Framework for Ecological Monitoring on Lands of the 

Alaska National Wildlife Refuges and Their Partners 

Open-File Report 2010–1300

U.S. Department of the Interior

U.S. Geological Survey

Framework for Ecological Monitoring 

on Lands of the Alaska National Wildlife 

Refuges and Their Partners

By Andrea Woodward and Erik A. Beever

Open-File Report 2010–1300

U.S. Department of the Interior

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

KEN SALAZAR, Secretary

U.S. Geological Survey

Marcia K. McNutt, Director

U.S. Geological Survey, Reston, Virginia: 2010

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Suggested citation:

Woodward, Andrea, and Beever, E.A., 2010, Framework for ecological monitoring on lands of Alaska National Wildlife 

Refuges and their partners, Anchorage, Alaska: U.S. Geological Survey Open-File Report 2010-1300, 94 p.
iii

Contents

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

Chapter 1. Context for Developing Broad-Scale Monitoring for Alaska NWRs..................................5

Chapter 2. Programmatic and Monitoring Objectives for Alaska NWRs .............................................9

Chapter 3. Developing Monitoring Program Strategy and Structure..................................................11

Chapter 4. Identifying Monitoring Indicators ..........................................................................................17

Chapter 5. Sample Design Considerations ..............................................................................................26

Chapter 6. Building Blocks for Alaska NWRs Monitoring Program ....................................................34

Chapter 7. Road Map for Developing Monitoring Plan..........................................................................44

Chapter 8. Conclusions ...............................................................................................................................46

Acknowledgments.......................................................................................................................................47

References Cited..........................................................................................................................................48

Appendix 1. Summary of National Park Service Inventory and Monitoring Program.....................53

Appendix 2. Summary of Inventory and Monitoring Program of Parks Canada ...............................56

Appendix 3. Summary of Forest Inventory and Assessment Program ...............................................59

Appendix 4. Summary of National Aquatic Resources Surveys..........................................................63

Appendix 5. Summary of United Kingdom Countryside Survey ...........................................................65

Appendix 6. Summary of Circumpolar Biodiversity Monitoring Program ..........................................67

Appendix 7. Summary of Environmental Monitoring and Assessment Network ..............................69

Appendix 8. Example Criteria and Weights for Ranking Indicators and Attributes ..........................71

Appendix 9. Ecological Monitoring Across Refuges .............................................................................73

Appendix 10. Monitoring Efforts by USFWS Programs Other than NWRS ........................................80

Appendix 11. Monitoring in Alaska by Agencies Other than USFWS .................................................84

Appendix 12. List of ecosystem components and processes monitored on U.S. National

Park Service lands, within each of four Inventory and Monitoring Networks in

Alaska...............................................................................................................................................86

Appendix 13. Notes from Manager’s Breakout Group at Forum on Ecoregional Monitoring

for the NWRS and Other Public Lands across Alaska.............................................................91
iv

Figures

Figure 1. Conceptual framework describing relationships among three types of

monitoring objectives and various aspects of monitoring-program structure ...... 9

Figure 2. Primary methods and strategies for distributing samples .............................. 28

Figure 3. Boundaries of Alaska National Wildlife Refuges in relation to Bird

Conservation Region (BCR) boundaries................................................... 35

Figure 4. Boundaries of Alaska National Wildlife Refuges, in relation to ecoregions

based on Nowacki and others (2001)...................................................... 37

Figure 5. Comparison among Nowacki-based ecoregions, boundaries of Alaska NWRs

and NPS units grouped by the four I&M networks in Alaska ........................ 39

Tables

Table 1. Examples of statutory mandates, management decisions, information needs,

and monitoring objectives that potentially affect USFWS at four spatial scales ... 6

Table 2. Summary of characteristics of broad-scale monitoring programs along several

dimensions of resource allocation ...................................................... 12

Table 3. Examples of monitoring topics and analyses relating to the purposes of

refuges dictated by Alaska National Interest Lands Conservation Act and the

Refuge Improvement Act, at multiple spatial scales relevant to Alaska National

Wildlife Refuges ........................................................................... 15

Table 4. Consequences of climate change that are of greatest concern to land

managers within each of four ecoregions within Alaska, as identified at the

(April 2009) Forum on Ecoregional Monitoring .......................................... 18

