Appendix D – The Greater Sage-Grouse Habitat Management Strategy 

Table of Contents 

Introduction ............................................................................................................................................... 136
 

COT Objective 1: Stop Population Declines And Habitat Loss...............................................................138
 

COT Objective 2: Implement Targeted Habitat Management And Restoration ......................................149
 

COT Objective 3: Develop And Implement State And Federal Conservation Strategies And Associated
 

Incentive-Based Conservation Actions And Regulatory Mechanisms......................................................150
 

COT Objective 4: Proactive Conservation Actions.................................................................................. 152
 

COT Objective 5: Development Of Monitoring Plans............................................................................. 154
 

Literature Cited ......................................................................................................................................... 180
 

COT Objective 6: Prioritize, Fund And Implement Research To Address Existing Uncertainties..........189
 

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Introduction 

The Wyoming Greater Sage-Grouse Approved Resource Management Plan Amendments (ARMPA) provides 

specific goals, objectives, management actions, and required design features for the conservation of Greater 

Sage-Grouse in Wyoming. These are the commitments made to meet the federal agencies’ national policy and 

direction for the conservation of Greater Sage-Grouse in light of the 2010 US Fish and Wildlife Service listing 

decision as warranted but precluded from listing under the Endangered Species Act. Through the National 

Planning Strategy, Bureau of Land Management (BLM), in coordination with US Fish and Wildlife Service 

(USFWS) have identified conservation measures to be included in the land use plans as the principal regulatory 

mechanisms to assure adequate conservation of the Greater Sage-Grouse and its habitat on public lands. 

The measures identified in the ARMPA have been developed in coordination with not just the USFWS, but 

also the State of Wyoming, including the Wyoming Game and Fish Department (WGFD), and local 

cooperating agencies including conservation districts and counties. 

Wyoming has established core population areas to help delineate landscape planning units by distinguishing 

areas of high biological value. These areas are based on the locations of breeding areas and are intended to 

help balance Greater Sage-Grouse habitat requirements with demand for energy development (Doherty et al. 

2011). The ARMPA is consistent with the Core Area Strategy, but contains additional restrictions to protect 

other resources, which results in added protections to Greater Sage-Grouse habitat and achieving conservation 

objectives identified in the Conservation Objectives Team (COT) report on BLM-managed public lands. The 

COT report indicates that the Core Area Strategy is a substantial regulatory mechanism that contributes to the 

conservation of Greater Sage-Grouse and balances the priorities of retaining a healthy Greater Sage-Grouse 

population on the landscape and energy development. 

This appendix will introduce the framework for implementation of Greater Sage-Grouse conservation 

measures within BLM Field Offices. Implementation is a combination of permitting activities under the 

auspices of management direction provided in the ARMPA, undertaking specific activities in pursuit of the 

goals and objectives identified in the plan and monitoring of sagebrush habitat and populations. 

The implementation framework outlined here is focused specifically towards Greater Sage-Grouse and is 

reflective of how the national strategy will be assimilated into the existing statewide implementation efforts 

currently in place in Wyoming. This framework has been developed mindful of the varying scales at which 

implementation will be evaluated at the local level to define successful conservation measures, at the state 

level to assess success of the statewide strategy, and across the species’ range. 

In 2013, the Director of the USFWS tasked staff with the development of range-wide conservation objectives 

for the sage-grouse to define the degree to which threats need to be reduced or ameliorated to conserve sagegrouse so that it is no longer in danger of extinction or likely to become in danger of extinction in the 

foreseeable future. Recognizing that state wildlife agencies have management expertise and management 

authority for sage-grouse, the USFWS created a COT of state and USFWS representatives to accomplish this 

task. 

The COT conservation framework consisted of (1) identifying sage-grouse population and habitat status and 

threats, (2) defining a broad conservation goal, (3) identifying priority areas for conservation, and (4) 

developing specific conservation objectives and measures. The COT used three parameters—population and 

habitat representation, redundancy, and resilience (Shaffer and Stein 2010, Redford et al. 2011)—as guiding 

concepts in developing the conservation goal, priority areas for conservation, conservation objectives, and 

measures. 

The COT report identified priority areas for Greater Sage-Grouse population habitats as Priority Areas for 

Conservation (PACs). PACs are recognized as key areas across the landscape that are necessary to maintain 

redundant, representative, and resilient populations of the species. The COT Report describes maintaining the 

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integrity of PACs as “the essential foundation for sage-grouse conservation.” PACs cover nearly 73 million 

acres across the West; within Wyoming, more than 15 million acres are considered priority habitat. Fifty-two 

percent of the priority habitat is BLM administered surface and 71 percent is BLM-administered minerals. 

Based upon 2007 through 2015 lek counts, PHMA in Wyoming contains an estimated 83 percent of the statewide population of Greater Sage-Grouse. 

Table 1. Greater Sage-Grouse Habitat within Wyoming 

Populations / Subpopulations: Wyoming Portion, Powder River and Wyoming Basins; Laramie; 

Jackson Hole; WAFWA Management Zones I & II 

Surface Estate Priority Area Acres (%) General Habitat Acres (%) Non-Habitat Acres (%) 

Private 5,655,716 (38) 14,028,015 (53) 7,004,437 

State 1,119,078 (7) 1,766,279 (7) 754,053 

BLM 7,823,055 (52) 9,296,487 (35) 328,750 

Other1 483,710 (3) 1,104,942 (5) 10,363,760 

Total 15,081,561 26,650,412 18,451,000 

Fluid Mineral 

Estate 

Priority Area Acres (%) General Habitat Acres (%) Non-Habitat Acres 

Non-federal 4,360,416 (29) 10,450,584 (40) 6,433,438 

BLM Managed2 10,721,145 (71) 15,745,138 (60) 12,017,562 

Total 15,081,561 26,195,722 

1

Excludes Wind River Indian Reservation Acreages 

2

BLM Managed Minerals includes 10,335,190 acres within National Parks, State Parks and Historic Sites, National 

Forests, National Wildlife Refuges and DOD Reservations. Of this total, BLM has jurisdiction on only 1,682,372 

acres. 

The conservation objectives identified in the COT Report, targeted at maintaining redundant, representative, 

and resilient sage-grouse habitats and populations, is the basis on which Wyoming’s Sage-grouse Proposed 

RMP Amendments were developed. Due to the variability in ecological conditions and the nature of the threats 

across the range of the sage-grouse, developing detailed, prescriptive species or habitat actions was not 

attainable at the range-wide scale. Specific strategies and actions necessary to achieve the conservation 

objectives have been developed by the BLM in cooperation with state and local governments to ensure 

implementation of activities to meet the objectives identified in the COT report. 

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COT Objective 1: Stop Population Declines and Habitat Loss 

“There is an urgent need to ‘stop the bleeding’ of continued population declines and habitat 

losses by acting immediately to eliminate or reduce the impacts contributing to population 

declines and range erosion. There are no populations within the range of sage-grouse that 

are immune to the threat of habitat loss and fragmentation (COT report 2013).” 

The COT report identified a series of threats to Greater Sage-Grouse habitat and the extent of those threats at 

the population scale. The management actions identified in the ARMPA were specifically designed to reduce 

the threats, as they were identified. The Wyoming RMPs encompass lands within WAFWA Management 

Zones 1 and 2. To ensure that the threats are adequately addressed by the ARMPA, a strategy for reviewing 

activities and projects on public lands to determine the extent of their impact on Greater Sage-Grouse habitat 

has also been developed. The following outlines the process by which all activities on public lands will be 

reviewed. 

The BLM will ensure that any activities or projects in Greater Sage-Grouse habitats would: 1) only occur in 

compliance with the Wyoming BLM’s Greater Sage-Grouse goals and objectives for priority management 

areas; and 2) maintain neutral or positive Greater Sage-Grouse population trends and habitat by avoiding, 

minimizing, and offsetting unavoidable impacts to assure a conservation gain at the scale of this land use plan 

and within Greater Sage-Grouse population areas, state boundaries, and WAFWA Management Zones through 

the application of mitigation for implementation-level decisions. The mitigation process will follow the 

regulations from the White House Council on Environmental Quality (CEQ) (40 CFR 1508.20; e.g. avoid, 

minimize, and compensate), hereafter referred to as the mitigation hierarchy, while also following Secretary 

of the Interior Order 3330 and consulting BLM, USFWS and other current and appropriate mitigation 

guidance. If it is determined that residual impacts to Greater Sage-Grouse from implementation-level actions 

would remain after applying avoidance and minimization measures to the extent possible, compensatory 

mitigation projects will be used to offset residual impacts, or the project may be deferred or denied if necessary 

to achieve the goals and objectives for priority and general management areas in the Wyoming BLM RMPs. 

To ensure that impacts from activities proposed in sage-grouse Core Areas are appropriately approved and 

mitigated as necessary, the BLM will apply mitigation measures and conservation actions and potentially 

modify the location, design, construction, and/or operation of proposed land uses or activities to comply with 

statutory requirements for environmental protection. The mitigation measures and conservation actions 

(Appendix C) for proposed projects or activities in these areas will be identified as part of the National 

Environmental Policy Act (NEPA) environmental review process, through interdisciplinary analysis involving 

resource specialists, project proponents, government entities, landowners or other surface management 

agencies. Those measures selected for implementation will be identified in the record of decision (ROD) or 

decision record (DR) for those authorizations and will inform a potential lessee, permittee, or operator of the 

requirements that must be met when using BLM-administered public lands and minerals to mitigate, per the 

mitigation hierarchy referenced above, impacts from the activity or project such that sage-grouse goals and 

objectives are met. Because these actions create a clear obligation for the BLM to ensure any proposed 

mitigation action adopted in the environmental review process is performed, there is assurance that mitigation 

will lead to a reduction of environmental impacts in the implementation stage and include binding mechanisms 

for enforcement (CEQ Memorandum for Heads of Federal Departments and Agencies 2011). 

To achieve the goals and objectives for core areas in the ARMPA, the BLM will assess all proposed land uses 

or activities such as road, pipeline, communication tower, or power line construction, fluid and solid mineral 

development, range improvements, and recreational activities proposed for location in core areas in a stepwise manner. The following steps identify a screening process for review of proposed activities or projects in 

these areas. This process will provide a consistent approach and ensure that authorization of these projects, if 

granted, will appropriately mitigate impacts and be consistent with ARMPA goals and objectives for sagegrouse. The following steps provide for a sequential screening of proposals. 

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Step 1 – Determine Proposal Adequacy 

This screening process is initiated upon formal submittal of a proposal for authorization for use of BLM lands. 

The actual documentation of the proposal would include at a minimum a description of the location, scale of 

the project and timing of the disturbance. The acceptance of the proposal(s) for review would be consistent 

with existing protocol and procedures for each type of use. Evaluating consistency with (at a minimum) state 

sage-grouse regulations. 

Step 2 – Evaluate Proposal Consistency with ARMPA 

Step 2.1 –The proposal will be reviewed to determine whether it would be allowed as prescribed in the 

ARMPA. For example, some activities or types of development are prohibited in sage-grouse habitat, such as 

wind developments in priority habitat. Evaluation of projects will also include an assessment of the current 

state of the adaptive management hard and soft triggers. If the proposal is for an activity that is specifically 

prohibited, the applicant should be informed that the application is being rejected since it would not be 

allowed, regardless of the design of the project. 

Step 2.2 –The proposal will be reviewed to determine whether it conforms with the Density and Disturbance 

Limitations. If the proposed activity occurs within a priority habitat management area (PHMA), evaluate 

whether the disturbance from the activity exceeds the limit on the amount of disturbance allowed within the 

activity or project area (Density/Disturbance Calculation Tool [DDCT] process). If current disturbance within 

the activity area or the anticipated disturbance from the proposed activity exceeds this threshold, the project 

would be deferred until such time as the amount of disturbance within the area has been reduced below the 

threshold, redesigned so as to not result in any additional surface disturbance (collocation) or redesigned to 

move it outside of PHMA. Should the project be a result of a valid existing right, BLM will work to minimize 

the disturbance and determine any residual impacts that may require appropriate mitigation. 

The maximum density of disruptive activities and surface disturbance allowed will be analyzed via the DDCT, 

and will be conducted by the Federal Land Management Agency on federal land and the project proponent on 

non-federal (private, state) land based on the ARMPA. 

State agency permit is needed, without a need for a federal permit: 

The first point of contact for addressing sage-grouse issues for any state permit application should be the 

WGFD. Project proponents (proponents) need to have a thorough description of their project and identify the 

potential effects on sage-grouse prior to submitting an application to the permitting agency. Project proponents 

should contact WGFD at least 45-60 days prior to submitting their application. More complex projects will 

require more time. It is understood that WGFD has a role of consultation, recommendation, and facilitation, 

and has no authority to either approve or deny the project. The purpose of the initial consultation with the 

WGFD is to become familiar with the project proposal and ensure the project proponent understands the 

DDCT and recommended stipulations. 

Federal agency permit is needed, with or without a state permit: 

When a project requires federal action prior to approval, the proponent should contact the federal agency 

responsible for reviewing the action. The federal agency and the proponent will determine the best process for 

completing the DDCT and receiving recommendations from WGFD. Project proponents (proponents) need to 

have a thorough description of their project and identify the potential effects on sage-grouse prior to submitting 

an application to the permitting agency. 

Maximum Density and Disturbance Process 

Density and Disturbance Calculation: The Density and Disturbance Calculation Tool, or DDCT, is a 

spatially-based tool that calculates both the average density of disruptive activities and total surface 

disturbance within the area affected by the project, or DDCT assessment area. The DDCT assessment area is 

created based on buffers around proposed projects (first buffer) in protected sage-grouse core areas, and 

subsequent buffers around any occupied, core area leks within the first buffer. A four mile buffer is used to 

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identify 75% of the sage-grouse use around a lek. All activities will be evaluated within the context of 

maximum allowable disturbance (disturbance percentages, location and number of disturbances) of suitable 

sage-grouse habitat within the DDCT assessment area. This tool allows for better siting of projects rather than 

averaging the density/disturbance calculation per section. 

All lands within core area boundaries are is considered suitable habitat unless documented. Mapped unsuitable 

habitat is treated neither as suitable habitat, nor disturbance, which results in the area being removed from the 

DDCT assessment area altogether. 

1. Density/Disturbance Calculation Tool (DDCT): Determine all occupied leks within a core population 

area that may be affected by the project by placing a 4 mile boundary around the project boundary (as 

defined by the proposed area of disturbance related to the project). All occupied leks located within 

the 4 mile boundary and within a core population area will be considered in this assessment. 

A four-mile boundary will then be placed around the perimeter of each of these lek(s). 

The core population area within the combined 4 mile buffer around both the leks and the 

project boundary creates the DDCT assessment area for each individual project. 

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Disturbance will be analyzed for the DDCT assessment area as a whole and for each individual 

lek within the DDCT assessment area. 

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Density of disruptive features will be analyzed for the DDCT assessment area as a whole and 

for each individual lek within the DDCT assessment area. 

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If there are no leks identified for this assessment within the 4 mile boundary around the project boundary, the 

DDCT assessment area will be that portion of the 4 mile project boundary within the core population area. 

2. Density and Disturbance analysis: The total number of discrete disruptive activity features, as well as 

the total disturbance acres within the DDCT assessment area will be determined through an evaluation 

of: 

a. Existing disturbance (sage-grouse habitat that is disturbed due to existing anthropogenic 

activity and wildfire). 

b. Approved permits (that have approval for on the ground activity) not yet implemented. 

c. Validating digitized disturbance through on the ground evaluation. 

The complete analysis package (DDCT results, mapbook, and Worksheet), and recommendations developed 

by consultation and review outlined herein will be forwarded to the appropriate permitting agency(s). WGFD 

recommendations will be included, as will other recommendations from project proponents and other 

appropriate agencies. Project proponent shall have access to all information used in developing 

recommendations. Where possible and when requested by the project proponent, state agencies shall provide 

the project proponent with potential development alternatives other than those contained in the project 

proposal. 

If the permit for which a proponent has applied expires, another DDCT analysis is required before issuing a 

new permit. An additional DDCT is not required for permit extensions or renewals when no changes are being 

authorized. Any project will need to comply with the current Executive Order. 

Step 2.3 – The BLM’s goal for any new activity or development proposal within core areas is to provide 

consistent implementation of project proposals which meet the BLM’s ARMPA goals and the population 

management objectives of the state. Activities would be consistent with the strategy where it can be 

sufficiently demonstrated that no declines to core populations would be expected as a result of the proposed 

action. Published research suggests that impacts to sage-grouse leks associated primarily with infrastructure 

and energy development are discernible at a distance of at least 4 miles and that many leks within this radius 

have been extirpated as a direct result of development (Walker et al. 2007, Walker 2008). Research also 

suggests that an evaluation of habitats and sage-grouse populations that attend leks within an 11-mile radius 

from the project boundary in the context of “large” projects may be appropriate in order to consider all seasonal 

habitats that may be affected for birds that use the habitats associated with the proposal during some portion 

of the life-cycle of seasonally migratory sage-grouse (Connelly et al. 2000). 

To determine the manner in which Greater Sage-Grouse may be impacted by proposed undertakings, the 

following will be reviewed in the site specific NEPA analysis to quantify the effects: 

•	 Greater Sage-Grouse habitat delineation maps. 

•	 Current science recommendations. 

•	 The ‘Base Line Environment Report’ (USGS) which identifies areas of direct and indirect effect for 

various anthropogenic activities. 

•	 Consultation with agency or state wildlife agency biologist. 

•	 Other methods needed to provide an accurate assessment of impacts. 

If the proposal will not have a direct or indirect impact on either the habitat or population, document the 

findings in the NEPA and proceed with the appropriate process for review, decision and implementation of 

the project. 

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Step 3–Apply Avoidance and Minimization Measures to Comply with Sage-Grouse Goals and 

Objectives 

If the project can be relocated so as to not have an impact on sage-grouse and still achieve objectives of the 

proposal and the disturbance limitations, relocate the proposed activity and proceed with the appropriate 

process for review, decision and implementation (NEPA and Decision Record). This Step does not consider 

redesign of the project to reduce or eliminate direct and indirect impacts, but rather authorization of the project 

in a physical location that will not impact Greater Sage-Grouse. If the preliminary review of the proposal 

concludes that there may be adverse impacts to sage-grouse habitat or populations in Step 2 and the project 

cannot be effectively relocated to avoid these impacts, proceed with the appropriate process for review, 

decision and implementation (NEPA and Decision Record) with the inclusion of appropriate mitigation 

requirements to further reduce or eliminate impacts to sage-grouse habitat and populations and achieve 

compliance with sage-grouse objectives. Mitigation measures could include design modifications of the 

proposal, site disturbance restoration, post project reclamation, etc. (see Appendix C) Compensatory or offsite 

mitigation may be required (Step 4) in situations where residual impacts remain after application of all 

avoidance and minimization measures. 

