.6 °C (Miller and others, 2011). A general geographic pattern of future sagebrush occurrence is characterized by substantial decreases in southern parts of the species’ 

range combined with some increases in the northern parts; 

models also forecast small increases in distribution at higher 

elevations, for example, at the interface with coniferous forest 

(Schlaepfer and others, 2012). Forecasts additionally suggest 

that sagebrush ecosystems may split into several large but 

disjoint areas: Washington, Sierra Nevada area, Oregon- northern Nevada, central Idaho, an area encompassing eastern Utah, 

Wyoming, Colorado, and eastern Montana-Saskatchewan 

(Schlaepfer and others, 2012).

Decreased annual precipitation negatively influenced 

needle-and-thread (Hespirostipa comata) population growth in 

sagebrush habitats, primarily by reducing survival of this grass 

species (Dalgleish, 2011). Herbaceous plants were detrimentally affected by a shift in precipitation timing in sagebrush 

habitats from predominantly winter (75 percent of total water 

occurring between October and April) to spring (80 percent 

of total water applied between April and July) as indicated by 

a pattern of lower herbaceous biomass, cover, and densities 

compared to the other treatments (Bates and others, 2006).

Importantly, the potential effects of climate change 

on sagebrush and sage-grouse outlined above are not supported—nor are they falsified—by empirical data. Projecting 

the potential consequences of global climate change requires 

scientists to extend correlational and mechanistic relations 

beyond observed data leading to uncertainty in results. Despite 

limitations, the potential effects of climate change may be 

reasonably factored into long-term conservation actions 

through recognition of risks and possibilities, but predicted 

responses of species and habitats to long-term, imprecise forecasts are unlikely to provide accurate details regarding future 

conditions. Projections of sage-grouse population trends and 

extinction probabilities used for management of the species 

generally extend 100 years into the future (see Garton, 2011), 

and during this period the projected changes to the climate and 

the effects these changes may have on sagebrush habitats may 

become sufficiently large to overwhelm any current trajectory of habitat loss and alteration (Miller and others, 2011). 

The empirical data presented suggests that potential effects of 

global climate change (such as prolonged drought) may influence the herbaceous understory in sagebrush habitats before 

effects on the shrub overstory become apparent.

A11. Habitat Treatments and Vegetation 

Management 

Given the historic reduction and conversion of the most 

productive communities within the sagebrush ecosystem, 

less than half of the original distribution of sagebrush ecosystems currently exists (Knick and Connelly, 2011b; Pyke, 

2011) making conservation of existing sagebrush habitats a 

priority. Consideration of modern habitat treatments in the 

context of historic treatments and disturbances, which can 

affect the regional distribution and condition of sagebrush at 

multiple scales, may be useful for planning, maintenance, and 

restoration of priority sagebrush habitats (albeit with different emphases depending on local conditions). Historic habitat 

treatments often focused on removal or reduction of sagebrush 
III. Characterization of Important Threats and Issues 107

in favor of improved herbaceous cover and productivity 

(Knick and others, 2011), whereas modern-era treatments have 

focused on fire control and fuel mitigation, noxious species 

control, and surface (soil) stabilization. Between 1929 and 

2004, more than 6,000 land and vegetation treatments (burning, mowing, chaining, cabling, chipping, logging, chemical 

application, furrowing, ripping, tillage, pitting, terracing, 

checks, scalping, and seeding) were conducted on BLM lands 

in Colorado, Idaho, Montana, Nevada, Oregon, and Wyoming1

(BLM Range Improvement Project database, Knick and others, 2011), which represents a large and coordinated effort to 

manipulate vegetation composition and structure, increase 

productivity, improve forage-browse quality, rejuvenate old 

growth, remove noxious or poisonous species, and manage 

structure and composition to protect buildings and manage 

fuels (Knick and others, 2011). 

Although rangewide compilation of precise acreage and 

locations of historic treatments does not exist, recent estimates 

suggest more than 4,000 km2 (988,400 acres) were treated 

within these States between 1997 and 2006 (617,750 acres 

[2,500 km2

] of prescribed burns; 346,000 acres [1,400 km2] of 

mechanical fuel treatments; and 154,700 acres [626 km2

 ] of 

mechanical habitat treatments). This results in an estimate of 

more than 8.15 million acres (33,000 km2

 ) treated (approaching 12 percent of sage-grouse habitat area based on mean values and a data-limited estimate of a highly variable activity). 

Vegetation manipulations were more prominent during the 

post-war (WWII) era, circa 1940–60, making this extrapolation based on modern treatment areas a conservative estimate. 

Accumulation of habitat treatments across a targeted 

landscape may outpace natural disturbance (Manier and 

others, 2005), suggesting that natural and anthropogenic 

disturbance history could be considered together for a comprehensive perspective on disturbance patterns and processes 

(capturing spatial and temporal dynamics) that influence 

sage-grouse habitats. Although treatments may have varied 

post-treatment effects, management treatments are typically 

designed to mimic natural processes, such as stimulating postdisturbance regeneration and (or) creating post-disturbance 

hazard levels (Baughman and others, 2010), without negative effects on public safety (for example, due to wildfire). 

Treated areas often have lasting effects that accumulate across 

the landscape and can affect resource use patterns for many 

years (Miller, 2008; Hess and Beck, 2012; Beck and others, 

2012; Chong and Anderson, 2010). Comprehensive (accurate 

and inclusive) records for historic treatments have not been 

compiled or published at this time (making accurate assessment of historic effects impossible, currently); however, local 

1

 Not all of these treatments were in sagebrush habitats (but we are unable 

to separate them at this time) so for these States these values may overestimate 

treatments in sagebrush; however, Calif., N. Dak., N. Mex., S. Dak., and Utah 

were excluded from this calculation as these States have lower ratio of sage to 

other types on BLM lands (for example, grasslands and woodlands); thus, we 

underestimate contribution to rangewide assessment by excluding these States 

leading to some balance in this index. These values are clearly not precise, but 

help provide context. 

planning and management efforts may incorporate this information when available. Importantly, due to perceived threat 

of wildfire and strong similarities in the detrimental effects of 

prescribed fire, mechanical and chemical treatments on habitat 

value for sage-grouse, “an immediate and potentially longterm result [of treatments in sagebrush habitats] is the loss of 

habitat” (U.S. Fish and Wildlife Service, 2010b). 

Current treatments and active vegetation management 

typically focus on vegetation composition and structure for 

fuels management, habitat management, and (or) productivity manipulation for improving the habitat and forage conditions for ungulates and other grazers, for example thinning 

sagebrush cover or treating invasive plants (Knick and others, 

2011). Locally and cumulatively across a region, the distribution of these treatments can affect the distribution of sagegrouse and sagebrush habitats by affecting the distribution of 

suitable cover and forage. Therefore, regional land-use plans 

that consider the distribution, composition, and condition of 

sage-grouse habitat (and potential for restoration), along with 

economic and planning criteria, may be able to improve habitat conditions using spatial patterns, habitat conditions, and 

treatment methods.

In addition to landscapes with large, intact patches of 

sagebrush, sage-grouse require high-quality habitat conditions 

including a diversity of herbaceous species, vegetative and 

reproductive health of native grasses, as well as an abundance 

of sagebrush, making management for high-condition in seasonally important habitats a priority; recent and ongoing management activities have sought to address these values making 

current activities relevant as they assist natural processes to 

recover from past disturbances. Residual vegetation cover, 

especially grass and litter, has often been noted as essential 

for concealment during nesting and brood-rearing (Sveum 

and others, 1998a; Sveum and others, 1998b; Kirol and others, 2012), suggesting opportunities to improve herbaceous 

cover (without sacrificing safety of sagebrush cover) may 

benefit fecundity. For example, adjusting timing and duration 

of livestock use to support quality conditions during seasonal 

use (that is, reduce or eliminate spring grazing in nesting and 

brood-rearing areas). Passive restoration is typically the most 

affordable approach to restoration treatment because it does 

not require directed human activities but rather depends on 

adjustments in processes and management structure that can 

be imparted through revised use strategies (Connelly and others, 2004, p.320). “The greatest land-use adjustment within the 

sage-grouse region that might bring about passive restoration 

is to change livestock management, largely because of the 

prevalence of livestock grazing as a land use” (Pyke, 2011, p. 

537). A previous review of literature discussed positive and

negative impacts of grazing on sage-grouse habitats (Beck and 

Mitchell, 2000) and indicated that simple modifications (such 

as removing livestock) may not have the desired consequences 

for habitat conditions (also see Section III. A9. Grazing). They 

suggested that treatments (prescribed fire, mechanical, and 

herbicide) that eradicate large areas of sagebrush be ceased 

but also indicated that thinning dense sagebrush down to 
108 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

approximately 15-percent cover can support herbaceous production as well as provide sufficient cover for sage-grouse in 

Wyoming sagebrush communities (Beck and Mitchell, 2000). 

Patchy applications are better than large, homogeneous burns, 

but the most xeric sites should be avoided; herbicide treatments and seeding of native species will be effective in many 

areas (Beck and Mitchell, 2000). If historic alteration of the 

habitat has not been too severe, then adjusting management 

practices (the grazing system or seasonal recreation closures, 

for example) has a reasonable chance of improving degraded 

or altered habitat conditions (Connelly and others, 2004). 

Though individual activities do not typically alter landscapescale habitat patterns, treatment areas and effects can accumulate with regional effects; revised treatment approaches that 

consider landscape distribution of habitat and disturbances can 

help insure a controlled, positive effect of treatments on sagegrouse populations. 

Because local priorities may include improved connectivity or increased habitat area, active restoration treatments 

may be warranted if target areas have transitioned into new 

vegetation states or other degradation of the site has occurred 

(Pyke, 2011). Site degradation may be severe in some locations such that critical soil-surface horizons have been reduced 

or lost, or establishment of “undesirable” species has been 

sufficient to displace native species, requiring direct manipulation and making passive management approaches unsuitable 

(Connelly and others, 2004). For example, if invasive species 

(for example, cheatgrass) or native species (for example, junipers, pinyon pines, and rabbitbrush) have replaced desirable 

dominant species, as is common in parts of the Great Basin, 

Snake River Plain (MZs III and IV) and elsewhere, then active 

removal of the invaders and seedings of native species may 

be required for successful restoration (Connelly and others, 

2004). Importantly, given the limited distribution of suitable 

sagebrush habitats and the cost of habitat restoration treatments, management plans that strategically protect intact 

sagebrush and restore impacted areas to enhance existing 

habitats (for example, connectivity of intact sagebrush) have 

the best chance of increasing the amount and quality of sagebrush cover and creating management flexibility in the future. 

Recognition of the relative condition and potential value of 

habitats can help determine options and priorities among 

regional and adjacent treatment areas and support considerations of cost, benefit, and risk. A treatment and restoration 

matrix represents a basic set of conditions and associated 

restoration options to guide scoping and preliminary planning 

steps (table 24). Further, distinction of well-directed, designed, 

and located treatments from historic treatments (with alternate 

goals but similar names) is useful for clarity in assessment 

and planning.

A12. Other Land Uses 

Recreation

Dispersed recreation activities (including but not limited 

to off-highway vehicles, camping, bicycling, and hunting), 

which utilize the extensive network of official and unofficial 

roads, have an extensive and difficult-to-measure impact on 

sagebrush and sage-grouse (also see Section III. A4. Infrastructure). Potential impacts include noise (Blickley and 

others, 2012), distribution of invasive plants, (With, 2004; 

Christen and Matlack, 2009; Bradley, 2010; Huebner, 2010), 

generation of fugitive dust (Gillies and others, 2005; Lee and 

others, 2007; Ouren and others, 2007; Padgett and others, 

2008), and effects on predator and prey behavior (Gavin and 

Komers, 2006; Poulin and Villard, 2011; Whittington and others, 2011). Uninhabited areas within the Great Basin ecoregion 

(MZs III and V) decreased 90 percent (22.2 million acres 

[90,000 km2

]) to less than 3 million acres (12,000 km2 ) with 

expansion driven by economic and recreation opportunities 

in the region (Knick and others, 2011); similarly, population 

densities have increased 19 percent in the Wyoming Basin 

region (MZ II) and 31 percent on the Colorado Plateau (MZ 

VII) since 1920 (Knick and others, 2011). With expanding 

populations comes greater human impacts (Leu and others, 

2008), which is magnified by popular access to public lands 

(Hansen and others, 2005) and dispersed uses that expand 

the human footprint. Impacts of roads and motorized trails 

include mortality due to collisions, behavior modifications due 

to noise, activity and habitat loss, alteration of the physical 

environment, leaching of nutrients, erosion, spread of invasive 

plants, and increased use and noise due to accessibility (Knick 

and others, 2011). Closing unused and unnecessary roads in 

and around sagebrush habitats (for example, seasonal closure 

of specified sage-grouse habitats) may reduce the footprint and 

associated impacts to wildlife. Restricting access to important 

habitat areas based on seasonal use and coincident with sagegrouse activities (for example, lekking, nesting, brood-rearing, 

and wintering) may decrease the impacts associated with 

humans but will not eliminate other impacts such as spread of 

invasive plants, predator movements, loss of cover, and erosion. Although specific work addressing effects of roads, trails, 

and OHV use on sagebrush habitats and sage-grouse has not 

been conducted, research suggests common effects including 

habitat loss and fragmentation, invasive plant spread, induced 

displacement or avoidance behavior, creation of movement 

barriers, noise, and direct encounters (Knick and others, 2011) 

and reducing the extent and influence of roads and trails can 

be incorporated into near-term and long-term plans for consolidating, conserving, and improving priority habitat areas. 

Other human-dimensions approaches may also prove valuable 

whereby closures and restrictions may be avoided by adjusting user behaviors through education and voluntary behavior 

changes.

Training Facilities

There are 87 Department of Defense (DoD) managed 

facilities distributed across the Sage-grouse Conservation Area 

with various operations and intensity of use among and within 

those facilities. Obvious land-use impacts were evident on 

approximately 17 percent of those lands, leaving substantial 
III. Characterization of Important Threats and Issues 109

Level of implementation 

for restoration.1

Good to High Condition, 

little departure from 

reference conditions

Moderate to Good Condition, 

some departure from reference 

conditions but some important 

components remain

Poor Condition, Change in 

Dominance, full departure from 

reference conditions, typically 

associated with change 

of system state

Description

Differences may be ascribed 

to good range conditions 

reducing need, complicating environmental factors 

that reduce potential and (or) 

social-political-management 

factors that limit options.

Structural and functional groups of 

vegetation are present—relative 

abundance and vigor of populations may vary; minor exotic/invasive species component may be 

part of pre-existing vegetation.

Functional or structural vegetation groups may be missing, under-represented, or in 

decline; invasive plants may be 

common but not dominant such 

that natives have been entirely 

displaced.

Sagebrush and tall grasses (usu. 

native) are missing or rare; invasive species dominate large areas; 

soil stability, water, and nutrient 

retention are likely altered; disturbance regimes may be altered.

Low effort

Minimal actions: maintain 

status and protect intact shrub 

stands (for example, from wildfire), monitor and treat invasive 

species, monitor productivity 

and grazing intensities to reserve appropriate cover. Adjust 

management as necessary to 

maintain status.

Passive Restoration, including rest from grazing may be 

supplemented with localized 

(small areas) treatments or 

restoration actions. If habitat 

and range conditions are not 

improved consider increasing 

Active Restoration.

Active Restoration required. 

Prioritize based on regional 

habitat distribution and spatially 

explicit strategic planning; Potential for success with minimal 

(less) effort exists if soil quality 

and condition is good, invasive 

species control is possible and 

practical (not cost prohibitive).

Moderate effort

Minimal actions: maintain 

status and protect intact shrub 

stands (for example, from 

wildfire), monitor and treat 

invasive species, monitor productivity and grazing intensities 

to reserve appropriate cover. 

Increase effort and alter management if condition decline is 

documented or suspected.

Passive Restoration, including rest from grazing may be 

supplemented with localized 

(small areas) treatments or 

restoration actions. If habitat 

and range conditions are not 

improved consider increasing 

Active Restoration.

Active Restoration required. 

Prioritize based on regional 

habitat distribution and spatially 

explicit strategic planning; Potential for success with minimal 

(less) effort exists if soil quality 

and condition is good, invasive 

species control is possible and 

practical (for example, not cost 

prohibitive).

High effort

Minimal actions: monitor and 

treat invasive species, monitor productivity and grazing 

intensities to reserve appropriate cover, maintain status and 

protect intact shrub stands (for 

example, from wildfire). Implement Passive Restoration and 

consider further altering management if condition decline is 

documented.

Passive Restoration recommended unless significant 

funds and motivation exist 

(for example, industrial site 

reclamation) for conducting 

Active Restoration of soils 

and vegetation. No change in 

action (for example, grazing 

rotation) will be the best practice in many areas—to avoid a 

sudden change in disturbance 

regime and (or) exotic species 

invasion.

Unless significant funds and 

motivation exist (for example, 

industrial site reclamation) for 

conducting Active Restoration 

of soils and vegetation, inventory and reclassification is recommended. New management 

plans may be developed based 

on the new designation.

*

Adapted from Pyke (2011).

1

Field estimation and comparison of results to models and (or) reference conditions is required for accurate determination of position within this matrix.

Table 24. Interpreting range condition for treatment and restoration: An adaptable and consistent decision matrix using vegetation 

and soil characteristics*

.
110 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

portions of some facilities available for conservation and 

management of native species (Knick and others, 2011). However, only 26 percent (1.68 million acres [6,815 km2

]) of DoD 

facilities in the region are sagebrush dominated, and thus they 

represent only 0.01 percent of the currently estimated sagegrouse range (165.5 million acres [670,000 km2

] total area). 

Whereas the land-use and conservation activities of DoD may 

have important local effects on the distribution of sage-grouse 

habitats (including effects on disturbance regimes) as well 

as some populations (for example, the Saylor Creek Range 

in Idaho), they represent only a small portion of the species’ 

range and therefore a small component of the conservation 

effort. Localized effects include woody plant eradication due 

to high-frequency fire returns (munitions testing and training) 

and fine-scale fragmentation due to concentrated, repeated 

vehicle maneuvers (Knick and others, 2011). 

Factor B. Population Overutilization 

In their review of threats to sage-grouse, USFWS recognized potential for “Overutilization for Commercial, Recreational, Scientific or Educational Purposes” as limited and 

not likely a factor (Valone and others, 2002) in the rangewide 

decline of sage-grouse. However, USFWS also recognized the 

ability of hunting to have significant effects on some populations, and further, the potential for interactive effects with 

indirect pressures from land-use development and other direct 

pressures, including predation and disease, makes close monitoring and annual adjustment of harvest rates a potentially 

important aspect of local population management. Importantly, 

sage-grouse are not currently commercially exploited anywhere in their range, and hunting of this species is prohibited 

in Canada and Washington. The other States within the species’ range have direct management authority over hunting, 

which is exercised through Fish and Game Divisions (see 

Section IV. Factor D). Utilization of sage-grouse populations 

includes hunting, religious and traditional uses, and research 

and education; the number of animals affected by hunting far 

outweighs the number of mortalities associated with traditional, research, and educational activities, which have been 

considered and were deemed insignificant. Therefore, hunting 

practices and regulations are primarily discussed here. 

To put hunting mortality in perspective, we recognize 

that sage-grouse, like other upland game birds, are exposed to 

a variety of predators including corvids (for example, common raven, Corvus corax), raptors (for example, golden eagle, 

Aquila chrysaetos), red fox (Vulpes vulpes), coyote (Canis 

latrans), badger (Taxidea taxus), weasels (Mustela spp.), 

ground squirrels (Spermophilus spp.), bobcat (Lynx rufus), 

western rattlesnake (Crotalus viridus), and bull snake (Pituophis catenifer) (Connelly and others, 2011a). Most mortality 

of sage-grouse is caused by predators during spring, summer, 

and fall seasons with limited mortality observed during winter 

months. Despite these natural pressures, significant mortality 

can be associated with hunting (Connelly and others, 2000b; 

Connelly and others, 2011a, p.66; Gibson and others, 2011). 

Hunting is generally concentrated during short periods of time 

in the fall, but several indigenous American tribes occasionally harvest animals in spring months. Besides concerns over 

additive mortality effects, which account for direct reductions 

in population numbers, research has documented potential bias towards adult-female mortality due to hunting, in 

particular, with an estimated 42 percent of seasonal female 

mortality associated with harvest practices (compared to 15 

percent in males) in Idaho; however, this differentiation was 

not observed in Montana and Wyoming (Connelly and others, 

2011a). If widespread and consistent, adult female bias could 

have important effects by altering the reproductive capacity 

of populations (Connelly and others, 2000b); further research 

and monitoring are needed along with potential for adjustment 

to harvest regulations, if warranted. At this time, “[n]o studies 

have demonstrated that hunting [or any other direct utilization] 

is a primary cause of reduced numbers of Greater [S]age-[G]

rouse” (Reese and Connelly, 2011, p.101), but evidence indicates significant variability in the abundance and distribution 

of birds through time and across landscape units, including 

decreased survival in October (hunting season) in some populations (Sedinger and others, 2011). Elucidation of connections between sage-grouse populations, habitat conditions, and 

mortality factors, including harvest, will require well-designed 

and implemented studies that can separate contributing factors.

B1. Hunting 

In recent decades, as information about sage-grouse 

mortality, survival, and reproductive rates has improved, and 

paradigms regarding population management were adjusted 

as State wildlife management agencies responded to population dynamics and declining population numbers by reducing 

annual harvests. Wyoming, Utah, Idaho, Oregon, Montana, 

and California reduced harvests in recent years through various regulatory mechanisms; Washington no longer permits 

harvest of sage-grouse, and Colorado, Nevada, North Dakota, 

and South Dakota have retained fairly consistent regulations 

during the past decade (Reese and Connelly, 2011). Nevada 

has closed several counties and hunting units to sage-grouse 

hunting (including Bi-State population protections) in the past 

20 years. Sage-grouse have not been commercially harvested 

since the 1930s; therefore, commercial hunting does not currently affect sage-grouse population dynamics (U.S. Fish and 

Wildlife Service, 2010b). Recent work comparing populations 

with consistently different harvest structures indicated that 

populations in areas closed to hunting had growing breeding populations, whereas areas open to hunting had declining 

population growth rates, even under moderate rates of harvest 

(Connelly and others, 2003a). Importantly, hunted populations within this study demonstrated both decreasing trends 

and increasing trends during the 6-year study, emphasizing 

the importance of local factors for determining harvest levels 

and the need to balance mortality within the tolerance of 
III. Characterization of Important Threats and Issues 111

each population (Connelly and others, 2003a; Sedinger and 

others, 2010).

Approaches and concepts used in upland small game 

management were developed early in the 20th century (circa 

1930s), and these early approaches employed little empirical 

evidence and a single universal paradigm to establish harvest 

rates (Strickland and others, 1994; Reese and Connelly, 2011). 

These early approaches assumed that all small game populations exhibited high reproductive rates and low year-to-year 

survival, thereby suggesting that hunting, even at high-harvest 

levels, was compensatory to over-wintering mortality (that is 

to say, winter survival rates account for greater mortality than 

hunting; therefore, there is no net effect on the population 

due to hunting). Based on this paradigm, harvest regulations 

have varied tremendously over time and from State-to-State 

during the past 100 years, including a population crash and 

subsequent recovery in the late 1800s (Reese and Connelly, 

2011). As research and harvest data for sage-grouse began to 

increase, evidence indicated that in some situations, harvest 

can have an additive effect on mortality, and the in mid-1990s, 

revised estimation of sage-grouse vital rates (life-span, mortality, and survival) caused Idaho and Wyoming to reduce the 

number of harvested animals (Reese and Connelly, 2011) to 

avoid additive mortality effects. Recent estimates and comparison of mortality rates for two populations, in Colorado and 

Nevada, found no evidence for additive mortality due to existing hunting of those populations (Sedinger and others, 2010).

Monitoring of harvest demographics along with lek 

counts and targeted population research combined have 

contributed to understanding of the dynamics of sage-grouse 

populations at landscape scales, including calculation of sex 

and age ratios, nest and brood success rates, and seasonal mortality (Autrienth, 1981). Further, hunters and hunting associations represent important supporters of wildlife conservation 

efforts from a range of social and political backgrounds; this 

constituency can be important for species conservation (Reese 

and Connelly, 2011). Nonetheless, appropriate harvest rates 

have not been determined for sage-grouse populations regionwide; however, several studies have addressed this issue 

(Autrienth, 1981; Crawford, 1982; Braun and Beck, 1985; 

Connelly and others, 2000a). Since public interest, population 

data, and management funds are derived from harvest of sagegrouse, hunting might be a part of conservation management 

in the future, for instance, if population numbers exceed suitable habitat. However, because populations appear to respond 

positively when released from hunting pressure, relief from 

hunting may remain a useful management strategy for populations with multiple, interacting stressors. 

B2. Religious and Traditional 

Several indigenous American tribes harvest sage-grouse 

populations within their jurisdictions associated with ceremonial practices and subsistence. Annual hunting occurs 

on the Wind River Indian Reservation (Wyoming), the 

Shoshone-Bannock Reservation (Idaho), and formerly on 

the Duck Valley Indian Reservation (Idaho-Nevada) (U.S. 

Fish and Wildlife Service, 2010b). Harvest activities on the 

Duck Valley Indian Reservation were suspended after West 

Nile virus caused precipitous population declines, demonstrating the ability of local governance bodies to respond to 

population estimates and adjust harvest practices accordingly. 

Harvest on the Wind River Reservation was limited to males 

on leks through 2009, and was perceived to have little to no 

measureable effect on the local populations; and all hunting 

on the Reservation has been closed at the recommendation 

of USFWS, due to population declines (Hnilicka, USFWS, 

Lander, Wyo., oral commun. April 2013). There are no known 

harvests of sage-grouse by indigenous tribes in Colorado, 

Oregon, North Dakota, South Dakota, or Washington (U.S. 

Fish and Wildlife Service, 2010b).

B3. Science and Education 

Dozens of scientific studies have been conducted on 

sage-grouse, including at least 50 that have directly handled 

birds. Based on 2005 estimates, the mortality rate due to 

capture, handling, or radio-tagging process was approximately 

2.7 percent of capture rate (68 mortalities of 2,491 captured) 

(U.S. Fish and Wildlife Service, 2010b); there is no evidence 

that this level of mortality causes measureable impacts on 

sage-grouse populations. Efforts to re-establish populations in 

several U.S. States and British Columbia documented translocation of more than 7,000 birds (Reese and Connelly, 1997); 

however, only 5 percent of these were successful in producing 

sustained resident populations, thus indicating high mortality risks and limited benefits from these activities (Reese and 

Connelly, 1997). However at least one translocation effort 

(Strawberry Valley, Utah) demonstrated greater success with 

estimated 60-percent survival rates (Baxter and others, 2008). 

Based on the low number of translocated animals distributed 

across many years, and the low number of mortalities associated with research and restoration activities relative to population totals and other sources of mortality, USFWS indicated 

that research and education effects on source populations were 

minimal (U.S. Fish and Wildlife Service, 2010b).

Factor C: Population Disease and Predation 

Disease 

Although sage-grouse are host to a wide array of parasites and pathogens, including macroparasitic arthropods, helminthes, and microparasites (protozoa, bacteria, viruses, and 

fungi) (Thorne and others, 1982; Connelly and others, 2004; 

Christiansen, 2011), little effort was devoted to the monitoring of disease in sage-grouse prior to the emergence of West 

Nile virus (WNv). As such, few records exist to reveal the role 

disease may have played in population declines of sage-grouse 

(Connelly and others, 2004; Christiansen, 2011; Connelly 

and others, 2011c). Thorough reviews of disease impacts on 
112 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

sage-grouse can be found in Christiansen and Tate (Wyoming 

Executive Order) and Connelly and others (2004). Ectoparasites supported by sage-grouse include lice, ticks, and dipterans (Connelly and others, 2004; Christiansen, 2011; Connelly 

and others, 2011c). Most ectoparasites cannot produce disease 

but serve as vectors of transmission and can be detrimental if 

the bird is stressed (Thorne and others, 1982; Peterson, 2004). 

High louse concentrations have been shown to limit breeding 

opportunities of male sage-grouse due to female avoidance 

of affected males and may therefore potentially impact the 

genetic diversity of the species (Boyce, 1990; Deibert, 1995; 

Connelly and others, 2011c). 

Two internal parasites have caused fatalities in sagegrouse: the disease coccidiosis is spread via protozoans 

Eimeria spp. (Connelly and others, 2004; Hagen and Bildfell, 

2007) and possibly ixodid ticks (Haimaphysalis cordeilishas). A tularemia (Francisella tularenis) outbreak coincided 

with the mortalities attributed to an ixodid tick infestation 

(Parker and others, 1932; Christiansen, 2011). It is likely 

that the tularemia, in combination with the high number of 

ticks feeding on the birds, resulted in bird mortalities (Christiansen, 2011). This is the only reported case of tularemia 

in sage-grouse. Coccidiosis, though not common today, was 

once prevalent throughout sage-grouse range (Christiansen, 

2011). This parasite causes decreased growth and significant 

mortality in young birds (Thorne and others, 1982; Connelly and others, 2004; Christiansen, 2011). Those birds that 

survive appear to develop immunity from subsequent infections (Thorne and others, 1982; Connelly and others, 2004). 

Outbreaks of coccidiosis have been clustered in areas where 

large numbers of birds gather causing the soil and water to 

become contaminated with fecal material (Scott, 1940; Honess, 1968; Connelly and others, 2004; Christiansen, 2011) and 

may regulate small, isolated populations of grouse (Peterson, 

2004). Some researchers suggest that the decline in coccidiosis 

cases is directly related to the declining density of sage-grouse 

(Christiansen, 2011).

Bacteria and fungi can also occur in sage-grouse (Scott, 

1940; Honess, 1968; Hausleitner, 2003; Connelly and others, 

2004; Peterson, 2004; Hagen and Bildfell, 2007; Christiansen, 

2011), but none currently play a role in limiting sage-grouse 

populations. This may change if environmental conditions 

result in greater concentrations of birds, leading to contamination of water supplies with fecal material (Christiansen, 2011). 

Prior to 2002, avian infectious bronchitis was the only identified virus infecting sage-grouse, and no clinical signs were 

noted (Peterson, 2004). West Nile virus (WNv) was introduced into North America in 1999 (Marra and others, 2004) 

and was first documented in sage-grouse in 2002 (Walker 

and Naugle, 2011). Although the disease is presently patchily 

distributed, it represents the only active disease that threatens 

sage-grouse populations with heavy mortality (U.S. Fish and 

Wildlife Service, 2010b). Sage-grouse are highly susceptible 

to WNv and suffer high rates of mortality (Clark and others, 

2006; McLean, 2006). For example, data from four studies 

showed a 25 percent decline in sage-grouse numbers in July 

and August of 2003 (Naugle and others, 2004) and decline in 

male and female lek attendance in 2004 (Walker and others, 

2004). Populations not exposed to WNv did not experience 

a similar decline. Deaths from WNv occur in mid-summer, 

a time when survival is typically high (Schroeder and others, 1999; Aldridge and Brigham, 2003a) making these losses 

additive and reducing annual survival (Naugle and others, 

2005). These data suggest that WNv could contribute to local 

population extirpation (Walker and others, 2004; Naugle and 

others, 2005). Resistance to WNv is very low with exposure to 

the virus typically resulting in mortality of sage-grouse (Clark 

and others, 2006; Walker and Naugle, 2011). It is unknown if 

birds surviving exposure to WNv develop immunity to future 

exposure (Clark and others, 2006; Walker and Naugle, 2011) 

or if residual effects such as reduced productivity or overwinter survival occur (Walker and others, 2007b).

The distribution and probability of WNv outbreak in 

these rural semiarid environments is poorly understood; however, the WNv life-cycle provides applicable insights. The primary vector of WNv in sagebrush ecosystems is the mosquito 

Culex tarsalis (Naugle and others, 2004; Naugle and others, 

2005; Walker and Naugle, 2011). WNv persists through a mosquito-bird-mosquito infection cycle (McLean, 2006), although 

bird-to-bird transmission has been observed (McLean, 2006; 

Walker and Naugle, 2011). The severity of WNv outbreaks 

and the transmission of the disease are primarily regulated by 

environmental factors including temperature, precipitation, 

and proximity to anthropogenic water sources, which support 

mosquito larvae (McLean, 2006; Reisen and others, 2006; 

Walker and Naugle, 2011). Mosquito activity and virus amplification is hindered by cold temperatures, restricting transmission to the summer months (Naugle and others, 2005; Zou and 

others, 2007). Cooler ambient temperatures at higher elevations and in more northerly locations may reduce the exposure 

risk of sage-grouse living in these areas (Naugle and others, 

2004; Naugle and others, 2005; Walker and Naugle, 2011).

Although C. tarsalis is able to overwinter and individual 

mosquitos emerge as infected adults in the spring (Clark 

and others, 2006; Walker and Naugle, 2011), the species is 

dependent on the availability of warm pools of water for 

larval development. As such, the ongoing proliferation of 

anthropogenic surface-water features (stock ponds, coal bed 

methane discharge ponds, irrigated agricultural fields, and 

so forth) could help maintain or possibly increase the occurrence of WNv on the landscape (Friend, 2001; Zou and others, 

2006; Walker and others, 2007b; Walker and Naugle, 2011). 

Mosquitoes are able to disperse up to 18 km (11.2 mi) from 

their larval pond (Clark and others, 2006; Walker and Naugle, 

2011) implying that the entire sage-grouse range could potentially be exposed to the virus and that the prevalence of it will 

likely increase (U.S. Fish and Wildlife Service, 2010b). If 

minimizing the impact of WNv on sage-grouse is warranted 

due to local population dynamics, controlling the number of 

mosquitos emerging from anthropogenic water sources and 

reducing availability of these water features as habitat may be 

important options. Sage-grouse do not require standing water 
III. Characterization of Important Threats and Issues 113

(Schroeder and others, 1999; Connelly and others, 2004); 

therefore, the practice of placing water developments in arid 

landscapes for the benefit of sage-grouse may be reduced or 

eliminated (Clark and others, 2006; Walker and Naugle, 2011) 

without expectation of population impacts. Water sources may 

have specific value for managing some landscapes, but the 

threat of spreading WNv through anthropogenic water sources 

indicates consideration of control or mitigation to discourage 

breeding mosquitos either through construction, modification, or management (Doherty, 2007) may be warranted. The 

biting midge Culicoides sonorensis has also been identified as 

a possible vector of WNv (Schmidtmann, 2005); this species requires muddy banks to lay its eggs and therefore may 

particularly be a factor in areas with large numbers of stock 

ponds. C. sonorensis is an important vector of blue-tongue in 

ruminants, and though it is not known if they actively feed on 

avifauna, WNv was found in a midge sample from the Powder 

River Basin, Wyoming (Schmidtmann, 2005). Because of the 

large number of water sources and their widespread distribution, mitigation measures may be cost prohibitive (U.S. Fish 

and Wildlife Service, 2010b), but may be warranted when 

sage-grouse populations are small, isolated, or genetically limited (U.S. Fish and Wildlife Service, 2010b). Caution is warranted when employing mosquito control to ensure that benefit 

from reducing the occurrence of WNv is not overshadowed by 

cascading ecological effects (Marra and others, 2004). WNv 

fowl vaccines were tested in captive birds and were largely 

ineffective (Clark and others, 2006; Walker and Naugle, 2011). 

Development of a sage-grouse specific vaccine would require 

market incentive and would likely not be practical for largescale deployment (U.S. Fish and Wildlife Service, 2010b).