Table 5. Species, taxonomic groups and resource categories listed in refuge purposes

identified in ANILCA ........................................................................ 20

Table 6. List of potential monitoring indicators suggested by ecoregional-scale

conceptual models ........................................................................ 23

Table 7. Characteristics of simple random, cluster, and systematic sampling methods,

in the context of long-term ecological monitoring....................................... 27

Table 8. Advantages and disadvantages of equal-probability, stratified, and

unequal-probability sampling designs, in the context of long-term ecological

monitoring .................................................................................... 28
v

Table 9. Allocation of visits to 20 hypothetical sites, across 5 years of monitoring............ 29

Table 10. Federal and state lands in Alaska by ecoregion ....................................... 31

Table 11. A potential suite of indicators for which monitoring, assessment and

interpretation may occur at state-wide, ecoregional and refuge-specific

extents within Alaska ..................................................................... 32

Table 12. Examples of monitoring designs and temporal re-visit strategies that could be

used to guide monitoring of indicators listed in table 11 .............................. 33

Table 13. Entities within or adjacent to Alaska that perform monitoring of indicators in

table 11, and those that participate collaboratively, but are not the lead in

monitoring of each indicator (including entities that may monitor the indicator

in the future) ................................................................................. 40

Table 14. The top four priorities for inventory needs for National Wildlife Refuges in 

Alaska, as determined by each of four multi-disciplinary, multi-affiliation

groups at the (April 2009) Forum on Ecoregional Monitoring........................... 43

Table 15. A roughly sequential list of activities that are typically accomplished in the

development of an integrative, long-term program of monitoring natural

resources across broad spatial scales ................................................... 44

Tables—Continued
vi

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Executive Summary

National Wildlife Refuges in Alaska and throughout 

the U.S. have begun developing a spatially comprehensive 

monitoring program to inform management decisions, and 

to provide data to broader research projects. In an era of 

unprecedented rates of climate change, monitoring is essential 

to detecting, understanding, communicating and mitigating 

climate-change effects on refuge and other resources under 

the protection of U.S. Fish and Wildlife Service. Moreover, 

monitoring results must address spatial scales broader than 

individual refuges. This document provides guidance for 

building a monitoring program for refuges in Alaska that 

meets refuge-specific management needs while also allowing 

synthesis and summary of ecological conditions at the 

ecoregional and statewide spatial scales.

Chapter 1. Context for Developing Broad-Scale 

Monitoring for the Alaska NWRs

The National Wildlife Refuge System (NWRS) of the 

U.S. Fish and Wildlife Service (USFWS) maintains and 

protects approximately 38 million ha (hectares) of wildlife 

habitat in 551 refuges and other units of the system1. More 

than 81 percent (that is, 31 million ha; 77 million acres) of 

the NWRS holdings occur in the 16 refuges in Alaska, and 

24 percent of the Alaskan refuges is designated Wilderness. 

Refuges in Alaska provide critical habitat for resident and 

migratory animals. Their large size, relatively sparse human 

population, and Alaska’s extremely low road density means 

that these refuges contain complete, comparatively intact 

ecosystems, in contrast with most refuges in the rest of the 

country. Besides being guided by legislation (The Refuge 

Administration Act, as amended) governing the entire refuge 

system, refuges in Alaska also are regulated by specific rules 

authorized by the Alaska National Interest Lands Conservation 

Act (ANILCA). In 1980, ANILCA created and/or expanded 

refuges and other conservation system units across Alaska. 

ANILCA mandated that these 16 refuges be managed to 

protect a wider range of characteristics than do other U.S. 

Framework for Ecological Monitoring on Lands of 

Alaska National Wildlife Refuges and Their Partners

By Andrea Woodward and Erik A. Beever

refuges, namely to conserve natural landscapes, wildlife 

species dependent on vast relatively undeveloped areas, and 

entire ecosystems; and to provide opportunities for subsistence 

use. 