Step 4 – Apply Compensatory Mitigation or Reject / Defer Proposal 

If screening of the proposal has determined that direct and indirect impacts cannot be eliminated through 

avoidance or minimization, evaluate the proposal to determine if compensatory mitigation can be used to 

offset the remaining adverse impacts and achieve sage-grouse goals and objectives. If the impacts cannot be 

effectively mitigated, reject or defer the proposal. The criteria for determining this situation could include but 

are not limited to: 

•	 The current trend within the priority habitat is down and additional impacts, whether mitigated or not, 

could lead to further decline of the species or habitat. 

•	 The proposed mitigation is inadequate in scope or duration, has proven to be ineffective or is unproven 

is terms of science based approach. 

•	 The project would impact habitat that has been determined to be a limiting factor for species 

sustainability. 

•	 Other site specific information and analysis that determined the project would lead to a downward 

change of the current species population or habitat and not comply with sage-grouse goals and 

objectives. 

If, following application of available impact avoidance and minimization measures, the project can be 

mitigated to fully offset impacts and assure conservation gain to the species and comply with sage-grouse 

goals and objectives, proceed with the appropriate process for review, decision and implementation (NEPA 

and Decision Record). 

Mitigation 

General 

In undertaking BLM management actions and, consistent with valid existing rights and applicable law, in 

authorizing third party actions that result in habitat loss and degradation, the BLM will require and assure 

mitigation that provides a net conservation gain to the species, including accounting for any uncertainty 

associated with the effectiveness of such mitigation. This will be achieved by avoiding, minimizing, and 

compensating for impacts by applying beneficial mitigation actions. In Wyoming, the USFWS has found that 

“the core area strategy, if implemented by all landowners via regulatory mechanism, would provide adequate 

protection for sage-grouse and their habitats in the state.” The BLM will implement actions to achieve the 

goal of net conservation gain consistent with the Wyoming Strategy (EO 2015-4). Compensatory mitigation 

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would be used when avoidance and minimization measures consistent with EO 2015-4 are inadequate to 

protect core population area Greater Sage-Grouse. 

Mitigation will follow the regulations from the White House Council on Environmental Quality (CEQ) (40 

CFR 1508.20; e.g. avoid, minimize, and compensate), hereafter referred to as the mitigation hierarchy. If 

impacts from BLM management actions and authorized third party actions that result in habitat loss and 

degradation remain after applying avoidance and minimization measures (i.e. residual impacts), then 

compensatory mitigation projects will be used to provide a net conservation gain to the species. Any 

compensatory mitigation will be durable, timely, and in addition to that which would have resulted without 

the compensatory mitigation (see glossary). 

The BLM, via the WAFWA Management Zone Greater Sage-Grouse Conservation Team, will develop a 

WAFWA Management Zone Regional Mitigation Strategy that will inform the NEPA decision making 

process including the application of the mitigation hierarchy for BLM management actions and third party 

actions that result in habitat loss and degradation. A robust and transparent Regional Mitigation Strategy will 

contribute to Greater Sage-Grouse habitat conservation by reducing, eliminating, or minimizing threats and 

compensating for residual impacts to Greater Sage-Grouse and its habitat. 

The BLM’s Regional Mitigation Manual MS-1794 serves as a framework for developing and implementing a 

Regional Mitigation Strategy. The following sections provide additional guidance specific to the development 

and implementation of a WAFWA Management Zone Regional Mitigation Strategy. 

Developing a WAFWA Management Zone Regional Mitigation Strategy 

The BLM, via the WAFWA Management Zone Greater Sage-Grouse Conservation Team, will develop a 

WAFWA Management Zone Regional Mitigation Strategy to guide the application of the mitigation hierarchy 

for BLM management actions and third party actions that result in habitat loss and degradation. The strategy 

should consider any state-level Greater Sage-Grouse mitigation guidance that is consistent with the 

requirements identified in this appendix. The Regional Mitigation Strategy should be developed in a 

transparent manner, based on the best science available and standardized metrics. 

As described in the ARMPA, the BLM will establish a WAFWA Management Zone Greater Sage-Grouse 

Conservation Team (hereafter, Team) to help guide the conservation of Greater Sage-Grouse, within 90 days 

of the issuance of the Record of Decision. The Strategy will be developed within one year of the issuance of 

the Record of Decision. 

The Regional Mitigation Strategy should include mitigation guidance on avoidance, minimization, and 

compensation, as follows: 

•	 Avoidance 

–	 Include avoidance areas (e.g. right-of-way avoidance/exclusion areas, no surface occupancy 

areas) already included in laws, regulations, policies, and/or land use plans (e.g. RMPs, state 

plans); and, 

–	 Include any potential, additional avoidance actions (e.g. additional avoidance best management 

practices) with regard to Greater Sage-Grouse conservation. 

•	 Minimization 

–	 Include minimization actions (e.g. required design features, best management practices) already 

included in laws, regulations, policies, land use plans, and/or land-use authorizations; and, 

–	 Include any potential, additional minimization actions (e.g. additional minimization best 

management practices) with regard to Greater Sage-Grouse conservation. 

•	 Compensation 

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–	 Include discussion of impact/project valuation, compensatory mitigation options, siting, 

compensatory project types and costs, monitoring, reporting, and program administration. Each 

of these topics is discussed in more detail below. 

•	 Residual Impact and Compensatory Mitigation Project Valuation Guidance 

o	 A common standardized method should be identified for estimating the value of 

the residual impacts and value of the compensatory mitigation projects, including 

accounting for any uncertainty associated with the effectiveness of the projects. 

o	 This method should consider the quality of habitat, scarcity of the habitat, and the 

size of the impact/project. 

o	 For compensatory mitigation projects, consideration of durability (see glossary), 

timeliness (see glossary), and the potential for failure (e.g. uncertainty associated 

with effectiveness) may require an upward adjustment of the valuation. 

o	 The resultant compensatory mitigation project will, after application of the above 

guidance, result in proactive conservation measures for Greater Sage-Grouse 

(consistent with BLM Manual 6840 – Special Status Species Management, section 

.02). 

•	 Compensatory Mitigation Options 

o	 Options for implementing compensatory mitigation should be identified, such as: 

- Utilizing certified mitigation/conservation bank or credit exchanges. 

- Contributing to an existing mitigation/conservation fund. 

- Authorized-user conducted mitigation projects. 

o	 For any compensatory mitigation project, the investment must be additional (i.e. 

additionality: the conservation benefits of compensatory mitigation are 

demonstrably new and would not have resulted without the compensatory 

mitigation project). 

•	 Compensatory Mitigation Siting 

o	 Sites should be in areas that have the potential to yield a net conservation gain to 

the Greater Sage-Grouse, regardless of land ownership. 

o	 Sites should be durable (see glossary). 

o	 Sites identified by existing plans and strategies (e.g. fire restoration plans, invasive 

species strategies, healthy land focal areas) should be considered, if those sites 

have the potential to yield a net conservation gain to Greater Sage-Grouse and are 

durable. 

•	 Compensatory Mitigation Project Types and Costs 

o	 Project types should be identified that help reduce threats to Greater Sage-Grouse 

(e.g. protection, conservation, and restoration projects). 

o	 Each project type should have a goal and measurable objectives. 

o	 Each project type should have associated monitoring and maintenance 

requirements, for the duration of the impact. 

o	 To inform contributions to a mitigation/conservation fund, expected costs for 

these project types (and their monitoring and maintenance), within the WAFWA 

Management Zone, should be identified. 

•	 Compensatory Mitigation Compliance and Monitoring 

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o	 Mitigation projects should be inspected to ensure they are implemented as 

designed, and if not, there should be methods to enforce compliance. 

o	 Mitigation projects should be monitored to ensure that the goals and objectives 

are met and that the benefits are effective for the duration of the impact. 

•	 Compensatory Mitigation Reporting 

o	 Standardized, transparent, scalable, and scientifically-defensible reporting 

requirements should be identified for mitigation projects. 

o	 Reports should be compiled, summarized, and reviewed in the WAFWA 

Management Zone in order to determine if Greater Sage-Grouse conservation has 

been achieved and/or to support adaptive management recommendations. 

•	 Compensatory Mitigation Program Implementation Guidelines 

o	 Guidelines for implementing the state-level compensatory mitigation program 

should include holding and applying compensatory mitigation funds, operating a 

transparent and credible accounting system, certifying mitigation credits, and 

managing reporting requirements. 

Incorporating the Regional Mitigation Strategy into NEPA Analyses 

The BLM will include the avoidance, minimization, and compensatory recommendations from the Regional 

Mitigation Strategy in one or more of the NEPA analysis’ alternatives for BLM management actions and third 

party actions that result in habitat loss and degradation and the appropriate mitigation actions will be carried 

forward into the decision. 

Implementing a Compensatory Mitigation Program 

The BLM needs to ensure that compensatory mitigation is strategically implemented to provide a net 

conservation gain to the species, as identified in the Regional Mitigation Strategy. In order to align with 

existing compensatory mitigation efforts, this compensatory mitigation program will be managed at a statelevel (as opposed to a WAFWA Management Zone or a Field Office), in collaboration with our partners (e.g. 

federal, Tribal, and state agencies). 

To ensure transparent and effective management of the compensatory mitigation funds, the BLM will enter 

into a contract or agreement with a third-party to help manage the state-level compensatory mitigation funds, 

within one year of the issuance of the Record of Decision. The selection of the third-party compensatory 

mitigation administrator will conform to all relevant laws, regulations, and policies. The BLM will remain 

responsible for making decisions that affect Federal lands. 

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COT Objective 2: Implement Targeted Habitat Management and Restoration 

“Some sage-grouse populations warrant more than the amelioration of the impacts from 

stressors to maintain sage-grouse on the landscape. In these instances, and particularly with 

impacts resulting from wildfire, it may be critical to not only remove or reduce anthropogenic 

threats to these populations but additionally to improve population health through active 

habitat management (e.g. habitat restoration). This is particularly important for those 

populations that are essential to maintaining range-wide redundancy and representation.” 

(COT report 2013) 

In many areas of Wyoming, amelioration of threats isn’t enough. Activities must be taken to enhance the 

habitat for continued success of Greater Sage-Grouse. This objective identifies the areas where ARMPA will 

put forth the commitments for habitat restoration and enhancement. 

The WGFD established local Greater Sage-Grouse working groups over 10 years ago. Each of these local 

working groups developed conservation plans which have served to guide conservation of Greater SageGrouse habitat at a local level. The management objectives for this federal land use plan were developed in 

coordination with the State of Wyoming, recognizing the ongoing work which has been done over the last 10 

years in Wyoming as a result of the conservation efforts identified by each of the local working groups. 

Upon completion of the planning process, with issuance of an Approved Plan and Record of Decision, 

subsequent implementation decisions will be put into effect by developing implementation (activity-level or 

project-specific) plans. These implementation decisions will be based upon the objectives identified in the 

Approved Plan and Record of Decisions, and will be coordinated with local working groups. 

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COT Objective 3: Develop and Implement State and Federal Conservation 

Strategies and Associated Incentive-based Conservation Actions and Regulatory 

Mechanisms. 

“To conserve sage-grouse and habitat redundancy, representation, and resilience, state and 

federal agencies, along with interested stakeholders within range of the sage-grouse should 

work together to develop a plan, including any necessary regulatory or legal tools (or use an 

existing plan, if appropriate) that includes clear mechanisms for addressing the threats to 

sage-grouse within PACs. Where consistent with state conservation plans, sage-grouse 

habitats outside of PACs should also be addressed. We recognize that threats can be 

ameliorated through a variety of tools within the purview of states and federal agencies, 

including incentive-based conservation actions or regulatory mechanisms. Federal land 

management agencies should work with states in developing adequate regulatory 

mechanisms. Federal land management agencies should also contribute to the incentivebased conservation and habitat restoration and rehabilitation efforts. In the development of 

conservation plans, entities (states, federal land management agencies, etc.) should 

coordinate with USFWS. This will ensure that the plans address the threats contributing to 

the 2010 warranted but precluded determination, and that conservation strategies will 

meaningfully contribute to future listing analyses.” (COT report 2013) 

Implementation Working Groups 

Implementation strategies for a landscape scale species requires coordination across multiple scales, as the 

work that is conducted at the local scale must be tracked and evaluated for overall success within core areas, 

the state of Wyoming across the region. As the Greater Sage-Grouse is formally managed by the State of 

Wyoming, and has a statewide strategy through Governor’s Executive Order 2011-05, implementation must 

be evaluated at that scale as well. For this reason, Wyoming Plans will utilize multiple types of working 

groups, representing each of the scales at which implementation will be tracked. 

National Level 

In December 2011, Wyoming Governor Matt Mead and Secretary of the Interior Ken Salazar co-hosted a 

meeting to address coordinated conservation of the sage-grouse across its range. Ten states within the range 

of the sage-grouse were represented, as were the Natural Resources Conservation Service (NRCS), and the 

Department of the Interior (DOI) — including representatives from the BLM and USFWS. The primary 

outcome of the meeting was the creation of a Sage-Grouse Task Force (Task Force) chaired by Governors 

Mead (Wyoming) and Hickenlooper (Colorado) and the Director of the BLM. The Task Force was directed 

to develop recommendations on how to best advance a coordinated, multi-state, range-wide effort to conserve 

the sage-grouse, including the identification of conservation objectives to ensure the long-term viability of the 

species. 

Regional Level 

Regional Level Teams (Sage-grouse Implementation Group) 

State Level 

The Sage-grouse Implementation Team (SGIT) has been established through Wyoming Legislature 

(Wyoming Statute 9-19-101(a)) to review data and make recommendations to the Governor of Wyoming 

regarding actions and funding to enhance and restore Greater Sage-Grouse habitats in Wyoming. Additionally, 

the SGIT is responsible for making recommendations to the Governor regarding regulatory actions necessary 

to maintain Greater Sage-Grouse populations and Greater Sage-Grouse habitats. 

Adaptive Management Working Group (AMWG) has been established in consultation with the SGIT to 

provide appropriate guidance for agencies with the ability to affect sage-grouse populations and/or habitat 

through their permitting authority. The AMWG includes BLM, USFWS, and State of Wyoming. 

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Local Level 

In 2000, a Local Working Group was established by the WGFD to develop and facilitate implementation of 

local conservation plans for the benefit of sage-grouse, their habitats, and whenever feasible, other species 

that use sagebrush habitats. This group prepared the Wyoming Greater Sage-Grouse Conservation Plan 

(Wyoming Sage-Grouse Working Group 2003) to provide coordinated management and direction across the 

state. In 2004, local Greater Sage-Grouse working groups were formed to develop and implement local 

conservation plans. Eight local working groups around Wyoming have completed conservation plans, many 

of which prioritize addressing past, present, and reasonably foreseeable threats at the state and local levels, 

and prescribe management actions for private landowners to improve Greater Sage-Grouse conservation at 

the local scale, consistent with Wyoming’s Core Population Area Strategy. 

Implementation Tracking 

Because the State of Wyoming continues to retain management of the species, and through implementation of 

the Executive Order, BLM Wyoming will continue to coordinate tracking of populations, disturbance and 

conservation actions. 

DDCT GIS for tracking disturbance 

Population counts 

Lek counts 

Conservation actions 

In addition to the tracking databases being maintained by the State of Wyoming, a national- Greater SageGrouse Land Use Plan Decision Monitoring and Reporting Tool is being developed to describe how the BLM 

will consistently and systematically monitor and report implementation-level activity plans and 

implementation actions for all plans within the range of sage-grouse. A description of this tool for collection 

and reporting of tabular and spatially explicit data will be included in the Record of Decision or approved 

plan. The BLM will provide data that can be integrated with other conservation efforts conducted by state and 

federal partners. 

Public Involvement 

A website where the public can quickly and easily access data concerning implementation will be developed 

and kept current on the Wyoming BLM database. Creating this website and maintaining it through the 

implementation cycle will be a vital part of implementation success. The public is welcome to provide 

implementation comments to the BLM any time during the cycle, but schedules for implementation planning 

decisions will be posted so the public can make timely comments. All Activity Plan Working Group meetings 

where recommendations are made to the BLM will be open to the public, and will provide for specific and 

helpful public involvement. This includes providing web-based information to the public prior to any Activity 

Plan Working Group meetings; such that members of the public can provide input to the working session, both 

early and mid-way through the scheduled meetings. 

The state sponsored LWG and SGIT meetings are advertised and open to the public. 

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COT Objective 4: Proactive Conservation Actions 

“Proactive, incentive based, voluntary conservation actions (e.g. Candidate Conservation 

Agreements with Assurances, Natural Resources Conservation Service programs) should be 

developed and/or implemented by interested stakeholders and closely coordinated across the 

range of the species to ensure they are complimentary and address sage-grouse conservation 

needs and threats. These efforts need to receive full funding, including funding for necessary 

personnel.” (COT report 2013) 

In addition to the conservation activities identified through implementation of the Resource Management Plan 

in coordination with the Local Working Group Conservation Plans, BLM will continue to partner with other 

agencies and stakeholders to identify conservation actions to benefit Greater Sage-Grouse habitat. Actions 

which may occur could include Candidate Conservation Agreements (CCA) with accompanying Candidate 

Conservation Agreements with Assurances (CCAA) and designation of conservation easements. 

CCAs are entered into when a potential threat to habitat is identified. BLM enters into CCAs with USFWS to 

identify potential threats and plan for conservation measures to address potential threats. The purpose of 

federal land CCAs and the accompanying non-federal CCAAs is to encourage conservation actions for species 

that are not yet listed as threatened or endangered. The goal is that enhancements in conservation can preclude 

the need for federal listing or so that conservation can occur before the status of the species has become so 

dire that listing is necessary. Although a single property owner’s activities may not eliminate the need to list, 

conservation, if conducted by enough property owners throughout the species’ range, can eliminate the need 

to list. 

The BLM will work with partners and stakeholders to develop species-specific or ecosystem-based 

conservation strategies and will work cooperatively with other agencies, organizations, governments, and 

interested parties for the conservation of sensitive species and their habitats to meet agreed on species and 

habitat management goals. Cooperative efforts are important for conservation based on an ecosystem 

management approach and will improve efficiency by combining efforts and fostering collaborative working 

relationships. 

