Bureau of Land Management Approved Resource Management Plan Amendment for Greater Sage-Grouse Wyoming

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

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

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 sage-

grouse 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 state-

wide 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

Other

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 Managed

10,721,145 (71)

15,745,138 (60)

12,017,562

Total

15,081,561

26,195,722

Excludes Wind River Indian Reservation Acreages

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 step-

wise 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 sage-

grouse. 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 state-

level (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 Sage-

Grouse 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 incentive-

based 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 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.

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 sage-

grouse 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 (mid-

scale), 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

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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 Sage-

Grouse 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, sage-

grouse habitat, and sage-grouse populations at the broad and mid scales.) For sage-grouse habitat at the fine

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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 sage-

grouse 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

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 sage-

grouse, 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

Urbanization

Wildfire

Conifer encroachment

Treatments

Invasive Species

Energy (oil and gas wells and development facilities)

Energy (coal mines)

Energy (wind towers)

Energy (solar fields)

Energy (geothermal)

Mining (active locatable, leasable, and salable

developments)

X X

Infrastructure (roads)

Infrastructure (railroads)

Infrastructure (power lines)

Infrastructure (communication towers)

Infrastructure (other vertical structures)

Other developed rights of ways

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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 pre-

EuroAmerican 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 Oak-

Mixed 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

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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 Euro-

American 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.

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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 multi-

scale 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-to-

year 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

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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

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create a consistent naming nomenclature for future data analyses. These population 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 sage-

grouse 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,

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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,

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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 sage-

grouse 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

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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 site-

scale 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-scale-

specific 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 sage-

grouse 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 sage-

grouse 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)

Literature Cited

Baruch-Mordo, S., J.S. Evans, J.P. Severson, D.E. Naugle, J.D. Maestas, J.M. Kiesecker, M.J. Falkowski, C.A.

Hagen, and K.P. Reese. 2013. Saving sage-grouse from the trees: A proactive solution to reducing a

key threat to a candidate species. Biological Conservation 167:233–241.

Connelly, J.W., S.T Knick, M.A. Schroeder, and S.J. Stiver. 2004. Conservation assessment of Greater Sage-

Grouse and sagebrush habitats. Unpublished report. Western Association of Fish and Wildlife

Agencies, Cheyenne, WY. Available at

http://sagemap.wr.usgs.gov/ docs/Greater_Sage-

grouse_Conservation_Assessment_060404.pdf.

Connelly, J.W., K.P. Reese, and M.A. Schroeder. 2003. Monitoring of Greater Sage-Grouse habitats and

populations. Station Bulletin 80. College of Natural Resources Experiment Station, University of

Idaho, Moscow, ID.

180

Connelly, J.W., M.A. Schroeder, A.R. Sands, and C.E. Braun. 2000. Guidelines to manage sage-grouse

populations and their habitats. Wildlife Society Bulletin 28:967–985.

Davies, K.W., C.S. Boyd, J.L. Beck, J.D. Bates, T.J. Svejcar, and M.A. Gregg. 2011. Saving the sagebrush

sea: An ecosystem conservation plan for big sagebrush plant communities. Biological Conservation

144:2573–2584.

Fry, J.A., G. Xian, S. Jin, J.A. Dewitz, C.G. Homer, L. Yang, C.A. Barnes, N.D. Herold, and J.D. Wickham.

2011. Completion of the 2006 National Land Cover Database for the conterminous United States.

PE&RS 77(9):858–864.

Garton, E.O., J.W. Connelly, J.S. Horne, C.A. Hagen, A. Moser, and M. Schroeder. 2011. Greater Sage-

Grouse population dynamics and probability of persistence. In: Greater Sage-Grouse: Ecology and

conservation of a landscape species and its habitats, edited by S.T. Knick and J.W. Connelly, 293–382.

Studies in Avian Biology, vol. 38. University of California Press, Berkeley, CA.

Grove, A.J., C.L. Wambolt, and M.R. Frisina. 2005. Douglas-fir’s effect on mountain big sagebrush wildlife

habitats. Wildlife Society Bulletin 33:74–80.

Gruell, G.E., J.K. Brown, and C.L. Bushey. 1986. Prescribed fire opportunities in grasslands invaded by

Douglas-fir: State-of-the-art guidelines. General Technical Report INT-198. U.S. Department of

Agriculture, Forest Service, Intermountain Research Station, Ogden, UT. 19pp.

Harju, S.M., M.R. Dzialak, R.C. Taylor, L.D. Hayden-Wing, J.B. Winstead. 2010. Thresholds and time lags in

effects of energy development on Greater Sage-Grouse populations.