Models suggest that the prevalence of WNv is likely to 

increase throughout the range of sage-grouse as the number 

of anthropogenic water sources and ambient temperatures 

increase (U.S. Fish and Wildlife Service, 2010b). Sagegrouse populations will respond differently to WNv infections 

depending on factors that affect exposure and susceptibility 

(Clark and others, 2006; Walker and Naugle, 2011). Though 

larger populations may be able to absorb losses from WNv as 

long as available habitat is sufficient (Clark and others, 2006; 

Walker and Naugle, 2011), a WNv outbreak in small, isolated, 

or genetically limited populations may be devastating and 

could reduce a population beyond a point where recovery is 

possible (Clark and others, 2006; Walker and Naugle, 2011). 

Sage-grouse gather in mesic habitats during the mid-to 

late summer (Connelly and others, 2000c) making them potentially more vulnerable to all of the pathogens discussed. More 

dispersed populations in less arid habitats may not suffer the 

same threats. Historically, obvious morbidity and mortality in 

sage-grouse caused by the pathogens discussed above was tied 

to higher concentrations of sage-grouse localized near water 

sources during dry conditions (Scott, 1940; Honess, 1968; 

Connelly and others, 2004; Christiansen, 2011). “Likely” 

climate-change scenarios, according to the Intergovernmental 

Panel on Climate Change (IPCC, 2007), suggest the impacts 

of disease on sage-grouse could increase (Neilson and others, 

2005) as habitat conditions become limiting due to increased 

temperatures and drought conditions predicted to occur across 

the sagebrush biome (IPCC, 2007). If realized, these conditions could particularly limit the availability of mesic areas, 

potentially leading to high densities of sage-grouse around 

these areas and other anthropogenic water sources. Past outbreaks of bacterial infections, coccidiosis and WNv, have been 

linked to such circumstances. 

Predation 

Typically sage-grouse live between 3 and 6 years, with 

individuals up to 9 years of age reported in the wild (Connelly and others, 2004). Predation is commonly identified as 

the primary cause of direct mortality for sage-grouse at all 

life stages (Schroeder and others, 1999; Connelly and others, 

2000; Connelly and others, 2011), but there is little published 

support for predation being a limiting factor in sage-grouse 

populations (Connelly and others, 2004), particularly in areas 

where there is high-quality habitat (Hagen, 2011). Sage-grouse 

have co-evolved with a suite of predators, including coyotes 

(Canis latrans), badgers (Taxidea taxus), bobcats (Felis rufus), 

and red fox (Vulpes vulpes). Several raptor species are common predators of juvenile and adult sage-grouse (Patterson, 

1952; Schroeder and others, 1999; Schroeder and Baydack, 

2001), and coyote, badger, common raven (Corvus corax), and 

black-billed magpie (Pica hudsonia) are regular nest predators. Ground squirrels (Spermophilus spp.) were once thought 

to be major nest predators, but recent evidence indicates that 

the mandibles of some ground squirrel species are physically 

unable to puncture sage-grouse eggs (Holloran and Anderson, 

2003; Coates, 2007). The degree and significance of snake 

predation on sage-grouse nests is unknown (Holloran and 

Anderson, 2003; Coates, 2007). Cryptic coloration, habitat 

selection, and behavioral patterns have allowed sage-grouse 

to persist throughout sagebrush habitats (Schroeder and others, 1999), co-existing with these predators. Although sagegrouse have a number of predators, none are known to focus 

on sage-grouse as a primary food source. Most predators of 

sage-grouse depend primarily on rodents and lagomorphs 

(Schroeder and others, 1999); however, alternate prey, such as 

sage-grouse, may still experience high-predation rates either 

because they are targeted when the primary prey become 

scarce or if predators kill indiscriminately as predator numbers 

increase (Norrdahl and Korpimaki, 2000).

Male sage-grouse have the greatest exposure to predation 

at leks (Schroeder and others, 1999; Schroeder and Baydack, 

2001; Hagen, 2011) where they congregate and perform conspicuous mating displays. The concentration of birds present 

may attract a variety of predators and affect grouse-avoidance 

behavior (Aspbury and Gibson, 2004; Boyko and others, 

2004). Because of the disproportionate predation on males 

during the breeding season, female sage-grouse have a longer 

life expectancy (Schroeder and others, 1999). Female sagegrouse are more susceptible to predators while nesting, but 

mortality rates are low as hens will abandon their nests when 
114 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

disturbed by predators (Hagen, 2011). Predation on sagegrouse outside of the lekking, nesting, and brood-rearing periods is rare (Connelly and others, 2000a; Moynahan and others, 

2006; Hagen, 2011). The highly polygynous nature of sagegrouse suggests that sage-grouse populations are more sensitive to predation upon females (U.S. Fish and Wildlife Service, 

2010b) because only a few males per lek breed each year. 

Predation of breeding hens and young chicks may negatively 

affect sage-grouse population numbers as these two cohorts 

are the most significant contributors to population productivity 

(Baxter and others, 2008; Connelly and others, 2011a).

Human encroachment into sagebrush habitats has 

affected the predator–sage-grouse dynamic. The act of altering 

the landscape can create an influx of predators into an area 

and lead to a decline in annual recruitment (Gregg and others, 1994; Delong and others, 1995; Braun, 1998; Schroeder 

and Baydack, 2001; Coates, 2007; Hagen, 2011). Predators 

that are closely associated with human development, red fox 

and corvids, have increased in abundance over the sagebrush landscape (Sovada and others, 1995). These species in 

particular have been shown to be efficient predators of nests 

and juvenile sage-grouse (Schroeder and others, 1999). As 

sage-grouse habitat is lost or fragmented due to energy development, agriculture, or exurban development, quality nesting 

and brood-rearing habitat becomes restricted (Bui, 2009). The 

higher density of grouse in lower quality habitat combined 

with potentially easier predator access along roads, fence 

rows, edges, and trails, may make foraging easier for predators 

(Connelly and others, 2004; Holloran, 2005; Holloran and others, 2005; Aldridge and Boyce, 2007; Bui, 2009). In addition 

to habitat loss and fragmentation, ranches, farms, and other 

housing developments have led to the introduction of domestic 

dogs (Canis domesticus) and cats (Felis domesticus) into sagegrouse habitats, both of which may prey upon grouse (Connelly and others, 2004; Holloran, 2005; Holloran and others, 

2005; Aldridge and Boyce, 2007; Bui, 2009). Roads have been 

shown to be particularly efficient as mechanisms of distribution for predators throughout the sagebrush landscape. Some 

mammalian species (Forman and Alexander, 1998; Forman, 

2000) and ravens (Knight and others, 1993; Connelly and 

others, 2004) have used these linear features to expand their 

distribution into previously unused regions, increasing the risk 

of predation to sage-grouse.

Nest predation has been linked to low herbaceous cover 

(Gregg and others, 1994; Delong and others, 1995; Braun, 

1998; Schroeder and Baydack, 2001; Coates, 2007; Coates 

and others, 2008; Hagen, 2011). Sage-grouse select nesting 

sites specifically based on the amount of grass and forb cover 

(Hagen and others, 2007) because it is needed to conceal the 

nest from predators. Reduction of grass height due to livestock 

grazing below 4 in. (18 cm) has been shown to negatively 

affect nest survival (Gregg and others, 1994). However, 

abundant cover has also been shown to facilitate badger 

predation because it attracts small mammals, the primary prey 

of badgers (Coates, 2007). Adequate grass and forb cover 

provides valuable hiding cover for young chicks (Schroeder 

and Baydack, 2001), a life stage during which mortality due 

to predation has been estimated to be highest, at 82 percent 

(Gregg and others, 2007). 

To support maintenance of suitable grass and forb cover 

and minimize associated predation risks, careful monitoring of 

grazing allotments within sage-grouse nesting habitat may be 

coupled with livestock management to ensure suitable grass 

and forb cover is reserved. In addition, pasture fencing creates 

perching sites for raptors and corvids and travel corridors 

for coyotes and foxes, increasing predation risk across many 

habitats (Call and Maser, 1985; Braun, 1998; Connelly and 

others, 2000b; Beck and others, 2003; Knick and others, 2003; 

Connelly and others, 2004) and leading to habitat avoidance 

by sage-grouse (Call and Maser, 1985; Braun, 1998; Connelly 

and others, 2000b,; Beck and others, 2003; Knick and others, 

2003; Connelly and others, 2004). 

Similarly, power poles, towers, and fence posts provide 

attractive hunting and roosting perches for corvids and raptors (Steenhof and others, 1993; Connelly and others, 2000b; 

Manville, 2002; Vander Haegen and others, 2002; Connelly 

and others, 2004). Power poles can increase a raptor’s range of 

vision and allow for greater speed during attacks, increasing 

their hunting efficiency (Steenhof and others, 1993; Connelly 

and others, 2000b; Manville, 2002; Vander Haegen and others, 

2002; Connelly and others, 2004). After the installation of 

transmission lines, densities of raptors and corvids increased 

markedly (Ellis, 1985; Steenhof and others, 1993) as did 

predation on sage-grouse (Ellis, 1985; Steenhof and others, 

1993). Power lines may also cause changes in lek dynamics, with lower growth rates observed on leks within 0.25 mi 

(0.4 km ) of new power lines in the Powder River Basin of 

Wyoming as compared to those farther from the lines. This 

was attributed to increased raptor predation (Braun and others, 

2002). Raptors and corvids forage on average 3.1 to 4.3 mi (5 

to 6.9 km ) from perching sites, potentially impacting 32 to 40 

percent of the sage-grouse conservation area (Connelly and 

others, 2004). Removing or reducing the number of perching structures and landfills in key nesting, brood rearing, and 

lekking habitats may reduce predation pressure on sage-grouse 

(Bui, 2009; Leu, 2011).

Predator Control

Although there is little published information supporting 

the notion that predation is a limiting factor on sage-grouse 

(Connelly and Braun, 1997; Connelly and others, 2000b; 

Schroeder and Baydack, 2001), arguments continue to be 

made supporting predator control as an important management 

action (Wambolt and others, 2002). Additionally, relatively 

high annual survival rates of adult sage-grouse (0.59–0.77 

for females, 0.37–0.63 for males) (Zablan and others, 2003) 

accompanied by documented ineffectiveness of coyote 

control in affecting nest survival in one area in Wyoming 

(Slater, 2003), further reinforce the idea that predation is not 

a widespread factor acting to depress sage-grouse populations. Where predator removal has been used as a management 
III. Characterization of Important Threats and Issues 115

tool, higher numbers of sage-grouse have sometimes been 

observed in the fall, but these gains have not carried over to 

spring breeding populations (Cote, 1997; Hagen, 2011; Leu, 

2011). The removal of coyotes in some areas has resulted in 

an increase in the numbers of mesopredators, which may have 

greater impacts on grouse populations (Mezquida and others, 2006). Similarly, raven removal in northeastern Nevada 

resulted in only short-term reductions in raven numbers 

(Coates, 2007), and any benefits to sage-grouse populations 

were negated by an increase in badger predation (Coates, 

2007). Predator removal may be warranted in areas with low 

habitat quality (that is, heavily fragmented or areas of high 

anthropogenic disturbance) supporting inflated numbers of 

synanthropic predators; however, predator numbers will 

rebound quickly without continual control (Hagen, 2011).

Factor E: Pesticides and Contaminants 

Because of the overlap between current cropland distributions and historically high-quality sagebrush habitats (deep 

loamy and sandy loam soils, valley bottoms, and wet meadows) and fidelity of sage-grouse populations to these habitats 

(Berry and Eng, 1985; Dunn and Braun, 1985; Fischer and 

others, 1993; Holloran and Anderson, 2005; Holloran and 

others, 2010), there can be considerable summer use of agricultural lands by sage-grouse even though current sagebrush 

cover may be relatively low. With these overlapping uses 

comes risk of poisoning by pesticides (Blus and others, 1989; 

Connelly and Blus, 1991) and other chemicals used in vegetation and pest management. Many of these factors may have 

indirect effects on health and fitness, in addition to the obvious 

effects on survival (Connelly and others, 2004; table 25).

Pesticides

Sage-grouse typically avoid human developments and 

highly cultivated landscapes; however, because these lands 

often replaced historically important habitats and remain 

adjacent to remaining sagebrush habitats, use of these areas 

characterized by “low nest success” and “poor chick survival” 

(due to increased risks) remains common on some landscapes 

(Aldridge and Boyce, 2007). Nonetheless, irrigated crops, hay, 

and pastures represent an attractive source of foods including 

insects, especially during drought years and later in the broodrearing season when native forbs become desiccated (Hagen, 

2007; Connelly and others, 2011d; Knick and others, 2011). 

Research using collared animals found that 18 percent of 

marked sage-grouse in Idaho used croplands adjacent to sagebrush habitat that had been sprayed by dimethoate and methamidophos (Blus and others, 1989). Posthumous assessments 

indicated 5 percent mortality in the first year and 16 percent in 

the following year due to organophosphorus poisoning. This 

research was focused in an area with extensive agricultural 

development adjacent to sagebrush habitats; therefore, similar 

concentrations may be anticipated in similarly developed 

areas, but this level of mortality would extend rangewide only 

with similar applications. 

In addition to direct impacts of pesticides through direct 

contact (Blus and others, 1989; Connelly and others, 2004), 

reduction of important seasonal foods such as forbs and 

insects can affect the forage base (Eng, 1952; Connelly and 

others, 2004); therefore, effects on sage-grouse seasonal habitat requirements may be an important consideration for pest 

and pesticide management. Insects are an important component of early brood-rearing habitat (Patterson, 1952; Klebenow and Gray, 1968; Johnson and Boyce, 1991). A complete 

assessment of early brood-rearing habitat includes an evaluation of insect abundance because they are an important part 

of seasonal diets. A depauperate or undependable invertebrate 

resource base is likely to depress growth rates and brood-rearing success (Connelly and others, 2004); however, vegetation 

alteration due to insect population peaks (outbreaks) may have 

negative effects on the forage base (Ritchie and Tilman, 1992; 

Scherber and others, 2010) suggesting need for future evaluation and management adaptation regarding population interactions with insect herbivores.

Herbicides 

In addition to pesticides, several herbicides are commonly applied in and around the sagebrush ecosystem; alteration of desirable components of the habitat may be targeted 

or unintentional depending on the vegetation targets, for 

example, sagebrush or invasive species. Many enhancement 

and sagebrush restoration treatments involved alterations that 

include the removal of sagebrush (Carr and Glover, 1970; Klebenow, 1970; Connelly and others, 2004) to increase the cover 

and productivity of herbaceous species in the treatment areas. 

Although these treatments continue in many areas, decreased 

emphasis on sagebrush removal or reduction and increased 

emphasis on reducing invasive plant-species distributions 

mean that some chemicals may be applied on, or adjacent to, 

priority habitat areas. Most modern chemicals are applied at 

levels expected to decay quickly with minimal soil residuals. 

For example 2,4-D (2,4-Dichlorophenoxyacetic acid) degrades 

rapidly with half-life values estimated at 1–14 days (Gervais 

and others, 2008; table 25); however, detectable residues can 

persist for up to a year (Tu and others, 2001). Similarly, other 

commonly applied chemical herbicides, such as Imazapic (Plateau®, American Cyanamid Co.), Tebuthiuron (Spike80®, Dow 

AgroSciences LLC), and Glyphosphate (Round-up®, Rodeo®, 

Monsanto Co.) that interrupt cell chemistry had minimal 

effects on test animals and decay quickly in the environment. 

Tebuthiuron may cause mild skin irritation in mammals but 

is essentially nonirritating (tested on rabbits and guinea pigs); 

single-dose oral toxicity is moderate in mammals (LD50 for 

rats is 488mg/kg), but it is not a known carcinogen (Dow 

AgroSciences, 1999). Glyphosphate inhibits enzyme and 

amino acid formation in chloroplasts of most plant species; 

these organelles are not present in animal cells making transferred toxicity unlikely. Glyphosphate has an average half-life 
116 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Table 25. Insecticides and herbicides certified for application and commonly applied on and around sagebrush habitats.

Chemical Use Direct/Acute Effects Indirect Effects

Dimethoate Pesticide, forage, seed alfalfa Very Toxic (Blus and others, 1989) Reduced availability of insects 

for food

Methamidophos Pesticide, seed alfalfa, potatoes; 

US registration cancelled 

9/23/2009

Very Toxic (Blus and others, 1989) Reduced availability of insects 

for food

Malathion Pesticide, grasshoppers Toxic Reduced availability of insects 

for food

Carbaryl Pesticide, grasshoppers Low to Moderately Toxic Reduced availability of insects 

for food

Dimilin Pesticide, grasshoppers Low Toxicity Reduced availability of insects 

for food

2,4-D Herbicide, sagebrush thinning Low Toxicity Reduced sagebrush cover; 

reduced forb availability

Plateau ® (Imazapic)1 Herbicide, cheatgrass No more than slightly toxic Reduced forb availability

Spike ® (Tebuthiuron) 1 Herbicide, sagebrush thinning Low to Moderately Toxic Reduced sagebrush cover

Roundup ® (Glyphosphate) 1 Herbicide No more than slightly toxic Reduced sagebrush cover; 

reduced forb availability

1 Imazapic, Tebuthiuron, and Glyphosphate have chemical actions that target plant physiology; it is highly unlikely that they have a direct effect on sagegrouse at levels typically applied (according to manufacturer instructions).

of 47 days (Tu and others, 2001). According to the manufacturers, direct exposure to these chemicals may cause eye 

irritation, absorption through the skin, and inhalation toxicity 

effects. They are not known to bioaccumulate in animals and 

are rapidly excreted in urine and feces rendering them mostly 

nontoxic to a wide range of nontarget organisms including 

mammals, birds, fish, aquatic invertebrates, and insects (Tu 

and others, 2001). Direct assessment of toxicity effects on 

sage-grouse have not been conducted, but existing information 

indicates little concern for direct effects of certified herbicides 

on sage-grouse health.

IV. Factor D: Policies and Programs

Affecting Sage-Grouse Conservation 

In 2010, a lack of adequate regulatory mechanisms 

was determined by the USFWS to be a substantial threat to 

sage-grouse in its 12-Month Findings for Petitions to List the 

Greater Sage-Grouse (U.S. Fish and Wildlife Service, 2010b). 

In an effort to address sage-grouse conservation needs, many 

agreements and partnerships have been established across 

the sage-grouse range with various levels of commitment, 

jurisdiction, and participation. The national efforts of the 

BLM and USFS were outlined at the beginning of this report. 

To support continued facilitation and integrated management 

across administrative and political boundaries, this section 

documents existing and proposed conservation efforts directed 

at sage-grouse, including regulatory and nonregulatory 

approaches by Federal, State, and local agencies, as well as 

private lands and, where appropriate, the threats those efforts 

seek to address. This section aims to provide land managers 

and agency planners with an overview of those conservation 

activities, programs, and regulations across the range so that 

local and regional planning efforts may be recognized and 

continuing coordination across political and administrative 

boundaries encouraged.

One of the key challenges in implementing sage-grouse 

conservation efforts is the mixed pattern of surface-land 

ownership and jurisdiction across the species’ range (Knick 

and Connelly, 2011b). This patchwork of land ownership is 

a result of historical public land policies that have guided 

disposition of public lands in the Western United States since 

their settlement (Knick and Connelly, 2011b). With such 

diverse ownership across a large range (table 26), regulatory actions and policies aimed at sage-grouse conservation require coordination across traditional geopolitical and 

landownership boundaries; a given population of sage-grouse 

can migrate between privately owned land and land administered by numerous Federal and State agencies (Stiver, 2011). 

Each class of surface ownership carries different management 

requirements and objectives. Notably, the BLM and USFS 

manage approximately 53 percent of the surface area across 

the region, with BLM jurisdiction over approximately 44 

percent of the sage-grouse range and USFS administration 
IV. Factor D: Policies and Programs Affecting Sage-Grouse Conservation 117

of 4 percent of the range (estimated using PPH and PGH; 

table 26). Therefore, more than 50 percent of the surface area 

across the range is managed for multiple (often competing) 

uses including requirements to balance commodity production 

with wildlife (Knick and Connelly, 2011). The USFWS is the 

only Federal agency with an exclusive wildlife conservation 

mandate; however, it manages only one percent of the species’ 

habitat (Knick, 2011). A large percent (31 percent) of surface 

area within the sage-grouse range remains in private ownership (Knick, 2011). States and other Federal agencies and 

departments manage the remainder of the surface area within 

the range (Knick, 2011). 

Rangewide Conservation Efforts

The range of the sage-grouse includes habitat within 

the United States and Canada, with 99 percent of the current 

population found in the United States and the remaining 1 

percent found in Canada (Stiver and others, 2006a). However, 

because the sage-grouse is not considered to be a migratory 

species, it is not afforded the protections of the Migratory Bird 

Treaty Act (16 U.S.C. § 703 et seq.; U.S. Fish and Wildlife 

Service, 2010b). 

Though not regulatory mechanisms, a series of Memoranda of Understanding (MOUs) have been entered into by 

various State and Federal agencies that acknowledge the collaboration among the signatories. The partnerships formed by 

the MOUs have produced a rangewide conservation framework (Stiver, 2011). In 2004, the Western Association of Fish 

and Wildlife Agencies (WAFWA) in cooperation with the 

USFS, BLM, USFWS, and USGS (U.S. Geological Survey), 

published the Conservation Assessment of Greater SageGrouse and Sagebrush Habitats (Connelly and others, 2004), a 

comprehensive, ecologically focused analysis that documented 

the current status and potential factors influencing the longterm conservation of sage-grouse populations and sagebrush 

ecosystems. In 2006, WAFWA released the Greater SageGrouse Comprehensive Conservation Strategy (Stiver and 

others, 2006a), which includes seven substrategies to “maintain and enhance populations and distribution of sage-grouse 

by protecting and improving sagebrush habitats and ecosystems that sustain these populations.” This strategy was itself 

a collaborative effort, reflecting the collective knowledge of 

local working groups, State and provincial conservation plans, 

Federal and State agencies, and a rangewide-issues forum 

(Stiver, 2011). In 2011, agency, academic, and private sector 

experts published a monograph on sage-grouse populations, 

sagebrush habitats, and the relations between land use and 

sage-grouse populations across the sage-grouse range (Knick 

and Connelly, 2011).

In the 2006 strategy, WAFWA recommended passage 

of the North American Sagebrush Ecosystem Conservation 

Act (NASECA, Stiver and others, 2006a). The NASECA is 

modeled after the North American Wetland Conservation Act, 

calls for leadership through the establishment of an NASECA 

Council, and proposes an initial five-year budget of $425 

million to be administered by a fiduciary entity and dispersed 

across MZs, States, and provinces (Stiver and others, 2006a). 

The precise details of NASECA are to be determined by the 

Western Governors’ Association, which along with WAFWA 

completed a draft version of the Act in 2009 (Stiver and others, 2006a; Western Governors’ Association, 2011). In 2011, 

the Western Governors’ Association requested Congress to 

pass the NASECA and appropriate the necessary funds for 

implementation (Western Governors’ Association, 2011), and 

if approved, it will provide a rangewide funding mechanism to 

implement WAFWA’s Comprehensive Conservation Strategy. 

Canadian Conservation Efforts

The sage-grouse is a protected species in Canada under 

schedule 1 of the Species at Risk Act (SARA; Canada Gazette, 

2002; U.S. Fish and Wildlife Service, 2010b). The Species 

at Risk Act, like its counterpart the Endangered Species Act, 

prohibits harming individuals within a protected species and 

allows for the protection of critical habitat (Aldridge and 

Brigham, 2003a). 

Sage-grouse are also protected under the laws of the 

provinces of Alberta and Saskatchewan, neither of which 

allow harvesting of individual birds (Aldridge and Brigham, 

2003a). In Saskatchewan, sage-grouse are listed as endangered 

under the Saskatchewan Wildlife Act, which restricts development within 1,640 ft (500 m) of leks and prohibits construction within 3,281 ft (1,000 m) of leks between March 15 and 

May 15 (Aldridge and Brigham, 2003a, p. 32). Additionally, under Saskatchewan’s Wildlife Habitat Protection Act, 

sage-grouse habitat is afforded protection from transfer and 

cultivation (Aldridge and Brigham, 2003a). Alberta protects 

individual birds, but not sage-grouse habitat (Aldridge and 

Brigham, 2003a). USFWS has acknowledged these protections 

but concluded they are insufficient to assure conservation of 

the species (U.S. Fish and Wildlife Service 2010b). 

United States Federal Agency Conservation 

Efforts

Natural Resources Conservation Service: SageGrouse Initiative 

Launched in 2010, the USDA NRCS Sage-Grouse 

Initiative (SGI) supports work with private landowners in 11 

Western States to improve habitat for sage-grouse while simultaneously improving working ranches (U.S. Natural Resources 

Conservation Service, 2012c). With approximately 31 percent 

of all sagebrush habitat across the range in private ownership 

(table 27; Stiver, 2011), a unique opportunity exists for NRCS 

to benefit sage-grouse and ensure the persistence of large and 

intact rangelands through implementation of the SGI (U.S. 

Fish and Wildlife Service, 2010a). 
118 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Table 26. Summary of management jurisdiction* across Management Zones (MZs) by acres of preliminary priority and preliminary 

general habitats (PPH and PGH, respectively).

PPH PGH

Management Zone

 Entity

Total Surface Area 

(acres)

SG 

Habitat 

(acres)

Area 

(%)

SG Habitat 

(acres)

Area 

(%)

MZ I–GP 84,110,800 11,636,400 13.8 34,663,000 41.2

BLM 8,325,300 2,994,300 36.0 4,524,900 54.4

Forest Service 4,532,500 292,400 6.5 515,300 11.4

Tribal and Other Federal 5,458,500 219,700 4.0 2,427,700 44.5

Private 54,998,900 7,132,500 13.0 24,682,800 44.9

State 5,421,400 995,600 18.4 2,498,400 46.1

Other 5,374,100 1,900 0.0 13,900 0.3

MZ II and VII–WB & CP 92,776,100 17,476,000 18.8 19,200,200 20.7

BLM 30,295,000 9,021,200 29.8 9,012,500 29.7

Forest Service 23,558,800 162,000 0.7 452,500 1.9

Tribal and Other Federal 7,086,200 784,000 11.1 1,354,600 19.1

Private 27,405,400 6,233,900 22.7 7,394,800 27.0

State 4,053,900 1,244,800 30.7 979,800 24.2

Other 376,700 30,100 8.0 6,000 1.6

MZ III–SGB 78,429,300 10,028,500 12.8 3,970,100 5.1

BLM 45,097,500 6,309,400 14.0 3,199,800 7.1

Forest Service 12,377,600 1,236,200 10.0 356,200 2.9

Tribal and Other Federal 5,282,700 260,800 4.9 29,100 0.6

Private 12,251,400 1,836,200 15.0 384,800 3.1

State 3,101,900 385,900 12.4 200 0.0

MZ IV–SRP 78,259,200 21,930,600 28.0 10,958,500 14.0

BLM 26,220,300 13,710,700 52.3 4,928,200 18.8

Forest Service 22,291,600 1,613,800 7.2 1,113,500 5.0

Tribal and Other Federal 2,431,000 633,600 26.1 522,500 21.5

Private 23,150,400 4,890,200 21.1 3,516,700 15.2

State 3,681,000 1,019,400 27.7 846,200 23.0

Other 484,800 62,900 13.0 31,400 6.5

MZ V–NGB 36,447,900 7,097,200 19.5 5,808,000 15.9

BLM 14,179,800 5,117,500 36.1 4,196,700 29.6

Forest Service 10,136,000 62,200 0.6 114,900 1.1

Tribal and Other Federal 1,964,700 717,100 36.5 101,800 5.2

Private 6,299,000 798,000 12.7 1,199,000 19.0

State 473,600 64,900 13.7 115,800 24.5

Other 3,394,700 337,500 9.9 79,800 2.4

*

Data Sources: BLM GSSP Surface Management Agency 2012; USFS Enterprise Data Warehouse 2012. Small differences between individual entity totals 

and MZ summary values may exist due to rounding of estimates during calculations.
IV. Factor D: Policies and Programs Affecting Sage-Grouse Conservation 119

Table 27. Sage-Grouse Initiative efforts by State (through 2011) with delineation of threats to sage-grouse targeted with mitigation.

State 

Acres to be 

Treated with 

Improved 

Grazing Systems

“High Risk” 

Fence to be 

Marked or 

Removed (ft)

Acres of 

Pinyon-Juniper 

to be Removed

Habitat Loss Due to 

Fire or Conversion 

for Agriculture

(total acres 

to be restored)

Brood Rearing 

Habitat 

Improvements 

(acres)

Conservation 

Easements 

(acres secured)

California 23,395 420,501 28,665 1,020 66 –

Colorado 18,817 9,676 555 3,661 4 5,017

Idaho 206,170 309,892 5,600 4,449 370 21,434

Montana 246,814 460,854 – 883 – 42,191

Nevada 4,571 81,637 7,423 3,732 5,883 3,695

N. Dakota 4,213 2,909 – 565 – –

Oregon 8,488 5,280 54,626 – – –

S. Dakota 127,812 – – – – –

Utah 48,462 52,765 18,525 11,986 – 14,980

Wyoming 414,422 401,281 22 29 60 120,706

Totals 1,103,164 1,744,795 115,416 26,325 6,383 208,023

Participation in the SGI program is voluntary, but willing 

participants enter into binding contracts or easements to ensure 

that conservation practices that enhance sage-grouse habitat 

are implemented (U.S. Fish and Wildlife Service, 2010a). 

Though participation is voluntary, and thus not a traditional 

regulatory approach, participating landowners are bound by 

contract (usually three to five years in duration) to implement, 

in consultation with NRCS staff, conservation practices if they 

wish to receive the financial incentives offered by the SGI. 

These financial incentives generally take the form of payments 

to offset costs of implementing conservation practices and 

easement or rental payments for long-term conservation (U.S. 

Fish and Wildlife Service, 2010b). Demand to participate in 

the program has been strong; as of March 2012, 462 ranchers 

were enrolled in the SGI, covering 1.7 million acres (6,880 

km2

; U.S. Natural Resources Conservation Service, 2012a). 

Funding for the SGI, through conservation programs provided 

for in the Food, Conservation, and Energy Act of 2008 (Farm 

Bill), has increased to meet the interest—from $21 million 

in fiscal year (FY) 2010 to more than $92 million in FY 

2011 (U.S. Natural Resources Conservation Service, 2012c). 

In addition to the economic incentives offered by the SGI, 

participating landowners also have the benefit of knowing 

that if the sage-grouse is listed as threatened or endangered, 

their efforts under the SGI will comply with the ESA (though 

participation does not by itself offer permits for incidental take 

or protection similar to a Candidate Conservation Agreement 

with Assurances). Although potentially effective at conserving 

sage-grouse populations and habitat on private lands, incentive-based conservation programs that fund the SGI generally 

require reauthorization from Congress under subsequent Farm 

Bills, and therefore these funding streams are potentially variable as they are subject to the political process. 

The NRCS is working to implement SGI conservation 

measures on private lands that address many of the threats 

to sage-grouse identified in the 2010 Listing Decision. Many 

of those threats, including fragmented landscapes and urban 

expansion, overgrazing, and conifer encroachment are also 

threats to sustainable ranching (U.S. Natural Resources 

Conservation Service, 2012c). Conversely, intact landscapes, 

an abundance of perennial grasses and forbs, invasive species 

management, and well-designed grazing plans benefit both 

sage-grouse and promote sustainable ranching (U.S. Natural 

Resources Conservation Service, 2012c).

Across the range, application of SGI conservation standards, including improved grazing systems, fence modification and removal, tree removal, and conservation easements 

vary from State to State. Grazing is the most widespread land 

use across the sagebrush biome (Connelly and others, 2004) 

and through the SGI, NRCS is working with landowners to 

implement grazing practices that, among other benefits to 

the species, increase cover in seasonal habitats (U.S. Natural 

Resources Conservation Service, 2012a). Nearly 415,000 

acres (1,680 km2

) in Wyoming have (or are under contract to 

receive) some form of improved grazing system that could 

support increased hiding cover (U.S. Natural Resources Conservation Service, 2012a). A component of grazing management, pasture fencing, has created a variety of threats to sagegrouse, such as mortality from collisions, increased predation 

due to perch sites and corridors, and habitat fragmentation 

(Call and Maser, 1985; Braun, 1998; Oyler-McCance and 

others, 2001; Beck and others, 2003; Knick and others, 2003; 

Connelly and others, 2004). Nearly 625 miles (1006 km) of 
120 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

fences were constructed annually from 1996 to 2002 in the 

sage-grouse range with most being constructed in Montana, 

Nevada, Oregon, and Wyoming (Connelly and others, 2004). 

Through the SGI program, participants have agreed to remove 

or mark nearly 350 miles (563 km) of high-risk fence (U.S. 

Natural Resources Conservation Service, 2012a). In Idaho, 

a recent study demonstrated that fence marking can lead to 

reduced sage-grouse collisions (Stevens and others, 2011). 

SGI has two particular approaches to restoring sagebrush 

habitats that have been degraded or modified. NRCS is working with landowners to remove juniper and other expanding 

conifers from valuable habitats. For example, 54,626 acres 

(405 km2

) of juniper and pine have already been treated in 

Oregon (MZs IV and V; table 27). Urbanization and conversion of habitat to agriculture, at the other end of the habitat 

change spectrum, have caused habitat loss and fragmentation 

across the Western United States, which has been determined 

to be a “key cause, if not the primary cause, of the decline 

of sage-grouse populations” (U.S. Fish and Wildlife Service, 

2010b). Conservation easements are one important approach 

to creating and maintaining large, intact sagebrush communities (U.S. Natural Resources Conservation Service, 2012a). 

At this time, NRCS has secured conservation easements 

on 208,023 acres (840 km2

) across the sage-grouse range 

(U.S. Natural Resources Conservation Service, 2012a) with 

the largest percentage of easements occurring in Wyoming 

(120,706 acres [490 km2

]), Montana (42,191 acres [171 km2]), 

and Idaho (21,434 acres [87 km2

]) (U.S. Natural Resources 

Conservation Service, 2012a).

Farm Service Agency: Conservation Reserve 

Program

Similar to the incentive-based programs that fund the 

SGI, the Conservation Reserve Program (CRP) is a program 

administered by the USDA Farm Service Agency (FSA, U.S. 

Farm Service Agency, 2010). CRP lands are generally taken 

out of agricultural production and planted with perennial 

vegetative cover. Generally, contracts under the CRP program run for 10–15 years (U.S. Farm Service Agency, 2010). 

Conversion of sagebrush to agriculture influences the ability 

of sagebrush-dominated landscapes to support sage-grouse 

through direct habitat loss and fragmentation (Connelly and 

others, 2004). CRP fields have provided valuable habitat in 

Washington (Schroeder and Vander Haegen, 2006), but the 

value of these lands to sage-grouse across its entire range has 

not been demonstrated (Stiver and others, 2006b). Launched 

in 2008, State Acres for Wildlife Enhancement (SAFE) is a 

program within CRP designed to “address state and regional 

high-priority wildlife objectives” (U.S. Farm Service Agency, 

2008). Several States across the sage-grouse range have 

directed SAFE efforts toward enhancing sagebrush habitat. In 

Colorado, SAFE project partners hope to enroll 12,600 acres 

(51 km2

) in CRP to restore and enhance habitat for several 

species of grouse, including sage-grouse. Montana and North 

Dakota are each aiming to enroll 1,000 acres (4 km2

) in SAFE 

to restore cropland to sagebrush habitat to benefit sage-grouse 

and other sagebrush obligate birds. South Dakota is looking to 

add 500 acres (2 km2

) to SAFE for the same purpose. Lastly, 

the SAFE program in northeast Wyoming is working to add 

10,000 acres (40 km2

) to restore critical habitat by converting 

cropland to perennial plant communities (U.S. Farm Service 

Agency, 2008).