Chapter 2. Programmatic and Monitoring Objectives for 

Alaska NWRs

Multiple sets of objectives are required to underpin 

the development of a monitoring program. Programmatic 

objectives derive from the agency information needs and 

context, which in turn reflect the resources for which the 

agency is responsible, the nature of the responsibility, and 

available management tools as defined by statute. The Alaska 

NWR monitoring program will be embedded in the national 

program that is being developed concurrently. The draft 

programmatic objectives for the national program include:

1. Meet the Refuge System’s legal mandate to monitor the 

status and trends of fish, wildlife, and plant populations 

on refuges, to preserve wilderness character, and to collect 

and manage information needed to maintain biological 

integrity, biological diversity, and environmental health, 

and to preserve the character of designated wilderness 

within the System.

2. Advance fish and wildlife conservation at refuge and 

broader landscape scales in an adaptive-management 

cycle by providing scientific information that supports 

conservation planning and design, guides learning through 

evaluation of conservation delivery, and provides a basis 

for hypothesis-driven research.

3. Implement monitoring of fish, wildlife, plants, physical 

resources, and ecological processes to reduce uncertainty 

in decisions related to impacts of climate change and 

other stressors, provide early warning of changing 

conditions, and guide development of management 

actions that facilitate adaptation to climate change.

4. Synthesize, interpret, and report on the condition of fish, 

wildlife, plants, and habitats conserved by the Refuge 

System in a manner that documents the contributions of 

the System within the context of the larger conservation 

estate and clearly communicates its value to the American 

public.

1

These numbers exclude the area added by establishment of the 

Northwestern Hawaiian Islands Marine National Monument, which is 

co-managed with NOAA.
2 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

5. Enhance effectiveness and reduce costs by coordinating 

and integrating monitoring of natural resources at 

landscape scales through collaboration with other Service 

programs, agencies, and organizations.

Monitoring objectives derive from the programmatic 

objectives and specifically reflect the information needs of 

the agency to describe what should be monitored. Refinement 

of these objectives leads to measurable objectives and the 

identification of indicators, attributes, and sample plans. 

Potential program-level monitoring objectives include:

1. Determine trends in population size of species subject to 

subsistence use.

2. Determine whether intact ecosystems and natural 

processes are being conserved within and across refuges, 

especially in response to climate change.

3. Determine trends in populations of focal species, where 

focal species are determined by the agency and include 

a subset of ‘trust’ species plus other priority species (for 

example, species especially sensitive to climate change).

4. Determine trends in water quality and quantity relative 

to legal standards and levels necessary for ecosystem 

function.

These objectives express the most general information 

needs. There may be refuge-specific, ecoregional, statewide, and in some cases, international aspects to all of these 

objectives.

Chapter 3. Developing Monitoring Program Strategy and 

Structure

Examples of how extant broad-scale monitoring programs addressed necessary trade-offs in monitoring program 

design were presented at the Forum on Ecoregional Monitoring for the NWRS and other Public Lands across Alaska, held 

April 2009, in Anchorage. Conclusions regarding considerations relevant to monitoring program development by staff of 

the Alaska NWRs include:

• Program commitment and relevance. Achieving 

sustained support requires regular reporting of results, 

and champions of the program at multiple political and 

administrative levels, which are all aided by having 

clear objectives and an organizational commitment to 

efficiency and effectiveness of the program. 

• Linkage to management. Monitoring results must 

provide relevant information and must be clearly 

communicated to management. Two classes of 

information needs exist for refuge managers: 

information regarding protection of biodiversity 

and ecosystem integrity, and information regarding 

management actions that are currently taken or are 

likely to be taken.

• Investment in Planning. The design of a monitoring 

program is not a trivial exercise, and its success 

depends on making carefully considered decisions. 

Rushing to the data-collection phase will compromise 

the program in the long term.

• Investment in Data Management. Monitoring results 

cannot be delivered promptly and accurately, nor can 

data be properly archived for future unforeseen uses, 

without a significant investment (about 30 percent of 

program budget) in data management.

• Adaptive monitoring. The monitoring program 

must be flexible to changes in information needs as 

resource condition changes in response to changes 

in system drivers; with changes in the political and 

social climate; as monitoring and research generate 

knowledge; and with changes in data collection 

technology. 

• Collaboration for efficiency. Collaboration with other 

agencies, and with national and international programs, 

especially for treaty species, will enhance the value of 

the NWRS program of monitoring in Alaska, even if 

data can be combined only qualitatively. 

• Context for monitoring design and interpretation. 