Conservation Easements are identified private lands with Greater Sage-Grouse habitat where the private 

landowners enter into voluntary agreements with the government to give up developmental rights which may 

adversely affect habitat. The most common way these areas may be used in Wyoming is for mitigation banks. 

Allowing development within some areas of historic Greater Sage-Grouse habitat or marginal habitat will 

require appropriate mitigation. In some cases the most appropriate mitigation may be for project proponents 

to buy credits at a conservation easement, thus creating a mitigation bank. Overall, the benefit is to the Greater 

Sage-Grouse, as it reduces the overall potential for fragmented habitat by ensuring there are areas with no 

development potential which could adversely affect the viability of the species. 

To learn more about what CCAs and CCAAs are in place for Greater Sage-grouse, please see the US Fish and 

Wildlife website: http://ecos.fws.gov/speciesProfile/profile/speciesProfile.action?spcode=B06W. 

Sweetwater River Conservancy Habitat Conservation Bank 

The Sweetwater River Conservancy Habitat Conservation Bank is the first conservation bank established for 

Greater Sage-Grouse. Located in central Wyoming, the bank manages habitat for Greater Sage-Grouse 

allowing energy development and other activities to proceed on other lands within Wyoming. A conservation 

bank is a site or suite of sites established under an agreement with the USFWS, intended to protect, and 

improve habitat for species. Credits may be purchased which result in perpetual conservation easements and 

conservation projects on the land to offset impacts occurring elsewhere. The Sweetwater River Conservancy 

Habitat Conservation Bank launched with 55,000 deeded acres of Greater Sage-Grouse habitat, and could 

expand up to 700,000 acres on other lands owned by the Sweetwater River Conservancy contingent upon 

demand (USFWS 2015). 

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Wyoming Landscape Conservation Initiative 

The Wyoming Landscape Conservation Initiative is a long-term science based effort to assess and enhance 

aquatic and terrestrial habitats at a landscape scale in southwest Wyoming, while facilitating responsible 

development through local collaboration and partnership. Collaborative efforts address multiple concerns at a 

scale that considers all activities on the landscape, and can leverage resources that might not be available for 

single agency projects. Greater Sage-Grouse initiatives from the Wyoming Landscape Conservation Initiative 

have included habitat enhancement efforts (e.g., invasive weed treatment, prescribed grazing strategies), and 

Greater Sage-Grouse research studies (Wyoming Landscape Conservation Initiative 2013). 

Powder River Basin Restoration Program 

The Powder River Basin Restoration Program is a collaborative partnership to restore and enhance Greater 

Sage-Grouse habitat on a landscape level in the Powder River Basin. The basin encompasses 13,493,840 acres 

in northeast Wyoming and southeast Montana. Surface ownership is composed of approximately 70 percent 

private lands, 14 percent BLM-administered lands (including 8 percent in Wyoming and 6 percent in 

Montana), 8 percent Forest Service lands, and 8 percent States of Wyoming and Montana lands. Subsurface 

mineral ownership is 50 to 60 percent federal (BLM 2014). 

The Powder River Basin Restoration Program is focusing on areas affected by the federal oil and gas 

development that has occurred over the past decade in the Powder River Basin in northeastern Wyoming. Its 

objectives are restoring or enhancing disturbed previously suitable habitat to suitable habitat for sagebrush 

obligate species, primarily Greater Sage-Grouse. This includes multiple sites affected by coal bed natural gas 

abandonment reclamation efforts, wildfires, and noxious and invasive plants. Priority will be given to those 

areas recognized as priority habitats (e.g., core population areas and connectivity corridors). 

Habitat objectives are meeting the needs for nesting, brood-rearing, and late brood-rearing. The program 

would contribute to efforts focused on the management and control of mosquitoes carrying West Nile virus 

and would include funding, labor, treatment locations, and other needs as determined. 

Additionally, efforts would be coordinated to reduce fuels in and near Greater Sage-Grouse habitat, to enhance 

sagebrush stands, support restoration efforts, and reduce the risk of high-severity wildfire. Pine stands and 

juniper woodlands would be managed for structural diversity and to reduce fuels, especially near PHMA, 

human developments, and recreation areas. 

Natural Resource Conservation Service Sage-Grouse Initiative 

The US Department of Agriculture, NRCS Sage-Grouse Initiative (SGI) is working with private landowners 

in 11 western states to improve habitat for Greater Sage-Grouse (Manier et al. 2013). With 13.5 million acres 

of Greater Sage-Grouse habitat in private ownership within MZ II/VII (Manier et al. 2013, p. 118), a unique 

opportunity exists for the NRCS to benefit Greater Sage-Grouse and to ensure the persistence of large and 

intact rangelands by implementing the SGI. 

Participation in the SGI program is voluntary, but willing participants enter into binding contracts or easements 

to ensure that conservation practices that enhance Greater Sage-Grouse habitat, such as fence marking, 

protecting riparian areas, and maintaining vegetation in nesting areas, are implemented. Participating 

landowners are bound by a contract (usually 3 to 5 years) 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 

easements or rental payments for long-term conservation. 

While potentially effective at conserving Greater 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, meaning future funding is not guaranteed. 

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COT Objective 5: Development of Monitoring Plans 

“A robust range-wide monitoring program must be developed and implemented for sagegrouse conservation plans, which recognizes and incorporates individual state approaches. 

A monitoring program is necessary to track the success of conservation plans and proactive 

conservation activities. Without this information, the actual benefit of conservation activities 

cannot be measured and there is no capacity to adapt if current management actions are 

determined to be ineffective.” (COT report 2013) 

The Greater Sage-Grouse Monitoring Framework 

Introduction 

The purpose of this Greater Sage-Grouse Monitoring Framework (hereafter, monitoring framework) is to 

describe the methods to monitor habitats and evaluate the implementation and effectiveness of the BLM 

planning strategy (BLM IM 2012-044) to conserve the species and its habitat. The regulations for the BLM 

(43 CFR 1610.4-9) require that land use plans establish intervals and standards, as appropriate, for monitoring 

and evaluations, based on the sensitivity of the resource to the decisions involved. Therefore, the BLM will 

use the methods described herein to collect monitoring data to evaluate implementation and effectiveness of 

the Greater Sage-Grouse (hereafter, sage-grouse) planning strategy and the conservation measures contained 

in land use plans. The type of monitoring data to be collected at the land use plan scale will be described in 

the monitoring plan, which will be developed after the signing of the ROD. For a summary of the frequency 

of reporting see Attachment A. Adaptive management will be informed by data collected at any and all scales. 

To ensure the BLM has the ability to make consistent assessments about sage-grouse habitats across the range 

of the species, this framework lays out the methodology for monitoring the implementation and evaluating the 

effectiveness of BLM actions to conserve the species and its habitat through monitoring that informs 

effectiveness at multiple scales. Monitoring efforts will include data for measurable quantitative indicators of 

sagebrush availability, anthropogenic disturbance levels, and sagebrush conditions. Implementation 

monitoring results will provide information to allow the BLM to evaluate the extent that decisions from the 

BLM RMP to conserve sage-grouse and its habitat have been implemented. Population monitoring 

information will be collected by state fish and wildlife agencies and will be incorporated into effectiveness 

monitoring as it is made available. 

This multi-scale monitoring approach is necessary as sage-grouse are a landscape species and conservation is 

scale-dependent whereby conservation actions are implemented within seasonal habitats to benefit 

populations. The four orders of habitat selection (Johnson 1980) used in this monitoring framework are 

described by Connelly et al. (2003) and Stiver et al. (2014) as first order (broad scale), second order (midscale), third order (fine scale), and fourth order (site scale) to apply them to sage-grouse habitat selection. The 

various scales may show differences because of the methods used. The broad and mid-scale may provide a 

generalize direction, however the suitability baseline (pre-euro) is not considered an accurate baseline. The 

current baseline will provide better information on trends provided the data used in the analysis is sound. 

Based upon the management actions related to the BLM and Wyoming Sage-grouse Executive Order, the 

broad and mid-scale may greatly underestimate the impacts of the threats outlined in the COT report. Habitat 

selection and habitat use by sage-grouse occurs at multiple scales and is driven by multiple environmental and 

behavioral factors. Managing and monitoring sage-grouse habitats are complicated by the differences in 

habitat selection across the range and habitat utilization by individual birds within a given season. Therefore, 

the tendency to look at a single indicator of habitat suitability or only one scale limits the ability for managers 

to identify the threats to sage-grouse and to respond at the appropriate scale. For descriptions of these habitat 

suitability indicators for each scale, see the Sage-grouse Habitat Assessment Framework (HAF) (Stiver et al. 

in press). 

Monitoring methods and indicators in this monitoring framework are derived from the current peer-reviewed 

science. Range wide best-available datasets for broad and mid-scale monitoring will be acquired. If these 

exiting datasets are not readily available or are inadequate, but are necessary to effectively inform the three 

154
 
 

 

 

 

measurable quantitative indicators (sagebrush availability, anthropogenic disturbance levels, and sagebrush 

conditions), the BLM will strive to develop datasets or obtain information to fill these data gaps. Datasets that 

are not readily available to inform the fine and site scale indicators will be developed. These data will be used 

to generate monitoring reports at the appropriate and applicable geographic scales, boundaries and analysis 

units: across the range of sage-grouse as defined by Schroeder et al. (2004), and clipped by Western 

Association of Fish and Wildlife Agencies (WAFWA) Management Zone (MZ) (Stiver et al. 2006) boundaries 

and other areas as appropriate for size (e.g., populations based on Connelly et al. 2004; Figure 1). This broad 

and mid-scale monitoring data and analysis will provide context for ARMPA areas; states; Greater SageGrouse priority habitat, general habitat and other sage-grouse designated management areas; and PACs as 

defined in the Greater Sage-Grouse Conservation Objectives: Final Report (COT, U.S. Fish and Wildlife 

Service 2013). Throughout the remainder of the document, all of these areas will be referred to as “sage-grouse 

areas.” 

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Figure 1. Map of Greater Sage-Grouse Range, Populations, Subpopulations and Priority 

Areas for Conservation as of 2013 

This monitoring framework is divided into two sections. The broad- and mid-scale methods, described in the 

following section, provide a consistent approach across the range of the species to monitor implementation 

decisions and actions, mid-scale habitat attributes (e.g., sagebrush availability and habitat degradation), and 

population changes to determine the effectiveness of the planning strategy and management decisions. (See 

Table 2, Indicators for monitoring implementation of the national planning strategy, ARMPA decisions, sagegrouse habitat, and sage-grouse populations at the broad and mid scales.) For sage-grouse habitat at the fine 

156
 
 

 

 

 

 

 

 

and site scales, this monitoring framework describes a consistent approach (e.g., indicators and methods) for 

monitoring sage-grouse seasonal habitats. Funding, support, and dedicated personnel for broad- and mid-scale 

monitoring will be renewed annually through the normal budget process. For an overview of BLM multiscale 

monitoring commitments, see Attachment A. 

Table 2. Indicators for Monitoring Implementation of the Strategy, Decisions, Sage-grouse 

Habitat, and Sage-grouse Populations at the Broad and Mid-scales.
 

Implementation Habitat 

Population (State 

Wildlife 

Agencies) 

Geographic Scales Availability Degradation Demographics 

Broad Scale: From 

the range of sagegrouse to WAFWA 

Management Zones 

BLM Planning Strategy 

goal and objectives 

Distribution and 

amount of sagebrush 

within the range 

Distribution and 

amount of energy, 

mining and 

infrastructure 

facilities 

WAFWA 

Management Zone 

population trend 

Mid-scale: From 

WAFWA 

Management Zone 

to populations. 

An analysis of ARMPA 

decisions across the 

designated scale 

Mid-scale habitat 

indicators (HAF 2014; 

Table 3 e.g., percent of 

sagebrush per unit area) 

Distribution and 

amount of energy, 

mining and 

infrastructure 

facilities (Table 3) 

Individual 

population trend 

Fine Scale: 

Pacs 

A summary of DDCT 

actions related to BLM 

mineral and surface 

resources in conjunction 

with other ownerships 

Areas that have greater 

than 5% sagebrush 

cover and non-habitat 

(unsuitable) that is less 

than 0.6miles from the 

suitable habitat. 

Distribution and 

amount of 

anthropogenic 

disturbances and 

wildfire occurrences 

impacting specific 

PACs. 

PAC Trends 

Site Scale 

DDCT level 

A summary of DDCT 

actions related to BLM 

mineral and surface 

resources. 

The available occupied 

habitat using the DDCT 

process. 

Distribution and 

amount of 

anthropogenic 

disturbances and 

wildfire occurrences 

impacting specific 

PACs. 

Individual lek 

Trends 

Broad Scale: From BLM Planning Strategy Distribution and Distribution and WAFWA 

the range of sage- goal and objectives amount of sagebrush amount of energy, Management Zone 

grouse to WAFWA within the range mining and population trend 

Management Zones infrastructure 

facilities 

Mid-scale: From RMP decisions Mid-scale habitat Distribution and Individual 

WAFWA indicators (HAF 2014; amount of energy, population trend 

Management Zone Table 3 e.g., percent of mining and 

to populations. sagebrush per unit area) infrastructure 

PACs facilities (Table 3) 

Broad and Mid-Scales 

First-order habitat selection, the broad scale, describes the physical or geographical range of a species. The 

first-order habitat of the sage-grouse is defined by populations of sage-grouse associated with sagebrush 

landscapes, based on Schroeder et al. 2004, and Connelly et al. 

2004, and on population or habitat surveys since 2004. An intermediate scale between the broad and mid 

scales was delineated by WAFWA from floristic provinces within which similar environmental factors 

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influence vegetation communities. This scale is referred to as the WAFWA Sage-Grouse Management Zones 

(MZs). Although no indicators are specific to this scale, these MZs are biologically meaningful as reporting 

units. 

Second-order habitat selection, the mid-scale, includes sage-grouse populations and PACs. The second order 

includes at least 40 discrete populations and subpopulations (Connelly et al. 2004). Populations range in area 

from 150 to 60,000 mi2 and are nested within MZs. PACs range from 20 to 20,400 mi2 and are nested within 

population areas. 

Other mid-scale landscape indicators, such as patch size and number, patch connectivity, linkage areas, and 

landscape matrix and edge effects (Stiver et al. in press) will also be assessed. The methods used to calculate 

these metrics will be derived from existing literature (Knick et al. 2011, Leu and Hanser 2011, Knick and 

Hanser 2011). 

Midscale indicators using the HAF can grossly underestimate the occupation of anthropogenic activities 

because of the use of 30m pixels. The HAF removes ‘non-’habitat from the suitability availability. There are 

no parameters that are provided to protect adjacent suitable habitat from development on these non-habitat 

parcels, thus making the adjacent non-habitat a potential threat by indirect impacts. 

The Wyoming BLM field offices will be actively participating in a fine and site scale monitoring that will 

more accurately reflect the impacts associated with direct and indirect effects of anthropogenic and wildfire 

impacts. 

A. Implementation (Decision) Monitoring 

Implementation monitoring is the process of tracking and documenting the implementation (or the progress 

toward implementation) of ARMPA decisions. The BLM will monitor implementation of project-level and/or 

site-specific actions and authorizations, with their associated conditions of approval/stipulations for sagegrouse, spatially (as appropriate) within Priority Habitat, General Habitat, and other sage-grouse designated 

management areas, at a minimum, for the Wyoming Greater Sage-Grouse ARMPA planning area. These 

actions and authorizations, as well as progress toward completing and implementing activity-level plans, will 

be monitored consistently across all planning units and will be reported to BLM headquarters annually, as 

well as reported to the State of Wyoming with numerical and spatial data twice a year, and a HQ summary 

report every 5 years, for the respective planning area. A national-level Greater Sage-Grouse Land Use Plan 

Decision Monitoring and Reporting Tool is being developed to describe how the BLM will consistently and 

systematically monitor and report implementation-level activity plans and implementation actions for all plans 

within the range of sage-grouse. A description of this tool for collection and reporting of tabular and spatially 

explicit data will be included in the Record of Decision or approved plan. The BLM will provide data that can 

be integrated with other conservation efforts conducted by state and federal partners. 

B. Habitat (Vegetation) Monitoring 

The U.S. Fish and Wildlife Service (USFWS), in its 2010 listing decision for the sage-grouse, identified 18 

threats contributing to the destruction, modification, or curtailment of sage-grouse habitat or range (75 FR 

13910 2010). The BLM will, therefore, monitor the relative extent of these threats that remove sagebrush, 

both spatially and temporally, on all lands within an analysis area, and will report on amount, pattern, and 

condition at the appropriate and applicable geographic scales and boundaries. These 18 threats have been 

aggregated into three broad- and mid-scale measures to account for whether the threat predominantly removes 

sagebrush or degrades habitat. (See Table 3, Relationship between the 18 threats and the three habitat 

disturbance measures for monitoring.) The three measures are: 

1. Sagebrush Availability (percent of sagebrush per suitable unit area) 

2. Habitat Degradation (percent of human activity per unit area) 

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3. Energy and Mining Density (facilities and locations per suitable unit area) 

These three habitat disturbance measures will evaluate disturbance on all lands within priority habitat, 

regardless of land ownership. The direct area of influence will be assessed with the goal of accounting for 

actual removal of sagebrush on which sage-grouse depend (Connelly et al. 2000) and for habitat degradation 

as a surrogate for human activity. Measure 1 (sagebrush availability) examines where disturbances have 

removed plant communities that support sagebrush (or have broadly removed sagebrush from the landscape). 

Measure 1, therefore, monitors the change in sagebrush availability–or, specifically, where and how much of 

the sagebrush community is available on lands that can support sagebrush within the range of sage-grouse. 

The sagebrush community is defined as the ecological systems that have the capability of supporting sagebrush 

vegetation and seasonal sage-grouse habitats within the range of sage-grouse (see Section B.1., Sagebrush 

Availability). Measure 2 (see Section B.2., Habitat Degradation Monitoring) and Measure 3 (see Section B.3., 

Energy and Mining Density) focus on where habitat degradation is occurring within suitable sagebrush soils 

by using the footprint/area of direct disturbance and the number of facilities at the mid-scale to identify the 

relative amount of degradation per geographic area of interest and in areas that have the capability of 

supporting sagebrush and seasonal sage-grouse use. Measure 2 (habitat degradation) not only quantifies 

footprint/area of direct disturbance but also establishes a surrogate for those threats most likely to have 

ongoing activity. Because energy development and mining activities are typically the most intensive activities 

in sagebrush habitat, Measure 3 (the density of active energy development, production, and mining sites) will 

help identify areas of particular concern for such factors as noise, dust, traffic, etc. that degrade sage-grouse 

habitat. 