Other Federal Agencies

In addition to BLM (Department of Interior [DOI]) and 

the Forest Service (USDA, USFS), the United States Departments of Defense (DOD), Energy (DOE), and other Interior 

Bureaus (DOI, including USFWS, National Park Service 

[NPS], and Bureau of Indian Affairs [BIA]) manage publically 

owned lands across sage-grouse range, and many of these 

lands have use restrictions that will also help support sagegrouse (table 28, fig. 30). Although BLM and USFS manage most of the sagebrush and sage-grouse habitats—other 

entities and agencies, combined, manage only 5 percent of 

sagebrush lands in the United States (Stiver, 2011)—cooperative management strategies may have local impacts or benefits 

and lands managed for other specified purposes remain part 

of distribution and management of the sage-grouse across 

the landscape. 

Fish and Wildlife Service, National Park Service, and 

Other Federal Designations

The USFWS directly manages only 1 percent of sagegrouse habitats as part of the National Wildlife Refuge System 

(Knick and Connelly, 2011b). Refuges are administered under 

the National Wildlife Refuge Administration Act of 1966 (16 

U.S.C. §668dd–668ee), as amended, for the purpose of “conservation, management and, where appropriate, restoration of 

the fish, wildlife and plant resources.” Several refuges within 

the range are currently revising their Comprehensive Conservation Plans (CCPs) as required by the 1997 National Wildlife Refuge Improvement Act. For instance, Hart Mountain 

National Antelope Refuge, which consists of 277,893 acres 

(1,125 km2

) of sagebrush-steppe in Lake County, Oregon, 

published a Notice of Intent in the Federal Register to revise 

its CCP in May 2012 (U.S. Fish and Wildlife Service, 2012,). 

The Notice of Intent identifies key issues to be analyzed in 

the CCP, many of which can benefit the refuge’s sage-grouse 

population: the impact of fire and juniper encroachment on the 

refuge’s sagebrush habitat, invasive species control, and land 

protection and planning to reduce habitat fragmentation (U.S. 

Fish and Wildlife Service, 2012). Sheldon National Wildlife 

Refuge, which encompasses 575,000 acres (2,327 km2

) of 

sagebrush-steppe in northwest Nevada, issued its Draft CCP 

in 2011 (U.S. Fish and Wildlife Service, 2011). Sage-grouse 

conservation is a major component of the CCP, which calls 

for, among other actions, restoration of sagebrush and riparian 

habitats through removal of all wild horses within the refuge, 
IV. Factor D: Policies and Programs Affecting Sage-Grouse Conservation 121

Table 28. Summary of areas managed for conservation and (or) protection* across Management Zones (MZ) by acres of preliminary 

priority and preliminary general habitat (PPH and PGH, respectively). 

PPH PGH

Management Zone

 Entity

SG Habitat 

(acres)

Area 

(acres)

Area 

(%)

SG Habitat 

(acres)

Area 

(acres)

Area 

(%)

MZ I–GP 11,636,400 364,800 3.13 34,663,000 811,000 2.34

BLM 2,994,300 68,600 2.29 4,524,900 103,900 2.30

Forest Service 292,400 100 0.03 515,300 0 0.00

Tribal and Other Federal 219,700 91,400 41.60 2,427,700 373,700 15.39

Private 7,132,500 195,700 2.74 24,682,800 315,800 1.28

State 995,600 9,000 0.90 2,498,400 17,600 0.70

Other 1,900 0 0.00 13,900 0 0.00

MZ II and VII–WB & CP 17,476,000 624,700 3.57 19,200,200 1,068,300 5.56

BLM 9,021,200 241,300 2.67 9,012,500 511,100 5.67

Forest Service 162,000 2,500 1.54 452,500 46,800 10.34

Tribal and Other Federal 784,000 93,300 11.90 1,354,600 105,700 7.80

Private 6,233,900 217,100 3.48 7,394,800 358,900 4.85

State 1,244,800 44,000 3.53 979,800 41,400 4.23

Other 30,100 26,500 88.04 6,000 4,400 73.33

MZ III–SGB 10,028,500 295,600 2.95 3,970,100 191,500 4.82

BLM 6,309,400 170,900 2.71 3,199,800 130,800 4.09

Forest Service 1,236,200 93,900 7.60 356,200 56,200 15.78

Tribal and Other Federal 260,800 11,000 4.22 29,100 3,700 12.71

Private 1,836,200 12,900 0.70 384,800 500 0.13

State 385,900 6,900 1.79 200 200 100.00

MZ IV–SRP 21,930,600 1,760,600 8.03 10,958,500 1,181,600 10.78

BLM 13,710,700 1,510,700 11.02 4,928,200 741,400 15.04

Forest Service 1,613,800 26,600 1.65 1,113,500 3,000 0.27

Tribal and Other Federal 633,600 76,000 11.99 522,500 254,800 48.77

Private 4,890,200 124,800 2.55 3,516,700 164,300 4.67

State 1,019,400 22,500 2.21 846,200 16,600 1.96

Other 62,900 0 0.00 31,400 1,500 4.78

MZ V–NGB 7,097,200 2,113,400 29.78 5,808,000 1,050,300 18.08

BLM 5,117,500 1,400,900 27.37 4,196,700 955,900 22.78

Forest Service 62,200 0 0.00 114,900 100 0.09

Tribal and Other Federal 717,100 695,700 97.02 101,800 74,900 73.58

Private 798,000 11,700 1.47 1,199,000 13,400 1.12

State 64,900 2,900 4.47 115,800 5,300 4.58

Other 337,500 2,200 0.65 79,800 800 1.00

*

Data Sources: National Conservation Easement Database; USGS Protected Areas Database (PAD-US); BLM NLCS, ACECs, and Wilderness and USFS 

Wilderness. Small differences between individual entity totals and MZ summary values may exist due to rounding of estimates during calculations.
122 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Figure 30. Overlap of Federal, State, and private (includes Non-government Organizations) conservation areas within preliminary 

priority and preliminary general habitats (PPH and PGH, respectively).
IV. Factor D: Policies and Programs Affecting Sage-Grouse Conservation 123

aggressive reduction of encroaching juniper, and control of 

invasive species, namely cheatgrass (Bromus tectorum; U.S. 

Fish and Wildlife Service, 2011). Again, where BLM or USFS 

administered lands border National Wildlife Refuges, there 

exists the potential for collaborative efforts that may have 

localized benefits to sage-grouse populations.

Several units within the National Park System are also 

planning for sage-grouse and sagebrush conservation. The 

City of Rocks National Reserve (CIRO, which is co-managed 

by the Idaho Department of Parks and Recreation) and Craters 

of the Moon National Monument and Preserve (CRMO, which 

is co-managed by the BLM) are located in the Upper Columbia River Basin in southern Idaho (MZ IV). Additionally, habitat selection studies have been conducted on the Jackson Hole 

sage-grouse population in and around Grand Teton National 

Park (Chong and others, 2011), a small, but high-profile 

population in Wyoming.

CRMO encompasses roughly 737,700 acres (2,985 km2

) 

in south-central Idaho, of which 70 percent is designated as 

either Wilderness Study Area or Wilderness (U.S. National 

Park Service and Bureau of Land Management, 2006). Observations by the Idaho Department of Fish and Game indicate a 

36 percent decrease in the number of sage-grouse leks in the 

last quarter century with 53 known leks recorded on BLMadministered lands within the monument (U.S. National Park 

Service and Bureau of Land Management, 2006). As described 

in the CRMO General Management Plan (2006), the agencies 

intend to prioritize vegetation restoration projects relative to 

sage-grouse populations (including enlarging and connecting 

habitats), as well as implement protective measures from the 

Idaho Sage-grouse Advisory Committee’s Conservation Plan, 

including use restrictions where needed near occupied leks 

(U.S. National Park Service and Bureau of Land Management, 

2006). CIRO is currently in the process of revising its General 

Management Plan.

Wilderness designations may also play a role in sustaining sage-grouse populations and conserving their habitat, 

however very few Wilderness areas contain sagebrush (table 

28); expansion to include current roadless areas could increase 

the area from about 6 percent to 9 percent of the sagebrush 

landscape (Crist and others, 2005). Lands designated as Wilderness must generally contain at least 5,000 acres (20 km2

) 

and are managed by the agency having jurisdiction over such 

lands before they were included in the National Wilderness 

Preservation System (16 U.S.C. § 1131 et seq.). Wilderness 

designations are subject to the political process because only 

Congress can designate Wilderness areas (16 U.S.C. § 1131 

et seq.). Wilderness areas are characterized by the absence of 

motorized equipment and mechanical transport, and commercial enterprises are prohibited (16 U.S.C. § 1131 et seq.); 

therefore, they do not host many of the anthropogenic threats 

to sage-grouse identified in the USFWS 2010 Listing Decision, such as habitat conversion for agriculture, urbanization, 

infrastructure, and energy development. 

Department of Defense 

There are approximately 87 Department of Defense 

(DoD) managed facilities distributed across the sage-grouse 

range with various operations and intensity of use among and 

within those facilities (Connelly and others, 2004). Because 

human access to many military installations is limited, these 

lands present an opportunity to conserve sage-grouse habitat; 

however, with only 26 percent (6,815 km2

 [1.7 million acres]) 

of DoD managed lands being sagebrush dominated, they represent approximately 0.01 percent of the currently estimated 

sage-grouse range (670,000 km2

 [165.5 million acres]). Seven 

military installations have confirmed sage-grouse populations, 

five of which are under the control of the Army: Dugway 

Proving Ground (Utah), Sheridan Training Area (Wyo.), 

Camp Guernsey (Wyo.), Hawthorne Army Depot (Nev.), and 

the Toole Army Depot (Utah). Two Air Force Bases (AFB) 

manage for known populations: Nellis AFB in Nevada and 

Mountain Home AFB, which administers the Saylor Creek and 

Juniper Butte Ranges in Idaho (U.S. Department of Defense 

and U.S. Fish and Wildlife Service, 2006).

At sites where military training exercises occur, such 

activities are generally destructive by their nature (Connelly 

and others, 2004) and may have substantial effects on habitats 

including the spread of exotic species, the potential for soil 

erosion, and the possibility of reduced ecosystem productivity from tracked and wheeled vehicle maneuvering, as well as 

fires from ordnance impacts (Belcher and Wilson, 1989; Shaw 

and Diersing, 1990; Watts, 1998). Obvious land-use impacts 

were evident on approximately 17 percent of the military lands 

surveyed by the Land Condition Trend Analysis, leaving substantial portions of some facilities available for conservation 

and management of native species (Knick and others, 2011).

Although the land-use and conservation activities of 

DOD may have important local effects on the distribution 

of sage-grouse habitats (including effects on disturbance 

regimes) as well as some populations, they represent only a 

small portion of the species’ range and therefore a small component of the conservation effort. When DOD facilities with 

sagebrush habitats fall within (partially or entirely) or adjacent 

to BLM or USFS planning and management units, then actions 

and planning that address sage-grouse conservation may benefit from recognition of resources, authorities, and activities 

associated with DOD lands that may benefit or harm sagegrouse in the planning process. Cooperation and collaboration 

with DOD, and other agencies that affect land-use patterns and 

habitat conditions (such as, Bureau of Reclamation, Department of Energy, USFS), during regional planning processes 

is important to ensure sound management and efficient use of 

public resources across political boundaries.

Department of Energy

The Idaho National Laboratory (INL) site consists of 

2,305 km2

 (570,000 acres) in the Upper Snake River Plain 

of southeastern Idaho (Whiting and Bybee, 2011) of which 

115 square miles was designated as the Sagebrush-Steppe 
124 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Ecosystem Reserve in July 1999 by the Secretary of Energy 

(INL Campus Development Office and North Wind, Inc., 

2011). The INL site is home to several sage-grouse populations and hosts numerous sage-grouse leks (INL Campus 

Development Office and North Wind, Inc., 2011; Whiting and 

Bybee, 2011). The INL includes most of the same issues found 

on the larger sage-grouse range. Wildland fires are relatively 

common on the site and an on-site fire department provides 

wildfire management in cooperation with the BLM and local 

authorities (INL Campus Development Office and North 

Wind, Inc., 2011). BLM administers permits to graze cattle 

and sheep on up to 340,000 acres (1,375 km2

) of the INL (INL 

Campus Development Office and North Wind, Inc., 2011). 

Nearly six percent of INL (approximately 34,000 acres, [138 

km2

]) consists of public roads and utility rights of way (INL 

Campus Development Office and North Wind, Inc., 2011). 

Other infrastructure includes an extensive power delivery 

system, including substations and a 62 mi (100 km) (60 miles 

of which are above ground) transmission loop (INL Campus 

Development Office and North Wind, Inc., 2011). 

From 1978 to 1980, fixed-wing aircraft and four-wheeldrive surveys identified 59 sage-grouse leks on or near the 

INL (Connelly, 1980). According to these data, it was determined that the INL populations were stable or increasing 

(Connelly, 1980). Monitoring of the INL sage-grouse populations was sporadic until a recent study collected data on lek 

attendance, activity, and distribution within the INL during 

the springs of 2009 and 2010 (Whiting and Bybee, 2011). 

Upon revisit, the number of active sage-grouse leks within the 

INL was less than half of historical leks (Whiting and Bybee, 

2011), although uncertainty associated with historic data and 

dynamic populations may confound these data. The authors 

concluded that the INL likely follows the regional trend of 

sage-grouse with populations declining in the 1980s and 1990s 

but stabilizing at the current low levels during the past decade 

(Garton and others, 2011; Whiting and Bybee, 2011). Annual 

spring surveys will be conducted on the INL to ultimately 

produce an index of population trends at the site (Whiting and 

Bybee, 2011). 

State and Local Working Group Conservation Efforts

States generally have broad authority to manage wildlife 

within their borders. All States within the range of sage-grouse 

have laws addressing wildlife conservation, but such laws 

are general in nature without specific mention of sage-grouse 

(U.S. Fish and Wildlife Service, 2010b, p. 13,974); nevertheless, States and local working groups (LWGs) across the sagegrouse range have developed conservation plans that direct 

management efforts at the State and regional level (Stiver, 

2011). Although such plans generally provide a management framework rather than regulations, they are a valuable 

mechanism for implementing efforts that conserve sage-grouse 

populations and their habitat. 

In addition to developing State and LWG conservation strategies, States can affect sage-grouse conservation by 

several other means. Governors of several States have issued 

executive orders (White and others, 1997) to offer greater 

regulatory force to sage-grouse conservation. Moreover, in 

addition to State fish and wildlife agencies, other State-level 

agencies may have authority to regulate activities that are 

threats to sage-grouse. This includes State agencies or commissions responsible for regulating oil and gas developments 

or siting power transmission lines. Lastly, all 10 States within 

the sage-grouse range own State trust lands, which each State 

manages for the benefit of various trustees (U.S. Fish and 

Wildlife Service, 2010b). Trust lands consist of two sections 

per township (four sections in Utah) and therefore usually 

represent a checkerboard of lands scattered around each State 

(Culp, 2005). Nevertheless, the cumulative area of State trust 

lands can be large—Montana’s trust lands include 5 million 

acres (20,230 km2

) of surface property, Utah holds 3.5 million 

(14,150 km2

) surface acres in trust, Wyoming and Colorado 

each have about 3 million (12,140 km2

) surface acres, and 

Idaho holds about 2.5 million acres (10,100 km2

) in trust 

(Culp, 2005). States generate revenue on State trust lands 

through various activities—disposition or leases for residential or commercial development, timber harvesting, mineral 

development, agricultural uses and recreation including fishing 

and hunting (Culp, 2005). These lands represent a potentially 

important component of long-term sage-grouse conservation; 

however, there are limitations due to the scattered distribution 

of these lands (reducing the potential benefit unless coordinated with management efforts on adjacent lands) and potential change in ownership and management due to the fiduciary 

trust responsibilities.

The following section presents a brief overview of 

conservation efforts within each State and, where applicable, 

the major threats those efforts seek to mitigate. A complete 

description of management efforts in each State is out of the 

scope of this report, and such information is available from 

individual States and LWGs. In 2011, the Western Governors 

Association released an inventory of State and local conservation initiatives for sage-grouse (Western Governors’ Wildlife 

Council, 2011).

California/Nevada 

In August 2000, then Nevada Governor Kenny Guinn 

appointed a Sage-Grouse Conservation Team that developed 

a conservation strategy for sage-grouse (Nevada Sage-Grouse 

Conservation Team, 2004). Through collaboration with the 

California Department of Fish and Game, the strategy was 

later expanded to include eastern California and LWGs in each 

State were identified and tasked with designing practical solutions for their respective region. The seven LWGs (including a 

Bi-State Planning Group) developed local conservation plans, 

which were submitted to the Governor’s Team for synthesis 

into a conservation plan for Nevada and eastern California 

(Nevada Sage-Grouse Conservation Team, 2004). 

The Greater Sage-Grouse Conservation Plan for Nevada 

and Eastern California prioritizes conservation efforts within 
IV. Factor D: Policies and Programs Affecting Sage-Grouse Conservation 125

both States. Immediate priorities identified include a comprehensive spatial analysis to determine those areas that support 

large populations of sage-grouse and are at high risk for wildfire or invasion of cheatgrass (Nevada Sage-Grouse Conservation Team, 2004). In 2012, the Nevada Department of Wildlife 

published its sage-grouse habitat categorization analysis, 

which delineated five classes of sage-grouse habitat ranging 

from essential/irreplaceable habitat to unsuitable habitat, to 

direct mitigation and conservation efforts within Nevada and 

California (Nevada Department of Wildlife, 2012).

Other top priorities identified by the Governor’s Team 

include wildfire pre-suppression treatments, fire control and 

vegetation management. The average fire size in the Southern 

Great Basin (MZ III) increased from 1980 to 2007 (U.S. Fish 

and Wildlife Service, 2010a). As much as 80 percent of the 

land within the Great Basin ecoregion (MZs III, IV, and V) is 

at risk of being displaced by cheatgrass in the next 30 years, 

and an estimated 35 percent of sagebrush in the region is at 

high risk of displacement by pinyon-juniper in the same time 

(Connelly and others, 2004). 

The Nevada Department of Wildlife, in cooperation with 

various Federal agencies, has implemented numerous conservation projects to confront these threats dedicating more than 

$2 million and totaling nearly 69,000 treated acres (280 km2

) 

on private lands and lands administered by Federal agencies 

from 2001 to 2009. These projects include pinyon-juniper 

removal, weed treatments, and fire rehabilitation (Nevada 

Department of Wildlife, 2011). More recently, Governor Brian 

Sandoval issued an Executive Order forming the Governor’s 

Greater Sage-Grouse Advisory Committee to recommend 

policies for the protection of sage-grouse (Nevada Executive 

Order, Mar. 30, 2012). The recommendations, released in July 

2012, provide management strategies to achieve “no net loss” 

for controllable activities and aggressive pre-suppression, initial attack, and restoration for uncontrollable events (Nevada 

Greater Sage-Grouse Advisory Committee, 2012). 

Colorado

Colorado’s Greater Sage-Grouse Conservation Plan 

(2008) prioritized threats across each of the State’s six sagegrouse populations: Meeker-White River, Middle Park, North 

Park, northern Eagle-southern Routt Counties, northwest 

Colorado, and Parachute-Piceance-Roan (Colorado Greater 

Sage-Grouse Steering Committee, 2008). Urbanization and 

associated habitat fragmentation are substantial threats to 

sage-grouse in portions of the sage-grouse range in Colorado (U.S. Fish and Wildlife Service, 2010a). The Colorado 

Division of Wildlife, through its Habitat Protection Program, 

secured 40,000 acres (162 km2

) of sage-grouse habitat through 

land purchases and conservation easements (Western Governors’ Wildlife Council, 2011). Such actions are part of the 

State’s strategy to mitigate what the USFWS described as 

the “key cause, if not the primary cause, of the decline of 

sage-grouse populations,” namely habitat fragmentation (U.S. 

Fish and Wildlife Service, 2010a). Within these recognized 

habitat regions, urbanization is occurring most heavily in 

Middle Park and northern Eagle-southern Routt Counties. 

Conservation easements benefiting sage-grouse total 8,883 

acres (36 km2

) and 2,430 acres (10 km2) of occupied habitat 

in the Middle Park and northern Eagle-southern Routt County 

areas, respectively (Colorado Greater Sage-Grouse Steering 

Committee, 2008). 

Oil and gas development has expanded at a rapid rate in 

portions of Colorado (threats to sage-grouse associated with 

such development are presented in previous sections of this 

report). Applications for permits-to-drill increased 50 percent between 2004 and 2005 and increased by an additional 

35 percent from 2005 to 2006. In 2005, 99 percent of these 

permits were for new wells. Current oil and gas development 

is concentrated in northwest Colorado (described as “moderate; increasing exponentially”) and Parachute-Piceance-Roan 

(“high; increasing exponentially”) areas (Colorado Greater 

Sage-Grouse Steering Committee, 2008). In 2009, then 

Colorado Governor Bill Ritter signed into law regulations to 

address sage-grouse conservation applicable to the Colorado 

Oil and Gas Conservation Commission. Pursuant to an MOU 

among that Commission, BLM, and USFS, these regulations 

apply to oil and gas permitting decisions on both private and 

Federal land within the State (Interagency MOU, 2009; U.S. 

Fish and Wildlife Service, 2010a). The new regulations require 

operators seeking a permit to drill to first determine if the proposed development occurs within “sensitive wildlife habitat” 

(C.R.S. § 34-60-128 and COGCC Rules and Regulations § 

1201). Operators are required to consult with the Colorado 

Division of Wildlife to avoid impacts on wildlife resources 

and mitigate any unavoidable impacts (COGCC Rules and 

Regulations § 1202a).

Idaho 

Wildfire, infrastructure, and proliferation of invasive species were the three most pressing threats (in order of priority) 

to sage-grouse in Idaho as determined by a panel of leading 

scientists in 2006 (Idaho Sage-Grouse Advisory Committee, 2006). The Idaho Sage-Grouse Conservation Plan contemplates the full spectrum of threats; several are addressed 

here. On March 9, 2012, Idaho Governor C.L. Otter issued 

Executive Order 2012-02, which established a 15-member 

Sage-Grouse Task Force to provide recommendations on the 

long-term viability of the species within the State. 

As in other States, the potential for wildfire to negatively 

affect vast acres of sage-grouse habitat represents a substantial threat to the persistence of the species and remains a top 

management priority in Idaho (Idaho Sage-Grouse Advisory 

Committee, 2006). Spread and establishment of cheatgrass and 

other annuals have contributed to reduced fire-return intervals 

in portions of the Snake River Plain (Young and others, 1987; 

Connelly and others, 2004). The Governor’s Sage-Grouse 

Task Force recommended identifying perennial grasslands 

with the highest risk for wildfire that are most likely to benefit from fuel-break construction (Idaho Sage-Grouse Task 
126 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Force, 2012). Numerous weed and fuel-break efforts have 

been undertaken, and a substantial number of acres has been 

treated on private, State, and Federally managed lands within 

the State with funds from the Governor’s Office of Species Conservation. The State has also focused efforts on fire 

restoration; several reseeding and rehabilitation projects have 

occurred since 2002, totaling 3,399 treated acres (13.75 km2

) 

(Idaho Sage-grouse Advisory Committee Technical Assistance 

Team, 2012). 

Infrastructure is also perceived as a substantial threat 

to sage-grouse in Idaho. There are approximately 1,500 

miles (2,414 km) of major power transmission lines within 

the State’s sage-grouse planning areas (Idaho Sage-Grouse 

Advisory Committee, 2006). Including a 3.1 mi (5 km ) buffer on either side of these lines expands the affected area to 

more than 4.5 million acres (18,200 km2

) (Idaho Sage-grouse 

Advisory Committee 2006). There are approximately 975 

mi (1,560 km) of major paved roads (interstate, Federal, and 

State) within Idaho sage-grouse planning areas, which, when 

a 6.2-mi (10-km ) buffer is considered, account for more than 

6.8 million acres (27,500 km2

) of affected area (Idaho SageGrouse Advisory Committee, 2006). A Governor’s Task Force 

recommended several management practices to mitigate the 

effects of infrastructure on sage-grouse including co-locating 

linear facilities, building new roads to the minimum specifications necessary, and time restrictions on construction of new 

facilities (Idaho Sage-Grouse Task Force, 2012). 

Spatial studies reveal several large tracts of annual grasslands, totaling nearly one million acres (4,050 km2

) within Idaho’s sage-grouse planning areas in south-central, southwestern, and western Idaho. The BLM manages approximately 62 

percent of these identified grasslands, whereas 29 percent are 

under private ownership (Idaho Sage-Grouse Advisory Committee, 2006). LWGs report numerous weed control efforts 

across various types of land ownership within the State. As of 

2011, nearly 9,300 acres (38 km2

) have been treated to control 

weeds (Idaho Sage-Grouse Advisory Committee Technical 

Assistance Team, 2012). The Governor’s Task Force recently 

recommended best-management practices regarding invasive 

species control to be incorporated into land-use-plan revisions 

(Idaho Sage-Grouse Task Force, 2012). 

Montana and the Dakotas

Energy development, grazing, and habitat conversion to 

agriculture are among the primary threats to sage-grouse in 

Montana (U.S. Fish and Wildlife Service, 2010a). Portions 

of two geological basins within the State are experiencing 

increased levels of energy development—the Powder River 

Basin (predominately coal-bed methane) in southeastern 

Montana and northeastern Wyoming and the Williston Basin 

in eastern Montana and the Dakotas (U.S. Fish and Wildlife 

Service, 2010a). The Powder River Basin serves as a link 

between the Wyoming Basin and central Montana sagegrouse populations; it is anticipated that this connectivity 

could be lost in the near future, in part, due to the intensive 

development in this region (U.S. Fish and Wildlife Service, 

2010a). Montana’s Management Plan and Conservation 

Strategy for Sage Grouse (2005) proposed several conservation actions to meet energy demands while minimizing effects 

to sage-grouse including surface occupancy restrictions (0.25 

miles around existing leks), restricting noise levels near leks, 

and avoidance of leks and critical habitat in siting infrastructure. Notably, in 2007, the Montana Department of Natural 

Resources and Conservation rejected a recommendation from 

the State’s Department of Fish, Wildlife and Parks to amend 

a stipulation placed on State trust land oil and gas leases to 

include sage-grouse protections (this amendment would have 

increased the no-surface-occupancy buffer radius to between 1 

and 1.8 miles and included timing restrictions on lands within 

4 miles from known leks). The decision cited concerns that 

the recommended restrictions would prevent the Department 

of Natural Resources and Conservation from protecting oil 

and gas resources under State lands from drainage by adjacent 

mineral owners (Montana Department of Natural Resources 

and Conservation Trust Land Management Division, 2007). 

Although sagebrush communities in the Northern Great 

Plains, including Montana, likely evolved with periodic grazing, many of these rangelands were overstocked in the late 

1800s and early 1900s, which altered the composition and 

productivity of sagebrush communities (Montana Sage-Grouse 

Work Group, 2005). Montana’s State Plan (2005) prescribes 

grazing management actions that maintain and enhance sagebrush rangelands while providing for agricultural commodities. These include incentives for private landowners to help 

achieve sage-grouse objectives (Montana Sage Grouse Work 

Group, 2005). As described above, the NRCS is working with 

private landowners around the State to implement improved 

grazing systems on more than 246,000 acres (995 km2

) in the 

State through its SGI program (U.S. Natural Resources Conservation Service, 2012a). The Montana Department of Fish, 

Wildlife and Parks, through contracts with private landowners, 

implemented grazing standards on more than 550,000 acres 

(2,226 km2

) of privately owned land in the State (Montana 

Sage Grouse Work Group, 2005). 

Large losses of sagebrush resulting from conversion 

to agriculture have occurred in the Great Plains MZ (MZ 

I). Across the State, the amount of acres converted to tilled 

agriculture increased annually from 2005 to 2009, with more 

than 25,000 acres (101 km2

) converted in that time. This threat 

is particularly prominent in the eastern two-thirds of the State 

(U.S. Fish and Wildlife Service, 2010a). Montana’s State Plan 

reported that the State’s Department of Fish, Wildlife and 

Parks intended to continue to negotiate conservation easements to conserve native rangelands by prohibiting subdivision and conversion to cropland. With funding through the 

Landowner Incentive and Upland Game Bird Programs, the 

Department of Fish, Wildlife and Parks anticipates protecting 

183,000 acres (740 km2

) of occupied private lands from herbicide spraying, prescribed burning, and conversion to cropland 

(Montana Sage Grouse Work Group, 2005). 
IV. Factor D: Policies and Programs Affecting Sage-Grouse Conservation 127

The populations at the eastern reaches of the range, in 

North and South Dakota, occupy a relatively small area in the 

western portions of both States and are known to be wellconnected to populations and habitats in eastern Montana. 

The issues threatening these populations are the same as the 

threats associated with neighboring populations in southeastern Montana and northeastern Wyoming including oil and gas 

development. Fourteen percent of the Federal mineral estate 

(902,000 acres [3,550 km2

], combined) within the sage-grouse 

conservation area in North and South Dakota are authorized 

for development (U.S. Fish and Wildlife Service, 2010a). 

Both States have management plans that address sage-grouse 

conservation, and BLM habitat management is coordinated 

among Montana, North Dakota, and South Dakota (within a 

single Field Office). 

Oregon 

Oregon’s “Wildlife Policy,” codified in Section 496.012 

of the Oregon Revised Statutes states “[i]t is the policy of the 

State of Oregon that wildlife should be managed to prevent 

serious depletion of any indigenous species...” Oregon’s 

Greater Sage-Grouse Conservation Assessment and Strategy 

provides a framework to maintain and enhance sage-grouse 

in the State. It accomplishes this by combining a “core area” 

approach, modeled after Doherty and others (2011b) with a 

complementary method to estimate connectivity corridors 

to approximate seasonal ranges (Oregon Department of Fish 

and Wildlife, 2011). Once core areas were identified, various 

sagebrush habitats within the State were categorized based 

on suitability for sage-grouse, and management guidelines 

were recommended for each category with greater restrictions in higher value habitat (Oregon Department of Fish and 

Wildlife, 2011). 

The Oregon conservation plan addresses many of the 

threats identified by the USFWS in the 2010 Listing Decision. 

The plan offers voluntary guidelines to mitigate each threat. 

Implementation of the guidelines will be directed by local 

Implementation Teams, consisting of Oregon Department 

of Fish and Wildlife personnel, Federal land management 

agency representatives and private entities. There are five 

Implementation Teams, corresponding to various BLM district 

boundaries within the State. Implementation Teams have 

initiated projects under the guidance of the State plan—from 

removing 90,000 acres (365 km2

) of juniper within the Burns 

District to treating nearly 30,000 acres (121 km2

) of invasive 

weeds in the Vale District (Oregon Department of Fish and 

Wildlife, 2011). 

Utah

Four MZs divide Utah (Connelly and others, 2004) 

representing the State’s diverse ecological and biological 

composition. Such variation also presents numerous threats 

to the State’s sage-grouse populations. Utah’s Sage-Grouse 

Planning Committee comprises members representing various 

backgrounds from public and private entities who prioritized 

threats to the species across the State. This prioritization incorporated the identification and prioritization of threats within 

Utah’s 11 Management Areas by LWGs (Utah Division of 

Wildlife Resources, 2009).

State-wide, the Planning Committee identified six major 

threats: invasive species expansion, habitat conversion, conifer 

encroachment, energy development, altered fire cycles, and 

predation (Utah Division of Wildlife Resources, 2009). Utah’s 

Greater Sage-Grouse Management Plan (2009) seeks to protect and maintain occupied habitat, while restoring 175,000 

acres (700 km2

) of habitat by 2014. The plan provides an overall strategy for use in implementing conservation actions by 

LWGs. LWGs in Utah provide annual updates detailing those 

actions taken for specific strategies identified in each LWG 

plan. According to a recent report, for the Strawberry Valley 

Adaptive Resource Management Area, 10,223 acres (41 km2

) 

have been purchased within the Management Area by the Utah 

Reclamation and Mitigation Commission. A full discussion of 

the management efforts within the State is available from the 

Utah State University Cooperative Extension. 

Wyoming

Estimates of sage-grouse populations indicate that Wyoming is home to the largest number of birds in the range of the 

species (U.S. Fish and Wildlife Service, 2010a). The State’s 

sage-grouse populations face a variety of threats—intensive 

energy development in the Powder River and Greater Green 

River Basins and extensive infrastructure, including power 

lines, fences, and roads (U.S. Fish and Wildlife Service, 

2010a). Eight LWGs around the State have completed conservation plans, many of which prioritize threats and prescribe 

management actions at the LWG scale.

At the State level, Wyoming Governor Matt Mead issued 

an executive order (Wyoming Executive Order June 2, 2011) 

that complemented (and replaced) several executive orders 

issued by his predecessor, Governor Dave Freudenthal (Wyoming Executive Order August 1, 2008 and August 18, 2010). 

The 2011 order further articulates the State’s Core Population 

Area Strategy (as initially described in the 2008 executive 

order) as an approach to balance sage-grouse conservation and 

development. It provides an approach to mitigating anthropogenic disturbances to sage-grouse. The USFWS believes that 

Wyoming’s Core Population Strategy, if extended to all landowners via regulatory mechanisms, would provide adequate 

protection for sage-grouse (U.S. Fish and Wildlife Service, 

2010a); however, universal implementation remains uncertain 

due to variety in ownership and management. 

Specifically, the 2011 order contains consultation 

requirements with the Wyoming Game and Fish Department for proposed activities requiring a State permit (Wyoming Executive Order June 2, 2011)—the Wyoming Game 

and Fish Department has no authority to either approve or 

deny the project. The order does apply to State trust lands in 

Wyoming covering almost 23 percent of sage-grouse habitat 

and contributing habitat benefiting approximately 80 percent 
128 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

of the estimated breeding population in the State (U.S. Fish 

and Wildlife Service, 2010a). The executive order does not 

restrict activities with a defined project boundary existing 

prior to August 1, 2008. All proposed activities are evaluated 

through a Density-Disturbance Calculation Tool to determine 

if the project would exceed recommended density-disturbance 

thresholds. Additionally, the 2011 order includes stipulations to be included in such permits with varying restrictions 

depending on whether the proposed development activity 

occurs within or outside delineated Core Population Areas 

(Wyoming Executive Order June 2, 2011). Wyoming’s Industrial Siting Council (within the State’s Department of Environmental Quality), which permits large development projects on 

all lands within the State, regardless of ownership, is subject to 

the terms of the executive order. This could offer sage-grouse 

considerable regulatory protection when considering large 

wind energy and other development projects within Wyoming 

(U.S. Fish and Wildlife Service, 2010a). 

V. Risk, Policies, and Actions:

Assessment of Dominant Threats 

and Potential Interactions within 

Management Zones 

Increasing human populations with concurrent increases 

in demand for resources, dynamic ecological processes, fire 

and fire effects, highly variable climate conditions, and potential synergistic feedbacks with ecological processes such as the 

distribution of invasive plant species will combine to increase 

disturbance and disruption of the sagebrush ecosystem. These 

interactions, and the subsequent distribution of habitats, 

represent the dynamic playing field where management and 

planning may influence changes to sagebrush-dominated 

landscapes throughout the Western United States, and this 

complicated framework will continue to present challenges 

for conservation of sage-grouse populations and habitats into 

the future (Knick and others, 2011). Projections for urban and 

exurban (suburban and rural subdivisions) growth across the 

Western United States mirror national projections, and some 

urban-growth areas are outpacing national trends (see U.S. 