Ecosystem conceptual models identify important 

elements and articulate hypotheses regarding 

system function, and therefore are useful tools for 

planning monitoring, linking monitoring to adaptive 

management, and learning from monitoring results. 

• Spatial scales. In general, refuge-specific monitoring 

plans will be most effective if embedded within an 

ecoregional and statewide monitoring framework so 

that results can contribute to, and be interpreted in, 

an ecoregional context. In some cases, monitoring 

projects may meet purely local needs, but that 

determination must be reached after consideration of 

the broader context.

• Temporal scales. An effective monitoring strategy 

recognizes that some monitoring objectives meet 

short-term, tactical needs and others meet long-term, 

strategic needs.

• Survey and monitoring designs. Probabilistic sample 

designs are necessary for extrapolating monitoring 

results from the sample to an entire population or 

region. 

 The structure of the monitoring program will reflect 

agency context and culture and must describe where 

responsibilities, capabilities and decisions reside both 

organizationally and spatially. Because monitoring objectives 

are hierarchical in time and space, a hierarchically designed 

monitoring structure is appropriate to consider.
Executive Summary 3

Chapter 4. Identifying Monitoring Indicators

Unlike most of the refuges in the contiguous United 

States, the Alaska refuges are expected to protect natural 

landscapes and entire ecosystems; wildlife species dependent 

on vast, relatively undeveloped areas; and particular species 

of conservation interest. Consequently, they are faced with 

a challenge similar to that of national parks. Namely, they 

must develop a monitoring program to assess whether 

protective management is successfully conserving something 

as complex and open-ended as biodiversity. In addition, 

the NWRS in Alaska has specific resources for which it is 

responsible and around which managers undertake active 

management (for example, species subject to subsistence 

harvest) for which an adaptive-management approach may 

be appropriate. A potential approach, therefore, is to develop 

two monitoring programs (Timko and Innes, 2009), (1) to 

address the strategic information need for understanding of 

status and trends of ecological integrity, and (2) to address the 

tactical information need to assist managers in assessing the 

effectiveness of management actions. Sources for indicators 

of ecological integrity include conceptual models at the 

refuge and ecoregional scales; sources of indicators for 

management actions include refuge purposes, as specified 

in ANILCA. There will always be more potential indicators 

than the program can feasibly accommodate, and there are a 

number of options and strategies for determining priorities and 

incorporating cost considerations.

Chapter 5. Developing Sample Frames

The primary consideration for designing a sample frame 

for any particular indicator is a specifically stated objective. 

Frequently, the identification and framing of a question is 

the most difficult task faced during the design of monitoring 

programs. Although staff of the Alaska NWRs are several 

steps away from articulating monitoring objectives, our 

discussion in Chapter 4 suggests that it is likely that there 

generally will be both tactical and strategic monitoring needs. 

The type of need, along with characteristics of the indicator, 

detail and confidence desired, opportunities for collaboration, 

and budget, determine the sampling strategy. One of three 

strategies is most commonly used: index (reference sites), 

especially appropriate when there is a model to extrapolate 

results; census (comprehensive), such as can be obtained using 

remote-sensing; and probabilistic samples, appropriate when 

the goal is to extrapolate results from a subset of a population 

to draw conclusions about an entire domain of interest. If 

a probabilistic strategy is adopted, there are many ways to 

construct the sample frame to maximize inference while 

accommodating the logistical challenges of operating in the 

Alaskan environment.

Chapter 6. Building Blocks for Alaska NWRs Monitoring 

Program

Several building blocks of the foundation for developing 

a monitoring program for Alaska NWRs include:

• Conceptual models. Refuge-specific and ecoregional 

conceptual models have already been developed for 

Alaska, although they will need refinement to address 

specific monitoring questions.

• Ecoregional Structure. A potential structure describing 

ecoregionally based groupings among refuges and 

with management units of other agencies has been 

developed based on extant ecoregional maps of Alaska. 

Ecoregions include Polar, Interior Alaska, Bering 

Coast, and North Pacific Coast.

• Existing Inventories from Alaska NWRs. Alaska refuges 

have existing inventories of selected resources, which 

provide baseline information and background for 

monitoring planning.

• Current Monitoring in and around Alaska NWRs. 