Table 3. Relationship between the 18 Threats and the Three Habitat Disturbance Measures 

for Monitoring. 

USFWS Listing Decision Threat Sagebrush 

Availability 

Habitat 

Degradation 

Density of 

Energy and 

Mining 

Agriculture X 

Urbanization X 

Wildfire X 

Conifer encroachment X 

Treatments X 

Invasive Species X 

Energy (oil and gas wells and development facilities) X X 

Energy (coal mines) X X 

Energy (wind towers) X X 

Energy (solar fields) X X 

Energy (geothermal) X X 

Mining (active locatable, leasable, and salable 

developments) X X 

Infrastructure (roads) X 

Infrastructure (railroads) X 

Infrastructure (power lines) X 

Infrastructure (communication towers) X 

Infrastructure (other vertical structures) X 

Other developed rights of ways X 

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Data availability may preclude specific analysis of individual layers. See the detailed methodology for more 

information. 

The methods to monitor disturbance found herein differ slightly from methods used in the Sage-Grouse 

Baseline Environmental Report (BER; Manier et al. 2013) that provided a baseline of datasets of disturbance 

across jurisdictions. One difference is that, for some threats, the data in the BER were for federal lands only. 

In addition, threats were assessed individually in that report, using different assumptions from those in this 

monitoring framework about how to quantify the location and magnitude of threats. The methodology herein 

builds on the BER methodology and identifies datasets and procedures to utilize the best available data across 

the range of the sage-grouse and to formulate a consistent approach to quantify impact of the threats through 

time. This methodology also describes an approach to combine the threats and calculate the three measures. 

B.1. Sagebrush Availability (Measure 1) 

Sage-grouse populations have been found to be more resilient where a percentage of the landscape is 

maintained in sagebrush (Knick and Connelly 2011), which will be determined by sagebrush availability. 

Measure 1 has been divided into two sub-measures to describe sagebrush availability on the landscape: 

Measure 1a: the current amount of sagebrush on the geographic area of interest, and 

Measure 1b: the amount of sagebrush on the geographic area of interest compared with the amount of 

sagebrush the landscape of interest could ecologically support. 

Measure 1a (the current amount of sagebrush on the landscape) will be calculated using this formula: [the 

existing updated sagebrush layer] divided by [the geographic area of interest]. The appropriate geographic 

areas of interest for sagebrush availability include the species’ range, WAFWA MZs, populations, and PACs. 

In some cases these sage-grouse areas will need to be aggregated to provide an estimate of sagebrush 

availability with an acceptable level of accuracy. 

Measure 1b (the amount of sagebrush for context within the geographic area of interest) will be calculated 

using this formula: [existing sagebrush divided by [pre-EuroAmerican settlement geographic extent of lands 

that could have supported sagebrush]. This measure will provide information to set the context for a given 

geographic area of interest during evaluations of monitoring data. The information could also be used to inform 

management options for restoration or mitigation and to inform effectiveness monitoring. 

The sagebrush base layer for Measure 1 will be based on geospatial vegetation data adjusted for the threats 

listed in Table 3. The following subsections of this monitoring framework describe the methodology for 

determining both the current availability of sagebrush on the landscape and the context of the amount of 

sagebrush on the landscape at the broad and mid scales. 

a. Establishing the Sagebrush Base Layer: The current geographic extent of sagebrush vegetation within 

the rangewide distribution of sage-grouse populations will be ascertained using the most recent version of the 

Existing Vegetation Type (EVT) layer in LANDFIRE (2013). LANDFIRE EVT was selected to serve as the 

sagebrush base layer for five reasons: 1) it is the only nationally consistent vegetation layer that has been 

updated multiple times since 2001; 2) the ecological systems classification within LANDFIRE EVT includes 

multiple sagebrush type classes that, when aggregated, provide a more accurate (compared with individual 

classes) and seamless sagebrush base layer across jurisdictional boundaries; 3) LANDFIRE performed a 

rigorous accuracy assessment from which to derive the rangewide uncertainty of the sagebrush base layer; 4) 

LANDFIRE is consistently used in several recent analyses of sagebrush habitats (Knick et al. 2011, Leu and 

Hanser 2011, Knick and Hanser 2011); and 5) LANDFIRE EVT can be compared against the geographic 

extent of lands that are believed to have had the capability of supporting sagebrush vegetation preEuroAmerican settlement [LANDFIRE Biophysical Setting (BpS)]. This fifth reason provides a reference 

point for understanding how much sagebrush currently remains in a defined geographic area of interest 

compared with how much sagebrush existed historically (Measure 1b). Therefore, the BLM has determined 

that LANDFIRE provides the best available data at broad and mid scales to serve as a sagebrush base layer 

for monitoring changes in the geographic extent of sagebrush. The BLM, in addition to aggregating the 

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sagebrush types into the sagebrush base layer, will aggregate the accuracy assessment reports from 

LANDFIRE to document the cumulative accuracy for the sagebrush base layer. The BLM-through its 

Assessment, Inventory, and Monitoring (AIM) program and, specifically, the BLM’s landscape monitoring 

framework (Taylor et al. 2014)-will provide field data to the LANDFIRE program to support continuous 

quality improvements of the LANDFIRE EVT layer. The sagebrush layer based on LANDFIRE EVT will 

allow for the mid-scale estimation of the existing percent of sagebrush across a variety of reporting units. This 

sagebrush base layer will be adjusted by changes in land cover and successful restoration for future 

calculations of sagebrush availability (Measures 1a and 1b). 

This layer will also be used to determine the trend in other landscape indicators, such as patch size and number, 

patch connectivity, linkage areas, and landscape matrix and edge effects (Stiver et al. in press). In the future, 

changes in sagebrush availability, generated annually, will be included in the sagebrush base layer. The 

landscape metrics will be recalculated to examine changes in pattern and abundance of sagebrush at the various 

geographic boundaries. This information will be included in effectiveness monitoring (See Section D., 

Effectiveness Monitoring). 

Within the BLM, field office–wide existing vegetation classification mapping and inventories are available 

that provide a much finer level of data than what is provided through LANDFIRE. Where available, these 

finer-scale products will be useful for additional and complementary mid-scale indicators and local-scale 

analyses (Fine and Site Scales). The fact that these products are not available everywhere limits their utility 

for monitoring at the broad and mid-scale, where consistency of data products is necessary across broader 

geographies. 

The sagebrush layer based on LANDFIRE EVT will allow for the mid-scale estimation of existing percent 

sagebrush across a variety of reporting units. This sagebrush base layer will be adjusted by changes in land 

cover and successful restoration for future calculations of sagebrush availability (Measures 1a and 1b). 

This layer will be used to determine the trend in other landscape indicators, e.g. patch size and number, patch 

connectivity, linkage areas, and landscape matrix and edge effects (Stiver et al. in press). In the future, changes 

in sagebrush availability, generated bi-annually, will be included in the sagebrush base layer. The landscape 

metrics will be recalculated to examine changes in pattern and abundance of sagebrush at the various 

geographic boundaries. This information will be included in effectiveness monitoring (See Section D). 

Data Sources for Establishing and Monitoring Sagebrush Availability 

In much the same manner as how the LANDFIRE data was selected as the data source, described above, the 

criteria for selecting the datasets (Table 4) for establishing and monitoring the change in sagebrush 

availability, Measure 1, were threefold: 

Nationally consistent dataset available across the range 

Known level of confidence or accuracy in the dataset 

Continual maintenance of dataset and known update interval 

Table 4. Datasets for Establishing and Monitoring Changes in Sagebrush Availability 

Dataset Source Update Interval Most Recent 

Version Year Use 

BioPhysical Setting 

(BpS) v1.1 

LANDFIRE Static 2008 Denominator for 

Sagebrush 

Availability (1.b.) 

Existing Vegetation 

Type (EVT) v1.2 

LANDFIRE Static 2010 Numerator for 

Sagebrush 

Availability 

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Dataset Source Update Interval Most Recent 

Version Year Use 

Cropland Data Layer 

(CDL) 

National Agricultural 

Statistics Service 

(NASS) 

Annual 2012 Agricultural Updates; 

removes existing 

sagebrush from 

numerator of 

sagebrush availability 

National Land Cover 

Dataset (NLCD) 

Percent 

Imperviousness 

Multi-Resolution 

Land Characteristics 

Consortium (MRLC) 

5 Year 2011 available in 

March 2014 

Urban Area Updates; 

removes existing 

sagebrush from 

numerator of 

sagebrush availability 

Fire Perimeters GeoMac Annual 2013 < 1,000 acres Fire 

updates; removes 

existing sagebrush 

from numerator of 

sagebrush availability 

Burn Severity Monitoring Trends in 

Burn Severity 

(MTBS) 

Annual 2012 available in 

April 2014 

> 1,000 acres Fire 

Updates; removes 

existing sagebrush 

from numerator of 

sagebrush availability 

except for unburned 

sagebrush islands 

LANDFIRE Existing Vegetation Type (EVT) Version 1.2: 

LANDFIRE EVT represents existing vegetation types on the landscape derived from remote sensing data. 

Initial mapping was conducted using imagery collected in approximately 2001. Since the initial mapping there 

have been two update efforts: version 1.1 represents changes before 2008, and version 1.2 reflects changes on 

the landscape before 2010. Version 1.2 will be used as the starting point to develop the sagebrush base layer. 

Ecological systems from the LANDFIRE EVT to be used in the sagebrush base layer were determined by 

sage-grouse subject matter experts through the identification of the ecological systems that have the capability 

of supporting sagebrush vegetation and could provide suitable seasonal habitat for the sage-grouse (Table 5). 

Two additional vegetation types that are not ecological systems were added to the EVT and are Artemisia 

tridentata ssp. vaseyana Shrubland Alliance and Quercus gambelii Shrubland Alliance. These alliances have 

species composition directly related to the Rocky Mountain Lower Montane - Foothill Shrubland ecological 

system and the Rocky Mountain Gambel Oak-Mixed Montane Shrubland ecological system, both of which 

are ecological systems in LANDFIRE BpS. In LANDFIRE EVT however, in some map zones, the Rocky 

Mountain Lower Montane - Foothill Shrubland ecological system and the Rocky Mountain Gambel OakMixed Montane Shrubland ecological system were named Artemisia tridentata ssp. vaseyana Shrubland 

Alliance and Quercus gambelii Shrubland Alliance respectively. 

Table 5. Ecological Systems in BpS and EVT Capable of Supporting Sagebrush Vegetation 

and Could Provide Suitable Seasonal Habitat for Greater Sage-Grouse. 

Ecological System Sagebrush Vegetation that the Ecological System has the 

Capability to Produce 

Colorado Plateau Mixed Low Sagebrush Shrubland 

Artemisia arbuscula ssp. longiloba 

Artemisia bigelovii 

Artemisia nova 

Artemisia frigida 

Artemisia tridentata ssp. wyomingensis 

162
 
 Ecological System Sagebrush Vegetation that the Ecological System has the 

Capability to Produce 

Columbia Plateau Scabland Shrubland Artemisia rigida 

Great Basin Xeric Mixed Sagebrush Shrubland 

Artemisia arbuscula ssp. longicaulis 

Artemisia arbuscula ssp. longiloba 

Artemisia nova 

Artemisia tridentata ssp. wyomingensis 

Inter-Mountain Basins Big Sagebrush Shrubland 

Artemisia tridentata ssp. tridentata 

Artemisia tridentata ssp. xericensis 

Artemisia tridentata ssp. vaseyana 

Artemisia tridentata ssp. wyomingensis 

Inter-Mountain Basins Mixed Salt Desert Scrub 

Artemisia tridentata ssp. wyomingensis 

Artemisia spinescens 

Wyoming Basins Dwarf Sagebrush Shrubland and 

Steppe 

Artemisia arbuscula ssp. longiloba 

Artemisia nova 

Artemisia tridentata ssp. wyomingensis 

Artemisia tripartita ssp. rupicola 

Columbia Plateau Low Sagebrush Steppe 

Artemisia arbuscula 

Artemisia arbuscula ssp. longiloba 

Artemisia nova 

Inter-Mountain Basins Big Sagebrush Steppe 

Artemisia cana ssp. cana 

Artemisia tridentata ssp. tridentata 

Artemisia tridentata ssp. xericensis 

Artemisia tridentata ssp. wyomingensis 

Artemisia tripartita ssp. tripartita 

Artemisia frigida 

Inter-Mountain Basins Montane Sagebrush Steppe 

Artemisia tridentata ssp. vaseyana 

Artemisia tridentata ssp. wyomingensis 

Artemisia nova 

Artemisia arbuscula 

Artemisia tridentata ssp. spiciformis 

Northwestern Great Plains Mixed grass Prairie 

Artemisia cana ssp. cana 

Artemisia tridentata ssp. vaseyana 

Artemisia frigida 

Northwestern Great Plains Shrubland 

Artemisia cana ssp. cana 

Artemisia tridentata ssp. tridentata 

Artemisia tridentata ssp. wyomingensis 

Western Great Plains Sand Prairie Artemisia cana ssp. cana 

Western Great Plains Floodplain Systems Artemisia cana ssp. cana 

Columbia Plateau Steppe and Grassland Artemisia spp. 

Inter-Mountain Basins Semi-Desert Shrub-Steppe 

Artemisia tridentata 

Artemisia bigelovii 

Artemisia tridentata ssp. wyomingensis 

Rocky Mountain Lower Montane-Foothill Shrubland 

Artemisia nova 

Artemisia tridentata 

Artemisia frigida 

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Ecological System Sagebrush Vegetation that the Ecological System has the 

Capability to Produce 

Rocky Mountain Gambel Oak-Mixed Montane 

Shrubland Artemisia tridentata 

Inter-Mountain Basins Curl-Leaf Mountain 

Mahogany Woodland and Shrubland 

Artemisia tridentata ssp. vaseyana 

Artemisia arbuscula 

Artemisia tridentata 

Artemisia tridentata ssp. vaseyana 

Shrubland Alliance (EVT only) 

Artemisia tridentata ssp. vaseyana 

Quercus gambelii Shrubland Alliance (EVT only) Artemisia tridentata 

Accuracy and Appropriate Use of LANDFIRE Datasets: 

Because of concerns over the thematic accuracy of individual classes mapped by LANDFIRE, all ecological 

systems listed in Table 5 will be merged into one value that represents the sagebrush base layer. With all 

ecological systems aggregated, the combined accuracy of the sagebrush base layer (EVT) will be much greater 

than if all categories were treated separately. 

LANDFIRE performed the original accuracy assessment of their EVT product on a map zone basis. There are 

20 LANDFIRE map zones that cover the historic range of sage-grouse as defined by Schroeder (2004). 

Attachment C lists the user and producer accuracies for the aggregated ecological systems that make up the 

sagebrush base layer and also defines user and producer accuracies. The aggregated sagebrush base layer for 

monitoring had producer accuracies ranging from 56.7% to 100% and user accuracies ranging from 57.1% to 

85.7%. 

LANDFIRE EVT data are not designed to be used at a local level. In reports of the percent sagebrush statistic 

for the various reporting units (Measure 1a), the uncertainty of the percent sagebrush will increase as the size 

of the reporting unit gets smaller. LANDFIRE data should never be used at the 30m pixel level (900m2 

resolution of raster data) for any reporting. The smallest geographic extent for using the data to determine 

percent sagebrush is at the PAC level; for the smallest PACs, the initial percent sagebrush estimate will have 

greater uncertainties compared with the much larger PACs. 

Agricultural Adjustments for the Sagebrush Base Layer: The dataset for the geographic extent of agricultural 

lands will come from the National Agricultural Statistics Service (NASS) Cropland Data Layer (CDL) 

(http://www.nass.usda.gov/research/Cropland/Release/index.htm). CDL data are generated annually, with 

estimated producer accuracies for “large area row crops ranging from the mid 80% to mid-90%,” depending 

on the state (http://www.nass.usda.gov/research/ Cropland/sarsfaqs2.htm#Section3_18.0). Specific 

information on accuracy may be found on the NASS metadata website 

(http://www.nass.usda.gov/research/Cropland/metadata/meta.htm). CDL provided the only dataset that 

matches the three criteria (nationally consistent, known level of accuracy, and periodically updated) for use in 

this monitoring framework and represents the best available agricultural lands mapping product. 

The CDL data contain both agricultural classes and nonagricultural classes. For this effort, and in the baseline 

environmental report (Manier et al. 2013), nonagricultural classes were removed from the original dataset. 

The excluded classes are: Barren (65 & 131), Deciduous Forest (141), Developed/High Intensity (124), 

Developed/Low Intensity (122), Developed/Med Intensity (123), Developed/Open Space (121), Evergreen 

Forest (142), Grassland Herbaceous (171), Herbaceous Wetlands (195), Mixed Forest (143), Open Water (83 

& 111), Other Hay/Non Alfalfa (37), Pasture/Hay (181), Pasture/Grass (62), Perennial Ice/Snow (112), 

Shrubland (64 & 152), Woody Wetlands (190). 

The rule set for adjusting the sagebrush base layer for agricultural lands (and for updating the base layer for 

agricultural lands in the future) is that once an area is classified as agriculture in any year of the CDL, those 

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pixels will remain out of the sagebrush base layer even if a new version of the CDL classifies that pixel as one 

of the nonagricultural classes listed above. The assumption is that even though individual pixels may be 

classified as a nonagricultural class in any given year, the pixel has not necessarily been restored to a natural 

sagebrush community that would be included in Table 5. A further assumption is that once an area has moved 

into agricultural use, it is unlikely that the area would be restored to sagebrush. Should that occur, however, 

the method and criteria for adding pixels back into the sagebrush base layer would follow those found in the 

sagebrush restoration monitoring section of this monitoring framework 

Urban Adjustments for the Sagebrush Base Layer 

The National Land Cover Dataset (NLCD) Percent Imperviousness was selected as the best available dataset 

to be used for urban updates. These data are generated on a five-year cycle and specifically designed to support 

monitoring efforts. Other datasets were evaluated and lacked the spatial specificity that was captured in the 

NLCD product. Any new impervious pixel will be removed from the sagebrush base layer during the update 

process. Although the impervious surface layer includes a number of impervious pixels outside of urban areas, 

there are two reasons why this is acceptable for this process. First, an evaluation of national urban area datasets 

did not reveal a layer that could be confidently used in conjunction with the NLCD product to screen 

impervious pixels outside of urban zones because unincorporated urban areas were not being included thus 

leaving large chunks of urban pixels unaccounted for in this rule set. Secondly, experimentation with setting 

a threshold on the percent imperviousness layer that would isolate rural features proved to be unsuccessful. 