Journal of

Wildlife Management

74(3):437–448.

Hemstrom, M. A., M. J. Wisdom, M. M. Rowland, B. Wales, W. J. Hann, and R. A. Gravenmier. 2002.

Sagebrush-steppe vegetation dynamics and potential for restoration in the Interior Columbia Basin,

USA. Conservation Biology 16:1243–1255.

Homer, C.G., C.L. Aldridge, D.K. Meyer, M.J. Coan, and Z.H. Bowen. 2009. Multiscale sagebrush rangeland

habitat modeling in southwest Wyoming: U.S. Geological Survey Open-File Report 2008–1027.

14pp.

Johnson, D.H. 1980. The comparison of usage and availability measurements for evaluating resource

preference. Ecology 61:65–71.

Knick, S.T., and J.W. Connelly (editors). 2011. Greater Sage-Grouse: Ecology and conservation of a landscape

species and its habitats. Studies in Avian Biology, vol. 38. University of California Press, Berkeley,

CA.

Knick, S.T., and S.E. Hanser. 2011. Connecting pattern and process in Greater Sage-Grouse populations and

sagebrush landscapes. In: Greater Sage-Grouse: Ecology and conservation of a landscape species

and its habitats, edited by S.T. Knick and J.W. Connelly, 383–405. Studies in Avian Biology, vol. 38.

University of California Press, Berkeley, CA.

Knick, S.T., S.E. Hanser, R.F. Miller, D.A. Pyke, M.J. Wisdom, S.P. Finn, E.T. Rinkes, and C.J. Henny. 2011.

Ecological influence and pathways of land use in sagebrush. In: Greater Sage-Grouse: Ecology and

conservation of a landscape species and its habitats, edited by S.T. Knick and J.W. Connelly, 203–251.

Studies in Avian Biology, vol. 38. University of California Press, Berkeley, CA.

LANDFIRE: LANDFIRE Existing Vegetation Type layer. (2013, June – last update.) U.S. Department of

the Interior, U.S. Geological Survey. [Online.] Available at:

http://landfire.cr.usgs.gov/viewer/

[2013,

May 8].

181

Leu, M., and S.E. Hanser. 2011. Influences of the human footprint on sagebrush landscape patterns:

implications for sage-grouse conservation. In: Greater Sage-Grouse: Ecology and conservation of a

landscape species and its habitats, edited by S.T. Knick and J.W. Connelly, 253–271. Studies in Avian

Biology, vol. 38. University of California Press, Berkeley, CA.

MacKinnon, W.C., J.W. Karl, G.R. Toevs, J.J. Taylor, M. Karl, C.S. Spurrier, and J.E. Herrick. 2011. BLM

core terrestrial indicators and methods. Tech Note 440. U.S. Department of the Interior, Bureau of

Land Management, National Operations Center, Denver, CO.

Manier, D.J., D.J.A Wood, Z.H. Bowen, R.M. Donovan, M.J. Holloran, L.M. Juliusson, K.S. Mayne, S.J.

Oyler-McCance, F.R. Quamen, D.J. Saher, and A.J. Titolo. 2013. Summary of science, activities,

programs, and policies that influence the rangewide conservation of Greater Sage-Grouse

(Centrocercus urophasianus): U.S. Geological Survey Open–File Report 2013–1098. 170pp.

NatureServe. 2011. International ecological classification standard: Terrestrial ecological classifications.

NatureServe Central Databases, Arlington, VA. Data current as of July 31, 2011.

Ong, S., C. Campbell, P. Denholm, R. Margolis, and G. Heath. 2013. Land-use requirements for solar power

plants in the United States. National Renewable Energy Laboratory, U.S. Department of Energy

Technical Report NREL/TP-6A20-56290. 39pp. Available at:

http://www.nrel.gov/docs/fy13osti/56290.pdf.

Pellant, M., P. Shaver, D.A. Pyke, and J.E. Herrick. 2005. Interpreting indicators of rangeland health, version

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.

Perry, J. Personal communication. February 12, 2014.

Pyke, D.A. 2011. Restoring and rehabilitating sagebrush habitats. In: Greater Sage-Grouse: Ecology and

conservation of a landscape species and its habitats, edited by S.T. Knick and J.W. Connelly, 531–548.

Studies in Avian Biology, vol. 38. University of California Press, Berkeley, CA.