Selected resources on all refuges are currently 

monitored by refuge staff members, other programs 

within USFWS, other agencies, or in collaboration 

with partners.

• Priorities for Baseline Information Needs. Refuge staff 

members have developed prioritized lists of needs for 

baseline information to create a context for monitoring.

• Technical Capabilities. Two data-management 

positions exist in Region 7 refuges, and two more 

regional-level positions will be hired this year (2010) 

to supplement the current data-management activities 

already being conducted by refuge staff.

Chapter 7. Road Map for Developing Monitoring Plan

A detailed list of decisions and activities, and the time 

needed for each, is provided. Given that this program is being 

instituted for the long term and it addresses both strategic 

and tactical information needs at multiple spatial scales in a 

rapidly changing and diverse environment, it is important to 

design it carefully. Although programmatic and monitoring 

objectives are yet to be developed by staff of Alaska NWRs, 

we nevertheless provide a list of potential monitoring 

topics and spatial scales based on statutory mandates and 

ecosystem conceptual models (table ES1). Our purpose is to 

provide a realistic example of a monitoring program as the 

basis for providing specific suggestions for sample frame 

and identifying partnerships with other agencies that are 

monitoring the same topic. This is not meant to discount the 

need for clearly stated monitoring objectives, nor the process 

of refining them to the detail of measureable objectives.
4 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Chapter 8. Conclusions

Efforts to develop an effective monitoring program 

embedded in an ecoregional framework across the Alaska 

NWRs have recognized that development of monitoring 

programs requires careful thought, support from agency 

staff, development of an infrastructure within the agency, and 

learning from the experiences of other agencies. Important 

concepts include:

• Monitoring programs must be guided by a hierarchy of 

objectives, including programmatic, monitoring, and 

measureable objectives.

• Refuge managers have both tactical and strategic 

information needs, and they must be addressed in 

different ways.

Table ES1. A potential suite of monitoring topics for which monitoring, assessment, and 

interpretation may occur at statewide, ecoregional and refuge-specific extents. 

[Note that for all topics except invasive species we have listed only the broadest extent at which monitoring 

may be appropriate. At the statewide extent, we identified topics for which a statewide map for that topic 

would be relevant for regulatory, conservation, management, or other decisions]

Spatial scale Monitoring topic

Alaska-wide Climate

Air quality, precipitation chemistry

Land cover

Phenology

Water quality and quantity

Deformities and contaminants in organisms

Ecoregion Habitat mosaics

Migratory species

Permafrost-related events and resources

Shoreline changes

Invasive species

Other landscape processes

Refuge Subsistence resources

Ecological keystones, ecosystem engineers, or key landscape modifiers

Local stressors and responses

Refuge-significant species not covered at ecoregional extent

Special plant and animal communities

• Information needs, and therefore program structure, 

are hierarchical in space and time, and occur on spatial 

(local to international) and temporal (short- to longterm) continua. Often, more-detailed information 

is needed in the short term at small spatial scales, 

compared to needs over longer time periods and at 

broad spatial scales.

• Maintaining flexibility to meet future needs and 

variable budgets, collaborating effectively with other 

agencies, and limiting the scope of monitoring projects 

to the actual information needs are challenging tasks. 

• Effective data management is expensive, but crucial to 

success of monitoring.

• Efforts expended in planning and careful development 

of monitoring will be rewarded by an effective 

monitoring program that will inform management 

decisions.
Chapter 1 5

Chapter 1. Context for Developing 

Broad-Scale Monitoring for Alaska 

NWRs

The National Wildlife Refuge System (NWRS) of the 

U.S. Fish and Wildlife Service (USFWS) maintains and 

protects approximately 38 million ha (hectares) of wildlife 

habitat in 550 refuges and other units throughout the USA1. 

More than 81 percent (that is, 31 million ha; 77 million acres) 

of the nationwide NWRS holdings occur in the 16 refuges 

in Alaska, and 24 percent of Alaskan refuges is designated 

Wilderness. Refuges in Alaska provide critical habitat 

for resident and migratory animals, including migratory 

passerines, shorebirds, waterfowl, and water birds arriving 

from distant parts of the world (for example, Southeast 

Asia, Africa, Mexico, Central and South America) as well 

as terrestrial and marine mammals. The refuges, which span 

millions of hectares, tend to be located at low elevations where 

they primarily protect tundra and boreal-forest biomes, and 

where wetlands and waterfowl are often prevalent. Their large 

size, in conjunction with Alaska’s relatively sparse human 

population and extremely low road density, means that these 

refuges contain complete, comparatively intact ecosystems, 

relative to most refuges in the rest of the country. 