No combination of values could be identified that would result in the consistent ability to limit impervious 

pixels outside urban areas. Therefore, to ensure consistency in the monitoring estimates, it was determined to 

include all impervious pixels. 

Fire Adjustments for the Sagebrush Base Layer: 

Two datasets were selected for performing fire adjustments and updates: GeoMac fire perimeters and 

Monitoring Trends in Burn Severity (MTBS). An existing data standard in the BLM requires that all fires of 

more than 10 acres are to be reported to GeoMac; therefore, there will be many small fires of less than 10 

acres that will not be accounted for in the adjustment and monitoring attributable to fire. Using fire perimeters 

from GeoMac, all sagebrush pixels falling within the perimeter of fires less than 1,000 acres will be used to 

adjust and monitor the sagebrush base layer. 

For fires greater than 1,000 acres, MTBS was selected as a means to account for unburned sagebrush islands 

during the update process of the sagebrush base layer. The MTBS program (http://www.mtbs.gov) is an 

ongoing, multiyear project to map fire severity and fire perimeters consistently across the United States. One 

of the burn severity classes within MTBS is an unburned to low-severity class. This burn severity class will 

be used to represent unburned islands of sagebrush within the fire perimeter for the sagebrush base layer. 

Areas within the other severity classes within the fire perimeter will be removed from the base sagebrush layer 

during the update process. Not all wildfires, however, have the same impacts on the recovery of sagebrush 

habitat, depending largely on soil moisture and temperature regimes. For example, cooler, moister sagebrush 

habitat has a higher potential for recovery or, if needed, restoration than does the warmer, dryer sagebrush 

habitat. These cooler, moister areas will likely be detected as sagebrush in future updates to LANDFIRE. 

Conifer Encroachment Adjustment for the Sagebrush Base Layer: 

Conifer encroachment into sagebrush vegetation reduces the spatial extent of sage-grouse habitat (Davies et 

al. 2011, Baruch-Mordo et al. 2013). Conifer species that show propensity for encroaching into sagebrush 

vegetation resulting in sage-grouse habitat loss include various juniper species, such as Utah juniper 

(Juniperus osteosperma), western juniper (Juniperus occidentalis), Rocky Mountain juniper (Juniperus 

scopulorum), pinyon species, including singleleaf pinyon (Pinus monophylla) and pinyon pine (Pinus edulis), 

ponderosa pine (Pinus ponderosa), lodgepole pine (Pinus contorta), and Douglas fir (Pseudotsuga menziesii) 

(Gruell et al. 1986, Grove et al. 2005, Davies et al. 2011). 

A rule set for conifer encroachment was developed to be used for determination of the existing sagebrush base 

layer. To capture the geographic extent of sagebrush that is likely to experience conifer encroachment, 

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ecological systems within LANDFIRE EVT version 1.2 (NatureServe 2011) were identified if they have the 

capability of supporting the conifer species (listed above) and have the capability of supporting sagebrush 

vegetation. Those ecological systems (Table 6) were deemed to be the plant communities with conifers most 

likely to encroach into sagebrush vegetation. Sagebrush vegetation was defined as including sagebrush species 

(Attachment B) that provide habitat for the Greater Sage-Grouse and are included in the Sage-Grouse Habitat 

Assessment Framework. An adjacency analysis was conducted to identify all sagebrush pixels that were 

directly adjacent to these conifer ecological systems and these immediately adjacent sagebrush pixels were 

removed from the sagebrush base layer. 

Table 6. Ecological Systems with Conifers Most Likely to Encroach into Sagebrush
 

Vegetation
 

EVT Ecological Systems Coniferous Species and Sagebrush Vegetation that the 

Ecological System has the Capability to Produce 

Colorado Plateau Pinyon-Juniper Woodland Pinus edulis 

Juniperus osteosperma 

Artemisia tridentata 

Artemisia arbuscula 

Artemisia nova 

Artemisia tridentata ssp. tridentata 

Artemisia tridentata ssp. wyomingensis 

Artemisia tridentata ssp. vaseyana 

Artemisia bigelovii 

Artemisia pygmaea 

Columbia Plateau Western Juniper Woodland and 

Savanna 

Juniperus occidentalis 

Pinus ponderosa 

Artemisia tridentata 

Artemisia arbuscula 

Artemisia rigida 

Artemisia tridentata ssp. vaseyana 

East Cascades Oak-Ponderosa Pine Forest and 

Woodland 

Pinus ponderosa 

Pseudotsuga menziesii 

Artemisia tridentata 

Artemisia nova 

Great Basin Pinyon-Juniper Woodland Pinus monophylla 

Juniperus osteosperma 

Artemisia arbuscula 

Artemisia nova 

Artemisia tridentata 

Artemisia tridentata ssp. vaseyana 

Northern Rocky Mountain Ponderosa Pine Woodland 

and Savanna 

Pinus ponderosa 

Artemisia tridentata 

Artemisia arbuscula 

Artemisia tridentata ssp. vaseyana 

Rocky Mountain Foothill Limber Pine-Juniper 

Woodland 

Juniperus osteosperma 

Juniperus scopulorum 

Artemisia nova 

Artemisia tridentata 

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EVT Ecological Systems Coniferous Species and Sagebrush Vegetation that the 

Ecological System has the Capability to Produce 

Rocky Mountain Poor-Site Lodgepole Pine Forest Pinus contorta 

Pseudotsuga menziesii 

Pinus ponderosa 

Artemisia tridentata 

Southern Rocky Mountain Pinyon-Juniper Woodland Pinus edulis 

Juniperus monosperma 

Artemisia bigelovii 

Artemisia tridentata 

Artemisia tridentata ssp. wyomingensis 

Artemisia tridentata ssp.vaseyana 

Southern Rocky Mountain Ponderosa Pine Woodland Pinus ponderosa 

Pseudotsuga menziesii 

Pinus edulis 

Pinus contorta 

Juniperus spp. 

Artemisia nova 

Artemisia tridentata 

Artemisia arbuscula 

Artemisia tridentata ssp. vaseyana 

Invasive Annual Grasses Adjustments for the Sagebrush Base Layer: There are no invasive species datasets 

from 2010 to the present (beyond the LANDFIRE data) that meet the three criteria (nationally consistent, 

known level of accuracy, and periodically updated) for use in the determination of the sagebrush base layer. 

For a description of how invasive species land cover will be incorporated in the sagebrush base layer in the 

future, see Monitoring Sagebrush Availability. 

Sagebrush Restoration Adjustments for the Sagebrush Base Layer: There are no datasets from 2010 to the 

present that could provide additions to the sagebrush base layer from restoration treatments that meet the three 

criteria (nationally consistent, known level of accuracy, and periodically updated); therefore, no adjustments 

were made to the sagebrush base layer calculated from the LANDFIRE EVT (version 1.2) attributable to 

restoration activities since 2010. Successful restoration treatments before 2010 are assumed to have been 

captured in the LANDFIRE refresh. 

a. Monitoring Sagebrush Availability 

Updating the Sagebrush Availability Sagebrush Base Layer 

Sagebrush availability will be updated annually by incorporating changes to the sagebrush base layer 

attributable to agriculture, urbanization, and wildfire. The monitoring schedule for the existing sagebrush base 

layer updates is as follows: 

2010 Existing Sagebrush Base Layer = [Sagebrush EVT] minus [2006 Imperviousness Layer] minus [2009 

and 2010 CDL] minus [2009/10 GeoMac Fires < 1,000 acres] minus [2009/10 MTBS Fires excluding 

unburned sagebrush islands] minus [Conifer Encroachment Layer] 

2012 Existing Sagebrush Update = [Base 2010 Existing Sagebrush Layer] minus [2011 Imperviousness 

Layer] minus [2011 and 2012 CDL] minus [2011/12 GeoMac Fires < 1,000 acres] minus [2011/12 MTBS 

Fires that are greater than 1,000 acres, excluding unburned sagebrush islands within the perimeter] 

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2013 and beyond Existing Sagebrush Updates = [Previous Existing Sagebrush Update Layer] minus 

[Imperviousness Layer (if new data are available)] minus [Next 2 years of CDL] minus [Next 2 years of 

GeoMac Fires < 1,000 acres] minus [Next 2 years MTBS Fires that are greater than 1,000 acres, excluding 

unburned sagebrush islands within the perimeter] plus [restoration/monitoring data provided by the field] 

Sagebrush Restoration Updates 

Restoration after fire, after agricultural conversion, after seedings of introduced grasses, or after treatments of 

pinyon pine and/or juniper, are examples of updates to the sagebrush base layer that can add sagebrush 

vegetation back in. When restoration has been determined to be successful through range wide, consistent, 

interagency fine and site-scale monitoring, the polygonal data will be used to add sagebrush pixels back into 

the broad and mid-scale sagebrush base layer. 

Measure 1b – Context for the change in the amount of sagebrush in a landscape of interest 

Measure 1b describes the amount of sagebrush on the landscape of interest compared with the amount of 

sagebrush the landscape of interest could ecologically support. Areas with the potential to support sagebrush 

were derived from the BpS data layer that describes sagebrush pre Euro-American settlement (biophysical 

setting (BpS) v1.2 of LANDFIRE). This measure (1b) will provide information during evaluations of 

monitoring data to set the context for a given geographic area of interest. The information could also be used 

to inform management options for restoration, mitigation and inform effectiveness monitoring. 

The identification and spatial locations of natural plant communities (vegetation) that are believed to have 

existed on the landscape (BpS) were constructed based on an approximation of the historical (pre EuroAmerican settlement) disturbance regime and how the historical disturbance regime operated on the current 

biophysical environment. BpS is composed of map units which are based on NatureServe’s (2011) terrestrial 

ecological systems classification. 

The ecological systems within BpS used for this monitoring framework are those ecological systems that have 

the capability of supporting sagebrush vegetation and could provide seasonal habitat for the sage-grouse. 

These ecological systems are listed in Table 5 with the exception of the Artemisia tridentata ssp. 

vaseyana Shrubland Alliance and the Quercus gambelii Shrubland Alliance. Ecological systems selected 

included sagebrush species or subspecies that are included in the Sage-Grouse Habitat Assessment Framework 

and are found in Attachment B. 

Attributable to the lack of any reference data, the BpS layer does not have an associated accuracy assessment. 

Visual inspection, however, of the BpS data reveals inconsistencies in the labeling of pixels among 

LANDFIRE map zones. The reason for these inconsistencies between map zones are the decision rules used 

to map a given ecological system will vary between map zones based on different physical, biological, 

disturbance and atmospheric regimes of the region. This can result in artificial edges in the map that are an 

artifact of the mapping process. However, metrics will be calculated at broad spatial scales using BpS potential 

vegetation type, not small groupings or individual pixels, therefore, the magnitude of these observable errors 

in the BpS layer is minor compared with the size of the reporting units. Therefore, since BpS will be used to 

identify broad landscape patterns of dominant vegetation, these inconsistencies will only have a minor impact 

on the percent sagebrush availability calculation. 

LANDFIRE BpS data are not designed to be used at a local level. In reporting the percent sagebrush statistic 

for the various reporting units, the uncertainty of the percent sagebrush will increase as the size of the reporting 

unit gets smaller. LANDFIRE data should never be used at the pixel level (30m2) for any reporting. The 

smallest geographic extent use of the data for this purpose is at the PAC level and for the smallest PACs the 

initial percent sagebrush remaining estimate will have greater uncertainties compared with the much larger 

PACs. 

168
 
 

 

 

 

 

 

 

Tracking 

BLM will analyze and monitor sagebrush availability (Measure 1) on a bi-annual basis and it will be used to 

inform effectiveness monitoring and initiate adaptive management actions as necessary. The 2010 estimate of 

sagebrush availability will serve as the base year and an updated estimate for 2012 will be reported in 2014 

after all datasets become available. The 2012 estimate will capture changes attributable to fire, agriculture, 

and urban development. Subsequent updates will always include new fire and agricultural data and new urban 

data when available. Restoration data that meets criteria of adding sagebrush areas back into the sagebrush 

base layer will begin to be factored in as data allows. Attributable to data availability, there will be a two year 

lag (approximately) between when the estimate is generated and when the data used for the estimate becomes 

available (e.g., the 2014 sagebrush availability will be included in the 2016 estimate). 

Future Plans 

Geospatial data used to generate the sagebrush base layer will be available through BLM’s EGIS Web Portal 

and Geospatial Gateway or through the authoritative data source. Legacy datasets will be preserved, so that 

trends may be calculated. Additionally, accuracy assessment data for all source datasets will be provided on 

the portal either spatially, where applicable, or through the metadata. Accuracy assessment information was 

deemed vital to share to help users understand the limitation of the sagebrush estimates and will be summarized 

spatially by map zone and included in the Portal. 

LANDFIRE plans to begin a remapping effort in 2015. This remapping has the potential to greatly improve 

overall quality of the data products primarily through the use of higher quality remote sensing datasets. 

Additionally, BLM and the Multi-Resolution Land Characteristics Consortium (MRLC) are working to 

improve the accuracy of vegetation map products for broad and mid-scale analyses through the Grass/Shrub 

mapping effort in partnership with the MRLC. The Grass/Shrub mapping effort applies the Wyoming multiscale sagebrush habitat methodology (Homer et al. 2009) to spatially depict fractional percent cover estimates 

for five components range and west-wide. These five components are percent cover of sagebrush vegetation, 

percent bare ground, percent herbaceous vegetation (grass and forbs combined), annual vegetation, and 

percent shrubs. One of the benefits of the design of these fractional cover maps is that they facilitate monitoring 

“with-in” class variation (e.g., examination of declining trend in sagebrush cover for individual pixels). This 

“with-in” class variation can serve as one indicator of sagebrush quality that cannot be derived from 

LANDFIRE’s EVT information. The Grass/Shrub effort is not a substitute for fine scale monitoring, but will 

leverage fine scale data to support the validation of the mapping products. An evaluation will be conducted to 

determine if either dataset is of great enough quality to warrant replacing the existing sagebrush layers. The 

earliest possible date for this evaluation will not occur until 2018 or 2019 depending on data availability. 

B.2. Habitat Degradation Monitoring (Measure 2) 

The measure of habitat degradation will be calculated by combining the footprints of threats identified in 

Table 3. The footprint is defined as the direct area of influence of “active” energy and infrastructure; it is used 

as a surrogate for human activity. Although these analyses will try to summarize results at the aforementioned 

meaningful geographic areas of interest, some may be too small to report the metrics appropriately and may 

be combined (smaller populations, PACs within a population, etc.). Data sources for each threat are found in 

Table 7, Geospatial Data Sources for Habitat Degradation. Specific assumptions (inclusion criteria for data, 

width/area assumptions for point and line features, etc.) and methodology for each threat, and the combined 

measure, are detailed below. All datasets will be updated annually to monitor broad- and mid-scale year-toyear changes and to calculate trends in habitat degradation to inform adaptive management. A 5-year summary 

report will be provided to the USFWS. 

a. Habitat Degradation Datasets and Assumptions 

Energy (oil and gas wells and development facilities) – This dataset will compile information from three oil 

and gas databases: the proprietary IHS Enerdeq database, the BLM Automated Fluid Minerals Support System 

(AFMSS) database, and the proprietary Platts (a McGraw-Hill Financial Company) GIS Custom Data 

(hereafter, Platts) database of power plants. Point data from wells active within the last 10 years from IHS and 

169
 
 

 

 

 

 

 

 

 

 

 

 

 

 

producing wells from AFMSS will be considered as a 5-acre (2.0ha) direct area of influence centered on the 

well point, as recommended by the BLM WO-300 (Minerals and Realty Management). Plugged and 

abandoned wells will be removed if the date of well abandonment was before the first day of the reporting 

year (i.e., for the 2015 reporting year, a well must have been plugged and abandoned by 12/31/2014 to be 

removed). Platts oil and gas power plants data (subset to operational power plants) will also be included as a 

5-acre (2.0ha) direct area of influence. 

Additional Measure: Reclaimed Energy-related Degradation. This dataset will include those wells that have 

been plugged and abandoned. This measure thereby attempts to measure energy-related degradation that has 

been reclaimed but not necessarily fully restored to sage-grouse habitat. This measure will establish a baseline 

by using wells that have been plugged and abandoned within the last 10 years from the IHS and AFMSS 

datasets. Time lags for lek attendance in response to infrastructure have been documented to be delayed 2–10 

years from energy development activities (Harju et al. 2010). Reclamation actions may require 2 or more years 

from the Final Abandonment Notice. Sagebrush seedling establishment may take 6 or more years from the 

point of seeding, depending on such variables as annual precipitation, annual temperature, and soil type and 

depth (Pyke 2011). This 10-year period is conservative and assumes some level of habitat improvement 10 

years after plugging. Research by Hemstrom et al. (2002), however, proposes an even longer period—more 

than 100 years—for recovery of sagebrush habitats, even with active restoration approaches. Direct area of 

influence will be considered 3 acres (1.2ha) (J. Perry, personal communication, February 12, 2014). This 

additional layer/measure could be used at the broad and mid-scale to identify areas where sagebrush habitat 

and/or potential sagebrush habitat is likely still degraded. This layer/measure could also be used where further 

investigation at the fine or site scale would be warranted to: 1) quantify the level of reclamation already 

conducted, and 2) evaluate the amount of restoration still required for sagebrush habitat recovery. At a 

particular level (e.g., population, PACs), these areas and the reclamation efforts/success could be used to 

inform reclamation standards associated with future developments. Once these areas have transitioned from 

reclamation standards to meeting restoration standards, they can be added back into the sagebrush availability 

layer using the same methodology as described for adding restoration treatment areas lost to wildfire and 

agriculture conversion (see Monitoring Sagebrush Restoration in Monitoring Sagebrush Availability). This 

dataset will be updated annually from the IHS dataset. 

Energy (coal mines) – Currently, there is no comprehensive dataset available that identifies the footprint of 

active coal mining across all jurisdictions. Therefore, point and polygon datasets will be used each year to 

identify coal mining locations. Data sources will be identified and evaluated annually and will include at a 

minimum: BLM coal lease polygons, U.S. Energy Information Administration mine occurrence points, U.S. 

Office of Surface Mining Reclamation and Enforcement coal mining permit polygons (as available), and U.S. 