Census Bureau Web site at http://www.census.gov/population/

www/projections). Fences, power transmission lines, communication towers, and roads are ubiquitous, albeit not evenly 

distributed, across sage-grouse range, and these structures 

have known, or sometimes presumed, effects on sage-grouse 

populations. Conversion of land for crops, livestock, resource 

extraction, and domestic expansion has long been a basic tenant of western civilization, and though the land has provided 

these essential goods and services, alteration of resource 

conditions, wildlife habitats, and ecosystem function creates a critical trade-off between land use and conservation 

of resources and natural heritage values (Defries and others, 

2004). Further, industrial development of public and private 

lands, including traditional fossil fuels, tar sands, and coal bed 

methane along with expansion of “renewable” energy sources 

such as wind, solar, and geothermal and the infrastructure 

required to support these operations represent widespread, 

unevenly distributed, pressures and impacts on sagebrush 

ecosystems and sage-grouse populations. This apparently 

philosophical or sociological debate regarding the balance 

among different land uses may seem peripheral to sage-grouse 

conservation; however, the management of these competing 

uses also involves fundamental, practical issues that affect the 

successful conservation of sage-grouse and sagebrush ecosystems. Thus, long-term challenges for regional planning, local 

habitat management, and wildlife conservation may be summarized by our ability to understand and manipulate a complicated and changing landscape for a balance among multiple 

uses and demands of some citizens and protection of common 

heritage and public interests including functioning ecosystems 

and wildlife habitat.

Sage-grouse are currently widespread (although in some 

areas densities are low), and relatively large areas continue 

to provide essential sagebrush habitats for the species; thus, 

long-term conservation of sage-grouse populations should be 

possible (Connelly and others, 2011b). The distributions of 

habitats, species, and human land uses are notably heterogeneous across large landscapes, and understanding the relations 

and processes that create these patterns, correlations, and aversions will assist in long-term planning. By helping to identify 

risks to habitat and resource conservation success, control 

and mitigation activities can be efficiently implemented by 

management agencies to reduce impacts and insure resiliency, 

and ultimately, to protect and conserve our natural heritage 

and natural resources for future generations. Rather than 

any single source of habitat degradation, the cumulative and 

synergistic impact of multiple disturbances, continued spread 

and dominance of invasive species, and increased impacts of 

land use continue to have the most significant influence on the 

trajectory of sagebrush ecosystems and sage-grouse populations (Connelly and others, 2011b). Future patterns of land 

use, combined with effective restoration and management, may 

improve, or degrade, the remaining sage-grouse ranges, but 

natural dynamics and unforeseen stochasticity promise to add 

complexity to future plans and landscapes, and these interactions are more difficult to control. Finally, population and 

habitat dynamics may be exaggerated for sage-grouse due to 

their strong affinity (obligate relation) with extensive, intact, 

and well-functioning sagebrush ecosystems, and because habitat limitations may magnify the effects of population stressors 

such as disease and disturbances such as wildfires.

Actions and Activities

The numerous efforts undertaken to identify threats 

to sage-grouse cumulatively suggest that invasive species, 

wildfire, grazing management and energy development—with 

the relative importance of each varying throughout the range 
V. Risk, Policies, and Actions: Assessment of Dominant Threats and Potential Interactions within Management Zones 129

of the species—pose the greatest risk to long-term conservation of sage-grouse (Connelly and others, 2011b). The 

Greater Sage-Grouse Comprehensive Conservation Strategy 

(GSGCCS; Stiver, 2011b) ranked potential habitat issues by 

region (eastern and western portions of the sage-grouse range) 

in order of immediacy, and the Greater Sage-Grouse Conservation Objectives Team: Final Report (2013) discusses details 

of populations which are not addressed here.

In the western portion of the range (especially MZs 

III, IV, and V), control of fire (removal from management, 

reduced human ignitions, and suppression of wildfires) and 

management of dispersed recreation have been identified as 

regional priorities for reducing disturbance to habitats and 

populations. Combating habitat degradation due to invasive 

plants was also deemed critical, and the current wide distribution and dominance by several invasive species (for example, 

cheatgrass and Medusahead) require risk assessment, prioritization, and strategic planning to focus funds and efforts 

to strategically protect and improve habitats. A combination 

of regional planning to determine the highest value areas, 

followed by local planning and implementation, will likely 

be required to address these species, which both degrade 

local habitats and agricultural productivity. These species are 

widespread across the region with severe infestations providing extensive seed sources and the necessity to manage across 

vast areas, multiple management units, and mixed ownership and administration. Manipulation of livestock grazing 

rotations and intensity to support conservation objectives for 

habitat condition and invasive plant control was identified as 

an important tool for managers throughout western portions of 

the sage-grouse range. In addition, increasing land use on, and 

around, public lands increases displacement of sage-grouse 

due to noise and activities; consideration of both near- and 

long-term habitat impacts of dispersed recreation and urban 

and exurban development were also identified as issues requiring attention. Trends in resource conditions and utilization, 

assessed locally and adapted seasonally, will be the most likely 

actions to affect short-term population trends when they are 

supported by regional planning and policy to reduce industrial 

impacts, eliminate new developments in priority habitats, and 

promote intact sagebrush ecosystems providing the necessary 

structure to substantiate local actions.

Similarly, on the eastern portion of the range (MZs I, 

II, and VII), invasive plant management and fire suppression 

remain important components of the conservation strategy. 

However, the GSGCCS (Stiver and others, 2006a) identified 

the reduction of impacts from the development of nonrenewable energy, and the support infrastructure (pipelines, roads, 

and structures) necessary for these developments, as top 

regional priorities for addressing declining sage-grouse populations. The potential for impacts across scales makes careful 

and deliberate planning at local and regional scales relevant 

to local populations. Consistent criteria for locating energy 

corridors, facilities, and infrastructure with minimal impacts 

to intact sagebrush communities and associated sage-grouse 

populations may incur benefits by concentrating activities and 

directing them away from the most sensitive areas and populations. To be useful and accurate, monitoring effectiveness of 

restoration and remediation projects may be coupled to landscape accounting for cumulative effects to insure treated and 

restored lands have required habitat values before additional 

sagebrush habitat is disturbed. 

Historically, sagebrush was common across the range 

of sage-grouse (all MZs), but it was least common on the 

Colorado Plateau (eastern half of MZ III), Columbia Plateau 

(MZ VI), and Great Plains (MZ I). Historically and currently, sagebrush is most common in the northern Great Basin 

(MZ V) and eastward across the sagebrush-steppe found in 

the Snake River Plain and the Wyoming Basin (MZs II and 

IV); however, as previously noted, the best big sagebrush 

ecological sites (those with deep loamy soils) have been 

largely converted to agriculture. Because sage-grouse depend 

on sagebrush through all seasons with consistent selection for 

areas with more sagebrush canopy cover (Johnson and others, 

2011), landscape-scale management for greater extent and 

connectivity of sagebrush communities and management and 

monitoring to maintain suitable shrub and herbaceous cover 

within that matrix are basic defining goals to direct conservation in all regions. Lek trends across the species’ range are 

positively associated with sagebrush cover at multiple scales; 

functioning sagebrush ecosystems that provide cover and 

forage during all seasons are a necessary condition for viable 

sage-grouse populations (Johnson and others, 2011). Treatments that reduce sagebrush cover in the near-term are not 

recommended but may be successful if carefully prescribed 

within a region possessing “excess sagebrush cover” and with 

reasonable expectations for realization of increased sagebrush 

cover and habitat quality in the future (likely 25 years or 

more). Importantly, the risk of wildfire, estimated using fuel 

models, is pronounced across several MZs with the greatest 

risk in the Great Basin region (MZs III, IV, and V) due largely 

to the influence of cheatgrass (see figs. 26 and 27A); however, 

large portions of other regions (MZs I and II) are also projected to be at high risk. Fuel mitigation while maintaining and 

sustaining sagebrush habitat values across large landscapes 

will remain an important and challenging balance for habitat 

managers into the future.

Management Zone Summaries

MZ I—Northern Great Plains

Management Zone I consists of four sage-grouse 

populations, each encompassing relatively large regions: the 

Dakotas, northern Montana, Powder River Basin, and Yellowstone watershed populations (Garton and others, 2011). 

Predicted population trends indicate that populations in this 

MZ have an 11 percent chance of falling below 200 males 

by 2037, and a 24 percent chance of falling below 200 males 

by 2107 (Garton and others, 2011). A majority (66 percent) 

of the sagebrush landscape in this MZ is privately owned; 

however, sage-grouse leks in the region remain relatively well 
130 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

connected (Knick, 2011; Knick and Hanser, 2011). Because a 

majority of the sage-grouse habitats within MZ I are privately 

owned, current options for habitat conservation—for example, 

conservation easements and farm bill programs that can only 

be applied to private lands—are a viable option for effective 

sage-grouse conservation throughout the region. Some CRP 

lands may create habitat refugia within converted landscapes 

when they include sagebrush cover; enrollment of 17 percent 

of an agricultural landscape in eastern Washington succeeded 

in reversing short-term population declines (Schroeder and 

Vander Haegen, 2011). Cover and productivity of native 

rangelands, including silver sagebrush (Art. cana) and big 

sagebrush (Art. tridentata), are essential for effective conservation of sage-grouse in this region. Limited sagebrush cover 

(naturally, due to environmental gradients favoring grassland 

systems) coupled with historic agricultural uses and current 

energy-production infrastructure make natural and induced 

habitat limitations a fundamental, limiting factor for local 

sage-grouse populations in this region. 

Major threats to sage-grouse habitats and populations 

occurring across populations in this MZ include oil and gas 

developments and conversion of native rangeland to crops 

(Conservation Objectives Team, 2013). Regional assessments 

estimated that 7.2 percent of priority and general habitats in 

MZ I are directly influenced by agricultural development, 

and >99 percent of these habitats are within 4.3 mi (6.9 km) 

of agriculture (table 4). Less than 1 percent of sage-grouse 

habitats are directly influenced by a natural gas or oil well; 

however, nearly 60 percent of the designated habitats lie 

within 11.8 mi (19 km) of a well (table 11, fig. 15)—the 

estimated effects area (Johnson and others, 2011; Taylor and 

others, 2012). More than 6.3 million acres (25,500 km2

, 14 

percent) of sage-grouse habitat is currently leased for the 

development of Federal fluid minerals (table 13). Additionally, 

most sage-grouse habitats within the MZ have the potential 

to be influenced by mining and (or) energy development 

(figs. 21 and 22), although current coal and mineral developments directly influence less than 1 percent of the lands in the 

region (tables 16 and 17). BLM managed grazing allotments 

“not meeting land health standards for wildlife with grazing 

as the causal factor” constitute 2 percent of MZ I and are not 

widespread throughout the region (fig. 28); however, most of 

the sage-grouse habitats in MZ I are privately owned and were 

not addressed in this analysis. Inappropriate livestock management is recognized for its potential to influence habitat quality 

and sage-grouse populations across the region (Conservation 

Objectives Team and others, 2013); however, details of local 

conditions and grazing management were not summarized 

here. Fire risk is generally low across MZ I, with 17 percent of 

priority and general habitats having a high risk for fire (table 

19); however, isolated areas, especially in central Montana, 

South Dakota, the border between Montana and Wyoming, 

and eastern Wyoming, are identified as having high fire risk 

(fig. 26). Risk of cheatgrass presence was not available for 

this region, but cheatgrass (and Japanese brome, Bromus 

arvensis) are known to occur across this region. Thus, risk of 

annual grass invasion, as well as annual-induced fire, appear to 

need better documentation across the region. To help prevent 

increasing cheatgrass dominance on these rangelands, potential for invasion can be assessed when planning habitat treatments and rehabilitating disturbed areas, with pre-disturbance 

abundance being a good indicator of potential for post-disturbance response (Davies and others, 2012). Urban development, power lines, vertical structures, and railroads directly 

influence less than 2 percent of the sage-grouse habitats in the 

region; however, this distribution is relatively dense compared 

to western portions of the range of sage-grouse (tables 5–9; 

figs. 10–13). 

MZ II and VII—Wyoming Basin and the Colorado 

Plateau

Management Zones II and VII include nine sage-grouse 

populations with the bulk of the area constituting the Wyoming Basin population; several smaller areas occupied by 

sage-grouse are distributed around the Wyoming Basin 

population, especially south of this population on the Colorado Plateau (Garton and others, 2011). Northern portions of 

this MZ currently represent the highest abundance of sagegrouse relative to other MZs across the range of the species 

(Conservation Objectives Team and others, 2012); projections 

indicate that the chance of populations in this region falling below 200 males by 2037 is 0.3 percent and a 16 percent 

chance populations falling below 200 males by 2107 (Garton 

and others, 2011). Leks in northern portions of MZs II and 

VII are the most highly connected in the range (Knick and 

Hanser, 2011a). Conversely, populations in southern portions 

of MZs II and VII (Colorado Plateau) are not as robust with 

a projected 96 percent chance of populations declining below 

200 males by 2037 and a 98 percent chance by 2107 (Garton 

and others, 2011). Additionally, leks in southern regions of the 

MZs are the least connected across the range of the species 

(Knick and Hanser, 2011). In contrast to MZ I, 54 percent of 

the sagebrush habitats in MZs II and VII are Federally managed (Knick and Connelly, 2011b). Therefore, conservation 

easements and farm bill programs that can only be applied 

to private lands will likely be ineffective as a sole means of 

conserving sage-grouse in these MZs; comparable programs 

affecting effective rehabilitation and restoration on public 

lands, at similar scales, are needed (Connelly and others, 

2011b). The Wyoming Basin (MZ II) is currently home to the 

largest regional extent and highest breeding density of sagegrouse in the Western United States with several important 

satellite populations including Jackson Hole, Wyoming, and 

Routt County, Colorado. Livestock grazing has been ubiquitous across these sagebrush dominated ranges, which also 

have seasonal importance for native elk, mule deer, pronghorn, 

and several herds of feral horses, for more than a century. 

Nonrenewable energy extraction (coal, oil, and natural gas), 

and more recently renewable energy production (wind farms), 

are superimposed over the habitat gradients created by natural 
V. Risk, Policies, and Actions: Assessment of Dominant Threats and Potential Interactions within Management Zones 131

environmental patterns and historic land uses, and the current combination of use and natural dynamics are sufficiently 

intense to cause measureable changes in sagebrush cover 

(Xian and others, 2012). Therefore, trends in land cover and 

land use are recognized as contributing to population declines, 

in this region, in the recent past.

The major threat to sage-grouse habitats and populations occurring across populations in MZs II and VII is energy 

development—primarily oil and gas development—and 

supporting infrastructure (Conservation Objectives Team and 

others, 2012); less than 1 percent of priority and general habitats are directly influenced by natural gas or oil wells; however, more than 75 percent of PPH and more than 80 percent 

of PGH lie within the likely effects buffer (11.8 mi [19 km 

]) providing an indication of the widespread and cumulative 

influence of energy infrastructure (table 11, fig. 14). Further, 

approximately 7.8 million acres (31,500 km2

, 21 percent) of 

the sage-grouse habitats in these MZs are currently leased for 

development of Federal natural gas or oil reserves (table 13). 

This region also has Federal leases for the research of oil shale 

extraction overlapping the southern populations (fig. 19A). 

The potential for coal mining, geothermal energy development, oil shale development, and wind energy development 

are also widespread throughout this MZ (figs. 18–24). In spite 

of these competing factors, the loss of habitat from subdivision and housing development and associated infrastructure 

(for example, roads) has been identified as the greatest threat 

to sage-grouse populations in southern portions of MZs II and 

VII (Conservation Objectives Team, 2013). Urban development, power lines, vertical structures, and railroads directly 

influence less than 5 percent of the sage-grouse habitats in the 

entire MZ, and these infrastructures are relatively dense in 

MZs II and VII compared to western portions of the range of 

sage-grouse (tables 5–9, figs. 10–13). For example, the proportion of sage-grouse habitat influenced directly by urban development in MZs I, II, and VII combined is 3.1 times higher; the 

amount directly influenced by power lines is 2.1 times higher, 

and the amount directly influenced by railroads is 1.9 times 

higher than the proportion directly influenced in the other MZs 

combined (tables 5–9). 

BLM managed grazing allotments not meeting wildlife 

standards consist of 4 percent of MZs II and VII and are not 

widespread throughout the region except in southern portions 

of the MZ (table 22, fig. 28); however, considerable portions 

of this region have not been recently assessed. Although areas 

not meeting standards are not widespread in the region, the 

Greater Sage-Grouse Comprehensive Conservation Strategy 

(Stiver and others, 2006a) ranked livestock grazing just below 

energy development and urbanization as an issue requiring 

immediate attention in eastern portions of the range of sagegrouse. Additionally, a large portion of central regions of this 

MZ (close to 5 million acres [20,200 km2

] across the entire 

MZ; table 23) is Federally managed wild horse and burro 

range (fig. 29), suggesting potential effects to sage-grouse of 

livestock grazing, and the compounding effects of feral grazers 

need to be considered across the region. Fire risk is generally 

low across MZ II and VII with 10 percent of priority and 

general habitats at high risk for fire (table 19); however, areas 

in northern and southern portions of the MZ are identified as 

having high fire risk (fig. 26). 

Cheatgrass is distributed across the region, however, 

generally not with the same abundance observed in the Great 

Basin region; some portions of this region, for example, the 

ownership “checkerboard” in southern Wyoming, are notably more thoroughly invaded than cooler parts of the region. 

Where severe infestation overlaps with PPH and PGH, 

management-intensive restoration may be considered. Current 

levels of disturbance have been sufficient to spread invasive 

species, and the historic combination of drought-stress and 

overutilization left sufficient niche space among native perennials for local proliferation. In many areas, short-term adaptations of grazing rotations to increase the cover of native perennials may be sufficient to restore high-quality habitats. Despite 

the perceived abundance and persistence of sagebrush in some 

parts of this region, extensive (or cumulative) treatments that 

remove sagebrush cover (even temporarily) are discouraged, 

unless said treatments represent a very small portion of an 

extensive, intact sagebrush stand (very rare) or are expressly 

designed to rehabilitate degraded, underutilized habitats.

MZ III—Southern Great Basin and Western 

Colorado Plateau

Management Zone III consists of 12 sage-grouse populations distributed throughout the region including the Southern 

Great Basin population in central and eastern Nevada, which 

contains the largest numbers of sage-grouse in MZ III (Conservation Objectives Team and others, 2013), several small 

populations in central Utah, and the Bi-State Distinct Population Segment along the California-Nevada border (Garton 

and others, 2011). Predicted population trends indicate that 

populations in this MZ have almost no chance of falling below 

200 males by 2037 and an 8 percent chance of falling below 

200 males by 2107 (Garton and others, 2011); however, these 

scenarios are limited in their ability to predict the future, especially stochastic events and novel environmental conditions, so 

caution is warranted. A majority (82 percent) of the sagebrush 

landscape in this MZ is Federally managed (predominantly 

BLM and USFS; table 26), indicating that actions on Federal 

lands are expected to have measurable population effects, and 

conservation measures on private lands may be less influential, 

as a whole, for conserving sage-grouse in this MZ. However 

as noted in sections above, large areas of influence exist from 

some threats; therefore, cooperation and prioritization of 

habitats across jurisdictions is still important in this Management Zone. This region is best characterized (for sage-grouse) 

by the large Southern Great Basin population, which occupies 

much of central and eastern Nevada; however, several smaller 

but significant populations persist, and priority management 

issues and challenges associated with these small populations 

may be distinctive from other populations in the region.
132 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Sagebrush cover is naturally limited and patchy across 

much of this region, as dictated by geologic substrates and 

formations that also help dictate (via topography) microclimates and local environmental conditions that enable sagebrush dominance, and this is evident in the lack of connectivity among subpopulations in this region (Knick and Hanser, 

2011). Well densities are currently low compared to other MZs 

(for example, MZs I and II). Current energy developments 

influence sage-grouse habitats in eastern portions of the MZ 

but are not widespread (figs. 14 and 16); however, more than 

1.8 million acres (7,285 km2

; 13 percent) of the sage-grouse 

habitats in the MZ are currently leased for Federal fluidmineral development (table 13) suggesting that some areas 

may receive increased pressure from energy development in 

the future. Additionally, coal and oil shale potential are high 

in eastern areas (Utah) of MZ III (figs. 19 and 23) indicating that development of these resources could affect already 

isolated populations in Utah. High potential for geothermal 

energy development coincides with sage-grouse habitats in 

central and western portions of MZ III (fig. 21B), and solarenergy potential is high in southern portions of the region 

indicating that these alternate energy sources could have 

impacts on sage-grouse habitats in southern Nevada and Utah 

in the future (depending on technology, financial markets, and 

public policies). 

In contrast, the number and size of areas affected annually by fire in this MZ are an order of magnitude greater than 

is typical in the Wyoming Basin (MZ II) to the east, suggesting that land-use disturbance has been replaced, or substituted, with frequent fire in these areas; this condition is often 

closely tied to the invasion and dominance of annual grasses, 

especially cheatgrass, due to their effect on fuels and firereturn intervals (figs. 25 and 26). Since 2000, 404,000 acres 

(1,635 km2

; 2.8 percent) of priority and general sage-grouse 

habitats (PPH and PGH combined) have burned in this MZ. 

Annual means suggest that only 13,500 acres (54 km2

; <2 percent) of habitats (PPH and PGH) burn each season; however, 

the observed maximum is more than 55,000 acres (220 km2

; 

0.5 percent of PPH and 1.4 percent of PGH in this region). 

Importantly, 63 percent of the region is considered at high risk 

for fire (tables 19, fig. 26). Conifer encroachment potentially 

affects more than 1.8 million acres (7,285 km2

; 13 percent) 

of priority and general habitats in MZ III (table 21). Precise 

estimates of actual impact are not available; therefore, evaluation of local habitat priorities and potential treatment benefits 

to inform planning efforts may require higher resolution data. 

Cheatgrass invasion has been widespread in this region for 

decades, and some former (historic) habitats are likely “unrecoverable” without unreasonable infusion of restoration effort 

(that is, it would be too expensive given current knowledge 

and technology); many of these areas are already excluded 

from current habitat distributions (fig. 1). Nonetheless, current 

estimates indicate more than 30 percent of PPH and 40 percent 

of PGH remain at high risk of invasion with notable risks 

remaining in some areas. Beyond managing risk, restoration 

of potentially valuable areas, such as those that would increase 

connectivity among seasonal habitats or subpopulations, or 

simply increase area and quality of current seasonal ranges, 

may become an important management option where natural 

and anthropogenic patterns and processes have fragmented 

and degraded habitats.

In addition to cheatgrass, widespread, intense land use 

coupled with natural variability and limitations of climate 

has resulted in measurable effects on rangeland conditions. 

Currently (2006), 1.6 million acres (6,475 km2

) of the BLM 

managed sage-grouse habitats in MZ III (17 percent) do not 

meet wildlife standards due to grazing impacts (table 22). 

Further, more than 4.1 million acres (16,590 km2

; 29 percent) 

of this area is designated wild horse and burro range; most of 

these areas are in central Nevada (table 23, fig. 29A). Horse 

and burro herbivory has been connected to intense resource 

use and measureable effects on range conditions and habitat 

quality (Beever and Aldridge, 2011).

Urbanized areas, power lines, and railroads influence 

habitats in eastern portions (Utah) of this MZ but are not widespread in central and western portions. Agricultural development influences less than 1 percent of the MZ, however due to 

indirect influences, 78 percent (the lowest proportion across 

MZs) of priority and general habitats are estimated to be 

affected by cropland (table 4, fig. 9). 

MZ IV—Snake River Plain

Management Zone IV consists of 11 sage-grouse populations distributed throughout the region with the bulk of the 

occupied area consisting of the Northern Great Basin and 

Snake-Salmon-Beaverhead, Idaho populations (Garton and 

others, 2011). Similarly to other regions, the Snake River Plain 

of southern Idaho has a long history of agricultural land uses 

that include irrigated crops and open-range livestock management. Historic conversion of the best sites (deepest soils) 

to agriculture (a practice that was widespread with nearly 

complete conversion in this region) has resulted in a residual 

sagebrush landscape that is inherently less productive than 

those of the past (prior to European colonization). Subsequently, most known populations in the region are relatively 

small and (or) separated from adjacent populations; important 

exceptions are the large population living in central Idaho 

(the largest outside of the Wyoming Basin) within the upper 

watershed of the Snake, Salmon, and Beaverhead Rivers, and 

the Northern Great Basin population living on the Snake River 

Plain (Conservation Objectives Team, 2013). Several small, 

isolated populations are located in predominantly northern 

portions of this MZ (Garton and others, 2011). Nonetheless, 

habitat availability remains a primary limiting factor in this 

region due to the combination of land-use and disturbance 

(fire) influences, and influences of current and historic land 

uses add to these effects through effects on the health and 

condition of available ranges.

Population trends and vulnerability models indicate that 

populations in this MZ have an 11 percent chance of falling below 200 males by 2037, and a 40-percent chance of 
V. Risk, Policies, and Actions: Assessment of Dominant Threats and Potential Interactions within Management Zones 133

falling below 200 males by 2107 (Garton and others, 2011). A 

majority (63 percent) of the sagebrush landscape in this MZ 

is Federally managed (Knick 2011), suggesting conservation 

measures on public lands may be expected to have measurable effects on sage-grouse populations, and the role of private 

lands will remain important but limited, in general, as a means 

of conserving sage-grouse in this MZ. Local importance 

and effectiveness of projects may be greater than rangewide 

effects due to local contributions to seasonal habitat quality 

and connectivity. 

Primary threats to sage-grouse habitats and populations 

occurring across populations in MZ IV include habitat loss and 

fragmentation as a result of wildfire (Conservation Objectives 

Team, 2013). Since 2000, more than 4.9 million acres (21,000 

km2

; 14 percent of PPH and 17 percent of PGH) of priority 

and general sage-grouse habitats have burned in this MZ, with 

an average of more than 239,000 acres (970 km2

) of priority 

habitats burned annually; more than 1 million acres (4,047 

km2

) burned in some years (table 18, fig. 25). For example, the 

Murphy Fire in Idaho and Nevada affected more than 650,000 

acres (2,630 km2

) of habitat in this MZ in 2007 (Conservation 

Objectives Team, 2013). Additionally, 81 percent of the region 

is considered at high risk for fire (table 19, fig. 26). Approximately 11.6 million acres (47,175 km2

; 53 percent) of PPH 

and 6.4 million acres (25,900 km2

, 58 percent) of PGH in MZ 

IV are considered high risk for cheatgrass, and these high-risk 

areas are widespread throughout the MZ (table 20, fig. 27A). 

Geothermal energy development potential is particularly 

high throughout MZ IV (fig. 21B). Very few active oil and gas 

wells exist in the MZ (fig. 14), although there has been some 

exploration historically, and less than 350,000 acres (1,400 

km2

; 1 percent) of sage-grouse habitats are currently leased 

for Federal fluid-mineral exploration (table 13). Additionally, 

coal and solar potential are low throughout the MZ (figs. 20 

and 22). Urbanized areas, power lines, and railroads influence 

habitats predominantly in eastern portions (eastern Idaho and 

southwestern Montana) of MZ IV (tables 5–9, figs. 10–13). 

However, designated energy corridors are located in southern portions of the MZ, and transmission lines are proposed 

in these areas, for example Gateway West (see http://www.

wy.blm.gov/nepa/cfodocs/gateway_west/map.html). Agricultural development influences 1 percent of the MZ, and 

85 percent of priority and general habitats are within 4.3 mi 

(6.9 km ) of cropland (table 4, fig. 9). 

Finally, historic and current land-use patterns affect 

habitat conditions, in addition to regional distributions. Currently (2006 assessment) more than 3.5 million acres (14,160 

km2

) of BLM managed sage-grouse habitats (19 percent) do 

not meet wildlife standards due to livestock (table 22, fig. 28) 

in this MZ; this is the largest area, absolutely and proportionally, of all MZs (albeit large portions of some other MZs were 

not assessed). Compounding the effects of large herbivores on 

ecosystem conditions, some habitat within this MZ (6 percent) 

is Federally managed wild horse and burro range including 

a relatively large area of priority habitat in northern Nevada 

(table 23, fig. 29A). Though managed grazing remains a part 

of the tools used to manage habitats into the future, with a 

potential role for addressing fuel accumulation and fire potential, invasive plants, and vegetation structure and composition, 

non-prescribed grazing (over-grazing), as determined by local 

conditions and climate patterns, is clearly implicated for its 

detrimental effects on rangeland health as well as habitat conditions, in some areas. Thus in this MZ, and other areas, where 

the interactions of ecosystem conditions, climate, and multiple 

herbivores may result in habitat degradation, close monitoring of productivity and off-take to manipulate and adjust use 

levels to maintain seasonal habitat quality may be necessary. 

Importantly, local conditions and environmental patterns 

(such as climate) are highly variable, and direct assessments 

are dated (>5 years old in most cases); therefore, trends and 

conditions assessed here may have changed. This reinforces 

the need for frequent evaluation and adjustments to balance 

multiple uses with habitat requirements of the native wildlife.

MZ V—Northern Great Basin

This MZ includes three large populations living on the 

western one-third of the Northern Great Basin region and a 

fourth, relatively large population in central Oregon (Garton and others, 2011). Predicted population trends indicate 

that populations in this MZ have a low (2 percent) chance of 

falling below 200 males by 2037 and a greater (29 percent) 

chance of falling below 200 males by 2107 (Garton and 

others, 2011). A majority of the sagebrush landscape in this 

MZ (77 percent) is Federally managed (Knick and Connelly, 

2011b), suggesting conservation measures that can only be 

applied to private lands may be insufficient for conserving 

sage-grouse in this region, but Federal habitat management 

may be expected to have a strong influence on these populations. Sage-grouse leks in this region are relatively well 

connected (second in rank behind Wyoming Basin; Knick and 

Hanser, 2011b); however, a national team of experts identified habitat loss and fragmentation due to wildfire and conifer 

encroachment as primary threats to sage-grouse in this region 

(Conservation Objectives Team, 2013). 

The Northern Great Basin region contains less “moderately” and “highly’ affected sage-grouse habitat than the westwide average. But it also contains the most extensive “low” 

land-use intensity distribution of all MZs indicating priorities 

focused on managing low-intensity, distributed land uses to 

conserve and improve habitat for grouse (passive approaches 

should be effective and efficient) may be critical to regional 

conservation success. Similarly, areas with intensive use that 

overlap priority habitats (PPH and PGH) may be readily prioritized for habitat improvements because these areas are less 

extensive than in adjacent regions. However, since 2000 more 

than 1.5 million acres (6,400 km2

; 12.2 percent) of priority 

(17.5 percent) and general (5.8 percent) sage-grouse habitats 

burned with an average size of more than 95,000 acres (385 

km2

) per year during this time span (table 18, fig. 25). Additionally, 67 percent of the region is considered at high risk 

for fire (table 19, fig. 26). Despite these fires, conifers have 
134 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

encroached on approximately 1.4 million acres (5,670 km2; 

11 percent) of priority and general habitats in MZ V (table 

21) indicating, again, that the spatial heterogeneity in habitat 

threats and conditions require local interpretation and adaptation to differentiate threats and develop specific management 

solutions. As another example, low sagebrush (A. arbuscula) 

is common only in the Northern Great Basin, although it 

occurs throughout the range at varying abundance (Johnson 

and others, 2011), and it is utilized by sage-grouse consistently 

here, in multiple seasons, including nesting and brood-rearing, 

making proper management and conservation of this ecological type important for sage-grouse conservation in this region. 

More than 5.6 million acres (22,735 km2; 43.5 percent) 

of MZ V are considered moderate to high risk for cheatgrass; a large block of high-risk priority habitat is located 

in northwestern Nevada (table 20, fig. 27A). More than 3.6 

million acres (14,570 km2; 28 percent) of sage-grouse habitats distributed throughout MZ V is Federally managed wild 

horse and burro range (table 23, fig. 29A). Approximately 6 

percent of BLM managed sage-grouse habitats in MZ V do 

not meet wildlife standards (table 22, fig. 28), with again a 

relatively large block of priority habitat not meeting standards 

in northwestern Nevada.

Finally, though no single threat supersedes others, there 

are various forms of industrial development that affect habitats 

in this region. No active oil and gas wells currently exist in the 

MZ (fig. 15), and no measurable additional acreage has been 

leased for fluid-mineral exploration (table 13). However, geothermal energy potential is high throughout the region indicating potential for future development (fig. 21). Urbanized areas, 

power lines, and railroads are less dense in MZ V than in 

eastern portions of the sage-grouse range (tables 5–9, figs.10–

13A). However, the Warm Springs Valley population, a small 

area on the California-Nevada border (Garton and others, 

2011), is known to be influenced by urbanization and a transmission line (Conservation Objectives Team, 2013). Agricultural developments currently influence less than 1 percent of 

the MZ; however, 75 percent of priority and general habitats 

are within the influence of cropland (table 4, fig. 9) indicating 

a high likelihood of influence, without direct displacement.

MZ VI—Columbia Basin

The sage-grouse habitats within the Columbia Basin are 

among the most developed (primarily agriculture) and heavily 

used landscapes still occupied by sage-grouse. These two, 

small populations are also affected by living near the distribution limits of the species and suitable sagebrush habitats. 

Washington populations do not significantly occupy BLM 

lands, so while important to the overall conservation of the 

species, this region is not directly addressed in this assessment. CRP lands can create habitat refugia within converted 

landscapes when they include sagebrush cover; enrollment of 

17 percent of an agricultural landscape in eastern Washington succeeded in reversing short-term population declines, 

whereas declines continued on adjacent landscape with fewer 

CRP-designated lands (Schroeder and Vander Haegen, 2011). 

These populations are recognized here but are part of an independent plan and assessment process.

Acknowledgments

This project was made possible through cooperative 

effort of many individuals, programs, and field office staffs, 

especially the Bureau of Land Management and U.S. Forest 

Service. We are particularly indebted to the legions of students, faculty, State and Federal research scientists who have 

contributed to the literature and knowledge about the sagegrouse biology, sagebrush habitats, and the complicated relations with natural and anthropogenic processes. We are also 

grateful to the many State and field office staff from the BLM 

and USFS that maintained and contributed data to the BLM 

National Operations Center for inclusion in our assessments. 

Tim Love from the USFS organized and centralized USFS 

data and information for this report. In addition to many local-, 

regional-, and national-scale efforts on behalf of the sagegrouse, we would like to formally recognize and appreciate the 

efforts of the Western Governors’ Association and the Western 

Association of Fish and Wildlife Agencies who have been 

leading the way in connecting the science and management 

of sage-grouse and sagebrush ecosystems for many years. 

Special thanks go to Susan Skagen and Shawn Espinosa, and 

to a long list of planners, biologists, ecologists, and managers 

for reviewing early versions of this report and helping to make 

it complete and coherent.
References Cited 135

References Cited

Aldrich, J.W., 1946, New subspecies of birds from western 

North America: Proceedings of the Biological Society 

of Washington, Biological Society of Washington, v. 59, 

p.129–136.

Aldrich, J.W., 1963, Geographic orientation of American 

tetraonidae: Journal of Wildlife Management, v. 27, no. 4, 

p. 529–545.

Aldrich, J.W., and Duvall, A.J., 1955, Distribution of 

American gallinaceous game birds: U.S. Fish & Wildlife 

Service: Circular 34, p.12–17.

Aldridge, C.L., 2000, Reproduction and habitat use by Sage 

Grouse (Centrocercus urophasianus) in a northern fringe 

population: Saskatchewan, Canada, University of Regina, 

M.S. thesis, 109 p.