Schroeder, M.A., C.L. Aldridge, A.D. Apa, J.R. Bohne, C.E. Braun, S.D. Bunnell, J.W. Connelly, P.A. Deibert,

S.C. Gardner, M.A. Hilliard, G.D. Kobriger, S.M. McAdam, C.W. McCarthy, J.J. McCarthy, D.L.

Mitchell, E.V. Rickerson, and S.J. Stiver. 2004. Distribution of sage-grouse in North America.

Condor 106: 363–376.

Stiver, S.J., A.D. Apa, J.R. Bohne, S.D. Bunnell, P.A. Deibert, S.C. Gardner, M.A.

Hilliard, C.W. McCarthy,

and M.A. Schroeder. 2006. Greater Sage‐Grouse

comprehensive conservation strategy. Unpublished

report. Western

Association of Fish and Wildlife Agencies, Cheyenne, WY. Available at

http://www.wafwa.org/documents/pdf/GreaterSage-grouseConservationStrategy2006.pdf.

Stiver, S.J., E.T. Rinkes, D.E. Naugle, P.D. Makela, D.A. Nance, and J.W. Karl. In press.

Sage-grouse habitat assessment framework: Multiscale habitat assessment tool. Bureau of Land Management

and Western Association of Fish and Wildlife Agencies. Technical Reference. U.S. Department of the

Interior, Bureau of Land Management, Denver, CO.

Taylor, J., E. Kachergis, G. Toevs, J. Karl, M. Bobo, M. Karl, S. Miller, and C. Spurrier. 2014. AIM-

monitoring: A component of the BLM assessment, inventory, and monitoring strategy. Tech Note

445. U.S. Department of the Interior, Bureau of Land Management, National Operations Center,

Denver, CO.

182

Toevs, G.R., J.J. Taylor, C.S. Spurrier, W.C. MacKinnon, M.R. Bobo. 2011. Bureau of Land Management

assessment, inventory, and monitoring strategy: For integrated renewable resources management. U.S.

Department of the Interior, Bureau of Land Management, National Operations Center, Denver, CO.

U.S. Department of Agriculture. National Agricultural Statistics Service Cropland Data Layer. {YEAR}.

Published crop-specific data layer [online]. USDA-NASS, Washington, D.C. Available at

http://nassgeodata.gmu.edu/CropScape/(accessed

{DATE}; verified {DATE}).

United States Department of the Interior, Bureau of Land Management. 2001. Handbook H-4180-1, Release

4-107. Rangeland health standards handbook. Available at

http://www.blm.gov/style/medialib/blm/wo/Information_Resources_Management/policy/

blm_handbook.Par.61484.File.dat/h4180-1.pdf.

U.S. Department of the Interior, Bureau of Land Management. 2005. Wind Energy Development

Programmatic Environmental Impact Statement (EIS). BLM Washington Office, Washington, D.C.

U.S. Department of the Interior, Bureau of Land Management. 2011. BLM national Greater Sage-Grouse land

use planning strategy. Instruction Memorandum No. 2012-044. BLM Washington Office, Washington,

D.C.

U.S. Department of the Interior, Fish and Wildlife Service. 2010. Endangered and threatened wildlife and

plants; 12-month findings for petitions to list the Greater Sage-Grouse (Centrocercus urophasianus)

as threatened or endangered. Proposed Rule. Federal Register 75: 13910–14014 (March 23, 2010).

U.S. Department of the Interior, Fish and Wildlife Service. 2013. Greater Sage-Grouse (Centrocercus

urophasianus) conservation objectives: Final report. U.S. Fish and Wildlife Service, Denver, CO.

183

Attachment A: An Overview of Monitoring Commitments

Implement-

ation

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 sage-

grouse

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 re-

prioritization

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 re-

prioritization of

ongoing

monitoring

work and budget

realignment

Additional

capacity or re-

prioritization

of ongoing

monitoring

work and

budget

realignment

Who has

primary

and

secondary

responsibili

ties for

reporting?

BLM FO &

BLM Planning

NOC

BLM SO &

appropriate

programs

WAFWA &

state wildlife

agencies

BLM SO,

NOC

Broad and mid-

scale at the

NOC, RMP at

BLM SO

BLM FO,

BLM SO

184

Broad and Mid scales

Fine and Site

Scales

Implement-

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%

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%

12.3%

Northwestern Rocky Mountains

66.7%

60.0%

7.3%

Southern Rocky Mountains

58.6%

56.7%

7.0%

Northern Cascades

75.0%

2.6%

Mogollon Rim

66.7%

100.0%

1.7%

Death Valley Basin

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 five-

year 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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