Geological Survey (USGS) Mineral Resources Data System mine occurrence points. These data will inform 

where active coal mining may be occurring. Additionally, coal power plant data from Platts power plants 

database (subset to operational power plants) will be included. Aerial imagery will then be used to digitize 

manually the active coal mining and coal power plants surface disturbance in or near these known occurrence 

areas. While the date of aerial imagery varies by scale, the most current data available from Esri and/or Google 

will be used to locate (generally at 1:50,000 and below) and digitize (generally at 1:10,000 and below) active 

coal mine and power plant direct area of influence. Coal mine location data source and imagery date will be 

documented for each digitized coal polygon at the time of creation. Subsurface facility locations (polygon or 

point location as available) will also be collected if available, included in density calculations, and added to 

the active surface activity layer as appropriate (if an actual direct area of influence can be located). 

Energy (wind energy facilities) – This dataset will be a subset of the Federal Aviation Administration (FAA) 

Digital Obstacles point file. Points where “Type_” = “WINDMILL” will be included. Direct area of influence 

of these point features will be measured by converting to a polygon dataset as a direct area of influence of 3 

acres (1.2ha) centered on each tower point. See the BLM’s “Wind Energy Development Programmatic 

Environmental Impact Statement” (BLM 2005). Additionally, Platts power plants database will be used for 

transformer stations associated with wind energy sites (subset to operational power plants), also with a 3-acre 

(1.2ha) direct area of influence. 

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Energy (solar energy facilities) – This dataset will include solar plants as compiled with the Platts power 

plants database (subset to operational power plants). This database includes an attribute that indicates the 

operational capacity of each solar power plant. Total capacity at the power plant was based on ratings of the 

in-service unit(s), in megawatts. Direct area of influence polygons will be centered over each point feature 

representing 7.3ac (3.0ha) per megawatt of the stated operational capacity, per the report of the National 

Renewable Energy Laboratory (NREL), “Land-Use Requirements for Solar Power Plants in the United States” 

(Ong et al. 2013). 

Energy (geothermal energy facilities) – This dataset will include geothermal wells in existence or under 

construction as compiled with the IHS wells database and power plants as compiled with the Platts database 

(subset to operational power plants). Direct area of influence of these point features will be measured by 

converting to a polygon dataset of 3 acres (1.2ha) centered on each well or power plant point. 

Mining (active developments; locatable, leasable, salable) – This dataset will include active locatable mining 

locations as compiled with the proprietary InfoMine database. Aerial imagery will then be used to digitize 

manually the active mining surface disturbance in or near these known occurrence areas. While the date of 

aerial imagery varies by scale, the most current data available from Esri and/or Google will be used to locate 

(generally at 1:50,000 and below) and digitize (generally at 1:10,000 and below) active mine direct area of 

influence. Mine location data source and imagery date will be documented for each digitized polygon at the 

time of creation. Currently, there are no known compressive databases available for leasable or salable mining 

sites beyond coal mines. Other data sources will be evaluated and used as they are identified or as they become 

available. Point data may be converted to polygons to represent direct area of influence unless actual surface 

disturbance is available. 

Infrastructure (roads) – This dataset will be compiled from the proprietary Esri StreetMap Premium for 

ArcGIS. Dataset features that will be used are: Interstate Highways, Major Roads, and Surface Streets to 

capture most paved and “crowned and ditched” roads while not including “two-track” and 4-wheel-drive 

routes. These minor roads, while not included in the broad- and mid-scale monitoring, may support a volume 

of traffic that can have deleterious effects on sage-grouse leks. It may be appropriate to consider the frequency 

and type of use of roads in a NEPA analysis for a proposed project. This fine- and site-scale analysis will 

require more site-specific data than is identified in this monitoring framework. The direct area of influence for 

roads will be represented by 240.2ft, 84.0ft, and 40.7ft (73.2m, 25.6m, and 12.4m) total widths centered on 

the line feature for Interstate Highways, Major Roads, and Surface Streets, respectively (Knick et al. 2011). 

The most current dataset will be used for each monitoring update. Note: This is a related but different dataset 

than what was used in BER (Manier et al. 2013). Individual BLM planning units may use different road layers 

for fine- and site-scale monitoring. 

Infrastructure (railroads) – This dataset will be a compilation from the Federal Railroad Administration Rail 

Lines of the USA dataset. Non-abandoned rail lines will be used; abandoned rail lines will not be used. The 

direct are of influence for railroads will be represented by a 30.8ft (9.4m) total width (Knick et al. 2011) 

centered on the non-abandoned railroad line feature. 

Infrastructure (power lines) – This line dataset will be derived from the proprietary Platts transmission lines 

database. Linear features in the dataset attributed as “buried” will be removed from the disturbance calculation. 

Only “In Service” lines will be used; “Proposed” lines will not be used. Direct area of influence will be 

determined by the kV designation: 1–199 kV (100ft/30.5m), 200–399 kV (150ft/45.7m), 400–699 kV 

(200ft/61.0m), and 700-or greater kV (250ft/76.2m) based on average right-of-way and structure widths, 

according to BLM WO-300 (Minerals and Realty Management). 

Infrastructure (communication towers) – This point dataset will be compiled from the Federal 

Communications Commission (FCC) communication towers point file; all duplicate points will be removed. 

It will be converted to a polygon dataset by using a direct area of influence of 2.5 acres (1.0ha) centered on 

each communication tower point (Knick et al. 2011). 

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Infrastructure (other vertical structures) – This point dataset will be compiled from the FAA’s Digital 

Obstacles point file. Points where “Type_” = “WINDMILL” will be removed. Duplicate points from the FCC 

communication towers point file will be removed. Remaining features will be converted to a polygon dataset 

using a direct area of influence of 2.5 acres (1.0ha) centered on each vertical structure point (Knick et al. 

2011). 

Other Developed Rights-of-Way – Currently, no additional data sources for other rights-of-way have been 

identified; roads, power lines, railroads, pipelines, and other known linear features are represented in the 

categories described above. The newly purchased IHS data do contain pipeline information; however, this 

database does not currently distinguish between above-ground and underground pipelines. If additional 

features representing human activities are identified, they will be added to monitoring reports using similar 

assumptions to those used with the threats described above. 

b. Habitat Degradation Threat Combination and Calculation 

The threats targeted for measuring human activity (Table 3) will be converted to direct area of influence 

polygons as described for each threat above. These threat polygon layers will be combined and features 

dissolved to create one overall polygon layer representing footprints of active human activity in the range of 

sage-grouse. Individual datasets, however, will be preserved to indicate which types of threats may be 

contributing to overall habitat degradation. This measure has been divided into three submeasures to describe 

habitat degradation on the landscape. Percentages will be calculated as follows: 

Measure 2a. Footprint by geographic area of interest: Divide area of the active/direct footprint 

by the total area of the geographic area of interest (% disturbance in geographic area of interest). 

Measure 2b. Active/direct footprint by historical sagebrush potential: Divide area of the active 

footprint that coincides with areas with historical sagebrush potential (BpS calculation from 

habitat availability) within a given geographic area of interest by the total area with sagebrush 

potential within the geographic area of interest (% disturbance on potential historical sagebrush 

in geographic area of interest). 

Measure 2c. Active/direct footprint by current sagebrush: Divide area of the active footprint that 

coincides with areas of existing sagebrush (EVT calculation from habitat availability) within a 

given geographic area of interest by the total area that is current sagebrush within the geographic 

area of interest (% disturbance on current sagebrush in geographic area of interest). 

Table 7. Geospatial Data Sources for Habitat Degradation (Measure 2) 

Degradation Type Subcategory Data Source Direct Area of 

Influence 

Area Source 

Energy (oil & gas) Wells IHS; BLM (AFMSS) 5.0ac (2.0ha) BLM 

WO-300 

Power Plants Platts (power plants) 5.0ac (2.0ha) BLM 

WO-300 

Energy (coal) Mines BLM; Forest Service; 

Office of Surface 

Mining Reclamation 

and Environment; 

USGS Mineral 

Resources Data 

System 

Polygon area 

(digitized) 

Esri/ Google Imagery 

Power Plants Platts (power plants) Polygon area 

(digitized) 

Esri Imagery 

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Degradation Type Subcategory Data Source Direct Area of 

Influence 

Area Source 

Energy (wind) Wind Turbines Federal Aviation 

Administration 

3.0ac (1.2ha) BLM 

WO-300 

Power Plants Platts (power plants) 3.0ac (1.2ha) BLM 

WO-300 

Energy (solar) Fields/Power Plants Platts (power plants) 7.3ac (3.0 ha)/MW NREL 

Energy (geothermal) Wells IHS 3.0ac (1.2ha) BLM 

WO-300 

Power Plants Platts (power plants) Polygon area 

(digitized) 

Esri Imagery 

Mining Locatable 

Developments 

InfoMine Polygon area 

(digitized) 

Esri Imagery 

Infrastructure (roads) Surface Streets 

(Minor Roads) 

Esri StreetMap 

Premium 

40.7 ft. (12.4m) USGS 

Major Roads Esri StreetMap 

Premium 

84.0 ft. (25.6m) USGS 

Interstate Highways Esri StreetMap 

Premium 

240.2 ft. (73.2m) USGS 

Infrastructure 

(railroads) 

ActiveLines Federal Railroad 

Administration 

30.8 ft. (9.4m) USGS 

Infrastructure 

(powerlines) 

1-199 kV Lines Platts (transmission 

lines) 

100 ft. (30.5 m) BLM 

WO-300 

200-399 kV Lines Platts (transmission 

lines) 

150 ft. (45.7m) BLM 

WO-300 

400-699 kV Lines Platts (transmission 

lines) 

200 ft. (61.0m) BLM 

WO-300 

700+ kV Lines Platts (transmission 

lines) 

250 ft. (76.2m) BLM 

WO-300 

Infrastructure 

(communication 

Towers Federal 

Communications 

Commission 

2.5 ac (1.0 ha) BLM 

WO-300 

B.3. Energy and Mining Density (Measure 3) 

The measure of density of energy and mining will be calculated by combining the locations of energy and 

mining threats identified in Table 3. This measure will provide an estimate of the intensity of human activity 

or the intensity of habitat degradation. The number of energy facilities and mining locations will be summed 

and divided by the area of meaningful geographic areas of interest to calculate density of these activities. Data 

sources for each threat are found in Table 7. Specific assumptions (inclusion criteria for data, width/area 

assumptions for point and line features, etc.) and methodology for each threat, and the combined measure, are 

detailed below. All datasets will be updated annually to monitor broad- and mid-scale year-to-year changes 

and 5-year (or longer) trends in habitat degradation. 

a. Energy and Mining Density Datasets and Assumptions 

Energy (oil and gas wells and development facilities) (See Section B.2., Habitat Degradation 

Monitoring.) 

Energy (coal mines) (See Section B.2., Habitat Degradation Monitoring.) 

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Energy (wind energy facilities) (See Section B.2., Habitat Degradation Monitoring.) Energy (solar energy 

facilities) (See Section B.2., Habitat Degradation Monitoring.) Energy (geothermal energy facilities) (See 

Section B.2., Habitat Degradation Monitoring.) Mining (active developments; locatable, leasable, salable) 

(See Section B.2., Habitat Degradation Monitoring.) 

b. Energy and Mining Density Threat Combination and Calculation 

Datasets for energy and mining will be collected in two primary forms: point locations (e.g., wells) and 

polygon areas (e.g., surface coal mining). The following rule set will be used to calculate density for 

meaningful geographic areas of interest including standard grids and per polygon: 

1.	 Point locations will be preserved; no additional points will be removed beyond the methodology 

described above. Energy facilities in close proximity (an oil well close to a wind tower) will be 

retained. 

2.	 Polygons will not be merged, or features further dissolved. Thus, overlapping facilities will be 

retained, such that each individual threat will be a separate polygon data input for the density 

calculation. 

3.	 The analysis unit (polygon or 640-acre section in a grid) will be the basis for counting the number of 

mining or energy facilities per unit area. Within the analysis unit, all point features will be summed, 

and any individual polygons will be counted as one (e.g., a coal mine will be counted as one facility 

within population). Where polygon features overlap multiple units (polygons or pixels), the facility 

will be counted as one in each unit where the polygon occurs (e.g., a polygon crossing multiple 640­

acre sections would be counted as one in each 640-acre section for a density per 640-acre-section 

calculation). 

4.	 In methodologies with different-sized units (e.g., MZs, populations, etc.) raw facility counts will be 

converted to densities by dividing the raw facility counts by the total area of the unit. Typically this 

will be measured as facilities per 640 acres. 

5.	 For uniform grids, raw facility counts will be reported. Typically this number will also be converted 

to facilities per 640 acres. 

6.	 Reporting may include summaries beyond the simple ones above. Zonal statistics may be used to 

smooth smaller grids to help display and convey information about areas within meaningful 

geographic areas of interest that have high levels of energy and/or mining activity. 

7.	 Additional statistics for each defined unit may also include adjusting the area to include only the area 

with the historical potential for sagebrush (BpS) or areas currently sagebrush (EVT). 

Individual datasets and threat combination datasets for habitat degradation will be available through the 

BLM’s EGIS web portal and geospatial gateway. Legacy datasets will be preserved so that trends may be 

calculated. 

C. Population (Demographics) Monitoring 

State wildlife management agencies are responsible for monitoring sage-grouse populations within their 

respective states. WAFWA will coordinate this collection of annual population data by state agencies. These 

data will be made available to the BLM according to the terms of the forthcoming Greater Sage-Grouse 

Population Monitoring Memorandum of Understanding (MOU) (2014) between WAFWA and the BLM. The 

MOU outlines a process, timeline, and responsibilities for regular data sharing of sage-grouse population 

and/or habitat information for the purposes of implementing sage-grouse ARMPA and subsequent 

effectiveness monitoring. Population areas were refined from the “Greater Sage-Grouse (Centrocercus 

urophasianus) Conservation Objectives: Final Report” (COT 2013) by individual state wildlife agencies to 

174
 
create a consistent naming nomenclature for future data analyses. These populat ion data will be used for 

analysis at the applicable scale to supplement habitat effectiveness monitoring of management actions and to 

inform the adaptive management responses. 

D. Effectiveness Monitoring 

Effectiveness monitoring will provide the data needed to evaluate BLM actions toward reaching the objective 

of the national planning strategy (BLM IM 2012-044) – to conserve sage-grouse populations and their habitat– 

and the objectives for the land use planning area. Effectiveness monitoring methods described here will 

encompass multiple larger scales, from areas as large as the WAFWA MZ to the scale of the ARMPA. 

Effectiveness data used for these larger-scale evaluations will include all lands in the area of interest, 

regardless of surface ownership/management, and will help inform where finer-scale evaluations are needed, 

such as population areas smaller than an RMP or PACs within an RMP (described in Fine and Site Scales). 

Data will also include the trend of disturbance within these areas of interest to inform the need to initiate 

adaptive management responses as described in the ARMPA. 

The BLM will coordinate with the State of Wyoming in evaluating the compliance of all actions within a sagegrouse core area. Evaluation of current disturbance, disruptions and conservation actions within a SG core 

area will be conducted to determine if all entities are in compliance with their specific standards and whether 

or not it indeed has not caused declines of sage-grouse populations. This approach also helps focus scarce 

resources to areas experiencing habitat loss, degradation, or population declines, without excluding the 

possibility of concurrent, finer-scale evaluations as needed where habitat or population anomalies have been 

identified through some other means. 

To determine the effectiveness of the sage-grouse national planning strategy, the BLM will evaluate the 

answers to the following questions and prepare a broad- and mid-scale effectiveness report: 

1.	 Sagebrush Availability and Condition: 

a.	 What is the amount of sagebrush availability and the change in the amount and condition of 

sagebrush? 

b.	 What is the existing amount of sagebrush on the landscape and the change in the amount 

relative to the pre-EuroAmerican historical distribution of sagebrush (BpS)? 

c.	 What is the trend and condition of the indicators describing sagebrush characteristics 

important to sage-grouse? 

2.	 Habitat Degradation and Intensity of Activities: 

a.	 What is the amount of habitat degradation and the change in that amount? 

b.	 What is the intensity of activities and the change in the intensity? 

c.	 What is the amount of reclaimed energy-related degradation and the change in the amount? 

d.	 What is the population estimation of sage-grouse and the change in the population estimation? 

3.	 How is the BLM contributing to changes in the amount of sagebrush? 

4.	 How is the BLM contributing to disturbance? 

The compilation of broad- and mid-scale data (and population trends as available) into an effectiveness 

monitoring report will occur on a 5-year reporting schedule (see Attachment A), which may be accelerated to 

respond to critical emerging issues (in consultation with the USFWS and state wildlife agencies). In addition, 

175
 
 

 

 

 

 

 

 

effectiveness monitoring results will be used to identify emerging issues and research needs and inform the 

BLM adaptive management strategy (Section 6 of this appendix). 

To determine the effectiveness of the sage-grouse objectives of the land use plan, the BLM will evaluate the 

answers to the following questions and prepare a plan effectiveness report: 

1.	 Is this plan meeting the sage-grouse habitat objectives? 

2.	 Are sage-grouse areas within the ARMPA meeting, or making progress toward meeting, land health 

standards, including the Special Status Species/wildlife habitat standard? 

3.	 Is the plan meeting the disturbance objective(s) within sage-grouse areas? 

4.	 Are the sage-grouse populations within this plan boundary and within the sage-grouse areas 

increasing, stable, or declining? 

The effectiveness monitoring report for this ARMPA will occur on a 5-year reporting schedule (see 

Attachment A) or more often if habitat or population anomalies indicate the need for an evaluation to facilitate 

adaptive management or respond to critical emerging issues. Data will be made available through the BLM’s 

EGIS web portal and the geospatial gateway. 

Methods 

At the broad and mid scales (PACs and above) the BLM will summarize the vegetation, disturbance, and 

(when available) population data. Although the analysis will try to summarize results for PACs within each 

sage-grouse population, some populations may be too small to report the metrics appropriately and may need 

to be combined to provide an estimate with an acceptable level of accuracy. Otherwise, they will be flagged 

for more intensive monitoring by the appropriate landowner or agency. The BLM will then analyze monitoring 

data to detect the trend in the amount of sagebrush; the condition of the vegetation in the sage-grouse areas 

(MacKinnon et al. 2011); the trend in the amount of disturbance; the change in disturbed areas owing to 

successful restoration; and the amount of new disturbance the BLM has permitted. These data could be 

supplemented with population data (when available) to inform an understanding of the correlation between 

habitat and PACs within a population. This overall effectiveness evaluation must consider the lag effect 

response of populations to habitat changes (Garton et al. 2011). 