Aldridge, C.L., and Boyce, M.S., 2007, Linking occurrence 

and fitness to persistence: Habitat–based approach for 

endangered Greater Sage-Grouse: Ecological Applications, 

v. 17, no. 2, p. 508–526.

Aldridge, C.L., and Brigham, R.M., 2003a, Distribution, 

abundance, and status of the Greater Sage-Grouse, 

Centrocercus urophasianus, in Canada: Canadian Field–

Naturalist, v. 117, p. 25–34.

Aldridge, C.L., and Brigham, R.M., 2003b, Sage-grouse 

nesting and brood habitat use in southern Canada: Journal 

of Wildlife Management, v. 67, p. 910–910.

Aldridge, C.L., Nielsen, S.E., Beyer, H.L., Boyce, M.S., 

Connelly, J.W., Knick, S.T., and Schroeder, M.A., 2008, 

Range-wide patterns of greater sage-grouse persistence: 

Diversity and Distributions, v. 14, p. 983–994.

Aldridge, C.L., Saher, D.J., Childers, T.M., Stahlnecker, 

K.E., and Bowen, Z.H., 2012, Crucial nesting habitat for 

Gunnison sage-grouse: A spatially explicit hierarchical 

approach: Journal of Wildlife Management, v. 76, 

p. 391–406.

Allendorf, F.W., and Leary, R.W., 1986, Heterozygosity and 

fitness in natural populations of animals, in Soule, M.E., ed., 

Conservation biology: the science of scarcity and diversity: 

Sunderland, Mass., U.S.A., Sinauer Associates, p. 51–65.

American Ornithologists’ Union, 1957, Check–list of North 

American birds, 5th ed., 139 p.

Anderson, E.D., Long, R.A., Atwood, M.P., Kie, J.G., 

Thomas, T.R., Zager, P., and Bowyer, R.T., 2012, Winter 

resource selection by female mule deer Odocoileus hemionus: functional response to spatio-temporal changes in 

habitat: Wildlife Biology, v. 18, p. 153–163.

Anderson, J.E. and Inouye, R.S., 2001, Landscape–scale 

changes in plant species abundance and biodiversity of a 

sagebrush steppe over 45 years: Ecological Monographs, 

v. 71, p. 531–556.

Anderson, L.D., 1991, Bluebunch wheatgrass defoliation 

effects and vigor recovery: Salmon, Idaho, Bureau of Land 

Management, 25 p.

Angell, R.F., 1997. Crested wheatgrass and shrub response 

to continuous or rotational grazing: Journal of Range 

Management, v. 50, p. 160–164.

Aspbury, A., and Gibson, R.M., 2004, Long-range visibility 

of greater sage grouse leks: a GIS-based analysis: Animal 

Behaviour, v. 67, p. 1127–1132.

Assal, T.J., Veblen, K.E., Farinha, M.A., Aldridge, C.L., 

Cassaza, M.E., and Pyke, D.A., 2012, Data resources for 

range-wide assessment of livestock grazing across the 

Sagebrush Biome: U.S. Geological Survey Data Series 690.

Atamian, M.T., Sedinger, J.S., Heaton, J.S., and Blomberg, 

E.J., 2010, Landscape-level assessment of brood rearing 

habitat for Greater Sage-Grouse in Nevada: Journal of 

Wildlife Management, v. 74, p. 1533–1543.

Autrienth, R.E., 1981, Sage grouse management in Idaho: 

Boise, Idaho, Idaho Department of Fish and Game, 

Research Report, available at http://fishandgame.idaho.gov/

public/wildlife/sageGrouse/.

Baker, W.L., 2006, Fire and restoration of sagebrush 

ecosystems: Wildlife Society Bulletin, v. 34, p. 177–185.

Baker, W.L., 2011, Pre- Euro-American and recent fire in 

sagebrush ecosystems, in Knick, S.T. and Connelly, J.W., 

eds., Greater sage-grouse: ecology and conservation of a 

landscape species: Berkeley, Calif., University of California 

Press, p. 185–202 .

Balch, J.K., Bradley, B.A., D’Antonio, C.M., and GomezDans, J., 2012, Introduced annual grass increases regional 

fire activity across the arid western USA (1980–2009): 

Global Change Biology, v. 19, p. 173–183.

Bartmann, R.M., White, G.C., Carpenter, L.H., and Garrott, 

R.A., 1987, Aerial mark-recapture estimates of confines 

mule deer in pinyon-juniper woodland: Journal of Wildlife 

Management, v. 51, p. 41–46.

Bates, J.D., Davies, K.W., and Sharp, R.N., 2011, Shrubsteppe early succession following juniper cutting and 

prescribed fire: Environmental Management, v. 47, 

p. 468–481.

Bates, J.D., Rhodes, E.C., Davies, K.W., and Sharp, R., 

2009, Postfire succession in Big Sagebrush Steppe with 

livestock grazing: Rangeland Ecology & Management, 

v. 62, p. 98–110.
136 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Bates, J.D., Svejcar, T., Miller, R.F., and Angell, R.A., 

2006, The effects of precipitation timing on sagebrush 

steppe vegetation: Journal of Arid Environments, v. 64, 

p. 670–697.

Baughman, C., Forbis, T.A., and Provencher, L., 2010, 

Response of two sagebrush sites to low-disturbance, 

mechanical removal of pinyon and juniper: Invasive Plant 

Science and Management, v. 3, p. 122–129.

Baxter, R.J., Flinders, J.T., and Mitchell, D.L., 2008, Survival, 

movements, and reproduction of translocated greater sagegrouse in Strawberry Valley, Utah: Journal of Wildlife 

Management, v. 72, p. 179–186.

Beck, J.L., Connelly, J.W., and Reese, K.P., 2009, Recovery 

of Greater Sage–Grouse habitat features in Wyoming Big 

Sagebrush following prescribed fire: Restoration Ecology, 

v. 17, p. 393–403.

Beck, J.L., Connelly, J.W., and Wambolt, C.L., 2012, 

Consequences of treating Wyoming Big Sagebrush 

to enhance wildlife habitats: Rangeland Ecology and 

Management, v. 65, no. 5, p. 444–455.

Beck, J.L., and Mitchell, D.L., 2000, Influences of livestock 

grazing on sage grouse habitat: Wildlife Society Bulletin, 

v. 28, p. 993–1002.

Beck, J.L., Mitchell, D.L., and Maxfield, B.D., 2003, Changes 

in the distribution and status of sage-grouse in Utah: 

Western North American Naturalist, v. 63, p. 203–214.

Beck, J.L., Reese, K.P, Connelly, J.W., and Lucia, M.B., 2006, 

Movements and survival of juvenile greater sage-grouse 

in southeastern Idaho: Wildlife Society Bulletin, v. 34, 

p. 1070–1078.

Beck, T.D.I., 1977, Sage grouse flock characteristics and 

habitat selection in winter: Journal of Wildlife Management, 

v. 41, p. 18–26.

Beever, E.A., and C.L., Aldridge, 2011, Influences of freeroaming equids on sagebrush ecosystems, with focus on 

greater sage-grouse, in Knick, S.T., and Connelly, J.W,. eds., 

Studies in avian biology, no.38: University of California 

Press, Berkeley, Cooper Ornithological Union, p. 273–291.

Belcher, J.W., and Wilson, S.D., 1989, Leafy spurge and the 

species composition of mixed grass prairie: Journal of 

Range Management, v. 42, p. 172–175.

Benedict, N.G., Oyler–McCance, S.J., Taylor, S.E., Braun, 

C.E., and Quinn, T.W., 2003, Evaluation of the eastern 

(Centrocercus urophasianus urophasianus) and western 

(Centrocercus urophasianus phaios) subspecies of sage–

grouse using mitochondrial control-region sequence data: 

Conservation Genetics, v. 4, p. 301–310.

Berry, J.D., and Eng, R.L., 1985, Interseasonal movements 

and fidelity to seasonal use areas by female sage-grouse. 

Journal of Wildlife Management, v. 49, p. 237–240.

Bi-State Local Planning Group, 2004, Greater sage-grouse 

conservation for the bi-state plan area of Nevada and 

eastern California: Bi-State Local Planning Group, First 

Edition, 193 p.

Blickley, J.L., Blackwood, D., and Patricelli, G.L., 2012, 

Experimental evidence for the effects of chronic 

anthropogenic noise on abundance of Greater Sage-Grouse 

at leks: Conservation Biology, v. 26, p. 461–471.

Blomberg, E.J., Sedinger, J.S., Atamian, M.T., and Nonne, 

D.V., 2012, Characteristics of climate and landscape 

disturbance influence the dynamics of Greater Sage-Grouse 

populations: Ecosphere, v. 3, p. 55–65.

Blus, L.J., Staley, C.S., Henny, C.J., Pendleton, G.W., 

Craig, T.H., Craig, E.H., and Halford, D.K., 1989, Effects 

of organophosphorus insecticides on sage grouse in 

southeastern Idaho: Journal of Wildlife Management, v. 53, 

p. 1139–1146.

Bouzat, J.L., Cheng, H.H., Lewin, H.A., Westemeier, R.L., 

Brawn, J. D., and Paige, K.N., 1998, Genetic evaluation 

of a demographic bottleneck in the greater prairie chicken: 

Conservation Biology, v. 12, p. 836–843.

Boyce, M.S., 1990, The red queen visits sage grouse leks: 

American Zoology, v. 30, p. 263–270.

Boyko, A.R., Gibson, R.M., and Lucas, 2004, How predation 

risk affects the temporal dynamics of avian leks: Greater 

Sage-Grouse versus golden eagles: American Naturalist, 

v. 163, p. 154–165.

Bradley, B.A., 2010, Assessing ecosystem threats from 

global and regional change: hierarchical modeling of risk 

to sagebrush ecosystems from climate change, land use 

and invasive species in Nevada, U.S.A.: Ecography, v. 33, 

p. 198–208.

Braun, C.E., 1998, Sage grouse declines in western North 

America: what are the problems?, in Proceedings of the 

Western Association of State Fish and Wildlife Agencies 

(WAFWA), p. 139–156.

Braun, C.E., Baker, M.F., Eng, R.L., Gashwiler, J.W., and 

Schroeder, M.H., 1976, Conservation committee report 

on effects of alteration of sagebrush communities on the 

associated avifauna: The Wilson Bulletin, v. 88, p. 165–171.

Braun, C.E., and Beck, T.D.I., 1985, Effects of changes in 

hunting regulations on sage grouse harvest and populations, 

in Beason, S.L., and Roberson, S.F., eds., Game harvest 

mangement: Kingsville, Tex., Caesar Kleberg Wildlife 

Research Institute, p. 335–343.
References Cited 137

Braun, C.E., Oedekoven, O.O., and Aldridge, C.L., 2002, Oil 

and gas development in western North America: Effects on 

sagebrush steppe avifauna with particular emphasis on sage 

grouse, in Rahm, J., ed., Transactions of the sixty-seventh 

North American wildlife and natural resource conference: 

Wildlife Management Inst., Washington, p. 337–349.

Briske, D.D., Derner, J.D., Brown, J.R., Fuhlendorf, S.D., 

Teague, W.R., Havstad, K.M., Gillen, R.L., Ash, A.J., and 

Willms, W.D., 2008, Rotational grazing on rangelands: 

reconciliation of perception and experimental evidence: 

Rangeland Ecology & Management, v. 61, p. 3–17.

Briske, D.D., S.D. Fuhlendorf, and F.E. Smeins, 2003, 

Vegetation dynamics on rangelands: a critique of the current 

paradigms: Journal of Applied Ecology, v. 40, p. 601–614.

Briske, D.D., and Hendrickson, J.R., 1998, Does selective 

defoliation mediate competitive interactions in a semiarid 

savanna? A demographic evaluation: Journal of Vegetation 

Science, v. 9, p. 611–622.

Brockway, D.G., Gatewood, R.G. and Paris, R.B., 2002, 

Restoring grassland savannas from degraded pinyon-juniper 

woodlands: effects of mechanical overstory reduction and 

slash treatment alternatives: Journal of Environmental 

Management, v. 64, p. 179–197.

Brown, J.K., 1982, Fuel and fire behavior prediction in big 

sagebrush: Research paper INT-290 83–B, USDA Forest 

Service, Intermountain Forest and Range Experiment 

Station, Ogden, Utah.

Bruce, J.R., Robinson, W.D., Petersen, S.L., and Miller, R.F., 

2011, Greater Sage-Grouse movements and habitat use 

during winter in central Oregon: Western North American 

Naturalist, v. 71, p. 418–424.

Bui, T.D., 2009, The effects of nest and brood predation by 

common ravens (Corvus corax) on Greater Sage-Grouse 

(Centrocercus urophasianus) in relation to land use in 

western Wyoming: University of Washington.

Bureau of Land Management, 1999, Out of ashes, An 

opportunity: Report of the Great Basis Restoration 

Initiative: Boise, Idaho, BLM National Office of Fire 

and Aviation, 28 p., available at http://www.sagestep.org/

educational_resources. 

Bureau of Land Management, 2008, Wildfire season and 

sage-grouse conservation: Washington, D.C. Bureau of 

Land Management.

Bureau of Land Management, 2011a, BLM National Sage–

Grouse Land Use Planning Strategy: Washington, D.C., 

Bureau of Land Management, Instruction Memorandum. 

Bureau of Land Management, 2011b, Greater Sage-Grouse 

interim management policies and procedures: Washington, 

D.C., Bureau of Land Management, Instruction 

Memorandum. 

Bureau of Land Management, 2011c, Notice of intent to 

prepare environmental impact statements and supplemental 

revironmental impact statements to incorporate Greater 

Sage-Grouse conservation measures into land use plans and 

land management plans: Washington, D.C, Federal Register 

40 CFR 1501.7.

Bureau of Land Management, 2012, Notice of correction 

to notice of intent to prepare environmental impact 

statements and supplemental environmental impact 

statements to incorporate Greater Sage-Grouse conservation 

measures into land use plans and land management plans: 

Washington, D.C., Federal Register 43 CFR 1610.2., 

p. 7178–7179.

Bureau of Land Management, 2012b, Oil shale and tar sands 

programmatic EIS information center: Bureau of Land 

Management, BLM–WO–GI–08–005–3900, DOI No. DES 

12–01, accessed December 2012 at http://ostseis.anl.gov. 

Bureau of Land Management, 2012c, Final solar energy 

development programmatic EIS: Bureau of Land 

Management, FES 12–24: DOE/EIS–0403, final EIS 

published July 2012, available at http://solareis.anl.gov.

Burkhardt, J.W., and Tisdale, E.W., 1976, Causes of juniper 

invasion in southwestern Idaho: Ecology, v. 57, p. 472–484.

Bush, K.L., 2009, Genetic diversity and paternity analysis of 

endangered Canadian Greater Sage–Grouse (Centrocercus 

urophasianus): Edmonton, Alberta, Canada, University of 

Alberta, Ph.D. dissertation.

Cagney, J., Bainter, E., Budd, R., Christiansen, T., Herren, V., 

Holloran, M.J., Rashford, B., Smith, M.D., and Williams, 

J., 2010, Grazing influence, objective development, and 

mangement in Wyoming’s Greater Sage–Grouse habitat: 

Laramie, University of Wyoming, Cooperative Extension 

Service Report.

Call, M., and Maser, W.C., 1985, Wildlife habitats in managed 

rangelands—The Great Basin of southeastern Oregon sage 

grouse: La Grande, Oreg., U.S. Department of Agriculture, 

Forest Service, General Technical Report, 30 p.

Canada Gazette, 2002, Species at risk act: Canada Gazette, 

428 p.

Carpenter, J., Aldridge, C., and Boyce, M.S., 2010, Sagegrouse habitat selection during winter in Alberta: Journal of 

Wildlife Management, v. 74, p. 1806–1814.

Carr, H.D., and Glover, F.A., 1970, Effects of sagebrush 

control on sage grouse: North American Wildlife and 

Natural Resources Conference Transcripts, p. 205–215.
138 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Chong, G.W., Wetzel, W.C., and Holloran, M.J., 2011, Greater 

Sage–Grouse of Grand Teton National Park: Where do they 

roam?: Park Science, v. 27, p. 42–49.

Chong, G.W., and Anderson, P.J., 2010, Applying greenness 

indices to evaluate sagebrush treatments in the WLCI 

region, in Bowen, Z.H., and others, U.S. Geological 

Survey science for the Wyoming landscape conservation 

initiative—2009 Annual Report: U.S. Geological Survey 

Open-File Report 2010–1231, p. 59–63.

Christen, D.C., and Matlack, G.R., 2009, The habitat and 

conduit functions of roads in the spread of three invasive 

plant species: Biological Invasions, v. 11, p. 453–465.

Christensen, N.L., 1985, Shrubland fire regimes and their 

evolutionary consequences, in Pickett, S.T.A., and 

White, P.S., The ecology of natural disturbance and patch 

dynamics: San Diego, Calif., Academic Press, , p. 85–100. 

Christiansen, T., 2009, Fence marking to reduce Greater 

Sage–Grouse (Centrocercus urophasianus) collisions and 

mortality near—Summary of interim results: Farson, Wyo., 

Wyoming Game and Fish Department. 

Christiansen, T.J., and Tate, C.M., 2011, Parasites and 

infectious disease of Greater Sage-Grouse, in Knick, 

S.T., and Connelly, J.W., eds., Greater Sage-Grouse: 

ecology and conservation of a landscape species and its 

habitats: Berkeley, University of California Press, Cooper 

Ornithological Union, no. 38, 47 p.

Clark, L., Hall, J., McLean, R., Dunbar, M., Klenk, K., 

Bowen, R., and Smeraski, C.A. 2006, Susceptibility of 

Greater Sage-Grouse to experimental infection with West 

Nile virus: Journal of Wildlife Diseases, v. 42, p. 14–22.

Clifford, M.J., Cobb, N.S., and Buenemann, M., 2011, Longterm tree cover dynamics in a pinyon-juniper woodland: 

climate-change-type drought resets successional clock. 

Ecosystems, v. 14, p. 949–962.

Coates, P.S., 2007, Greater Sage-Grouse (Centrocercus 

urophasianus) nest predation and incubation behavior: 

Boise, Idaho State University.

Coates, P.S., Connelly, J.W., and Delehanty, D.J., 2008, 

Predators of Greater Sage-Grouse nests identified by video 

monitoring: Journal of Field Ornithology, v. 79, p. 421–428.

Colorado Greater Sage-Grouse Steering Committee, 2008, 

Colorado Greater Sage-Grouse conservation plan: Denver, 

Colorado Division of Wildlife.

Condon, L., Weisberg, P.J., and Chambers, J.C., 2011, Abiotic 

and biotic influences on Bromus tectorum invasion and 

Artemisia tridentata recovery after fire: International 

Journal of Wildland Fire, v. 20, p. 597–604.

Connelly, J., 2005, Challenging dogma—Changing 

paradigms—Sage grouse harvest management in the United 

States: Sage Grouse News, v. 29, p. 7–11.

Connelly, J.W., 1980, Ecology of sage grouse on the INEL 

Site: Idaho Department of Fish and Game, Report Federal 

Aid Project W–160–R–7.

Connelly, J.W., 1982, An ecological study of sage grouse 

in southeastern Idaho: Pullman, Wash., Washington State 

University.

Connelly, J.W., Apa, A.D., Smith, R.B., and Reese, K.P., 

2000a, Effects of predation and hunting on adult sage 

grouse Centrocercus urophasianus in Idaho: Wildlife 

Biology, v. 6, p. 227–232.

Connelly, J.W., Arthur, W.J., and Markham, O.D., 1981, Sage 

grouse leks on recently disturbed sites: Journal of Range 

Management, v. 34, p. 153–154.

Connelly, J.W., and Blus, L.J., 1991, Effects of pesticides on 

upland game—A review of herbicides and organophosphate 

and carbamate insecticides: Corvallis, Oreg., U.S. 

Environmental Protection Agency, p. 238–239.

Connelly, J.W., and Braun, C.E., 1997, A review of longterm changes in sage grouse populations in western North 

America: Wildlife Biology, v. 3, p. 229–234.

Connelly, J.W., and Doughty, L.A., eds., 1989, Sage grouse 

use of wildlife water developments in southeastern Idaho: 

Boise, Idaho.

Connelly, J.W., Hagen, C.A., and Schroeder, M.A., 2011a, 

Characteristics and dynamics of Greater Sage-Grouse 

populations, in Knick S.T., and Connelly, J.W., eds., Greater 

Sage–Grouse: ecology of a landscape species and its 

habitats: Berkeley, Calif., University of California Press, 

Cooper Ornithological Union, Studies in Avian Biology 

No. 38, p. 53–68.

Connelly, J.W., Knick, S.T., Braun, C.E., Baker, W.L., 

Beever, E.A., Christiansen, T., Doherty, K.E., Garton, 

E.O., Hagen, C.A., Hanser, S.E., Johnson, D.H., Leu, M., 

Miller, R.F., Naugle, D.E., Oyler-McCance, S.J., Pyke, 

D.A., Reese, K.P., Schroeder, M.A., Stiver, S.J., Walker, 

B.L., and Wisdom, M.J., 2011b, Conservation of Greater 

Sage-Grouse: a synthesis of current trends and future 

management, in Knick, S.T., and Connelly, J.W., eds., 

Greater Sage–Grouse: Ecology of a landscape species and 

its habitats: Berkeley, Calif., University of California Press, 

Cooper Ornthological Union, no. 38, p. 549–563.

Connelly, J.W., Knick, S.T., Schroeder, M.A,. and Stiver, S.J., 

2004, Conservation assessment of Greater Sage-Grouse and 

sagebrush habitats: Report to the Western Association of 

Fish and Wildlife Agencies (WAFWA), 610 p.
References Cited 139

Connelly, J.W., Reese, K.P., Garton, E.O., and CommonsKemner, M.L., 2003a, Response of Greater Sage-Grouse 

Centrocercus urophasianus populations to different levels 

of exploitation in Idaho, U.S.A.: Wildlife Biology, v. 9, 

p. 335–340.

Connelly, J.W., Reese, K.P., and Schroeder, M.A., 2003b, 

Monitoring of Greater Sage-Grouse habitats and 

populations: Moscow, Idaho, University of Idaho, College 

of Natural Resources Experiment Station.

Connelly, J.W., Rinkes, E.T., and Braun, C.E., 2011d, 

Characteristics of Greater Sage-Grouse habitats—A 

landscape species at micro and macro scales, in Knick, S.T., 

and Connelly, J.W., eds., Greater Sage-Grouse: ecology 

of a landscape species and its habitats: Berkeley, Calif., 

University of California Press, Cooper Ornithological 

Union, p. 69–84.

Connelly, J.W., Schroeder, M.A., Sands, A.R., and Braun, 

C.E., 2000b, Guidelines to manage sage grouse populations 

and their habitats: Wildlife Society Bulletin, v. 28, 

p. 967–985.

Conservation Objectives Team, Abele, S., Budd, R., Budeau, 

D., Connelly, J., Deibert, P.A., Delevan, J., Espinosa, S., 

Gardner, S.C., Griffin, K., Harja, J., Northrup, R., Robinson, 

A., Schroeder, M., and Souza, P, 2013, Sage-grouse 

conservation objectives report: Denver, Colo., U.S. Fish and 

Wildlife Service, 62 p., appendix, available at http://www.

fws.gov/mountain-prairie/species/birds/sagegrouse/.

Copeland, H.E., Doherty, K.E., Naugle, D.E., Pocewicz, 

A., and Kiesecker, J.M., 2009, Mapping oil and gas 

development potential in the U.S. Intermountain West and 

estimating impacts to species: PLoS One, v. 4, p. e7400.

Copeland, H.E., Pocewicz, A., and Kiesecker, J.M., 2011, 

Geography of energy development in western North 

America: potential impacts on terrestrial ecosystems, 

in Naugle, D.E., ed., Energy development and wildlife 

conservation in western North America: Washington, D.C., 

Island Press, p. 7–25.

Cote, I.M., and Sutherland, W.J., 1997, The effectiveness 

of removing predators to protect bird populations: 

Conservation Biology, v. 11, p. 395–405.

Crawford, J.A., 1982, History of sage grouse in Oregon: 

Oregon Wildlife, p. 3–6.

Crawford, J.A., Olson, R.A., West, N.E., Mosley, J.C., 

Schroeder, M.A., Whitson, T.D., Miller, R.F., Gregg, 

M.A., and Boyd, C.S., 2004, Ecology and management 

of sage-grouse and sage-grouse habitat: Journal of Range 

Management, v. 57, p. 2–19.

Cresswell, W., Lind, J., and Quinn, J.L., 2010, Predatorhunting success and prey vulnerability: quantifying the 

spatial scale over which lethal and nonlethal effects 

of predation occur: Journal of Animal Ecology, v. 79, 

p. 556–562.

Crist, M.R., Wilmer, B., and Aplet, G.H., 2005, Assessing the 

value of roadless areas in a conservation reserve strategy: 

biodiversity and landscape connectivity in the northern 

Rockies: Journal of Applied Ecology, v. 42, p. 181–191.

Culp, P.W., Conradi, D.B., and Tuell, C.C., 2005, Trust 

lands in the American West: a legal overview and policy 

assessment: Cambridge, Mass., Lincoln Institute of Land 

Policy/Sonoran Institute Joint Venture on State Trust Lands.

D’Antonio, C.M., Chambers, J.C., Loh, R., and Tunison, J.T., 

2009, Applying ecological concepts to the management 

of widespread grass invasions: Management of Invasive 

Weeds, p. 123–149.

Dalgleish, H.J., Koons, D.N. Hooten, M.B., Moffet, C.A., 

and Adler, P.B., 2011, Climate influences the demography 

of three dominant sagebrush steppe plants: Ecology, v. 92, 

p. 75–85.

Davies, G.M., Bakker, J.D., Dettweiler-Robinson, E., 

Dunwiddie, P.W., Hall, S.A., Downs, J., and Evans, J., 

2012, Trajectories of change in sagebrush steppe vegetation 

communities in relation to multiple wildfires: Ecological 

Applications, v. 22, p. 1562–1577.

Davies, K.W., 2010, Revegetation of medusahead—Invaded 

sagebrush Steppe: Rangeland Ecology & Management, 

v. 63, p. 564–571.

Defries, R.S., Foley, J.A., and Asner, G.P., 2004, Land-use 

choices: balancing human needs and ecosystem function: 

Ecology Abstracts.

Deibert, P.A., 1995, The effects of parasites on sage grouse 

(Centrocercus urophasianus) mate selection: Laramie, 

University of Wyoming, M.S. thesis. 

Delong, A.K., Crawford, J.A., and Delong, D.C., Jr., 

1995, Relationships between vegetational structure and 

predation of artificial sage grouse nests: Journal of Wildlife 

Management, v. 59, p. 88–92.

Dobkin, D.S., Rich, A.C., and Pyle, W.H., 1998, Habitat 

and avifaunal recovery from livestock grazing in a 

riparian meadow system of the northwestern Great Basin: 

Conservation Biology, v. 12, p. 209–221.

Doherty, K.E., Beck, J.L., and Naugle, D.E., 2011a, 

Comparing ecological site descriptions to habitat 

characteristics influencing Greater Sage-Grouse nest 

site occurrence and success: Rangeland Ecology & 

Management, v. 64, p. 344–351.
140 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Doherty, K.E., Naugle, D.E., Copeland, H., Pocewicz, A., and 

Kiesecker, J., 2011b, Energy development and conservation 

tradeoffs: systematic planning for Greater Sage-Grouse in 

their eastern range, in Knick S.T., and Connelly, J.W., eds., 

Greater Sage-Grouse: ecology of a landscape species and 

its habitats: Berkeley, Calif., University of California Press, 

Cooper Ornithological Society, p. 505–516.

Doherty, K.E., Naugle, D.E., and Evans, J.S., 2010a, A 

currency for offsetting energy development impacts: horsetrading sage-grouse on the open market: Plos One, v. 5, 

electronic.

Doherty, K.E., Naugle, D.E., and Walker, B.L., 2010b, Greater 

Sage-Grouse nesting habitat: the importance of managing 

at multiple scales: Journal of Wildlife Management, v. 74, 

p. 1544–1553.

Doherty, K.E., Naugle, D.E., Walker, B.L., and Graham J.M., 

2008, Greater Sage-Grouse winter habitat selection and 

energy development: Journal of Wildlife Management, 

v. 72, p. 187–195.

Doherty, K.E., Tack, J.D., Evans, J.S., and Naugle, D.E., 

2010c, Mapping breeding densities of Greater Sage-Grouse: 

atool for range-wide conservation planning: Denver, Colo., 

Bureau of Land Management.

Doherty, M.K., 2007, Mosquito populations in the Powder 

River Basin, Wyoming—A comparison of natural, 

agricultural and effluent coal bed natural gas aquatic 

habitats: Bozeman, Montana State University, M.S. thesis.

Dow AgroSciences, LLC, 1999, Spike*80 DF herbicide: 

Indianapolis, Ind., Dow AgroSciences, LLC.

Drut, M.S., 1994, Status of sage grouse with emphasis on 

populations in Oregon and Washington, 42 p.

Dunn, P.O., and Braun, C.E., 1985, Natal dispersal and lek 

fidelity of sage-grouse: Auk, v. 102, p. 621–627.

Dzialak, M.R., Olson, C.V., Harju, S.M., Webb, S.L., and 

Winstead, J.B., 2012, Temporal and hierarchical spatial 

components of animal occurrence: conserving seasonal 

habitat for greater sage-grouse: Ecosphere, v. 3, p. 1–17.

Dzialak, M.R., Webb, S.L., Harju, S.M., Winstead, J.B., 

Wondzell, J.J., Mudd, J.P., and Hayden-Wing, L.D., 

2011, The spatial pattern of demographic performance as 

a component of sustainable landscape management and 

planning: Landscape Ecology, v. 26, p. 775–790.

Ellis, K.L., 1985, Effects of a new transmission line on 

distribution and aerial predation of breeding male sage 

grouse: Final report, 28 p.

Eng, R.L., 1952, A two-summer study of the effects on bird 

populations of chlordane bait and aldrin spray as used for 

grasshopper control: Journal of Wildlife Management, v. 16, 

p. 326–337.

Eng, R.L., 1963, Observations of the breeding biology of male 

sage grouse: Journal of Wildlife Management: v. 27, p. 

841–846.

Epanchin-Niell, R., Englin, J., and Nalle, D., 2009, Investing 

in rangeland restoration in the Arid West, U.S.A.: 

countering the effects of an invasive weed on the long-term 

fire cycle: Journal of Environmental Management, v. 91, 

p. 370–379.

Erichsen-Arychuk, C., Bork, E.W., and Bailey, A.W., 2002, 

Northern dry mixed prairie responses to summer wildlife 

and drought: Journal of Range Management, v. 55, 

p. 164–170.

Fedy, B.C., Aldridge, C.L., Doherty, K.E., O’Donnell, M., 

Beck, J.L., Bedrosian, B., Holloran, M.J., Johnson, G.D., 

Kaczor, N.W., Kirol, C.P., Mandich, C.A., Marshall, D., 

McKee, G., Olson, C., Swanson, C.C., and Walker, B.L., 

2012, Interseasonal movements of greater sage-grouse, 

migratory behavior, and an assessment of the core regions 

concept in Wyoming: Journal of Wildlife Management, 

v. 76, p. 1062–1071.

Fedy, B.C. and Doherty, K.E., 2011, Population cycles are 

highly correlated over long time series and large spatial 

scales in two unrelated species: Greater Sage-Grouse and 

cottontail rabbits: Oecologia, v. 165, p. 915–924.

Fedy, B.C., Martin, K., Ritland, C., and Young, J.R., 

2008, Genetic and ecological data provide incongruent 

interpretations of population structure and dispersal 

in naturally subdivided populations of white-tailed 

ptarmigan (Lagopus leucura): Molecular Ecology, v. 17, 

p. 1905–1917.

Finch, D.M, ed., 2012, Climate change in grasslands, 

shrublands, and deserts of the interior American West: a 

review and needs assessment: Fort Collins, Colo., USDA 

Forest Service, Rocky Mountain Research Station, Gen. 

Tech. Rep. RMRS–GTR–285, 139 p.

Finch, W.I., 1996, Uranium provinces of North America—

Their definition, distribution and models: Department of 

Energy, 24 p.

Fischer, R.A., Apa, A.D., Wakkinen, W.L., and Reese, K.P., 

1993, Nesting-area fidelity of sage grouse in southeastern 

Idaho: Condor, v. 95, p. 1038–1041.

Forman, R.T.T, 2000, Estimate of the area affected 

ecologically by the road system in the United States: 

Conservation Biology, v. 14, p. 31–35.
References Cited 141

Forman, R.T.T., and Alexander, L.E., 1998, Roads and their 

major ecological effects: Annual Review of Ecology and 

Systematics, v. 29, p. 207-217.

Frankham, R., 1995, Effective population size/adult 

population size ratios in wildlife: a review: Genetical 

Research, v. 66, p. 95–107.

Friend, M.R., McLean, G., Dein, F.J., 2001, Disease 

emergence in birds—Challenges for the twenty–first 

century: The Auk, v. 118, p. 290–303.

Friggens, M.M., Warwell, M.V., Chambers, J.C., and Kitchen, 

S.G., 2012, Modeling and predicting vegetation response of 

Western USA grasslands, shrublands, and deserts to climate 

change, in Finch, D.M., ed., Climate change in grasslands, 

shrublands, and deserts of the interior American West: a 

review and needs assessment: USDA Forest Service, Rocky 

Mountain Research Station, RMRS–GTR–285, p. 1–12.

Garton, E.O., Connelly, J.W., Horne, J.S., Hagen, C.A., 

Moser, A., and Schroeder, M., 2011, Greater Sage-Grouse 

population dynamics and probability of persistence, 

in Knick, S.T., and Connelly, J.W., eds., Greater SageGrouse: ecology of a landscape species and its habitats: 

Berkeley, Calif., University of California Press, Cooper 

Ornithological Union, p. 293–381.

Gavin, S.D., and Komers, P.E., 2006, Do pronghorn 

(Antilocapra americana) perceive roads as a predation 

risk?: Canadian Journal of Zoology–Revue Canadienne 

De Zoologie 84, p. 1775–1780.

Gervais, J.A., Luukinen, B., Buhl, K., and Stone, D., 2008, 

2,4–D technical fact sheet: Oregon State University 

Extension Services.

Gibson, R.M., Bleich, V.C., McCarthy, C.W., and Russi, T.L., 

2011, Hunting lowers population size in Greater SageGrouse, in Sandercock, B.K., Martin, K., and Segelbacher, 

G., ed., Ecology, conservation and management of grouse: 

Berkeley, Calif., University of California Press, p. 307–315.

Gillies, J.A., Etyemezian, V., Kuhns, H., Nikolic, D., and 

Gillette, D.A., 2005, Effect of vehicle characteristics on 

unpaved road dust emissions: Atmospheric Environment, 

v. 39, p. 2341–2347.

Gilpin, M., and Hanski, I., 1991, Metapopulation dynamics: 

empirical and theoretical investigations: London, United 

Kingdom, Academic Press.

Gilpin, M.E., and Soule, M.E., 1986, Minimum viable 

populations: processes of species extinctions, in Soule, 

M.E., ed., Conservation biology: the science of scarcity and 

diversity: Sunderland, Mass., Sinauer Associates, p. 19–34.

Gregg, M.A., 1991, Use and selection of nesting habitat by 

sage grouse in Oregon: Corvallis, Oreg., Oregon State 

University, M.S. thesis.

Gregg, M.A., Crawford, J.A., Drut, M.S., and DeLong, A.K., 

1994, Vegetational cover and predation of sage grouse 

nests in Oregon: Journal of Wildlife Management, v. 58, 

p. 162–166.

Gregg, M.A., Dunbar, M.R., and Crawford, J.A., 2007, Use of 

implanted radiotransmitters to estimate survival of Greater 

Sage-Grouse chicks: Journal of Wildlife Management, v. 71, 

p. 646–651.

Hagen, C.A., 2010, Impacts of energy development on prairie 

grouse ecology: a research synthesis: Transactions North 

American Wildlife and Natural Resources Conference, 

v. 75, p. 96–103.

Hagen, C.A., 2011, Predation on Greater Sage-Grouse—Facts, 

process and effects, in Knick, S.T., and Connelly, J.W., eds., 

Greater Sage-Grouse: ecology of a landscape species and 

its habitats: Berkeley, Calif., University of California Press, 

Cooper Ornithological Union, p. 95–100.

Hagen, C.A., and Bildfell, R.J., 2007, An observation of 

Clostridium perfringens in Greater Sage-Grouse: Journal of 

Wildlife Diseases, v. 43, p. 545–547.

Hagen, C.A., Connelly, J.W., and Schroeder, M.A., 2007, 

A meta-analysis of Greater Sage-Grouse Centrocercus 

urophasianus nesting and brood-rearing habitats: Wildlife 

Biology, v. 13, p. 42–50.

Hagen, C.A., Willis, M.J., Glenn, E.M., and Anthony, R.G., 

2011, Habitat selection by Greater Sage-Grouse during 

winter in southeastern Oregon: Western North American 

Naturalist, v. 71, p. 529–538.

Hall, F.C., and Bryant, L., 1995, Herbaceous stubble height as 

a warning of impending cattle grazing damage to riparian 

areas: Portland, Oreg., USDA Forest Service, Pacific 

Northwest Research Station, PNW-GTR-362.

Hansen, A.J., Knight, R.L., Marzluff, J.M., Powell, S., Brown, 

K., Gude, P.H., and Jones, K., 2005, Effects of exurban 

development on biodiversity—Patterns, mechanisms 

and research needs: Ecological Applications, v. 15, 

p. 1893–1905.

Hanski, I., 1998, Metapopulation dynamics: Nature, v. 396, 

p. 41–49.

Hanski, I., and Thomas, C.D., 1994, Metapopulation dynamics 

and conservation: a spatially explicit model applied to 

butterflies: Biological Conservation, v. 68, p. 167–180.

Harju, S.M., Dzialak, M.R., Taylor, R.C., Hayden-Wing, 

L.D., and Winstead, J.B., 2010, Thresholds and time lags 

in effects of energy development on Greater Sage-Grouse 

populations: Journal of Wildlife Management, v. 74, 

p. 437–448.
142 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Hausleitner, D., 2003, Population dynamics, habitat use and 

movements of Greater Sage-Grouse in Moffat County, 

Colorado: Moscow, University of Idaho.

Hausleitner, D., Reese, K.P., and Apa, A.D., 2005, Timing 

of vegetation sampling at Greater Sage-Grouse nests: 

Rangeland Ecology & Management, v. 58, p. 553–556.

Hedrick, P.W., and Kalinowski, S.T., 2000, Inbreeding 

depression in conservation biology: Annual Review of 

Ecology and Systematics, v. 31, p. 139–162.

Hess, J.E., and Beck, J.L., 2012, Burning and mowing 

Wyoming Big Sagebrush: do treated sites meet minimum 

guidelines for Greater Sage-Grouse breeding habitats? 

Wildlife Society Bulletin, v. 36, p. 85–93.

Holechek, J., Galt, D., Joseph, J., Navarro, J., Kumalo, G., 

Molinar, F., and Thomas, M., 2003, Moderate and light 

cattle grazing effects on Chihuahuan Desert rangelands: 

Journal of Range Management, v. 56, p. 133–139.

Holechek, J.L., Pieper, R.D., and Herbel, C.H., 1989, Range 

management: principles and practices: Englewood Cliffs, 

N.J., Regents-Prentice Hall.

Holloran, M.J., 2005, Greater Sage-Grouse (Centrocercus 

urophasianus) population response to natural gas field 

development in western Wyoming: Laramie, University of 

Wyoming, M.S. Thesis.

Holloran, M.J., and Anderson, S.H., 2005, Spatial distribution 

of Greater Sage-Grouse nests in relatively contiguous 

sagebrush habitats: Condor, v. 107, p. 742–752.

Holloran, M.J., Fedy, B.C., and Dahlke, J., in press, Winter 

habitat selection of Greater Sage-Grouse relative to 

activity levels at natural gas well pads: Journal of Wildlife 

Management.

Holloran, M.J., Heath, B.J., Lyon, A.G., Slater, S.J., Kuipers, 

J.L., and Anderson, S.H., 2005, Greater Sage-Grouse 

nesting habitat selection and success in Wyoming: Journal 

of Wildlife Management, v. 69, p. 638–649.

Holloran, M.J., Kaiser, R.C., and Hubert, W.A., 2010, Yearling 

Greater Sage-Grouse response to energy development in 

Wyoming: Journal of Wildlife Management, v. 74, p. 65–72.

Honess, R.F., and Post, G., 1968, History of an epizootic in 

sage grouse: University of Wyoming Agricultural Extension 

Station, Science Monograph, v. 14, 32 p.

Hornaday, W.T., 1916, Save the sage grouse from 

extinction—A demand from civilization to the Western 

States: New York Zoological Park Bulletin, v. 5, 

p. 179–219.

Huebner, C.D., 2010, Spread of an invasive grass in closedcanopy deciduous forests across local and regional 

environmental gradients: Biological Invasions, v. 12, 

p. 2081–2089.

Hull, S.D., Robel, R.J., and Kemp, K.E., 1996, Summer avian 

abundance, invertebrate biomass, and forbs in Kansas CRP: 

Prairie Naturalist, v. 28, p. 1–12.

Hupp, J.W., and Braun, C.E., 1991, Geographic variation 

among sage-grouse in Colorado: Wilson Bulletin, v. 103, 

p. 255–261.

Hupp, J.W., and Braun, C.E., 1989, Topographic distribution 

of sage grouse foraging in winter: Journal of Wildlife 

Management, v. 53, p. 823–829.

Idaho Sage-Grouse Advisory Committee, 2006, Conservation 

plan for the Greater Sage-Grouse in Idaho.

Idaho Sage-Grouse Advisory Committee Technical Assistance 

Team, 2012, Idaho sage–grouse local working groups 

Statewide annual report 2011.

Idaho Sage-Grouse Task Force, 2012, Idaho Governor’s SageGrouse Task Force recommendations.

INL Campus Development Office and North Wind, Inc., 

2011, Idaho National Laboratory comprehensive land use 

and environmental stewardship report: Idaho Falls, Idaho 

National Laboratory, unpublished Federal report.

Interagency MOU, 2009, Memorandum of understanding 

Among Bureau of Land Management (Colorado State 

Office), U.S. Forest Service (United States Forest Service, 

Rocky Mountain Region), and Colorado Oil and Gas 

Conservation Commission Concerning Oil and Gas 

Permitting on BLM and NFS Lands in Colorado. 

IPCC, 2007, An assessment of the Intergovernmental Panel 

on Climate Change: Intergovernmental Panel on Climate 

Change.

Jamison, B.E., Robel, R.J., Pontius, J.S., and Applegate, 

R.D., 2002, Invertebrate biomass: associations with lesser 

prairie-chicken habitat use and sand sagebrush density 

in southwestern Kansas: Wildlife Society Bulletin, v. 30, 

p. 517–526.

Jensen, B.M., 2006, Migration, transition range and landscape 

use by Greater Sage-Grouse (Centrocercus urophasianus): 

Laramie, University of Wyoming.

Jimenez, J.A., Hughes, K.A., Alaks, G., Graham, L., and Lacy, 

R.C., 1994, An experimental study of inbreeding depression 

in a natural habitat: Science, v. 266, p. 271–273.

Johnsgard, P.A., 1983, The grouse of the world: Lincoln, 

University of Nebraska Press, 411 p.
References Cited 143

Johnson, D.J., Holloran, M.J., Connelly, J.W., Hanser, S.E., 

Amundson, C.L., and Knick, S.T., 2011, Influences of 

environmental and anthropogenic features on Greater 

Sage-Grouse population, 1997–2007, in Knick, S.T., and 

Connelly, J.W., eds., Studies in avian biology: Berkeley, 

Calif., University of California Press, Cooper Ornithological 

Union, p. 407–450.

Johnson, G.D., and Boyce, M.S., 1991, Survival, growth 

and reproduction of captive- reared sage grouse: Wildlife 

Society Bulletin, v. 19, p. 88–93.

Johnson, J.A., and Dunn, P.O., 2006, Low genetic variation 

in the heath hen prior to extinction and implications for the 

conservation of prairie-chicken populations: Conservation 

Genetics, v. 7, p. 37–48.

Kahn, N.W., Braun, C.E., Young, J.R., Wood, S., Mata, D.R., 

and Quinn, T.W., 1999, Molecular analysis of genetic 

variation among large- and small-bodied sage grouse using 

mitochondrial control-region sequences: Auk, v. 116, 

p. 819–824.

Keane, R.E., Agee, J.K., Fule, P., Keeley, J.E., Key, C., 

Kitchen, S.G., Miller, R., and Schulte, L.A., 2008, 

Ecological effects of large fires on US landscapes: benefit or 

catastrophe?: International Journal of Wildland Fire, v. 17, 

p. 696–712.

Keller, L.F., Arcese, P., Smith, J.N.M., Hochachka, W.M., and 

Stearns, S.C., 1994, Selection against inbred song sparrows 

during a natural population bottleneck: Nature, v. 372, 

p. 356–357.

Keller, L.F., and Waller, D.M., 2002, Inbreeding effects in 

wild populations: Trends in Ecology & Evolution, v. 17, 

p. 230–241.

Kirol, C.P., 2012, Quantifying habitat importance for 

Greater Sage-Grouse population persistence in an energy 

development landscape: Laramie, University of Wyoming, 

M.S. thesis.

Kirol, C.P., Beck, J.L., Dinkins, J.B., and Conover, M.R., 

2012, Microhabitat selection for nesting and brood-rearing 

by the Greater Sage-Grouse in xeric big sagebrush: Condor, 

v. 114, p. 75–89.

Klebenow, D.A., 1970, Sage grouse versus sagebrush control 

in Idaho [Herbicides]: Journal of Range Management, v. 23, 

p. 396–400.

Klebenow, D.A., and Gray, G.M., 1968, Food habits of 

juvenile sage grouse: Journal of Range Management, 21, 

p. 80–83.

Klemmedson, J.O., and Smith, J.G., 1964, Cheatgrass (Bromus 

tectorum L.): Botanical Review, v. 30, p. 226–262.

Knapp, P.A., 1996, Cheatgrass (Bromus tectorum L.) 

dominance in the Great Basin Desert—History, persistence, 

and influences to human activities: Global Environmental 

Change—Human and Policy Dimensions, v.6, p. 37–52.

Knick, S.T., 2011, Historical development, principal Federal 

legislation and current management of sagebrush habitats 

implications for conservation, in Knick, S.T., and Connelly, 

J.W., eds., Greater Sage-Grouse: ecology of a landscape 

species and its habitats: Berkeley, Calif., University of 

California Press, Cooper Ornithological Society, p. 13–32.

Knick, S.T., and Connelly, JW., 2011a, Greater Sage-Grouse 

and sagebrush—Introduction to the landscape, in Knick, 

S.T., and Connelly, J.W., eds., GreaterSage-Grouse: ecology 

and conservation of a landscape species and its habitats: 

Berkeley, Calif., University of California Press, Cooper 

Ornithological Society, p. 1–9.

Knick, S.T., and Connelly, J.W., eds., 2011b, Greater SageGrouse: ecology and conservation of a landscape species 

and its habitats: Berkeley, Calif., University of California 

Press, Cooper Ornithological Union Studies in Avian 

Biology no. 38.

Knick, S.T., Dobkin, D.S., Rotenberry, J.T., Schroeder, M.A., 

Vander Haegen, W.M., and Van Riper, C., III., 2003, 

Teetering on the edge or too late? Conservation and research 

issues for avifauna of sagebrush habitats: Condor, v. 105, 

p. 611–634.

Knick, S.T., and Hanser, S.E., 2011, Connecting pattern and 

process in Greater Sage-Grouse populations and sagebrush 

landscapes, in Knick S.T., and Connelly, J.W., eds., Greater 

Sage-Grouse: ecology of a landscape species and its 

habitats: Berkeley, Calif., University of California Press, 

Cooper Ornithological Union, p. 383–406.

Knick, S.T., Hanser, S.E., Miller, R.F., Pyke, DA., Wisdom, 

M.J., Finn, S.P., Rinkes, E.T., and Henny, C.J., 2011, 

Ecological influence and pathways of land use in sagebrush, 

in Knick, S.T., and Connelly, J.W., eds., Greater SageGrouse: ecology of a landscape species and its habitats: 

Berkeley, Calif., University of California Press, Cooper 

Ornithological Union, p. 203–252.

Knight, R.L., Knight, H.A.L., and Camp, R.J., 1993, Raven 

populations and land-use patterns in the Mojave Desert, 

California: Wildlife Society Bulletin, v. 21, p. 469–471.

Kolada, E.J., Sedinger, J.S., and Casazza, M.L., 2009, Nest 

site selection by Greater Sage-Grouse in Mono County, 

California: Journal of Wildlife Management, v. 73, 

p. 1333–1340.

Kuipers, J.L., 2004, Grazing system and linear corridor 

influences on Greater Sage-Grouse (Centrocercus 

urophasianus) habitat selection and productivity: Laramie, 

University of Wyoming, M.S. thesis. 
144 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Lacy, R.C., 1997, Importance of genetic variation to 

the viability of mammalian populations: Journal of 

Mammalogy, v. 78, p. 320–325.

Lacy, R.C., Alaks, G., and Walsh, A., 1996, Hierarchical 

analysis of inbreeding depression in Peromyscus polionotus: 

Evolution, v. 50, p. 2187–2200.

Larson, T.A., 1978, History of Wyoming (3rd ed.): Lincoln, 

Nebr., Univerisity of Nebraska Press.

Laycock, W.A., 1978, Factors affecting choice of management 

strategies within the sagebrush ecosystem United States, 

Artemisia tridentata, in The sagebrush ecosystem: a 

symposium: Logan, Utah State University, College of 

Natural Resources, p. 230–236.

LeBeau, C.W., 2012, Evaluation of Greater Sage-Grouse 

reproductive habitat and response to wind energy 

development in south-central, Wyoming: Laramie, 

University of Wyoming, M.S. thesis.

Lee, C.H., Shih, C.A., Chien, C.C., Fang, S.S., Lin, L.L., and 

Lin, M.D., 2007, Estimation of fugitive dust emission factor 

for truck moving on dredging road: Journal of the Chinese 

Institute of Civil and Hydraulic Engineering, v. 19, p. 467.

Leonard, K.M., Reese, K.P. and Connelly, J.W., 2000, 

Distribution, movements and habitats of sage grouse, 

Centrocercus urophasianus, on the Upper Snake River Plain 

of Idaho: changes from the 1950s to the 1990s: Wildlife 

Biology, v. 6, p. 265–270.

Lesica, P., Cooper, S.V., and Kudray, G., 2007, Recovery 

of big sagebrush following fire in southwest Montana: 

Rangeland Ecology & Management, v. 60, p. 261–269.

Leu, M., and Hanser, S.E., 2011, Influences of the human 

footprint on sagebrush landscape patterns, in Knick, S.T., 

and Connelly, J.W., eds., Greater Sage-Grouse: ecology 

of a landscape species and its habitats: Berkeley, Calif., 

University of California Press, Cooper Ornithological 

Union, p. 253–271.

Leu, M., Hanser, S.E., and Knick, S.T., 2008, The 

human footprint in the west—A large scale analysis of 

anthropogenic impacts: Ecological Applications, v. 18, 

p. 1119–1139.

Lowe, B.S., Delehanty, D.J., and Connelly, J.W., 2009, Greater 

Sage-Grouse Centrocercus urophasianus use of threetip 

sagebrush relative to big sagebrush in south-central Idaho: 

Wildlife Biology, v. 15, p. 229–236.

Lyon, A.G., and Anderson, S.H., 2003, Potential gas 

development impacts on sage grouse nest initiation and 

movement: Wildlife Society Bulletin, v. 31, p. 486–491.

Manier, D.J., and Hobbs, N.T., 2007, Large herbivores in 

sagebrush steppe ecosystems: livestock and wild ungulates 

influence structure and function: Oecologia, v. 152, 

p. 739–750.

Manier, D.J., Hobbs, N.T., Theobald, D.M., Reich, R.M., 

Kalkhan, M.A., and Campbell, M.R., 2005, Canopy 

dynamics and human caused disturbance on a semi-arid 

landscape in the Rocky Mountains, U.S.A.: Landscape 

Ecology, v. 20, p. 1–17.

Manville, A.M., 2002, Bird strikes and electrocutions at 

power lines, communication towers and wind turbines––

State of the art and state of the science—next steps toward 

mitigation, 28 p.

Marra, P.P., Griffing, S., Caffrey, C., Kilpatrick, A.M., 

McLean, R., Brand, C., Saito, E., Dupuis, A.P., Kramer, 

L., and Novak, R., 2004, West Nile virus and wildlife: 

BioScience, v. 54, p. 393–402.

McLean, R.G., 2006, West Nile virus in North American birds: 

Ornithological Monographs, v. 60, p. 44–64.

Meinke, C.W., Knick, S.T., and Pyke, D.A., 2009, A 

spatial model to prioritize sagebrush landscapes in the 

Intermountain West (U.S.A.) for restoration: Restoration 

Ecology, v. 17, p. 652–659.

Mensing, S., Livingston, S., and Barker, P., 2006, Longterm fire history in Great Basin sagebrush reconstructed 

from macroscopic charcoal in spring sediments, Newark 

Valley, Nevada: Western North American Naturalist, v. 66, 

p. 64–77.

Mezquida, E.T., Slater, S.J., and Benkman, C.W., 2006, Sagegrouse and indirect interactions: Potential implications of 

coyote control on sage-grouse populations: Condor, v. 108, 

p. 747–759.

Miller, M.E., 2008, Broad-scale assessment of rangeland 

health, Grand Staircase-Escalante National Monument, 

U.S.A.: Rangeland Ecology & Management, v. 61, 

p. 249–262.

Miller, R.F., 2001, Pre- and post-settlement fire regimes in 

mountain big sagebrush steppe and aspen, the northwestern 

Great Basin: Final report 2001 to the National Interagency 

Fire Center.

Miller, R.F., and Eddleman, L.L., 2000, Spatial and temporal 

changes of sage grouse habitat in the sagebrush biome: 

Corvallis, Oregon State University Agricultural Experiment 

Station.

Miller, R.F., and Heyerdahl, E.K., 2008, Fine-scale variation 

of historical fire regimes in sagebrush-steppe and 

juniper woodland: an example from California, U.S.A.: 

International Journal of Wildland Fire, v. 17, p. 245–254.
References Cited 145

Miller, R.F., Knick, S.T., Pyke, D.A., Meinke, C.W., Hanser, 

S.E., Wisdom, M.J. and Hild, A.L., 2011, Characteristics 

of sagebrush habitats and limitations to long-term 

conservation, in Knick, S.T., and Connelly, J.W., eds., 

Greater Sage-Grouse: ecology of a landscape species and 

its habitats: Berkeley, Calif., University of California Press, 

Cooper Ornithological Union, p. 145–184.

Miller, R.F., and Rose, J.A., 1995, Historic expansion of 

Juniperus occidentalis (Western juniper) in southeastern 

Oregon: Great Basin Naturalist, v. 55, p. 37–45.

Miller, R.F., Svejcar, T.J., and Rose, J.A., 2000, Impacts 

of western juniper on plant community composition and 

structure: Journal of Range Management, v. 53, p. 574–585.

Miller, R.F., Svejcar, T.J., and West, N.E., 1994, Implications 

of livestock grazing in the intermountain sagebrush 

region—Plant composition, in Vavra, M., Laycock, W.A., 

and Pieper, R.D., eds., Ecological implications of livestock 

herbivory in the west, p. 101–146.

Montana Department of Natural Resources & Conservation 

Trust Land Management Division, 2007, Sage grouse 

mitigation for oil & gas operations on State school 

trust lands: Montana Department of Natural Resources 

& Conservation Trust Land Management Division, 

unpublished report on file in Montana State office.

Montana Sage Grouse Work Group, 2005, Management plan 

and conservation strategies for sage grouse in Montana—

Final: Montana Fish, Wildlife & Parks.

Mooney, H.A., and Cleland, E.E., 2001, The evolutionary 

impact of invasive species: Proceedings of the National 

Academy of Science, v. 98, p. 5446–5451.

Moynahan, B.J., Lindberg, M.S., Rotella, J.J., and Thomas, 

J.W., 2007, Factors affecting nest survival of Greater 

Sage-Grouse in northcentral Montana: Journal of Wildlife 

Management, v. 71, p. 1773–1783.

Moynahan, B.J., Lindberg, M.S., and Thomas, J.W., 2006, 

Factors contributing to process variance in annual survival 

of female Greater Sage-Grouse in Montana: Ecological 

Applications, v. 16, p. 1529–1538.

Mueggler, W.F., 1950, Effects of spring and fall grazing by 

sheep on vegetation of the upper snake river plains: Journal 

of Range Management, v. 3, p. 308–315.

Natural Resources Conservation Service, 2011, Introduction 

to NRCS’ new sage-grouse initiative: wildlife conservation 

through sustainable ranching: Washington, D.C., 

Department of Agriculture. 

Naugle, D.E., Aldridge, C.L., Walker, B.L., Cornish, T.E., 

Moynahan, B.J., Holloran, M.J., Brown, K., Johnson, G.D., 

Schmidtmann, E.T., Mayer, R.T., Kato, C.Y., Matchett, 

M.R., Christiansen, T.J., Cook, W.E., Creekmore, T., Falise, 

R.D., Rinkes, E.T., and Boyce, M.S., 2004, West Nile 

virus—Pending crisis for Greater Sage-Grouse: Ecology 

Letters, v. 7, p. 704–713.

Naugle, D.E., Aldridge, C.L., Walker, B.L., Doherty, K.E., 

Matchett, M.R., McIntosh, J., Cornish, T.E., and Boyce, 

M.S., 2005, West Nile virus and sage-grouse—What 

more have we learned?: Wildlife Society Bulletin, v. 33, 

p. 616–623.

Naugle, D.E., Doherty, K.E., Walker, B.L., Holloran, M.J., 

and Copeland, H.E., 2011, Energy development and Greater 

Sage-Grouse, in Knick, S.T., and Connelly, J.W., eds., 

Greater Sage-Grouse: ecology of a landscape species and 

its habitats: Berkeley, Calif., University of California Press, 

Cooper Ornithological Union, p. 489–504.

Neel, L.A., 1980, Sage grouse response to grazing 

management in Nevada: Reno, University of Nevada, 

M.S. thesis.

Neilson, R.P., Lenihan, J.M., Buchelet, D., and Drapek, 

R.J., 2005, Climate change implication for sagebrush 

ecosystems: North American Wildlife and Natural 

Resources, 70th Conference, Transactions of Wildlife 

Management Institute, Arlington, Va., p. 145–159.

Nelle, P.J., Reese, K.P., and Connelly, J.W., 2000, Long-term 

effects of fire on sage grouse habitat: Journal of Range 

Management, v. 53, p. 586–591.

Nevada Department of Wildlife, 2011, NDOW actions to 

avoid ESA listing of Greater Sage-Grouse: Nevada Board of 

Wildlife Commissioners Meeting Procedings. 

Nevada Department of Wildlife, 2012, Greater Sage-Grouse 

habitat categorization: Reno, Nevada Department of 

Wildlife, unpublished report.

Nevada Executive Order, Mar. 30, 2012, Establishing a 

Greater Sage-Grouse advisory committee: Reno, Nev., 

Governor’s Office, State of Nevada, No. 2012–09. 

Nevada Greater Sage-Grouse Advisory Committee, 2012, 

Strategic plan for conservation of sage-grouse in Nevada: 

Reno, Nevada Greater Sage-Grouse Advisory Committee, 

unpublished report.

Nevada Sage-Grouse Conservation Team, 2004, Greater 

Sage-Grouse conservation plan for Nevada and eastern 

California: Reno, Nevada Sage-Grouse Conservation Team, 

unpublished report.
146 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Norrdahl, K., and Korpimaki, E., 2000, Do predators limit 

the abundance of alternative prey? Experiments with 

vole-eating avian and mammalian predators: Oikos, v. 91, 

p. 528–540.

Oregon Department of Fish and Wildlife, 2011, Greater SageGrouse conservation assessment and strategy for Oregon: 

a plan to maintain and enhance populations and habitat: 

Oregon Department of Fish and Wildlife.

Ouren, D.S., Hass, C., Melcher, C.P., Stewart, P., Ponds, D., 

Sexton, N.R., Burris, L. Fancher, T., and Bowen, Z.H., 

2007, Environmental effects of off-highway vehicles on 

Bureau of Land Management lands: a literature synthesis, 

annotated bibliographies, and internet resources: Reston, 

Va., U.S. Geological Survey.

Owens, M.K., and Norton, B.E., 1990, Survival of juvenile 

basin sagebrush under different grazing regimes: Journal of 

Range Management, v. 43, p. 132–135.

Oyler-McCance, S.J., Burnham, K.P., and Braun, C.E., 2001, 

Influence of changes in sagebrush on Gunnison sage grouse 

in southwestern Colorado: Southwestern Naturalist, v. 46, 

p. 323–331.

Oyler-McCance, S.J., Kahn, N.W., Burnham, K.P., Braun, 

C.E., and Quinn, T.W., 1999, A population genetic 

comparison of large- and small-bodied sage grouse in 

Colorado using microsatellite and mitochondrial DNA 

markers: Molecular Ecology, v. 8, p. 1457–1465.

Oyler-McCance, S.J., St. John, J., Taylor, S.E., Apa, A.D., and 

Quinn, T.W., 2005a, Population genetics of Gunnison sagegrouse: implications for management: Journal of Wildlife 

Management, v. 69, p. 630–637.

Oyler-McCance, S.J., Taylor, S.E., and Quinn, T.W., 2005b, 

A multilocus population genetic survey of the Greater 

Sage-Grouse across their range: Molecular Ecology, v. 14, 

p. 1293–1310.

Padgett, P.E., Meadows, D., Eubanks, E., and Ryan, W.E., 

2008, Monitoring fugitive dust emissions from off-highway 

vehicles traveling on unpaved roads and trails using passive 

samplers: Environmental Monitoring and Assessment, 

v. 144, p. 93–99.

Parker, R.R., Philip, C.B., and Davis, G.E., 1932, Tularaemia 

occurrence in the sage hen, Centrocercus urophasianus: 

Public Health Reports, v. 47, p. 479–487.

Patterson, R.L., 1952, The sage grouse in Wyoming: Denver, 

Colo., Sage Books, Inc., Wyoming Game and Fish 

Commission, 344 p.

Petersen, S.L., Stringham, T.K., and Roundy, B.A., 2009, A 

process-based application of State-and-transition models: 

a case study of Western Juniper (Juniperus occidentalis) 

encroachment: Rangeland Ecology & Management, v. 62, 

p. 186–192.

Peterson, M.J., 2004, Parisites and infectious diseases of 

prairie grouse: should managers be concerned?: Wildlife 

Society Bulletin, v. 32, p. 35–55.

Pickett, S.T.A., and White, P.S., 1985, Patch dynamics: a 

synthesis, in Pickett, S.T.A., and White, P.S., The ecology of 

natural disturbance and patch dynamics: San Diego, Calif., 

Academic Press, p. 371–384.

Piertney, S.B., MacColl, A.D.C., Bacon, P.J. ,and Dallas, 

J.F., 1998, Local genetic structure in red grouse (Lagopus 

lagopus scoticus): evidence from microsatellite DNA 

markers: Molecular Ecology, v. 7, p. 1645–1654.

Ponzetti, J.M., McCune, B., and Pyke, D.A., 2007, Biotic 

soil crusts in relation to topography, cheatgrass and fire 

in the Columbia Basin, Washington: Bryologist, v. 110, 

p. 706–722.

Poulin, J.F., and Villard, M.A., 2011, Edge effect and matrix 

influence on the nest survival of an old forest specialist, the 

Brown Creeper (Certhia americana): Landscape Ecology, 

v. 26, p. 911–922.

Provencher, L., Forbis, T.A., Frid, L., and Medlyn, G., 

2007, Comparing alternative management strategies of 

fire, grazing, and weed control using spatial modeling: 

Ecological Modelling, v. 209, p. 249–263.

Pyke, D.A., 2011, Restoring and rehabilitating sagebrush 

habitats, in Knick, S.T., and Connelly, J.W., eds., Greater 

Sage-Grouse: ecology of a landscape species and its 

habitats: Berkeley, Calif., University of California Press, 

Cooper Ornithological Union, p. 531–548.

Rau, B.M., Johnson, D.W., Blank, R.R., Tausch, R.J., Roundy, 

B.A., Miller, R.F., Caldwell, T.G., and Lucchesi, A., 2011, 

Woodland expansion’s influence on belowground carbon 

and nitrogen in the Great Basin U.S.: Journal of Arid 

Environments, v. 75, p. 827–835.

Reed, D.H., and Bryant, E.H., 2000, Experimental tests of 

minimum viable population size: Animal Conservation, v. 3, 

p. 7–14.

Reed, D.H., and Frankham, R., 2003, Correlation between 

fitness and genetic diversity: Conservation Biology, v. 17, 

p. 230–237.

Reese, K.P., and Connelly, J.W., 1997, Translocations of 

sage grouse Centrocercus urophasianus in North America: 

Wildlife Biology, v. 3, p. 235–241.
References Cited 147

Reese, K.P., and Connelly, J.W., 2011, Harvest management 

for Greater Sage-Grouse, in Knick, S.T., and Connelly, J.W., 

eds., Greater Sage-Grouse: ecology of a landscape species 

and its habitats: Berkeley, Calif., University of California 

Press, Cooper Ornithological Union, p. 101–112.

Reisen, W.K., Fang, Y., and Martinez, V.M., 2006, Effects 

of temperature on the transmission of West Nile virus by 

Culex tarsalis (Diptera–Culicidae): Journal of Medical 

Entomology, v. 43, p. 309–317.

Remington, T.E., and Braun, C.E., 1991, How surface coal 

mining affects sage grouse, North Park, Colorado: Colorado 

Division of Wildlife, unpublished report.

Rhodes, E.C., Bates, J.D., Sharp, R.N., and Davies, K.W., 

2010, Fire effects on cover and dietary resources of sagegrouse habitat: Journal of Wildlife Management, v. 74, 

p. 755–764.

Ritchie, M.E., and Tilman, D., 1992, Interspecific competition 

among grasshoppers and their effect on plant abundance 

in experimental field environments: Oecologia, v. 89, 

p. 524–532.

Romme, W.H., Allen, C.D., Balley, J.D., Baker, W.L., 

Bestelmeyer, B.T., Brown, P.M., Eisenhart, K.S., Floyd, 

M.L., Huffman, D.W., Jacobs, B.F., Miller, R.F., Muldavin, 

E.H., Swetnam, T.W., Tausch, R.J. ,and Weisberg, P.J., 

2009, Historical and modern disturbance regimes, stand 

structures, and landscape dynamics in pinon-juniper 

vegetation of the Western United States: Rangeland Ecology 

& Management, v. 62, p. 203–222.

Root, H.T., and McCune, B., 2012, Regional patterns of 

biological soil crust lichen species composition related to 

vegetation, soils, and climate in Oregon, U.S.A.: Journal of 

Arid Environments, v. 79, p. 93–100.

Rowland, M.M., Leu, M., Hanser, S., Finn, S.P., Aldridge, 

C.L., Knick, S.T., Suring, L.H., Boyd, J.M., Wisdom, M.J., 

and Meinke, C.W., 2006, Assessment of threats to sagebrush 

habitats and associated species of concern in the Wyoming 

basins: Boise, Idaho, U.S. Geological Survey, unpublished 

report on file.

Rowland, M.M., Suring, L.H., and Wisdom, M.J., 2010, 

Assessment of habitat threats to shrublands in the Great 

Basin: a case study, in Pye, J.M., Rauscher, H.M., Sands, 

Y., Lee, D.C., and Beatty, J.S., eds., Environmental 

threat assessment and application to forest and rangeland 

management: USDA Forest Service, General Technical 

Report, PNW-GTR-802, p. 673–685.

Sankey, T.T., and Germino, M.J., 2008, Assessment of 

juniper encroachment with the use of satellite imagery and 

geospatial data: Rangeland Ecology & Management, v. 61, 

p. 412–418.

Saunders, D.A., Hobbs, R.J., and Margules, C.R., 1991, 

Biological consequences of fragmentation: a review: 

Conservation Biology, v. 5, p. 18–32

Scherber, C., Heimann, J., Kohler, G., Mitschunas, N., and 

Weisser, W.W., 2010, Functional identity versus species 

richness: herbivory resistance in plant communities: 

Oecologia, v. 163, p. 707–717.

Schlaepfer, D.R., Lauenroth, W.K., and Bradford, J.B., 2012, 

Effects of ecohydrological variables on current and future 

ranges, local suitability patterns, and model accuracy in big 

sagebrush: Ecography, v. 35, p. 374–384.

Schroeder, M.A., 1997, Unusually high reproductive effort 

by sage grouse in a fragmented habitat in north-central 

Washington: Condor, v. 99, p. 933–941.

Schroeder, M.A., 2008, Variation in Greater Sage-Grouse 

morphology by region and population: U.S. Fish and 

Wildlife Service, unpublished report, 19 p.

Schroeder, M.A., Aldridge, C.L., Apa, A.D., Bohne, J.R., 

Braun, C.E., Bunnell, S.D., Connelly, J.W., Deibert, P.A., 

Gardner, S.C., Hilliard, M.A., Kobriger, G.D., McAdam, 

S.M., McCarthy, C.W., McCarthy, J.J., Mitchell, D.L., 

Rickerson, E.V., and Stiver, S.J., 2004, Distribution of sagegrouse in North America: Condor, v. 106, p. 363–376.

Schroeder, M.A., and Baydack, R.K., 2001, Predation and the 

management of prairie grouse: Wildlife Society Bulletin, 

v. 29, p. 24–32.

Schroeder, M.A., and Robb, L.A., 2003, Fidelity of Greater 

Sage-Grouse Centrocercus urophasianus to breeding 

areas in a fragmented landscape: Wildlife Biology, v. 9, 

p. 291–299.

Schroeder, M.A., and Vander Haegen, W.M., 2006, Use of 

conservation reserve program fields by Greater Sage-Grouse 

and other shrub steppe-associated wildlife in Washington 

State: Olympia, Wash., Washington Department of Fish and 

Wildlife, Wildlife Program.

Schroeder, M.A., and Vander Haegen, W.M., 2011, Response 

of GreaterSage-Grouse to the conservation reserve program 

in Washington State, in Knick, S.T., and Connelly, J.W., 

eds., Greater Sage-Grouse: ecology of a landscape species 

and its habitats: Berkeley, Calif., University of California 

Press, Cooper Ornithological Union, p. 517–530.

Schroeder, M.A., Young, J.R., and Braun, C.E., 1999, Sage 

grouse (Centrocercus urophasianus), in Poole A.W., and 

Gill, F.,eds., The birds of North America, no.425: Ithaca, 

N.Y., p. 28.