Calculating Question 1, National Planning Strategy Effectiveness: The amount of sagebrush available in the 

large area of interest will use the information from Measure 1a (I.B.1., Sagebrush Availability) and calculate 

the change from the 2012 baseline to the end date of the reporting period. To calculate the change in the 

amount of sagebrush on the landscape to compare with the historical areas with potential to support sagebrush, 

the information from Measure 1b (I.B.1., Sagebrush Availability) will be used. To calculate the trend in the 

condition of sagebrush at the mid-scale, three sources of data will be used: the BLM’s Grass/Shrub mapping 

effort (Future Plans in Section B.1., Sagebrush Availability); the results from the calculation of the landscape 

indicators, such as patch size (described below); and the BLM’s Landscape Monitoring Framework (LMF) 

and sage-grouse intensification effort (also described below). The LMF and sage-grouse intensification effort 

data are collected in a statistical sampling framework that allows calculation of indicator values at multiple 

scales. 

Beyond the importance of sagebrush availability to sage-grouse, the mix of sagebrush patches on the landscape 

at the broad and mid-scale provides the life requisite of space for sage-grouse dispersal needs (see the HAF). 

The configuration of sagebrush habitat patches and the land cover or land use between the habitat patches at 

the broad and mid scales also defines suitability. There are three significant habitat indicators that influence 

habitat use, dispersal, and movement across populations: the size and number of habitat patches, the 

connectivity of habitat patches (linkage areas), and habitat fragmentation (scope of unsuitable and non-habitats 

between habitat patches). The most appropriate commercial software to measure patch dynamics, 

176
 
 

 

 

 

 

 

 

 

 

 

connectivity, and fragmentation at the broad and mid scales will be used, along with the same data layers 

derived for sagebrush availability. 

The BLM initiated the LMF in 2011 in cooperation with the NRCS. The objective of the LMF effort is to 

provide unbiased estimates of vegetation and soil condition and trend using a statistically balanced sample 

design across BLM lands. Recognizing that sage-grouse populations are more resilient where the sagebrush 

plant community has certain characteristics unique to a particular life stage of sage-grouse (Knick and 

Connelly 2011, Stiver et al. in press), a group of sage-grouse habitat and sagebrush plant community subject 

matter experts identified those vegetation indicators collected at LMF sampling points that inform sage-grouse 

habitat needs. The experts represented the Agricultural Research Service, BLM, NRCS, USFWS, WAFWA, 

state wildlife agencies, and academia. The common indicators identified include: species composition, foliar 

cover, height of the tallest sagebrush and herbaceous plant, intercanopy gap, percent of invasive species, 

sagebrush shape, and bare ground. To increase the precision of estimates of sagebrush conditions within the 

range of sage-grouse, additional plot locations in occupied sage-grouse habitat (Sage-Grouse Intensification) 

were added in 2013. The common indicators are also collected on sampling locations in the NRCS National 

Resources Inventory Rangeland Resource Assessment (http://www.nrcs.usda.gov/wps/portal/nrcs/detail/ 

national/technical/nra/nri/?&cid=stelprdb1041620). 

The sage-grouse intensification baseline data will be collected over a 5-year period, and an annual sage-grouse 

intensification report will be prepared describing the status of the indicators. Beginning in year 6, the annual 

status report will be accompanied with a trend report, which will be available on an annual basis thereafter, 

contingent on continuation of the current monitoring budget. This information, in combination with the 

Grass/Shrub mapping information, the mid-scale habitat suitability indicator measures, and the sagebrush 

availability information will be used to answer Question 1 of the National Planning Strategy Effectiveness 

Report. 

Calculating Question 2, National Planning Strategy Effectiveness: Evaluations of the amount of habitat 

degradation and the intensity of the activities in the area of interest will use the information from Measure 2 

(Section B.2., Habitat Degradation Monitoring) and Measure 3 (Section B.3., Energy and Mining Density). 

The field office will collect data on the amount of reclaimed energy-related degradation on plugged and 

abandoned and oil/gas well sites. The data are expected to demonstrate that the reclaimed sites have yet to 

meet the habitat restoration objectives for sage-grouse habitat. This information, in combination with the 

amount of habitat degradation, will be used to answer Question 2 of the National Planning Strategy 

Effectiveness Report. 

Calculating Question 3, National Planning Strategy Effectiveness: The change in sage-grouse estimated 

populations will be calculated from data provided by the state wildlife agencies, when available. This 

population data (Section C., Population [Demographics] Monitoring) will be used to answer Question 3 of the 

National Planning Strategy Effectiveness Report. 

Calculating Question 4, National Planning Strategy Effectiveness: The estimated contribution by the BLM to 

the change in the amount of sagebrush in the area of interest will use the information from Measure 1a (Section 

B.1., Sagebrush Availability). This measure is derived from the national datasets that remove sagebrush 

(Table 4). To determine the relative contribution of BLM management, the current Surface Management 

Agency geospatial data layer will be used to differentiate the amount of change for each management agency 

for this measure in the geographic areas of interest. This information will be used to answer Question 4 of the 

National Planning Strategy Effectiveness Report. 

Calculating Question 5, National Planning Strategy Effectiveness: The estimated contribution by the BLM to 

the change in the amount of disturbance in the area of interest will use the information from Measure 2a 

(Section B.2., Monitoring Habitat Degradation) and Measure 3 (Section B.3., Energy and Mining Density). 

These measures are all derived from the national disturbance datasets that degrade habitat (Table 7). To 

determine the relative contribution of BLM management, the current Surface Management Agency geospatial 

data layer will be used to differentiate the amount of change for each management agency for these two 

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measures in the geographic areas of interest. This information will be used to answer Question 5 of the 

National Planning Strategy Effectiveness Report. 

Answers to the five questions for determining the effectiveness of the national planning strategy will identify 

areas that appear to be meeting the objectives of the strategy and will facilitate identification of population 

areas for more detailed analysis. Conceptually, if the broad-scale monitoring identifies increasing sagebrush 

availability and improving vegetation conditions, decreasing disturbance, and a stable or increasing population 

for the area of interest, there is evidence that the objectives of the national planning strategy to maintain 

populations and their habitats have been met. Conversely, where information indicates that sagebrush is 

decreasing and vegetation conditions are degrading, disturbance in sage-grouse areas is increasing, and/or 

populations are declining relative to the baseline, there is evidence that the objectives of the national planning 

strategy are not being achieved. Such a determination would likely result in a more detailed analysis and could 

be the basis for implementing more restrictive adaptive management measures. 

With respect to the land use plan area, the BLM will summarize the vegetation, disturbance, and population 

data to determine if the ARMPA is meeting the plan objectives. Effectiveness information used for these 

evaluations includes BLM surface management areas and will help inform where finer-scale evaluations are 

needed, such as seasonal habitats, corridors, or linkage areas. Data will also include the trend of disturbance 

within the sage-grouse areas, which will inform the need to initiate adaptive management responses as 

described in the ARMPA. 

Calculating Question 1, Land Use Plan Effectiveness: The condition of vegetation and the allotments meeting 

land health standards (as articulated in “BLM Handbook 4180-1, Rangeland Health Standards”) in sage-grouse 

areas will be used to determine the ARMPA’s effectiveness in meeting the vegetation objectives for sagegrouse habitat set forth in the plan. The field office/ranger district will be responsible for collecting this data. 

In order for this data to be consistent and comparable, common indicators, consistent methods, and an unbiased 

sampling framework will be implemented following the principles in the BLM’s AIM strategy (Taylor et al. 

2014; Toevs et al. 2011; MacKinnon et al. 2011), in the BLM’s Technical Reference “Interpreting Indicators 

of Rangeland Health” (Pellant et al. 2005), and in the HAF (Stiver et al. in press) or other approved WAFWA 

MZ–consistent guidance to measure and monitor sage-grouse habitats. This information will be used to answer 

Question 1 of the Land Use Plan Effectiveness Report. 

Calculating Question 2, Land Use Plan Effectiveness: Sage-grouse areas within the ARMPA that are achieving 

land health stands (or, if trend data are available, that are making progress toward achieving them)— 

particularly the Special Status Species/wildlife habitat land health standard—will be used to determine the 

ARMPA’s effectiveness in achieving the habitat objectives set forth in the plan. Field offices will follow 

directions in “BLM Handbook 4180-1, Rangeland Health Standards,” to ascertain if sage-grouse areas are 

achieving or making progress toward achieving land health standards. One of the recommended criteria for 

evaluating this land health standard is the HAF indicators. 

Calculating Question 3, Land Use Plan Effectiveness: The amount of habitat disturbance in sage-grouse areas 

identified in the ARMPA will be used to determine the ARMPA’s effectiveness in meeting the plan’s 

disturbance objectives. National datasets can be used to calculate the amount of disturbance, but field office 

data will likely increase the accuracy of this estimate. This information will be used to answer Question 3 of 

the Land Use Plan Effectiveness Report. 

Calculating Question 4, Land Use Plan Effectiveness: The change in estimated sage-grouse populations will 

be calculated from data provided by the state wildlife agencies, when available, and will be used to determine 

ARMPA effectiveness. This population data (Section C., Population [Demographics] Monitoring) will be used 

to answer Question 4 of the Land Use Plan Effectiveness Report. 

Results of the effectiveness monitoring process for the ARMPA will be used to inform the need for finer-scale 

investigations, initiate adaptive management actions as described in the ARMPA, initiate causation 

determination, and/or determine if changes to management decisions are warranted. The measures used at the 

178
 
 

 

 

 

 

 

 

 

 

broad and mid scales will provide a suite of characteristics for evaluating the effectiveness of the adaptive 

management strategy. 

Fine and Site Scales 

Fine-scale (third-order) habitat selected by sage-grouse is described as the physical and geographic area within 

home ranges during breeding, summer, and winter periods. At this level, habitat suitability monitoring should 

address factors that affect sage-grouse use of, and movements between, seasonal use areas. The habitat 

monitoring at the fine and site scale (fourth order) should focus on indicators to describe seasonal home ranges 

for sage-grouse associated with a lek or lek group within a population or subpopulation area. Fine- and sitescale monitoring will inform the ARMPA effectiveness monitoring (see Section D., Effectiveness Monitoring) 

and the hard and soft triggers identified in the ARMPA’s adaptive management section. 

The BLM will coordinate with the State of Wyoming to share conservation, disturbance and vegetation 

analysis data to provide a core by core evaluation to make necessary adjustments in activity, priorities and 

other actions. 

Site-scale habitat selected by sage-grouse is described as the more detailed vegetation characteristics of 

seasonal habitats. Habitat suitability characteristics include canopy cover and height of sagebrush and the 

associated understory vegetation. They also include vegetation associated with riparian areas, wet meadows, 

and other mesic habitats adjacent to sagebrush that may support sage-grouse habitat needs during different 

stages in their annual cycle. 

As described in the Conclusion, details and application of monitoring at the fine and site scales will be 

described in the implementation-level monitoring plan for the ARMPA. The need for fine- and site-scalespecific habitat monitoring will vary by area, depending on proposed projects, existing conditions, habitat 

variability, threats, and land health. Examples of fine- and site-scale monitoring include: habitat vegetation 

monitoring to assess current habitat conditions; monitoring and evaluation of the success of projects targeting 

sage-grouse habitat enhancement and/or restoration; and habitat disturbance monitoring to provide localized 

disturbance measures to inform proposed project review and potential mitigation for project impacts. 

Monitoring plans should incorporate the principles outlined in the BLM’s AIM strategy (Toevs et al. 2011) 

and in “AIM-Monitoring: A Component of the Assessment, Inventory, and Monitoring Strategy” (Taylor et 

al. 2014). Approved monitoring methods are: “BLM Core Terrestrial Indicators and Methods” (MacKinnon 

et al. 2011); The BLM’s Technical Reference “Interpreting Indicators of Rangeland Health” (Pellant et al. 

2005); and, “Sage-Grouse Habitat Assessment Framework: Multiscale Assessment Tool” (Stiver et al. in 

press). 

Other state-specific disturbance tracking models include: the BLM’s Wyoming DDCT 

(http://ddct.wygisc.org/) and the BLM’s White River Data Management System in development with the 

USGS. Population monitoring data (in cooperation with state wildlife agencies) should be included during 

evaluation of the effectiveness of actions taken at the fine and site scales. 

Fine- and site-scale sage-grouse habitat suitability indicators for seasonal habitats are identified in the HAF. 

The HAF has incorporated the Connelly et al. (2000) sage-grouse guidelines as well as many of the core 

indicators in the AIM strategy (Toevs et al. 2011). There may be a need to develop adjustments to height and 

cover or other site suitability values described in the HAF; any such adjustments should be ecologically 

defensible. To foster consistency, however, adjustments to site suitability values at the local scale should be 

avoided unless there is strong, scientific justification for making those adjustments. That justification should 

be provided. WAFWA MZ adjustments must be supported by regional plant productivity and habitat data for 

the floristic province. If adjustments are made to the site-scale indicators, they must be made using data from 

the appropriate seasonal habitat designation (breeding/nesting, brood-rearing, winter) collected from sagegrouse studies found in the relevant area and peer-reviewed by the appropriate wildlife management 

agency(ies) and researchers. 

179
 
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

When conducting land heath assessments, the BLM should follow, at a minimum, “Interpreting Indicators of 

Rangeland Health” (Pellant et. al. 2005) and the “BLM Core Terrestrial Indicators and Methods” (MacKinnon 

et al. 2011). For assessments being conducted in sage-grouse designated management areas, the BLM should 

collect additional data to inform the HAF indicators that have not been collected using the above methods. 

Implementation of the principles outlined in the AIM strategy will allow the data to be used to generate 

unbiased estimates of condition across the area of interest; facilitate consistent data collection and rollup 

analysis among management units; help provide consistent data to inform the classification and interpretation 

of imagery; and provide condition and trend of the indicators describing sagebrush characteristics important 

to sage-grouse habitat (see Section D., Effectiveness Monitoring). 

Conclusion 

This Greater Sage-Grouse Monitoring Framework was developed for all of the RMPs involved in the sagegrouse planning effort. As such, it describes the monitoring activities at the broad and mid scales and provides 

a guide for the BLM to collaborate with partners/other agencies to develop the ARMPA’s specific monitoring 

plan. 

The BLM Greater Sage-Grouse Disturbance and Monitoring Subteam 

Membership 

Gordon Toevs (BLM -WO) Robin Sell (BLM-CO) 

Duane Dippon (BLM-WO) Paul Makela (BLM-ID) 

Frank Quamen (BLM-NOC) Renee Chi (BLM-UT) 

David Wood (BLM-NOC) Sandra Brewer (BLM-NV) 

Vicki Herren (BLM-NOC) Glenn Frederick (BLM-OR) 

Matt Bobo (BLM-NOC) Robert Skorkowsky (Forest Service) 

Michael “Sherm” Karl (BLM-NOC) Dalinda Damm (Forest Service) 

Emily Kachergis (BLM-NOC) Rob Mickelsen (Forest Service) 

Doug Havlina (BLM-NIFC) Tim Love (Forest Service) 

Mike Pellant (BLM-GBRI) Pam Bode (Forest Service) 

John Carlson (BLM-MT) Lief Wiechman (USFWS) 

Jenny Morton (BLM -WY) Lara Juliusson (USFWS) 

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core terrestrial indicators and methods. Tech Note 440. U.S. Department of the Interior, Bureau of 

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Oyler-McCance, F.R. Quamen, D.J. Saher, and A.J. Titolo. 2013. Summary of science, activities, 

programs, and policies that influence the rangewide conservation of Greater Sage-Grouse 

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plants in the United States. National Renewable Energy Laboratory, U.S. Department of Energy 

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4. Technical Reference 1734-6. U.S. Department of the Interior, Bureau of Land Management, 

National Science and Technology Center, Denver, CO. BLM/WO/ST-00/001+1734/REV05. 122pp. 

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S.C. Gardner, M.A. Hilliard, G.D. Kobriger, S.M. McAdam, C.W. McCarthy, J.J. McCarthy, D.L. 

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and M.A. Schroeder. 2006. Greater Sage‐Grouse comprehensive conservation strategy. Unpublished 

report. Western Association of Fish and Wildlife Agencies, Cheyenne, WY. Available at 

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183
 
- 

 

 

Attachment A: An Overview of Monitoring Commitments 

Implementation 

Broad and Mid scales 

Sagebrush 

Availability 

Habitat 

Degradation Population Effectiveness 

Fine and Site 

Scales 

How will 

the data be 

used? 

Tracking and 

documenting 

implementatio 

n of land use 

plan decisions 

and inform 

adaptive 

management 

Tracking 

changes in land 

cover 

(sagebrush) 

and inform 

adaptive 

management 

Tracking 

changes in 

disturbance 

(threats) to 

sage-grouse 

habitat and 

inform 

adaptive 

management 

Tracking 

trends in sagegrouse 

populations 

(and/or leks; as 

determined by 

state wildlife 

agencies) and 

inform 

adaptive 

management 

Characterizing 

the relationship 

among 

disturbance, 

implementation 

actions, and 

sagebrush 

metrics and 

inform adaptive 

management 

Measuring 

seasonal 

habitat, 

connectivity at 

the fine scale, 

and habitat 

conditions at 

the site scale, 

calculating 

disturbance 

and inform 

adaptive 

management 

Who is 

collecting 

the data? 

BLM FO NOC and 

NIFC 

National data 

sets (NOC), 

BLM FOs 

State wildlife 

agencies 

through 

WAFWA 

Comes from 

other broad and 

mid-scale 

monitoring 

types, analyzed 

by the NOC 

BLM FO and 

SO, (with 

partners) 

including 

disturbance 

How often 

are the data 

collected, 

reported 

and made 

available to 

USFWS? 

Collected and 

reported 

annually; 

summary every 

5 years 

Updated and 

changes 

reported 

annually; 

summary 

reports every 5 

years 

Collected and 

changes 

reported 

annually; 

summary 

reports every 5 

years 

State data 

reported 

annually per 

WAFWA 

MOU; 

summary 

reports every 5 

years 

Collected and 

reported every 5 

years 

(coincident with 

ARMPA 

evaluations) 

Collection and 

trend analysis 

ongoing, 

reported every 

5 years or as 

needed to 

inform 

adaptive 

management 

What is the 

spatial 

scale? 

Summarized 

by ARMPA 

with flexibility 

for reporting 

by other units 

Summarized 

by PACs (size 

dependent) 

with flexibility 

for reporting 

by other units 

Summarized 

by PACs (size 

dependent) 

with flexibility 

for reporting 

by other units 

Summarized 

by PACs (size 

dependent) 

with flexibility 

for reporting 

by other units 

Summarized by 

MZ, and 

ARMPA with 

flexibility for 

reporting by 

other units (e.g., 

PAC) 

Variable (e.g., 

projects and 

seasonal 

habitats) 

What are 

the 

potential 

personnel 

and budget 

impacts? 