Scott, J.W., 1940, The role of coccidia as parasites of wildlife: 

Journal of the Colorado-Wyoming Academy of Science, 

v. 2, p. 45.
148 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Sedinger, B.S., Sedinger, J.S., Espinosa, S., Atamian, M.T., 

and Blomberg, E.J., 2011, Spatial-temporal variation in 

survival of harvested Greater Sage-Grouse, in Sandercock, 

B.K., Martin, K., and Segelbacher, G., eds., Ecology, 

conservation and management of grouse: Berkeley, Calif., 

University of California Press, p 317–328.

Sedinger, J.S., White, G.C., Espinosa, S., Partee, E.T., and 

Braun, C.E., 2010, Assessing compensatory versus additive 

harvest mortality: An example using Greater Sage-Grouse: 

Journal of Wildlife Management, v. 74, no. 2, p. 326–332.

Shaw, R.B., and Diersing, V.E., 1990, Tracked vehicle 

impacts on vegetation at the Pinon Canyon Maneuver 

Site, Colorado: Journal of Environmental Quality, v. 19, 

p. 234–243.

Shinneman, D.J., and Baker, W.L., 2009, Environmental and 

climatic variables as potential drivers of post-fire cover 

of cheatgrass (Bromus tectorum) in seeded and unseeded 

semiarid ecosystems: International Journal of Wildland Fire, 

v. 18, p. 191–202.

Shinneman, D.J., Baker, W.L., and Lyon, P., 2008, Ecological 

restoration needs derived from reference conditions for a 

semi-arid landscape in western Colorado, U.S.A.: Journal of 

Arid Environments, v. 72, p. 207–227.

Simberloff, D., 1988, The contribution of population and 

community biology to conservation science: Annual Review 

of Ecology and Systematics, v. 19, p. 473–511.

Slater, S.J., 2003, Sage-grouse (Centrocercus urophasianus) 

use of different-aged burns and the effects of coyote 

control in southwestern Wyoming: Laramie, University of 

Wyoming.

Smith, J.T., Flake, L.D., Higgins, K.F., Kobriger, G.D., and 

Homer, C.G., 2005, Evaluating lek occupancy of Greater 

Sage-Grouse in relation to landscape cultivation in the 

Dakotas: Western North American Naturalist, v. 65, 

p. 310–320.

Smith, R.E., 2013, Conserving Montana’s sagebrush 

highway: long distance migration in sage-grouse: Missoula, 

University of Montana, Department of Wildlife Biology, 

M.S. thesis. 

Sovada, M.A., Sargeant, A.B., and Grier, J.W., 1995, 

Differential effects of coyotes and red foxes on duck nest 

success: Journal of Wildlife Management, v. 59, p. 1–9.

State of Wyoming, 2011, Greater Sage-Grouse core area 

protection: Casper, State of Wyoming.

Steenhof, K., Kochert, M.N., and Roppe, J.A., 1993, Nesting 

by raptors and common ravens on electrical transmission 

line towers: Journal of Wildlife Management, v. 57, 

p. 271–281.

Stevens, B.S., 2011, Impacts of fences on Greater SageGrouse in Idaho: collision, mitigation, and spatial ecology: 

Moscow, University of Idaho, M.S. thesis.

Stevens, B.S., Reese, K.P., and Connelly, J.W., 2011, Survival 

and detectability bias of avian fence collision surveys in 

sagebrush steppe: Journal of Wildlife Management, v. 75, 

p. 437–449.

Stevens, B.S., Reese, K.P., Connelly, J.W., and Musil, D.D., 

2012, Greater Sage-Grouse and fences: does marking 

reduce collisions?: Wildlife Society Bulletin, v. 36, 

p. 297–303.

Stiver, S.J., 2011, The legal status of Greater Sage-Grouse: 

organizational structure of planning efforts, in Knick, S.T., 

and Connelly, J.W., eds., Greater Sage-Grouse: ecology 

of a landscape species and its habitats: Berkeley, Calif., 

University of California Press, Cooper Ornithological 

Union, p. 33–49.

Stiver, S.J., Apa, A.D., Bohne, J., Bunnell, S.D., Deibert, 

P.A., Gardner, S.C., Hilliard, M.A., McCarthy, C.W., 

and Schroeder, M.A., 2006, Greater Sage-Grouse: 

comprehensive conservation strategy: Cheyenne, Wyo., 

Western Association of Fish and Wildlife Agencies 

(WAFWA).

Stiver, S.J., Rinkes, E.T., and Naugle, D.E., 2010, Sagegrouse habitat assessment framework: multiscale habitat 

assessment tool: Boise, Idaho, U.S. Bureau of Land 

Management Report, Idaho State Office, 135 p.

Strand, E.K., Robinson, A.P., and Bunting, S.C., 2007, Spatial 

patterns on the sagebrush steppe/Western juniper ecotone: 

Plant Ecology, v. 190, no. 2, p.159–173.

Strickland, M.D., Harju, H.J., McCaffery, K.R., Miller, H.W., 

Smith, L.M., and Stoll, R.J., 1994, Harvest management, in

Bookhout, T.A. ,ed., Research and management techniques 

for wildlife and habitats: Bethesda, Md., The Wildlife 

Society, p. 445–473.

Suter Ii, G.W., 1978, Effects of geothermal energy 

development on fish and wildlife: Topical briefs, Fish and 

Wildlife resources and electrical power generation FWS/

OBS–76/206, 26 p.

Sveum, C.M., Crawford, J.A., and Edge, W.D., 1998a, Use 

and selection of brood-rearing habitat by sage grouse in 

south-central Washington: Great Basin Naturalist, v. 58, 

p. 344–351.

Sveum, C.M., Edge, W.D., and Crawford, J.A., 1998b, 

Nesting habitat selection by sage grouse in south-central 

Washington: Journal of Range Management, v. 51, 

p. 265–269.
References Cited 149

Swenson, J.E., Simmons, C.A., and Eustace, C.D., 1987, 

Decrease of sage grouse Centrocerus urophasianus after 

ploughing of sagebrush steppe: Biological Conservation, 

v. 41, p. 125–132.

Tack, J.D., 2009, Sage-grouse and the human footprint: 

implications for conservation of small and declining 

populations: Missoula, University of Montana.

Tack, J.D., Naugle, D.E., Carlson, J.C., and Fargey, P.J., 

2012, Greater Sage-Grouse Centrocercus urophasianus

migration links the U.S.A. and Canada: a biological basis 

for international prairie conservation: Oryx, v. 46, p. 64–68.

Taylor, R.L., Walker, B.L., Naugle, D.E., and Mills, L.S., 

2012, Managing multiple vital rates to maximize Greater 

Sage-Grouse population growth: Journal of Wildlife 

Management, v. 76, p. 336–347.

Taylor, S.E., and Young, J.R., 2006, A comparative behavioral 

study of three Greater Sage-Grouse populations: The Wilson 

Journal of Ornithology, v. 118, p. 36–41.

Tewalt, S.J., Kinney, S.A., and Merrill, M.D., 2008, GIS 

representation of coal-bearing areas in North, Central, and 

South America: U.S. Geological Survey Open-File Report 

2008–1257, available at http://pubs.usgs.gov/of/2008/1257/.

Thompson, T.R., 2012, Dispersal ecology of Greater 

Sage-Grouse in northwestern Colorado: evidence from 

demographic and genetic methods: Moscow, University of 

Idaho, Ph.D. dissertation.

Thorne, E.T., Kingston, N., Jolley, W.R., and Bergstrom, R.C., 

1982, Diseases of wildlife in Wyoming (2nd ed.), 353 p.

Thurow, T.L., and Taylor, C.A., 1999, Viewpoint: the role 

of drought in range management: Journal of Range 

Management, v. 52, p. 413–419.

Tischendorf, L., and Fahrig, L., 2000, On the usage and 

measurement of landscape connectivity: Oikos, v. 90, 

p. 7–19.

Tu, M., Hurd, C., and Randall, J.M., 2001, Weed control 

methods handbook—Tools & techniques for use in natural 

areas: The Nature Conservancy, 219 p.

U.S. Department of Defense and U.S. Fish and Wildlife 

Service, 2006, Greater Sage-Grouse Fact Sheet.

U.S. Farm Service Agency, 2008, Conservation Reserve 

Program State Acres for Wildlife Enhancement (SAFE) Fact 

Sheet.

U.S. Farm Service Agency, 2010, Record of Decision 

for Conservation Reserve Program Supplemental 

Environmental Impact Statement.

U.S. Fish and Wildlife Service, 2010a, Conference Report for 

the Natural Resource Conservation Service Sage-Grouse 

Initiative.

U.S. Fish and Wildlife Service, 2010b, Endangered and 

threatened wildlife and plants, 12-month findings for 

petitions to list the Greater Sage-Grouse (Centrocercus 

urophasianus) as threatened or endangered: Washington, 

D.C., FWS–R6–ES–2010–0018, Federal Register, v. 75, 

no. 55 (March 23, 2010), 107 p.

U.S. Fish and Wildlife Service, 2011, Sheldon National 

Wildlife Refuge Draft Comprehensive Conservation 

Plan and Environmental Impact Statement: U.S. Fish and 

Wildlife Service.

U.S. Fish and Wildlife Service, 2012, Hart Mountain National 

Antelope Refuge, Lake County, OR, draft comprehensive 

conservation plan and draft environmental impact 

statement: Washington, D.C., Federal Register, v. 77, 

no. 102 (May 25, 2012). 

U.S. National Park Service and Bureau of Land Management, 

2006, Craters of the Moon National Monument and Preseve 

Management Plan: U.S. National Park Service and Bureau 

of Land Management.

U.S. Natural Resources Conservation Service, 2012a, 

Contributions to the annual status review for Greater SageGrouse: U.S. Natural Resources Conservation Service , 

unpublished report.

U.S. Natural Resources Conservation Service, 2012c, Sagegrouse initiative status report fiscal year 2010–2011: U.S. 

Natural Resources Conservation Service. 

Utah Division of Wildlife Resources (UDWR), 2009, Utah 

Greater Sage-Grouse management plan: Salt Lake City, 

Utah Department of Natural Resources, Division of Wildlife 

Resources, Publication 09–17.

Vallentine, J.F., 1990, Kind and mix of grazing animals, in J.F. 

Vallentine, ed., Grazing management (1st ed.): San Diego, 

Calif., Academic Press, p. 217–242.

Valone, T.J., Meyer, M., Brown, J.H., and Chew, R.M., 2002, 

Timescale of perennial grass recovery in desertified arid 

grasslands following livestock removal: Conservation 

Biology, v. 16, p. 995–1002.

Van Poolen, H.W., and Lacey, J.R., 1979, Herbage response to 

grazing systems and stocking intensities: Journal of Range 

Management, v. 32, p. 250–253.

Vander Haegen, W.M., Schroeder, M.A., and DeGraaf, R.M., 

2002, Predation on real and artificial nests in shrub steppe 

landscapes fragmented by agriculture: The Condor, v. 104, 

p. 496–506.
150 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Veblen, K.E., Pyke, D.A., Aldridge, C.L., Casazza, M.L., 

Assal, T.J., and Farinha, M.A., 2011, Range-wide 

assessment of livestock grazing across the sagebrush biome: 

Reston, Va., U.S. Geological Survey.

Vitousek, P.M., 1990, Biological invasions and ecosystem 

processes—Towards an integration of population biology 

and ecosystem studies: Oikos, v. 57, p. 7–13.

Walker, B.L., and Naugle, D.E., 2011, West Nile virus ecology 

in sagebrush habitat and impacts on Greater Sage-Grouse 

populations, in Knick, S.T., and Connelly, J.W., eds., 

Greater Sage-Grouse: ecology of a landscape species and 

its habitats: Berkeley, Calif., University of California Press, 

Cooper Ornithological Union, p.127–143.

Walker, B.L., Naugle, D.E., and Doherty K.E., 2007a, Greater 

Sage-Grouse population response to energy development 

and habitat loss: Journal of Wildlife Management, v. 71, 

p. 2644–2654.

Walker, B.L., Naugle, D.E., Doherty, K.E., and Cornish, T.E., 

2004, Outbreak of West Nile virus in Greater Sage-Grouse 

and guidelines for monitoring, handling and submitting 

dead birds: Wildlife Society Bulletin, v. 32, p. 1–7.

Walker, B.L., Naugle, D.E., Doherty, K.E., and Cornish, T.E., 

2007b, West Nile virus and Greater Sage-Grouse: estimating 

infection rate in a wild bird population: Avian Diseases, 

v. 51, p. 691–696.

Wambolt, C.L., Harp, A.J., Welch, B.L., Shaw, N., Connelly, 

J.W., Reese, K.P., Braun, C.E., Klebenow, D.A., McArthur, 

E.D., Thompson, J.G., Torell, L.A., and Tanaka, J.A., 2002, 

Conservation of Greater Sage-Grouse on public lands in the 

Western U.S.: implications of recovery and management 

policies: Policy Analysis Center for Western Public Lands 

(PACWPL). 

Watts, S.E., 1998, Short-term influence of tank tracks on 

vegetation and microphytic crusts in shrubsteppe habitat: 

Environmental Management, v. 22, p. 611–616.

Weins, J.A., Stenseth, N.C., Van Horn, B., and Ims, R.A., 

1993, Ecological mechanisms and landscape ecology: 

Oikos, v. 66, p. 369–380.

West, N.E., 1983, Western intermountain sagebrush steppe, in

West, N.E., ed., Ecosystems of the World, p. 351–374.

West, N.E., 1988, Intermountain deserts, shrub steppes, 

and woodlands, in Barbour, M.G., and Billings, W.D., 

eds., North American terrestrial vegetation: New York, 

Cambridge University Press, p. 209–230.

West, N.E., and Yorks, T.P., 2002, Vegetation responses 

following wildfire on grazed and ungrazed sagebrush semidesert: Journal of Range Management, v. 55, p. 171–181.

West, N.E., and Young, J.A., 2000, Intermountain valleys and 

lower mountain slopes, in Barbour, M.G., and Billings, eds., 

North American terrestrial vegetation (2nd ed.): New York, 

Cambridge University Press, p. 256–284.

Westemeier, R.L., Brawn, J.D., Simpson, S.A., Esker, T.L., 

Jansen, R.W., Walk, J.W., Kerschner, E.L., Bouzat, J.L., 

and Paige, K.N., 1998, Tracking the long-term decline 

and recovery of an isolated population: Science, v. 282, 

p. 1695–1698.

Western Association of Fish and Wildlife Agencies, 2008, 

Greater Sage-Grouse population trends: an analysis of 

lek count databases 1965–2007: Denver, Colo., Western 

Association of Fish and Wildlife Agencies, 126 p.

Western Governors’ Association, 2011, Policy resolution 11–9: 

sage-grouse and sagebrush conservation: Denver, Colo., 

Western Governors’ Association.

Western Governors’ Wildlife Council, 2011, Inventory of State 

and local governments’ conservation initiatives for sage 

grouse: Denver, Colo.,Western Governors’ Association.

White, D., Minotti, P.G., Barczak, M.J., Sifneos, J.C., 

Freemark, K.E., Santelmann, M.V., Steinitz, C.F., 

Kiester, A.R., and Preston, E.M.,1997, Assessing risks to 

biodiversity from future landscape change: Conservation 

Biology, v. 11, p. 349–360.

Whiting, J.C., and Bybee, B., 2011, Annual report of surveys 

for historic sage-grouse leks on the Idaho National Energy 

Laboratory: Unpublished report.

Whittington, J., Hebblewhite, M., DeCesare, N.J., Neufeld, 

L., Bradley, M., Wilmshurst, J., and Musiani, M., 2011, 

Caribou encounters with wolves increase near roads 

and trails: a time-to-event approach: Journal of Applied 

Ecology, v. 48, p. 1535–1542.

Wiens, J., 2002, Predicting species occurrences: progress, 

problems, and prospects, in Scott, J.M., Heglund, P.J., 

Morrison, M.L., Haufler, J.B., Rapheal, M.G., Wall, W.A., 

and Samson, F.B., eds., Predicting species occurrences: 

issues of accuracy and scale: Washington, D.C., Island 

Press.

Winward, A.H., 2004, Sagebrush of Colorado—Taxonomy, 

distribution, ecology and management, 39 p.

Wisdom, M.J., Meinke, C.W., Knick, S.T., and Schroeder, 

M.A., 2011, Factors associated with extirpation of sagegrouse, in Knick, S.T., and Connelly, J.W., eds., Greater 

Sage-Grouse: ecology of a landscape species and its 

habitats: Berkeley, Calif., University of California Press, 

Cooper Ornithological Union, p. 451–474.
References Cited 151

Wisdom, M.J., Rowland, M.M., Hemstrom, M.A., and Wales, 

B.C., 2005, Landscape restoration for Greater Sage-Grouse: 

implications for multiscale planning and monitoring, in

Shaw, N.L., Pellant, M., and Monsen, S.B., eds., Sage 

grouse habitat restoration symposium proceedings, 

2001 June 4–7, Boise, Idaho: Fort Collins, Colo., U.S. 

Department of Agriculture, Forest Service, Rocky Mountain 

Research Station, p. 62–69.

Wisdom, M.J., Rowland, M.M., Wales, B.C., Hemstrom, 

M.A., Hann, W.J., Raphael, M.G., Holthausen, R.S., 

Gravenmier, R.A., and Rich, T.D., 2002, Modeled effects 

of sagebrush-steppe restoration on Greater Sage-Grouse in 

the interior Columbia Basin, U.S.A.: Conservation Biology, 

v. 16, p. 1223–1231.

With, K.A., 2004, Assessing the risk of invasive spread in 

fragmented landscapes: Risk Analysis, v. 24, p. 803–815.

Wright, H.A., 1970, Response of big sagebrush and threetip sagebrush to season of clipping: Journal of Rangeland 

Management, v. 23, p. 20–22.

Wrobleski, D.W., and Kauffman, J.B., 2003, Initial effects of 

prescribed fire on morphology, abundance, and phenology 

of forbs in big sagebrush communities in southeastern 

Oregon: Restoration Ecology, v. 11, p. 82–90.

Wyoming Executive Order No. 2008–2, August 1, 2008, 

Greater Sage-Grouse core area protection: Casper, Wyo., 

Governor’s Office, State of Wyoming.

Wyoming Executive Order No. 2010–4, August 18, 2010, 

Greater Sage-Grouse core area protection: Casper, Wyo., 

Governor’s Office, State of Wyoming.

Wyoming Executive Order No. 2011–5, June 2, 2011, 

Greater Sage-Grouse core area protection: Casper, Wyo., 

Governor’s Office, State of Wyoming.

Xian, G., Homer, C.G., and Aldridge, C.L., 2012, Effects 

of land cover and regional climate variations on longterm spatiotemporal changes in sagebrush ecosystems: 

Geoscience & Remote Sensing, v. 49, p. 378–396.

Yost, A.C., Petersen, S.L., Gregg, M., and Miller, R., 

2008, Predictive modeling and mapping sage grouse 

(Centrocercus urophasianus) nesting habitat using 

Maximum Entropy and a long-term dataset from southern 

Oregon: Ecological Informatics, v. 3, p. 375–386.

Young, J.A., and Evans, R.A., 1978, Population dynamics 

after wildfires in sagebrush grasslands: Journal of Range 

Management, v. 31, p. 283–289.

Young, J.A., Evans, R.A., and Kay, B.L., 1987, Cheatgrass: 

Rangelands, v. 9, p. 266–270.

Young, J.R., Braun, C.E., Oyler-McCance, S.J., Hupp, J.W., 

and Quinn, T.W., 2000, A new species of sage–grouse 

(Phasianidae:Centrocercus) from southwestern Colorado: 

Wilson Bulletin, v. 112, p. 445.

Young, J.R., Hupp, J.W., Bradbury, J.W., and Braun, C.E., 

1994, Phenotypic divergence of secondary sexual 

traits among sage grouse, Centrocercus urophasianus, 

populations: Animal Behaviour, v. 47, p. 1353–1362.

Zablan, M.A., Braun, C.E., and White, G.C., 2003, Estimation 

of Greater Sage-Grouse survival in North Park, Colorado: 

Journal of Wildlife Management, v. 67, p. 144–154.

Zou, L., Miller, S.N., and Schmidtmann, E.T., 2006, Mosquito 

larval habitat mapping using remote sensing and GIS—

Implication of coalbed methane development and West Nile 

virus: Journal of Medical Entomology, v. 43, p. 1034–1041.

Zou, L., Miller, S.N., and Schmidtmann, E.T., 2007, A GIS 

tool to estimate West Nile virus risk based on a degree-day 

model: Environmental Monitoring and Assessment, v. 129, 

p. 413–420.
152 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

Appendix. Data Sources and Analysis 

for the Greater Sage-Grouse Threat 

Assessment

Introduction

The primary purpose of the geospatial analysis is to 

quantitatively assess the location, magnitude, and extent 

of the primary threats to Greater Sage-Grouse (hereafter, 

sage-grouse) habitats and populations. Understanding these 

factors and being able to compare differences between areas 

across the range of the species provides overarching biological information that informs planning. For landscape species 

(defined in this context as a species where populations occupy 

large ranges that cross traditional management boundaries), 

the evaluation of current and future status (such as the impact 

associated with alternatives in the context of the National 

Environmental Protection Act (NEPA) planning and review 

process) must take into account biologically meaningful 

scales, which may be larger than the planning area being 

assessed. This allows specific areas to be put into the larger 

context so that decision makers can understand more sitespecific conditions, place finer resolution data into context, 

and make allocation and other land-use planning decisions. 

The tradeoffs and prioritization inherent in applying a conservation strategy first require understanding the nature and 

extent of threats across the range of a species and then looking 

at smaller scale areas in context to allocate resources to reduce 

threats in these areas that are meaningful for the species.

Therefore, we strove to collect geospatial data representing the threats to sage-grouse as identified by scientific 

research and outlined in the 2010 USFWS listing decision. We 

measured the direct impact to sage-grouse habitats, as well as 

the indirect impacts to habitats and populations through applying buffer distances representing impacts to the species as 

identified in the literature. These potential measures of impact 

were then compared to current BLM preliminary priority habitat and preliminary general habitat delineations (see Section 1) 

to understand the condition and threats across the highest 

densities of sage-grouse and sagebrush habitats as well as the 

rest of the currently occupied range. In addition, we examined 

surface-management entities in relation to each threat so that 

multiple landowners and managers across the range of the 

sage-grouse can understand impacts under their jurisdiction 

as well as neighboring jurisdictions. This landscape approach 

allows for population-level assessments despite checkerboards 

of surface-management entities. Overall this effort is intended 

to provide information to conservation planning teams to 

understand the issues, determine appropriate alternatives, 

and ultimately provide biologically meaningful analyses of 

sage-grouse populations (for example, information on the past 

and current conditions for cumulative impact analyses in the 

WAFWA Management Zones for sage-grouse).

Methodology

Identification of Threats

Threats for the sage-grouse are identified in the 2010 

USFWS listing decision for five factors. These common 

threats and issues fall into categories that were recognized by 

USFWS in the published findings—habitat change (Factor 

A), over-utilization (Factor B), disease and predation (Factor 

C), policy and land use (Factor D), and chemical poisoning 

(Factor E). Primarily threats that can be represented spatially 

with current data are found in Factor A. Factors B through D 

are typically described qualitatively, although for this report, 

Factor D information was collected for management classifications with the purpose of identifying areas where habitats 

are protected from development. For each threat we collected 

information in up to four categories (if data were available):

1. Land Allocation and Management—management focus 

(conservation versus multiple use) and data associated 

with reduction and or limitation of threat categories (table 

A-1)

2. Current Threats—physical footprints and locations of 

anthropogenic features and natural processes that impact 

sage-grouse habitats (tables A-2, and A-3)

3. Valid Existing Rights—management decisions and 

projects approved but where features may not currently 

exist (includes leasing and allocation decisions from land 

management agencies where data could be collected in 

the project time frames) (tables A-2 and A-3)

4. Potential Threats—data on the potential of anthropogenic 

features and natural processes; in many cases these are 

associated where land uses may occur but do not take into 

account distribution, infrastructure, or other factors necessary for actual projects to be located in these areas (tables 

A-2 and A-3)

Determination of Direct and Indirect Distances

Direct impact of any particular threat was measured 

as acres of physical ground disturbance or linear miles of 

the feature. In many cases polygon data were available that 

represented the physical footprint of a feature, but in some 

cases, we buffered point features with appropriate distances to 

represent the typical footprint of development (see tables A-1 

and A-4). These distances were derived from programmatic 

Environmental Impact Statement (EIS) documents, industry 

standards, or expert opinion (see tables A-1 and A-4).

Section 3 of this report identifies multiple literature 

sources that reported effects associated with the threats identified in the USFWS listing decision. We selected the indirect 

impact distances as appropriate for each threat, based on peerreviewed scientific literature that represented impacts typical 

of sage-grouse populations across the range. These distances 
Appendix. Data Sources and Analysis for the Greater Sage-Grouse Threat Assessment 153

may not represent impact for all populations, but many come 

from rangewide or cross-population analyses where a statistical impact at the buffered distance was identified. They are 

used in the report to identify issues that should be looked at 

more closely during the creation of land management and 

conservation plans for sage-grouse (tables A-1 and A-4). We 

chose to use distances where an impact could be determined, 

not necessarily a more specific look at avoidance behaviors 

associated with a feature. Therefore, it is important to note 

that impacts across an indirect buffer distance are likely not 

uniform; typically there is a decay function that more fully 

represents the relation. In setting metrics or thresholds for 

site-specific applications and analyses, the additional scientific 

summaries in this document along with local knowledge on 

home-range size, migratory patterns, habitat availability, and 

other factors, are important when interpreting the effects on 

sage-grouse habitat and populations and addressing specific 

questions or objectives associated with impacts to sage-grouse 

habitats and populations. 

Collection of Geospatial Data

All data analysis was conducted by the BLM’s National 

Operations Center in Lakewood, Colo. Data was collected 

and assembled from National BLM sources, individual BLM 

States, USFS national sources, and external sources depending on the authoritative source for types of features (tables 

A-2 and A-3). In some cases data from multiple sources was 

aggregated to best represent the feature or phenomenon. In 

addition, some data was only available for Federal lands or for 

only a part of the study area.

Geospatial data were acquired for all threats identified in 

the USFWS listing decision that can be represented spatially. 

These data were acquired rangewide, as available, from both 

internal (BLM and USFS) and external sources beginning 

in August 2011 (tables A-2 and A-3). All data, both internal 

and external, were considered the “best available” at the time 

of data collection. National data were “frozen” in June and 

July of 2012, with updates made to some datasets as late as 

December 2012. Other data (for example, compiled from other 

sources) were the most current available, based on the supplying office, agency, or organization (see tables A-2 and A-3). 

Internal data were compiled using intra-agency data calls and 

often included data submitted in segments, from different 

administrative units, across the BLM and USFS management 

areas (see fig. A-1 for the full process). These datasets were 

aggregated and reviewed, but time constraints limited the 

ability to revise these data for quality and completeness, fix 

geometry errors (gaps and overlaps), and edge-match across 

jurisdictions (fig. A-1). The metadata associated with each 

dataset details the analysis and methodology procedures and 

provides details relating to specific data.

After data collection was complete, input datasets were 

preprocessed. Preprocessing steps included reclassification, 

attributing, buffering, and other formatting tasks. Categorizing datasets into relevant attributes and supplementing them 

with additional attributes was necessary for data compatibility. 

Collaboratively developed priority habitat designations (PPH 

and PGH) were combined with surface management agency 

(SMA) and WAFWA management-zone polygons into one 

master summary file (MSF) with a unique identification (ID) 

reflecting the specific combination of habitat (PPH or PGH), 

management entity, and WAFWA MZ for each polygon to 

provide for efficient, repeatable, and consistent data analysis. 

All datasets were clipped to the rangewide study area, and 

small and superfluous polygons were dissolved, to reduce the 

number of features and remove unnecessary attributes. Finally, 

data were sorted into point, line, and polygon features for 

different analyses that reflected the represented footprint and 

modeled effects (see table A-1).

Overlay comparisons were generated using ArcGIS 

Model Builder (version 10.0) with separate models created 

for point, line, and polygon input data (see fig. A-1). In brief, 

these models intersect the input data with the master summary file (MSF), which includes representation of the spatial 

summary units (MZs), and dissolve the resulting intersect file 

to single polygons based on the unique ID assigned in the 

intersection. Finally, statistics were calculated for each threat 

overlay using the number of points, linear miles, or area within 

the specific combination of habitat type, management entity, 

and MZ. The resulting data were then exported from the GIS 

to Microsoft Excel for summary calculations (fig. A-1). For 

each of the categories/types of data, the pre-processing steps 

were as follows: 

Base Layers

Preliminary Priority Habitat/Preliminary General Habitat

This dataset is the consolidated submissions of State-submitted Greater Sage-Grouse Preliminary Priority and Preliminary General Habitats (table A-2). These data are a snapshot 

of State defined PPH/PGH polygons as of June 26th, 2012 

– priority habitats may also be described as “core areas” in 

some contexts. States may have continued to refine the PPH/

PGH designations beyond this date. Specifics on each State’s 

submission follow:

• California—PPH and PGH: FINAL DRAFT; Developed cooperatively by California BLM and California 

Department of Fish and Game.

• Colorado—PPH and PGH: FINAL DRAFT; Developed 

by Colorado Parks and Wildlife in cooperation with 

Colorado BLM.

• Idaho—PPH and PGH: Version 2 (April 2012); Developed by the Idaho BLM State Office with input from 

Idaho BLM Field Offices, the U.S. Forest Service, and 

Idaho Department of Fish and Game. Version 2 reflects 

refinements and additional data that were incorporated 

into Version 1 following further analysis and public 
154 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

scoping for the BLM Sage-Grouse Conservation Planning effort. 

• Montana—PPH and PGH: FINAL DRAFT; Developed 

by Montana Fish, Wildlife and Parks and reviewed by 

Montana BLM 

• Nevada—PPH and PGH: SEMIFINAL DRAFT; 

Developed by Nevada Department of Wildlife in cooperation with Nevada BLM (90 percent completed).

• North Dakota—PPH: FINAL DRAFT; Developed by 

North Dakota Game and Fish Department in cooperation with Montana/Dakotas BLM; PGH: FINAL 

DRAFT; Distribution of Sage-Grouse in North 

America (Schroeder and others, 2004).

• Oregon—PPH and PGH: FINAL DRAFT; Developed 

by Oregon Department of Fish and Wildlife in cooperation with Oregon BLM.

• South Dakota—PPH and PGH: FINAL DRAFT; 

Acquired from Montana/Dakotas BLM.

• Utah—PPH: SEMIFINAL DRAFT; Developed by 

Utah Division of Wildlife Resources; under review by 

Utah Governor’s Office; Utah BLM will use Division of Wildlife Resources (DWR) Occupied Habitat 

(9/2011) in the interim; PGH: All DWR Occupied 

Habitat is considered Priority, so PGH does not apply.

• Wyoming—PPH and PGH: PPH (June 2010): Core 

Management Areas-Version 3; Developed by the 

Wyoming Governor’s Sage-Grouse Implementation 

Team and Wyoming Game and Fish Department in 

cooperation with Wyoming BLM (PGH modified from 

Distribution of Sage-Grouse in North America; Schroeder and others, 2004).

WAFWA Management Zones

This dataset depicts the Management Zone boundaries 

as defined by the Western Association of Fish and Wildlife 

Agencies for Greater and Gunnison Sage-Grouses in the 

Western United States and Canada. It was not altered in 

any way for this effort. MZ II and VII were combined for 

summary analyses.

Federal Agency Management (Surface Management)

This dataset provides management data for all Federal 

agencies, as well as State, local, and private lands. It was 

updated with U.S. Forest Service authoritative data provided 

in May 2012. Because of inconsistencies in the manner in 

which BLM States define and categorize SMA designations, 

and in order to focus analysis on BLM and USFS management at the landscape scale, the following Federal agencies 

and tribal entities were classified into one category called 

“Tribal and Other Federal”: BIA, BOR, BPA, COE, DOD, 

DOE, Federal Aviation Administration (FAA), FWS, GSA, 

NPS, tribal and non-forest USDA. Other minor land management entities, topology errors, unknown areas, and unclassified areas were combined into an “other” category during final 

summary of the data. In addition, areas classified as water 

were removed to restrict the summary tables to terrestrial 

habitats.

Land Allocation and Management

Federal Fluid Minerals—Areas Closed to Oil and Gas 

Leasing

This polygon dataset is the consolidated submissions for 

locations closed to oil and gas development data from BLM 

States. Areas overlapping with submitted oil and gas leases 

and leases held-by-production polygons were removed. 

Conservation Focused and Protected Areas

The National Conservation Easement polygon database 

was subset to include only those features where “Duration” = 

“Permanent.”

USGS Protected Areas Database (PAD-US, v. 1.2)

polygons with level of protection (GAP Status) codes 1 and 

2 (see below) or unknown were subset to provide National 

Park Service and State and private lands polygon datasets. 

Additionally, Wilderness and USFWS Refuges datasets were 

supplemented with additional refuge or wilderness features 

found in PAD-US. Finally, ACEC (Areas of Critical Environmental Concern) and NLCS (National Landscape Conservation System) polygons were categorized by GAP Status code 

using PAD-US, and only those with codes 1, 2, or unknown 

were retained. 

GAP Status codes 1 and 2 are defined as follows:

1. An area having permanent protection from conversion of natural land cover and a mandated management plan in operation to maintain a natural state 

within which disturbance events (of natural type, 

frequency, intensity, and legacy) are allowed to proceed without interference or are mimicked through 

management.

2. An area having permanent protection from conversion of natural land cover and a mandated management plan in operation to maintain a primarily natural state, but which may receive uses or management 

practices that degrade the quality of existing natural 

communities, including suppression of natural disturbance. 

National Landscape Conservation System (NLCS) and 

Areas of Critical Environmental Concern (ACEC) polygons 

provided by the BLM data steward were subset to include only 

those with PAD-US GAP Status categories 1, 2, or unknown. 

Input NLCS units included National Conservation Areas, 
Appendix. Data Sources and Analysis for the Greater Sage-Grouse Threat Assessment 155

Wilderness Study Areas, National Monuments, Cooperative Management and Protection Areas, and Outstanding 

Natural Areas.

Wilderness polygons were derived from all wildernessland polygons from the BLM and USFS Wilderness databases, 

supplemented with NPS and FWS Wilderness from PAD-US.

USFWS Refuges polygons from the National Wildlife 

Refuge Boundary and Parcel Data database were supplemented with additional data from the PAD-US database where 

“Primary Designation Type” = “National Wildlife Refuge” and 

GAP Status category was 1, 2, or unknown.

National Park Service polygons were determined by pulling a subset of PAD-US where “Own_Name” = “0145” (NPS) 

and GAP Status was 1, 2, or unknown.

State and Private land polygons with GAP Status categories of 1, 2, or unknown were pulled from PAD-US by selecting “Own_Type” = “03”’ OR “Own_Type” = “04” OR “Own_

Type” = “05” (State, regional and local) or “Own_Type” = 

“07” (private).

Because there was overlap of polygons in the above datasets, they were merged and dissolved before conservation area 

on PPH and PGH statistics were calculated.

Current Threats

Agricultural Development

This polygon dataset is a subset of the USDA National 

Agricultural Statistics Service’s (NASS) Cropland Data Layer 

(CDL). For the purpose of creating a crop-specific layer, the 

following features were excluded from this dataset: Barren, 

Deciduous Forest, Developed/High Intensity, Developed/Low 

Intensity, Developed/Med Intensity, Developed/Open Space, 

Evergreen Forest, Grassland Herbaceous, Herbaceous Wetlands, Mixed Forest, Open Water, Other Hay/Non Alfalfa, Pasture/Hay, Pasture/Grass, Perennial Ice/Snow, Shrubland, and 

Woody Wetlands. Raster data were converted to polygon vector data and were buffered to create indirect influence areas.

Urbanized Areas

This polygon dataset is a subset of the City Limits dataset 

from Tele Atlas ESRI Street Map Premium for ArcGIS v 9.0. 

City limit polygons falling on Bureau of Indian Affairs land, 

which were also found to be of limited development using 

aerial imagery inspection, were manually removed from this 

dataset. Features were buffered to create indirect influence 

areas.

Major Power Lines and Associated Infrastructure

This polygon dataset is a compiled layer of two power 

line datasets, which together provide the most complete 

spatial representation of this threat across the study area. 

Linear features from power lines in the Western United States, 

ICBEMP existing utility corridors dataset, 2004, and transmission lines, substations, electric power generation plants, 

and energy distribution control facilities from the EV Energy 

Map, Platts/Global Energy, 2005, were merged to create a 

combined layer. Features (lines and points) were then buffered to create direct and indirect influence areas. We did not 

calculate linear distances because minor spatial errors between 

the dataset resulted in sections of power lines being duplicated. Buffering and dissolving features off of these linear 

features represented direct impacts of development as an acre 

footprint and removed issues of double counting from a linear 

mile measurement.

Communication Towers and Other Vertical Structures

This dataset is compiled from the FAA Digital Obstacles 

point file and the Federal Communications Commission 

(FCC) communication towers point file. Points with “Type_” 

= “WINDMILL” were removed from the FAA file and were 

processed in a separate analysis. Additionally, all duplicate 

points were removed. Finally, features were buffered to create 

direct and indirect influence areas.

Fences

This dataset is a merged layer of allotment and pasturedata files submitted by the USFS and the BLM. This aggregate 

dataset identifies pasture and allotment borders, represented as 

linear features, for allotments within BLM and USFS managed public lands. This acts as a surrogate for fences for those 

areas with BLM or USFS management (in many cases only 

a portion of a pasture or allotment) and therefore does not 

represent fence density for areas with solely other Federal or 

non-Federal management. 

Interstate, Highway, and Secondary Roads

This dataset is a subset of the ESRI Tele Atlas ESRI 

StreetMap Premium for ArcGIS v 9.0 2008, Dynamap Transportation version 5.2, 2003, Detailed Streets dataset. The 

following queries were used to select interstates, highways 

(primary and secondary), and secondary (other) road types: 

Interstates, “FCC” IN ( ‘A10’, ‘A11’, ‘A12’, ‘A15’, ‘A16’, 

‘A17’, ‘A18’); Highways, “FCC” IN ( ‘A20’, ‘A21’, ‘A22’, 

‘A23’, ‘A24’, ‘A25’, ‘A26’, ‘A27’, ‘A28’, ‘A30’, ‘A31’, 

‘A32’, ‘A33’, ‘A34’, ‘A35’, ‘A36’, ‘A37’, ‘A38’); and Other 

roads, “FCC” IN ( ‘A40’, ‘A41’, ‘A42’, ‘A43’, ‘A44’, ‘A45’, 

‘A46’, ‘A47’, ‘A48’, ‘A50’, ‘A51’, ‘A52’, ‘A60’, ‘A64’, 

‘A70’). Linear features were then buffered to create direct 

and indirect influence areas. The three-road-type buffer files 

were combined for each influence distance with overlap areas 

removed for analysis. 

Major Railroads

This dataset includes abandoned and non-abandoned 

railroads from the Federal Railroad Administration (FRA) Rail 

Lines of the U.S.A. dataset. Abandoned and non-abandoned 

rail lines were separated into two linear files using the attribute 

indicating the status of the rail line. Non-abandoned linear 
156 Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse

features were buffered to create direct and indirect influence 

areas, whereas abandoned features were buffered to create 

only direct influence areas.

Large Wildfires

This dataset includes polygon data representing the 

perimeters of wildfires submitted to the Geospatial MultiAgency Coordination (GeoMAC) Group occurring during 

the period 2000 through 2012. Polygon areas were used to 

represent direct influence.

Moderate to High Probability of Cheatgrass Occurrence

This is a modeled dataset created to depict the probability 

of cheatgrass occurrence in several floristic regions (Meinke 

and others, 2009). Inputs for regression analysis included 

elevation, precipitation, soil pH, soil depth, soil salinity, and 

available water capacity extracted at 6,736 field sampling 

locations where cheatgrass occurrence was determined. The 

data were subset using the 5–10 percentile range to reflect a 

“moderate to high” risk of cheatgrass occurrence as in Meinke 

and others (2009). Raster data were converted to polygon vector data. Polygon areas were used to represent direct influence.

Pinyon-Juniper and Other Conifer Encroachment Risk

This is a derived dataset using the methodology from the 

BLM Rapid Ecological Assessment of the Northern Basin and 

Range and Snake River Plain (DOI, 2010). To create this layer, 

GIS focal statistics were used to identify areas of adjacency 

between sagebrush and pinyon/juniper, and sagebrush and any 

other cells classified as conifer, as classified in the National 

GAP landcover GIS database. These cells were then buffered 

120 meters into sagebrush to represent potential expansion 

into sagebrush areas. Raster data were converted to polygon 

vector data for analysis. Polygon areas were used to represent 

direct influence.

Grazing

This dataset consists of BLM grazing allotments and 

pastures polygon supplemented with the 2008 BLM Land 

Health database (Veblen and others, 2011; Assal and others, 

2012). Allotments were selected from the database that were 

not meeting land-health standards for wildlife with grazing 

as the causal factor in the non-achievement, as well as those 

allotments where an assessment had not been completed. 

These allotments were then joined to the BLM Geospatial 

Science Support Program (GSSP), National Allotment GIS 

dataset on June, 28 2012, using the unique State allotment ID. 

Of the 1,135 allotment records from the spreadsheet, 21 were 

not able to be mapped. Polygon areas were used to represent 

direct influence.

Wild Horse and Burro Herd Management Areas (HMAs)

This polygon dataset is a compilation of BLM wild horse 

and burro and USFS wild horse and burro HMA polygons. 

Polygon areas were used to represent direct influence.

Oil and Gas Development Related Wells

This dataset is a compilation of two oil and gas well 

databases: the proprietary IHS Corporation Enerdeq database 

and the BLM Automated Fluid Minerals Support System 

(AFMSS) database. Wells producing within the last ten years 

from IHS and Active wells from AFMSS, as well as plugged 

and abandoned within the last 10 years from both datasets, 

were buffered by 62 m to provide direct effects. Producing 

wells from IHS and Active wells from AFMSS were buffered 

by 3 km and 19 km to provide indirect effects. We chose the 

ten-year criterion for inclusion of wells as our analysis of 

time-lag effects suggested that there is a delay of 2–10 years 

between activity associated with energy development and its 

measurable effects on lek attendance; therefore, flagging past 

development allows identification of areas where issues from 

production and development from fields may remain. The 

IHS dataset includes the following states: Calif., Colo., Idaho, 

Mont., N. Dak., Nev., Oreg., S. Dak., Utah, and Wyo. downloaded in December 2012. It was subset to exclude points 

occurring also in the BLM AFMSS database. AFMSS data 

are current as of December 19, 2012, for the following BLM 

States: Calif., Colo., Idaho, Mont., N. Dak., Nev., Oreg., S. 

Dak., Utah, and Wyo. Points from both datasets were aggregated by square mile to create the well density figure. 

Federal Managed Coal, Surface Mining Development

This polygon dataset is the consolidated submissions for 

Federal coal lease data. Leases were defined as surface coal 

leases and subset from the original dataset based on guidance 

from BLM planners and mineral specialists. Polygon features 

were used for direct footprint and buffered for indirect influence areas.

Mining and Minerals Materials Disposal (Federal 

Minerals Only)

This polygon dataset is a compilation of two datasets 

consolidated from submissions from BLM States. The two 

datasets include mineral materials disposal sites and locatable 

mining claims. Both datasets were submitted as polygon data. 

Polygon areas were used to represent direct influence and were 

buffered to create indirect influence areas.

Wind Turbines

This dataset is compiled from the Federal Aviation 

Administration Digital Obstacles point file to include points 

where “Type_” = “WINDMILL”. Aerial imagery was used to 
Appendix. Data Sources and Analysis for the Greater Sage-Grouse Threat Assessment 157

verify that these points represent wind turbines. All duplicate 

points were removed and features were buffered to create 

direct and indirect influence areas.

Valid Existing Rights

Federal Geothermal Leasing

This polygon dataset is the consolidated submissions for 

geothermal lease and approved project data from BLM State 

offices. Lease boundaries defined polygons that represented 

direct influence areas with existing rights.

Federally Managed Fluid Minerals—Leased Areas and 

Status

These datasets (leased areas and leases held by production) are a compilation of polygon datasets consolidated from 

submissions from BLM States. The two datasets include (1) 

oil and gas leases (limited to “Authorized”: Case-types beginning with 310, 311, or 312 and not held by production, as 

needed) and (2) oil and gas leases held by production (limited 

to “Authorized”: Case-types beginning with 310, 311, or 312, 

and HbP codes of 650, 651 or other attribute field populated to 

indicate held by production). 

Oil Shale Leases

This polygon dataset is the consolidated submissions for 

oil shale research, development, and demonstration lease data 

from BLM States.

BLM Wind Energy Rights of Way (ROW)

This polygon dataset is the consolidated submissions for 

wind energy rights of way and approved authorizations data 

from BLM States.

Potential Threats

Large Fire—High Burn Probability

A derived dataset based on a national burn probability (BP) 

raster dataset for the United States was generated for the 

2012 Fire Program Analysis (FPA) System. These data were 

provided by the National Interagency Fire Center (NIFC). The 

source raster was subset to the rangewide analysis area and 

reclassified to nominal classifications creating two categories 

of data, plus a zero category: Non-burnable = 0, Low probability = 0.00002–0.0043, and High Probability = 0.0043–0.0732. 

The high-probability dataset was subset as a raster file and 

then converted to vector format for analysis.

Coal Potential

This dataset includes polygons from the America’s Coal 

Potential database compiled and published by the USGS 

(Tewalt and others, 2008).

Oil and Gas Potential

This is the raster dataset for relative oil and gas potential as described in Copeland and others (2009) “Mapping 

Oil and Gas Development Potential in the US Intermountain 

West and Estimating Impacts to Species.” This continuous 

dataset, ranked from 0–100, was categorized into Low = 0–33, 

Medium = 34–66, and High = >66 categories for map display.

Geothermal Potential

This dataset includes polygons from the Idaho National 

Engineering & Environmental Laboratory (INEEL) of regions 

favorable for the discovery and shallow depth (less than 1,000 

m) of thermal water of sufficient temperature for direct-heat 

applications.

Solar Potential

This polygon dataset provides information on the photovoltaic solar resource potential (US 9805 latilt) for the 48 contiguous States as published by the National Renewable Energy 

Laboratory (NREL). Map display categories follow those used 

in the Draft Programmatic Environmental Impact Statement 

(PEIS) for Solar Energy Development in Six Southwestern 

States (DES 10-59, DOE/EIS-0403; solareis.anl.gov) to show 

areas with an occurrence potential greater than 5.5 kWh/m2/

day (kilowatt hours per square meter per day). Reaming areas 

have the potential for less than 5.5 kWh/m2/day.

Oil Shale and Tar Sands

This polygon dataset is from the 2008 Oil Shale and Tar 

Sands PEIS. It includes merged features from the stratigraphic 

unit files for oil shale in Colo., Utah, and Wyo., which have 

been designated as “most geologically prospective,” as well as 

“special tar sand areas” in Utah.

Wind Potential

This polygon dataset is a consolidated annual average 

wind resource potential at a 50-m height from NREL Statelevel shapefile data. Categories for medium and high were 

created from the original data as follows: Medium = Fair (3 

or 200–300) and High = Good (4 or 400–500), Excellent (5 

or 500–600), Outstanding (6 or 600–800), and Superb (7 or 

>800). Original 50-m-resolution data was resampled to 5-km 

resolution.
General Description Data Source Indicator Area of Influence 

Habitat Conversion to Agriculture USDA Cropland (Categories identified by CEA Team) Acres Direct: polygon area Indirect: 6.9 km Boa

Ln

Urbanization Urban Areas—ESRI City Boundaries Acres Direct: polygon area Indirect: 6.9 km Boa

L

Infrastructure (Power lines) Global Energy/ Platts, Market significant power lines (gen >115kV) & assoc. structures Acres Direct: 200 meters Indirect: 6.9 km Elli

CBBL

Infrastructure (Comm. Towers) FCC Acres Direct: 1 ha (56.4 m) Indirect: 6.9 km Boa

L

Infrastructure (Other Vertical Structures) FAA (non-wind) Acres Direct 1 ha (56.4 m) Indirect: 6.9 km Boa

L

Infrastructure (Fences) BLM Range Allotment GSSP Miles Direct: Miles StevInfrastructure (Roads) ESRI Roads (Interstate, Federal and State Highway, Secondary) Acres Direct: 73.2 m, 25.6 m, 12.4 m Indirect: 7.5 km, 3 km, 3 km Hol

LyoCon

Infrastructure (Railroads) ESRI Railroads Acres Direct: 9.4 m Indirect: 3 km KniFire History NIFC (Fire Polygons, 2001–2012) Acres Direct: Fire Acres Invasive Plant (Exotic Annual Grass) Model—Cheatgrass (Great Basin only) Acres Direct: High and Moderate Probability Polygons Mei

P-J (Conifer) Encroachment Northern Great Basin Assessment Model Acres Direct: 120m DOGrazing (Domestic Livestock) BLM Allotments (not meeting Land Health Standards [habitat due to livestock grazing]) Acres Direct: “not meeting” Polygon Areas

Grazing (Wild Horses & Burros) BLM HMAs (GSSP), FS HMAs Acres Direct: Polygon Areas

Table A-1. Direct and indirect buffer distances used to represent effects of human infrastructure and activities on Greater Sage-Grouse for this Rep

literature describing these relations. 
Table A-1. Direct and indirect buffer distances used to represent effects of human infrastructure and activities on Greater Sage-Grouse for this Rep

literature describing these relations.—Continued 

General Description Data Source Indicator Area of Influence 

Energy (Nonrenewable; O&G) IHS Well location data (non-plugged, or plugged 

only in the last 10 years)

Acres Direct: 3 acres

Indirect:19 km

WalUSFJohTay

Energy (Nonrenewable; Coal) BLM State Offices (Surface Mines) Acres Direct: Polygon Areas 

Indirect: 19 km

JohTay

Mining (Locatable Mining Claims) BLM State Offices—WO 300 Data Call Acres Direct: Polygon Areas

Indirect: 2.5 km

Bra

Mining (Mineral Materials Disposal 

Sites)

BLM State Offices—WO 300 Data Call Acres Direct: Polygon Areas

Indirect: 2.5 km

 Bra

Energy (Renewable—Wind) FAA Acres Direct: 3 acres (62m buffer)

Indirect: 6.9 km

BraBoa

L

Energy (Renewable—Geothermal) BLM State Offices Acres Direct: Polygon Areas Joh

Tay
Table A-2. Internal (BLM) data sources. Analysis Dataset Source Data Type Publication Date or Received Date 

Base and Greater Sage-Grouse Habitat BLM Land Use Plans (LUP) BLM Geospatial Services Strategic Plan (GSSP) Polygon June 2012 

BLM Subsurface Minerals Administration BLM State offices: CO, MT, UT, WY Polygon May 2012 

Federal Surface Management Agency BLM GSSP Polygon May 2012 

Forest Service Administrative Units USFS Enterprise Data Warehouse Polygon July 2012 

GRSG Planning Regions and EIS Boundaries Derived from BLM Land Use Plans GSSP Polygon May 2012 

Conservation ACEC BLM GSSP Polygon May 2012 

NLCS (National Conservation Areas, Wilderness Study Areas, National Monuments, Cooperative Management and Protection Areas, Outstanding Natural Areas, and Forest Reserves) BLM GSSP Polygon June 2012 

Wilderness (BLM) BLM GSSP Polygon June 2012 

Wilderness (USFS) USFS1 Enterprise Data Warehouse Polygon April 2012 

Current Threat Coal Leases Individual BLM State, District and Field offices Polygon November 2011– May 2012 

Decadal Fires—Fire Perimeters, 2000–2012 Geospatial Multi-Agency Coordination (GeoMAC) Group Polygon January 2013 

Fences (BLM)—Grazing Allotments and Pastures BLM GSSP Line (converted from polygon) May 24, 2012 

Fences (USFS) —Grazing Allotments and Pastures USFS Enterprise Data Warehouse Line (converted from polygon) July 2012 

Geothermal Leases Individual BLM State, District and Field offices Polygon November 2011– May 2012 

Grazing (BLM)—allotment/pasture designations Veblen, K.E. and others, 2011, Assal, T.J. and others, 2012, BLM GSSP grazing allotment and pasture polygons Polygon May 24, 2012 

Grazing (BLM)—Land Health Standards Veblen and others, 2011, Assal and others, 2012, BLM GSSP Polygon May 24, 2012 

Grazing (USFS) USFS1 Enterprise Data Warehouse Polygon July 2012 

Mining and Mineral Materials Disposal—

Mineral-Material Disposal Sites and Locatable Mining Claims

Individual BLM State, District and Field offices Polygon November 2011– December 2012 
Table A-2. Internal (BLM) data sources.—Continued 

Analysis Dataset Source Data Type Publication Date or Received Date 

Oil & Gas Wells (AFMSS) BLM Automated Fluid Minerals Support System (AFMSS) Database Point December 2012 

Wild Horse and Burro Areas (USFS) USFS1 Enterprise Data Warehouse Polygon May 2012 

Wild Horse and Burro Herd Management 

Areas (BLM ) BLM GSSP Polygon May 2012 

Valid Existing Rights

Federal Fluid Minerals—Areas Closed to 

Oil and Gas Leasing Individual BLM State, District and Field offices Polygon November 2011– December 2012 

Oil and Gas leases Individual BLM State, District and Field offices Polygon October 2011– May 2012 

Oil and Gas leases—Held by Production Individual BLM State, District and Field offices Polygon October 2011– May 2012 

Oil Shale Leases Individual BLM State, District and Field offices Polygon November 2011– December 2012 

Solar Right of Ways—Approved and Authorized Individual BLM State, District and Field offices Polygon November 2011– May 2012 

Wind Energy Rights of Way—Approved 

and Authorized Individual BLM State, District and Field offices Polygon November 2011– May 2012 

Potential Threat

Fire Probability USFS1—Missoula Fire Sciences Laboratory, Fire Program Analysis System, “High” category, NIFC Raster May 2012 

1 The U.S. Forest Service makes no warranty, expressed or implied, including the warranties of merchantability and fitness for a particular purpose, nor assumes any legal liab

accuracy, reliability, completeness or utility of these geospatial data, or for the improper or incorrect use of these geospatial data. These geospatial data and related maps or graphare not intended to be used as such. The data and maps may not be used to determine title, ownership, legal descriptions or boundaries, legal jurisdiction, or restrictions that may private land. Natural hazards may or may not be depicted on the data and maps, and land users should exercise due caution. The data are dynamic and may change over time. Ththe limitations of the geospatial data and to use the data accordingly.
Table A-3. External data sources Analysis Dataset Source Data Type Publication Date or Received Date Data Currency Date Base and Greater Sage-Grouse Habitat Preliminary General Habitat Individual State BLM offices and State wildlife agencies Polygon September 2011– June 2012 June 2012 http://www.blm.gov/wo/st/en/pro

documents_and_resources.htm

Preliminary Priority Habitat Individual State BLM offices and State wildlife agencies Polygon September 2011– June 2012 June 2012 http://www.blm.gov/wo/st/en/pro

documents_and_resources.htm

WAFWA management zones, Version 2 Western Association of Fish and Wildlife Agencies Polygon October 2006 October 2006 http://sagemap.wr.usgs.gov/ftp/S

ver2_20061018.zip Current Distribution of sage-grouse Western Association of Fish and Wildlife Agencies Polygon February 2002 1999 http://sagemap.wr.usgs.gov/FTPgrouse_distribution_sgca.zip Sage-grouse Breeding Bird Density BLM August 2010 August 2010 http://www.blm.gov/wo/st/en/prosage-grouse-conservation/bird

Sage-grouse Populations Western Association of Fish and Wildlife Agencies Polygon 2004 2004 http://sagemap.wr.usgs.gov/ftp/s

and http://sagemap.wr.usgs.gov/ftp

Sage-grouse lek spatial connectivity USGS (SAB) Polygon June 2010 December 2007 http://sagemap.wr.usgs.gov/ftp/sDistribution of sagebrush Western Association of Fish and Wildlife Agencies Polygon 2011 2006 http://sagemap.wr.usgs.gov/ftp/sSage-grouse Genetic Sampling Sites Oyler-McCance and others, 2005b Point 2005 2005 See Oyler-McCance and others, Sagebrush Biomes Western Association of Fish and Wildlife Agencies Polygon 2004 2004 http://sagemap.wr.usgs.gov/FTP

provinces_sgca.zip Conservation Conservation Easements National Conservation Ease- ment Database, Version 1 Polygon August 2011 August 2011 http://databasin.org/ NPS Lands Protected Areas Database, V 1.2 Polygon April 2011 February 2011 http://gapanalysis.usgs.gov/padu

Private Conservation Lands Protected Areas Database, V 1.2 Polygon April 2011 February 2011 http://gapanalysis.usgs.gov/paduWilderness (NPS and FWS) Protected Areas Database, V 1.2 Polygon April 2011 February 2011 http://gapanalysis.usgs.gov/paduWildlife Refuges (Other) Protected Areas Database, V 1.2 Polygon April 2011 February 2011 http://gapanalysis.usgs.gov/paduWildlife Refuges (USFWS) National Wildlife Refuge Boundary and Parcel Data Polygon April 2011 May 2011 http://www.fws.gov/GIS/data/Ca

Boundaries.zip
Table A-3. External data sources.—Continued

Analysis Dataset Source Data Type Publication Date or Received Date Data Currency Date

Current Threat

Agriculture—Cropland

National Agricultural Statistics Service Cropland Data 

Layer, crop categories

Raster June 2012 2011 http://nassgeodata.gmu.edu/Crop

Cheatgrass Probability Model

Meinke and others, 2009; Mike 

Pellant, personal communication

Polygon June 2012 2008 http://sagemap.wr.usgs.gov/ftp/s

Communication Towers Federal Communications Commission Point July 2009 April 2009 http:/wireless.fcc.gov/geographi

Oil & Gas Wells (buffered points) Enerdeq IHS database Point December 2011 October 2001– November 2011 Licensed proprietary data set ht

oil-gas-information/index.asp

Pinyon-Juniper & Conifer 

Encroachment (derived)

National GAP Analysis 

Program Raster February 2010 February 2010 http://gapanalysis.usgs.gov/

Power lines (>115kv) and Associated 

Structures

EV Energy Map, Platts/Global 

Energy Line September 2005 September 2005 Licensed proprietary data set http

Power lines in the Western United 

States, 2004

ICBEMP existing utility 

corridors data set Line 2004 2003 http://sagemap.wr.usgs.gov/ftp/r

hf.shp

Railroads

 Federal Railroad Administration (FRA) Rail Lines of 

the USA

Line July 2011 July 2011 http://app.databasin.org/app/pa

8a6878c3004fb38e59a6b08f9

Roads (interstates, highways, and 

secondary)

Tele Atlas ESRI StreetMap 

Premium for ArcGIS v 9.0, Dynamap Transportation version 5.2, 2003

Line April 2008 July 2003 ESRI Data & Maps is available 

software.

Urbanized Areas—City Limits Tele Atlas ESRI StreetMap Premium for ArcGIS v 9.0 Polygon April 2008 April 2008 ESRI Data & Maps available as Vertical Structures Federal Aviation Administration Digital Obstacles File Point December 2011 September 2011 https://nfdc.faa.gov/tod/public/TWater Developments BLM Rangeland Improvement Project Database Polygon October 2007 October 2007 http://sagemap.wr.usgs.gov/ftp/s

RIPS.zip
Analysis Dataset Source Data Type Publication Date or Received Date Data Currency Date Wind Towers Federal Aviation Administration Digital Obstacles File Point December 2011 September 2011 https://nfdc.faa.gov/tod/public/T

Potential Threat Coal Potential Americas Coal Potential— USGS Polygon January 2008 January 2006 http://pubs.usgs.gov/of/2008/125

Geothermal Potential Idaho National Engineering & Environmental Laboratory Polygon November 2003 May 2003 www.inel.gov Oil and Gas Potential Copeland, H., K. Doherty, D. Naugle, A. Pocewicz, J. Kiesecker (2010) Mapping Oil and Gas Development Potential Raster 2009 2009 http://www.plosone.org/article/ info%3Adoi%2F10.1371%2FjOil Shale and Tar Sands Oil Shale and Tar Sands Pro- grammatic Environmental Impact Statement (PEIS)— Argonne National Laboratory Polygon 2008 1980–2008 http://ostseis.anl.gov/guide/mapSolar Potential National Renewable Energy Laboratory Polygon December 2005 December 2005 http://www.nrel.gov/gis/data_soWind Potential National Renewable Energy Laboratory Polygon December 2010 2003 http://www.nrel.gov/gis/data_wi

Table A-3. External data sources.—Continued
Table A-4. Summary of research documenting specific consequences, land-use development, and anthropogenic activities and infrastructure on Gr

Threat or Issue Location Comparison Covariate Investigated Spatial Scale(s) Investigated Sage-Grouse Response Comment 

Agricultural 

Conversion

Wyoming, 

Montana, and Colorado 

Lek count 

comparison

Proportion of 

land area converted from sagebrush

Variable scales 

surrounding leks

Conversion of ≥16% of 

sagebrush-dominated area around leks correlated with a 50 to 100% decline in male lek occupancy

Review of several s

Agricultural 

Conversion Historic range

Currently 

occupied compared to unoccupied

Proportion of 

land area in cropland

2,975 km2 around 

random points

Cropland exceeding 25% 

associated with extirpated range

Agricultural 

Conversion Historic range

Currently 

occupied compared to unoccupied

Proportion of 

land area in cropland

1,018 km2 around 

random points

Sagebrush cover <27% 

associated with extirpated range

Extirpated range ha

times more area agriculture compto occupied rang

Agricultural 

Conversion Montana Lek count comparison Proportion of land area in cropland 202 km2 of study area

Conversion of 30% of 

sagebrush-dominated habitat patches resulted in 73% decline in number of breeding males on leks

Habitats converted 

used by sage-gropredominantly in winter

Agricultural 

Conversion Current range Lek count comparison Proportion of land area in cropland 5 km (79 km2) and 18 km (1,018 km2) buffers of leks Decline in lek trends to 2.5% of the area within 5 km or 1.5% of the area within 18 km of leks was cropland

Lek counts stabilize

as percent croplaincreased beyond proportions; few occurred in areas proportion of agrtural land exceed50% 

Infrastructure—

Roads

Wyoming, 

Utah

Lek activity 

comparison

Distance to 

Interstate 80

7.5 km and 15 

km buffer of Interstate 80

No leks within 2 km of the 

interstate; reduced numbers of leks within 7.5 km of the interstate compared to numbers of leks 7.5 to 15 km from interstate

Infrastructure—

Roads

Wyoming, 

Utah

Lek count 

comparison

Distance to 

Interstate 80

7.5-km and 15-

km buffer of Interstate 80

Higher rates of decline in the 

number of males on leks (1970–2003) within 7.5 km compared to leks 7.5 to 15 km from the interstate
Table A-4. Summary of research documenting specific consequences, land-use development, and anthropogenic activities and infrastructure on Gr

—Continued Threat or Issue Location Comparison Covariate Investigated Spatial Scale(s) Investigated Sage-Grouse Response Comment 

Infrastructure— Roads Montana, Canada Comparison of occurrence of large (>25 males) vs. small leks Length of road (road density) 3.2-km buffer of leks Probability of occurrence of large lek approached 0% as the length of road exceeded 100 km Infrastructure— Roads Colorado Lek count comparison Traffic volumes Unspecified Increased traffic (coal mine road upgrade) correlated with 94% decline in number of sage-grouse over a 5-year period on leks <2 km from road Infrastructure— Roads Wyoming Lek count comparison Traffic volumes 3-km buffer of leks Decline in lek counts positively correlated with increased traffic volumes Vehicle activity on 

when grouse preon leks had greatinfluence on malattendance comproads with no vehactivity during thperiod 

Infrastructure— Roads Wyoming Females breeding on impacted vs. unimpacted leks; nest site selection Impacted leks within 3 km of road N/A (study area) Females from impacted leks: had 24% lower probability of initiating a nest; moved twice as far from lek to nest; were less likely to initiate nests in consecutive years compared to females from non-impact- ed leks 

Infrastructure— Transmission Lines Utah Lek count comparison Distance to transmis- sion line 200-m buffer of leks 72% decline in number of sage- grouse on a lek 2 years post- transmission line erection Daily dispersal patt

from a lek during breeding season rupted 

Infrastructure—

Transmission Lines Colorado Pellet occurrence

Distance to 

transmission line Unspecified

Pellet occurrence increased as 

distance from transmission line increased up to 600 m
Threat or Issue Location Comparison Covariate Investigated Spatial Scale(s) Investigated Sage-Grouse Response Comment 

Infrastructure—

Power Lines Wyoming Lek activity comparison

Distance to 

power line; Proportion of land area within 350 m of power line

Multiple buffers 

to 6.4 km (129 km2) of leks

Probability of an active lek 

decreased with closer proximity to poles and increasing 

proportion of area within 350 m of power line within 6.4 km of lek

Infrastructure—

Transmission Lines Wyoming

Sage-grouse 

female nesting and broodrearing (early and late) occurrence

Distance to 

transmission line N/A (study area)

Sage-grouse avoided broodrearing habitats within 

4.7 km of transmission line

Infrastructure—

Fences Idaho Collision occurrence

Lek size; Distance to lek; 

Topography; Fence density

2.5-km buffer 

of leks

Probability of collision higher 

in areas with (1) increased fence density; (2) decreased distance to nearest lek; (3) increased lek size; (4) lower topographic ruggedness

Collisions more com

on fences construof steel t-posts anor with large distances between p(decreased visibi

Energy development—

Natural gas

Eastern range 

of species

Lek count 

comparison

Well pad 

densities

3.2-km buffer 

of leks

Well pad densities exceeding 

1 pad/mi2 (section) negatively influence number of 

sage-grouse on leks

Review of several s

Energy development—

Natural gas Wyoming Lek count comparison Well pad densities 8.5-km buffer of leks

Impacts to the number of sagegrouse on leks found at well 

pad densities >0.4 to 0.8 well pads/km2 (0.15 to 0.3 

pads/section)

Common well pad 

densities of 1.5 a3.1 pads/km2 (4 a

pads/section) assated with lek coudeclines ranging 13–74% and 77–respectively

Table A-4. Summary of research documenting specific consequences, land-use development, and anthropogenic activities and infrastructure on Gr

—Continued
Table A-4. Summary of research documenting specific consequences, land-use development, and anthropogenic activities and infrastructure on Gr

—Continued Threat or Issue Location Comparison Covariate Investigated Spatial Scale(s) Investigated Sage-Grouse Response Comment 

Energy development— Natural gas Wyoming Lek activity comparison Well pad densities 1-km buffer of leks 0% probability of lek occurrence when well pad densities exceeded 6.5 pads/mi2 (section) 

Energy development— Natural gas Montana, Canada Comparison of occurrence of large (>25 males) vs. small leks Well pad densities 12.3-km buffer of leks Large leks did not occur in areas where well pad densities exceeded 2.5 pad/ mi2 (section) 

Energy development— Natural gas Wyoming Lek count comparison Distance to well pads (pad presence (1) vs. absence (0) within buffers of leks) Multiple buffers to 4.8 km of leks Well pads within smaller buf- fers (<1.6–2 km) around leks associated with 35–76% fewer sage-grouse on leks compared to leks with no well pads within these buffers Leks that had at lea

well pad within 0had 35 to 92% fesage-grouse comto leks with no wpads within this b

Energy development— Natural gas Eastern range of species Lek count comparison Distance to well pads N/A (study area) Impacts to the number of males on leks were most severe when infrastructure occurred near leks; impacts remained discernible out to distances of 6.2 to 6.4 km Review of several sEnergy development— Natural gas Wyoming Sage-grouse female nesting occurrence Distance to well pads N/A (study area) Yearling females avoided nesting within 950 m of well pads 

Energy development—

Natural gas Wyoming

Sage-grouse 

female nesting and broodrearing (early and late) occurrence

Distance to 

well pads; proportion of buffer disturbed by gas development activities

Multiple buffers to 

1.26 km (5 km2) 

of seasonally selected sites

Females avoided nesting 

and brood-rearing in areas with increased numbers of visible wells within a 1-km2 

area; females avoided sites when the proportion of a 5-km2 area disturbed by gas 

development exceeded 8% 
Threat or Issue Location Comparison Covariate Investigated Spatial Scale(s) Investigated Sage-Grouse Response Comment 

Energy development—

Natural gas Wyoming

Sage-grouse 

chicks survival

Proportion 

of buffer disturbed by gas development activities

Multiple buffers to 

1.26 km (5 km2) 

of seasonally selected sites

Chick survival decreased when 

the proportion of a 1-km2

area disturbed by gas development exceeded 4% 

Energy development—

Natural gas Canada

Sage-grouse 

chicks survival

Well pad 

densities

Multiple buffers 

to 1 km (3 km2) 

of seasonally selected sites

Chick survival decreased with 

increasing numbers of visible wells within 1 km of broodrearing locations

Energy development—

Natural gas Canada

Sage-grouse 

winter occurrence

Distance to 

well pads N/A (study area)

Sage-grouse avoided habitats 

within 1.9 km of infrastructure during winter 

Energy development—

Wind Wyoming

Sage-grouse 

nest and chick survival

Distance 

to wind turbine

N/A (study area)

Nest and chick survival 

decreased as distance to turbine decreased

Study investigated 

short-term responsage-grouse to a energy facility; imof the facility manot be realized wtime-frame of stu

Habitat Fragmentation Idaho Movement patterns N/A (study area) Sage-grouse used an annual range of at least 2,764 km2 

Habitat Fragmentation Historic range

Currently 

occupied compared to unoccupied

Proportion of 

land area in cropland

1,018 km2 around 

random points

Sagebrush patch size in occupied range averaged 4,173 ha 

Habitat Fragmentation Idaho, Wyoming Movement patterns N/A (study area)

Sagebrush patch sizes >4,000 

ha required for successful reproduction and over-winter survival

Habitat Fragmentation Wyoming Movement patterns N/A (study area) 314-km2 area necessary to maintain breeding habitat around a single lek 

Table A-4. Summary of research documenting specific consequences, land-use development, and anthropogenic activities and infrastructure on Gr

—Continued
Figure A-1. Model-builder process flowchart.
Publishing support provided by: 

Denver Publishing Service Center

For more information concerning this publication, contact:

Center Director, USGS Fort Collins Science Center

2150 Centre Ave., Bldg. C

Fort Collins, CO 80526-8118

(970)226-9398

Or visit the Fort Collins Science Center Web site at:

http://www.fort.usgs.gov/
Manier and others—Science Activities, Programs, and Policies That Influence Conservation of Greater Sage-Grouse—Open-File Report 2013–1098