Additional 

capacity or reprioritization 

of ongoing 

monitoring 

work and 

budget 

realignment 

At a minimum, 

current skills 

and capacity 

must be 

maintained; 

data mgmt. 

cost are TBD 

At a minimum, 

current skills 

and capacity 

must be 

maintained; 

data mgmt. and 

data layer 

purchase cost 

are TBD 

No additional 

personnel or 

budget impacts 

for BLM 

Additional 

capacity or reprioritization of 

ongoing 

monitoring 

work and budget 

realignment 

Additional 

capacity or reprioritization 

of ongoing 

monitoring 

work and 

budget 

realignment 

Who has 

primary 

and 

secondary 

responsibili 

ties for 

reporting? 

BLM FO & 

SO 

BLM Planning 

NOC 

WO 

NOC 

BLM SO & 

appropriate 

programs 

WAFWA & 

state wildlife 

agencies 

BLM SO, 

NOC 

Broad and midscale at the 

NOC, RMP at 

BLM SO 

BLM FO, 

BLM SO 

184
 
- Broad and Mid scales 

Fine and Site 

Implement- Scales 

ation 

What new 

processes/ 

tools are 

needed? 

National 

implementatio 

n data sets and 

analysis tools 

Sagebrush 

Availability 

Updates to 

national land 

cover data 

Habitat 

Degradation 

Data standards 

and roll-up 

methods for 

these data 

Population 

Standards in 

population 

monitoring 

(WAFWA) 

Effectiveness 

Reporting 

methodologies 

Data standards 

data storage; 

and reporting 

185
 
 

Attachment B - List of All Sagebrush Species and Subspecies Included in the 

Selection Criteria for Building the EVT and BPS Layers 

Artemisia arbuscula subspecies longicaulis
 

Artemisia arbuscula subspecies longiloba
 

Artemisia bigelovii
 

Artemisia nova
 

Artemisia papposa
 

Artemisia pygmaea
 

Artemisia rigida
 

Artemisia spinescens
 

Artemisia tripartita subspecies rupicola
 

Artemisia tripartita subspecies tripartita
 

Tanacetum nuttallii
 

Artemisia cana subspecies bolanderi
 

Artemisia cana subspecies cana
 

Artemisia cana subspecies viscidula
 

Artemisia tridentata subspecies wyomingensis
 

Artemisia tridentata subspecies tridentata
 

Artemisia tridentata subspecies vaseyana
 

Artemisia tridentata subspecies spiciformis
 

Artemisia tridentata subspecies xericensis
 

Artemisia tridentata variety pauciflora
 

Artemisia frigida
 

Artemisia pedatifida
 

186
 
 

 

 

 

 

Attachment C – User and Producer Accuracies for Aggregated Ecological 

Systems within LANDFIRE Map Zones 

LANDFIRE Map Zone Name User 

Accuracy 

Producer 

Accuracy 

% of Map Zone 

within Historic 

Schroeder 

Wyoming Basin 76.9% 90.9% 98.5% 

Snake River Plain 68.8% 85.2% 98.4% 

Missouri River Plateau 57.7% 100.0% 91.3% 

Grand Coulee Basin of the Columbia Plateau 80.0% 80.0% 89.3% 

Wyoming Highlands 75.3% 85.9% 88.1% 

Western Great Basin 69.3% 75.4% 72.9% 

Blue Mountain Region of the Columbia Plateau 85.7% 88.7% 72.7% 

Eastern Great Basin 62.7% 80.0% 62.8% 

Northwestern Great Plains 76.5% 92.9% 46.3% 

Northern Rocky Mountains 72.5% 89.2% 42.5% 

Utah High Plateaus 81.8% 78.3% 41.5% 

Colorado Plateau 65.3% 76.2% 28.8% 

Middle Rocky Mountains 78.6% 73.3% 26.4% 

Cascade Mountain Range 57.1% 88.9% 17.3% 

Sierra Nevada Mountain Range 0.0% 0.0% 12.3% 

Northwestern Rocky Mountains 66.7% 60.0% 7.3% 

Southern Rocky Mountains 58.6% 56.7% 7.0% 

Northern Cascades 75.0% 75.0% 2.6% 

Mogollon Rim 66.7% 100.0% 1.7% 

Death Valley Basin 0.0% 0.0% 1.2% 

There are two anomalous map zones with 0% user and producer accuracies, attributable to no available 

reference data for the ecological systems of interest. 

User accuracy is a map-based accuracy that is computed by looking at the reference data for a class and 

determining the percentage of correct predictions for these samples. For example, if I select any sagebrush 

pixel on the classified map, what is the probability that I'll be standing in a sagebrush stand when I visit that 

pixel location in the field? Commission Error equates to including a pixel in a class when it should have 

been excluded (i.e., commission error = 1 – user’s accuracy). 

Producer accuracy is a reference-based accuracy that is computed by looking at the predictions produced 

for a class and determining the percentage of correct predictions. In other words, if I know that a particular 

area is sagebrush (I've been out on the ground to check), what is the probability that the digital map will 

187
 
correctly identify that pixel as sagebrush? Omission Error equates to excluding a pixel that should have 

been included in the class (i.e., omission error = 1 – producer’s accuracy). 

188
 
 

 

 

 

 

 

 

 

 

 

COT Objective 6: Prioritize, fund and implement research to address existing 

uncertainties 

“Increased funding and support for key research projects that will address uncertainties 

associated with sage-grouse and sagebrush habitat management is essential. Effective 

amelioration of threats can only be accomplished if the mechanisms by which those threats 

are imposed on the redundancy, representation, and resilience of the species and its 

habitats are understood.” (COT report 2013) 

In accordance with BLM policy, the Record of Decision and Approved Plan will establish intervals and 

standards for evaluations as part of the implementation strategy. Priorities will be established based on the 

identified threats in the planning area, the conservation objectives included as part of the Approved Plan, 

and any potential uncertainties associated with sage-grouse and associated habitat management. A part of 

this strategy will include development of a budget to accomplish each of the identified tasks and fund 

potential research topics to address any uncertainties. 

As new science pertaining to sage-grouse and habitat is continuously evolving, refined management 

strategies may be necessary to ensure that BLM is utilizing the most current science, information, and data 

regarding sage-grouse. It is for this reason that BLM has collaborated with the State of Wyoming and 

USFWS to develop an adaptive management strategy as a part of the planning process. 

Wyoming Greater Sage-Grouse Adaptive Management Plan 

The Greater Sage-Grouse adaptive management plan provides a means of addressing and responding to 

unintended negative impacts to Greater Sage-Grouse and its habitat will be addressed before consequences 

become severe or irreversible. This adaptive management plan: 

• Utilizes science based soft and hard adaptive management triggers, 

• Addresses multiple scales of data, and 

• Utilizes an adaptive management working group. 

Adaptive Management Triggers 

Adaptive management triggers are essential for identifying when potential management changes are needed 

in order to continue meeting greater Sage-Grouse Conservation objectives. With respect to sage-grouse, all 

regulatory entities in Wyoming, including the BLM, use soft and hard triggers. Soft and hard triggers are 

focused on three metrics: 1) number of active leks, 2) acres of available habitat, and 3) population trends 

based on annual lek counts. The hard and soft trigger data will be analyzed as soon as it becomes available 

after the signing of the ROD and then at a minimum, analyzed annually thereafter. 

Soft Triggers: 

Soft triggers are indicators that management or specific activities may not be achieving the intended results 

of conservation action or that unanticipated changes to populations or habitats have occurred that have the 

potential to place habitats or populations at risk. The soft trigger is any deviation from normal trends in 

habitat or population in any given year. Metrics include, but are not limited to, annual lek counts, wing 

counts, aerial surveys, habitat monitoring, and DDCT evaluations. BLM field offices, with the assistance 

of their respective land and resource management plan implementation groups, local WGFD offices, and 

local sage-grouse working groups will evaluate the metrics with the Adaptive Management Working Group 

(AMWG) on an annual basis. For population metrics, normal population trends are calculated as the fiveyear running mean of annual population counts. The purpose of these strategies is to address localized 

greater sage-grouse population and habitat changes by providing the framework in which management will 

189
 
 

 

 

 

 

 

 

 

 

change if monitoring identifies negative population and habitat anomalies in order to avoid crossing a hard 

trigger threshold. 

Hard Triggers: 

Hard triggers are indicators that management is not achieving desired conservation results. Hard triggers 

would be considered a catastrophic indicator that the species is not responding to conservation actions, or 

that a larger-scale impact or set of impacts is having a negative effect. 

Within the range of normal population variables (five-year running mean of annual population counts), hard 

triggers shall be determined to take effect when two of the three metrics exceeds 60% of normal variability 

for the area under management in a single year, or when any of the three metrics exceeds 40% of normal 

variability for a three year time period within a five-year range of analysis. A minimum of three consecutive 

years in a five-year period is used to determine trends (i.e., Y1-2-3, Y2-3-4, Y3-4-5). 

Adaptive Management Response 

Soft Triggers Response: 

Soft triggers require immediate monitoring and surveillance to determine causal factors and may require 

curtailment of activities in the short- or long-term, as allowed by law. The project level adaptive 

management strategies will identify appropriate responses where the project’s activities are identified as 

the causal factor. The management agency (BLM) and the AMWG will implement an appropriate response 

strategy to address causal factors not attributable to a specific project or to make adjustments at a larger 

regional or state-wide level. 

Hard Trigger Response: 

Upon determination that a hard trigger has been tripped, the BLM will immediately defer issuance of 

discretionary authorizations for new actions within the Biologically Significant Unit for a period of 90 days. 

In addition, within 14 days of a determination that a hard trigger has been tripped, the AMWG will convene 

to develop an interim response strategy and initiate an assessment to determine the causal factor or factors 

(hereafter called the causal factor assessment). 

An interim response strategy will be developed, and implemented to the extent permitted by law, within 90 

days of determination that a hard trigger has been tripped. The technical team will be consulted to identify 

the scope and scale of the interim strategy. Based on the recommendation of the AMWG, the BLM will 

implement an interim response strategy through an Instruction Memorandum or other management 

mechanisms to direct management until the causal factor(s) and appropriate response(s) can be determined. 

The interim response strategy will consist of appropriate management measures undertaken at the project 

stage, supported by the best available science, to address the specific metric which has been tripped and 

may include deferral of some activities as appropriate. Measures that were analyzed in this EIS and the 

COT, NTT reports, and NPT guidance will be reviewed in addition to current science to identify the most 

appropriate measures to be implemented as part of the interim response strategy. The BLM will comply 

with all applicable law in implementing such response(s), and, if applicable, will undertake a plan 

amendment or revision under BLM’s planning regulations and policies. 

Baseline sage-grouse population levels are established by pre-disturbance surveys, reference surveys and 

accounting for regional and statewide trends in population levels. Population counts in Wyoming are 

maintained by the WGFD. Estimates of population are determined based upon survey protocols determined 

by the WGFD, and are implemented consistently throughout the state. Population counts are tracked for 

individual leks and then calculated for each core area (PHMA). 

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Interim Strategy 

An interim response strategy will be developed, and implemented to the extent permitted by law, within 90 

days of determination that a hard trigger has been tripped. The technical team (see Implementation Groups 

below) will be consulted to identify the scope and scale of the interim strategy. Based on the 

recommendation of the AMWG, the BLM will implement an interim response strategy through an 

Instruction Memorandum or other management mechanisms to direct management until the causal factor(s) 

and appropriate response(s) can be determined. The interim response strategy will consist of appropriate 

management measures undertaken at the project stage, supported by the best available science, to address 

the specific metric which has been tripped and may include deferral of some activities as appropriate. 

Measures that were analyzed in this EIS and the COT, NTT reports, and NPT guidance will be reviewed in 

addition to current science to identify the most appropriate measures to be implemented as part of the 

interim response strategy. The BLM will comply with all applicable law in implementing such response(s), 

and, if applicable, will undertake a plan amendment or revision under BLM’s planning regulations and 

policies. 

The interim strategy will be implemented for the biologically significant unit (BSU), which, in Wyoming, 

is the core area, regardless of whether the core area crosses multiple planning boundaries. If it has been 

identified that more than one core area has the same hard triggers being tripped, or is trending towards 

triggers being tripped, the interim strategy will be implemented at the appropriate scale. 

Causal Factor Assessment 

The causal factor assessment will be completed within 180 days of determination that a hard trigger 

threshold has been crossed. Once the causal factor assessment is completed by the AMWG, the interim 

response strategy will be modified to adequately address the causal factors in consultation with the technical 

team. If a causal factor or factors cannot be identified, the interim response strategy shall stay in place until 

the cause can be determined and any new planning decision can be implemented. 

EIS Level Projects 

Each major project (EIS level) will include adaptive management strategies in support of the population 

management objectives for Greater Sage-Grouse set by the State of Wyoming, and will be consistent with 

the Wyoming Greater Sage-Grouse Adaptive Management Plan. These adaptive management strategies 

will be developed in partnership with the AMWG, WGFD, project proponents, partners, and stakeholders, 

incorporating the best available science. 

Implementation Groups 

Sage-Grouse Implementation Team 

The State of Wyoming’s strategy is implemented by the Sage-Grouse Implementation Team (SGIT), 

established by Executive Order in 2008 and codified in 2014 by the Wyoming Legislature (W.S. § 9-19­

101). The SGIT is a Governor appointed body with representation by federal agencies (BLM, Forest 

Service, USFWS, and NRCS), state agencies (WGFD, Department of Agriculture, Department of 

Environmental Quality, Wildlife and Natural Resource Trust Fund, Oil and Gas Conservation Commission, 

and Office of State Lands and Investments), the Wyoming Legislature, county governments, energy 

developers, mining companies, landowners, and non- governmental organizations. The BLM, USFWS, 

NRCS and the Forest Service all have an equal role in the SGIT. 

Land and Resource Management Plan – Implementation Teams 

Land and Resource Management Plans are implemented through implementation teams. These 

implementation teams include cooperating agencies who participated in the development of this land use 

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plan representing local, state, and federal agencies. These implementation teams will coordinate with the 

AMWG and others to evaluate metrics and management responses necessary to meet Greater Sage-Grouse 

conservation objectives within their planning area. 

Adaptive Management Working Group and Technical Team 

An Adaptive Management Working Group (AMWG) will be established in consultation with the SGIT to 

provide appropriate guidance for agencies with the ability to affect sage-grouse populations and/or habitat 

through their permitting authority. The AMWG will include BLM, Forest Service, USFWS, and State of 

Wyoming. The purpose of this group will be to initiate a response strategy should it be determined that a 

hard trigger has been tripped or if soft triggers are showing a trend across a region. A hard trigger may be 

tripped at any time, thus, upon identification of such event, current available population and habitat data 

will be reviewed by the AMWG with the assistance of a technical team comprised of agency biologists, 

scientists familiar with the Management Zone in question, and other individuals as appropriate (e.g., habitat 

managers, respective landowners, other appropriate representatives) to confirm that a hard trigger has been 

tripped. Upon verification of data showing that a hard trigger has been tripped, the AMWG will convene 

within 14 days. 

The AMWG will review monitoring data which has been collected by the appropriate local sage-grouse 

working groups in conformance with data collection standards. This group will meet annually to review all 

data collected in the prior year regarding Greater Sage-Grouse populations and habitats. Monitoring data 

will have been analyzed (by WGFD for population based metrics (leks, wing counts, etc. and by land 

managers [BLM, Forest Service, State of Wyoming] for habitat based metrics [DDCT, etc.]) Should the 

monitoring data suggest a trend toward a soft or hard trigger being tripped, they will 1. Identify what metric 

is indicating that trend (population or habitat); and 2. Identify a technical team to review the data and 

compile a range of activities which may be causing the trend. Should review of the monitoring data identify 

that multiple soft triggers have been tripped in one core area, or the same triggers have been tripped across 

multiple core areas, the technical team will be tasked with verifying the scope and intensity of the trends. 

Once the analysis of the trends has been completed by the technical team and reported back to the AMWG, 

the AMWG will make recommendations to the appropriate land managing agency regarding an interim 

adaptive management strategy to be implemented. Implementation will occur via the appropriate 

regulations and policy applicable for that agency. At that time, the State of Wyoming will conduct a review 

of the regulatory authority implementing the Sage-Grouse Core Area Strategy to determine if a State of 

Wyoming adaptive management strategy is warranted. 

Upon review of the annual data by the AMWG and technical team, the State of Wyoming, as part of the 

AMWG, will contact neighboring states within the respective Management Zone to inform them of any 

findings. Should a hard trigger be tripped, the trigger which has been tripped and any recommended 

adaptive management strategy being implemented will be shared with the appropriate neighboring state(s). 

Should the need arise for implementation of a multi-state adaptive management strategy; the AMWG will 

coordinate to develop an effective response. 

Small Leks 

Small leks will be given special consideration. Due to geographic variations a definition of “small” is not 

provided, rather determination of “small” will be made by the AMWG based upon recommendations of the 

scientific community. Generally, “small” is considered 10 or fewer males for a three year time period within 

a five-year range of analysis. If a trigger is hit based upon such a lek, then the adaptive management working 

group will evaluate the site-specific circumstances and determine appropriate remedial action. 

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Glossary Terms 

Additionality: The conservation benefits of compensatory mitigation are demonstrably new and would not 

have resulted without the compensatory mitigation project. (BLM Manual Section 1794). 

Avoidance mitigation: Avoiding the impact altogether by not taking a certain action or parts of an action. 

(40 CFR 1508.20(a)) (e.g., may also include avoiding the impact by moving the proposed action to a 

different time or location.) 

Compensatory mitigation: Compensating for the (residual) impact by replacing or providing substitute 

resources or environments. (40 CFR 1508.20) 

Compensatory mitigation projects: Specific, on-the-ground actions to improve and/or protect habitats 

(e.g. chemical vegetation treatments, land acquisitions, conservation easements). 

Compensatory mitigation sites: The durable areas where compensatory mitigation projects will occur. 

Durability (protective and ecological): The administrative, legal, and financial assurances that secure and 

protect the conservation status of a compensatory mitigation site, and the ecological benefits of a 

compensatory mitigation project, for at least as long as the associated impacts persist. (BLM Manual 

Section 1794). 

Minimization mitigation: Minimizing impacts by limiting the degree or magnitude of the action and its 

implementation. (40 CFR 1508.20 (b)) 

Residual impacts: Impacts from an authorized land use that remain after applying avoidance and 

minimization mitigation; also referred to as unavoidable impacts. 

Timeliness: The conservation benefits from compensatory mitigation accruing as early as possible or 

before impacts have begun. (BLM Manual Section 1794). 

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