National Wildlife Refuges in Alaska and throughout 

the U.S. have begun developing a spatially comprehensive 

monitoring program. Although individual units (refuges) 

have conducted inventory, monitoring, and research studies 

for decades, to date they rarely plan and conduct work 

collaboratively. Although questions and issues may be 

similar among refuges, sampling design and field protocols 

are often developed independently for each refuge, thus 

limiting the ability to share data efficiently among refuges 

and to extrapolate results across ecoregions. Yet especially 

in an era of global climate change, changes within any 

refuge must be considered in the context of larger scales. 

For example, a significant loss of habitat in one refuge may 

have no impact on a migratory bird population if the required 

habitat has shifted rather than disappeared. To address some 

of these shortcomings, the U.S. Geological Survey (USGS) is 

supporting USFWS in Alaska through analysis of past studies, 

conceptual modeling of ecoregions, and development of an 

ecoregional monitoring framework to address the challenges 

of contemporary climate change and other landscapescale drivers. This assistance will inform USFWS staff as 

they design and implement refuge-specific inventory and 

monitoring (I&M) plans as well as a regional I&M program 

for Alaska refuges. The specific improvements sought by 

USFWS include: 

1. Identification of refuge-specific gaps in existing I&M 

based on ecoregional-scale conceptual modeling and a 

better understanding of climate-change effects; 

2. A stronger conceptual foundation for selection of 

monitoring indicators; 

3. Consistency in study design for similar surveys on 

different units; and

4. An integrated and cohesive approach to address 

regionally-scaled ecological questions. 

Additionally, USFWS seeks to identify gaps in naturalresource monitoring at the landscape scale, and to ensure that 

their inventory and monitoring efforts complement programs 

of other agencies. Other entities conducting monitoring 

in Alaska include other divisions within USFWS, other 

federal agencies, Tribes, and the State of Alaska, as detailed 

in Chapter 7 below. These efforts reflect agency-specific 

concerns at refuge, biome, state, and continental scales. 

Results from each scale can be used to inform management 

decisions at that scale, but not necessarily at other scales. A 

major challenge will be to work within this nested hierarchy 

of monitoring efforts. In table 1, we provide examples of 

statutory mandates, management decisions, and consequent 

information required at multiple spatial scales.

To support USFWS management activities, monitoring 

reports can: (a) inform management decisions regarding 

subsistence and sport harvest activities; (b) describe the 

status and trends of trust species; (c) provide data to larger 

research projects (for example, use data on marine bird colony 

productivity to indicate changes in ocean conditions and 

forage fish stocks; understand migratory bird populations); 

and/or (d) improve basic understanding of system drivers 

and processes. In an era of unprecedented climate change, 

monitoring is essential to detecting, understanding, 

communicating, and mitigating climate-change effects on 

refuge and other resources under the protection of USFWS. 

This information will aid conservation of resources, inform 

habitat management, support education and interpretation 

efforts, and generally sustain all aspects of refuge 

management.

 In this report, we provide guidance for building a 

monitoring program that meets refuge-specific management 

needs while also allowing synthesis and summary of 

ecological conditions at ecoregional and statewide spatial 

scales. Considerations in the development of this framework 

include the characteristic features of the Alaska NWRs, such 

as their: unique legal mandates, distinctive setting (that is, 

more ecologically similar to other polar nations than to the rest 

of the U.S.) and size, and areal predominance in the national 

refuge system. The plan also incorporates lessons learned from 

other large-scale monitoring programs and current thinking 

on monitoring design. Finally, it considers the administrative 

context of the Alaska NWRs in terms of the monitoring 

plan emerging from the national program and the potential 

to collaborate with neighboring federal and state agencies. 

1

These numbers exclude the area added by establishment of the 

Northwestern Hawaiian Islands Marine National Monument, which is 

co-managed with NOAA.
6 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

This effort ideally would complement and integrate with the 

national monitoring plan, providing valuable input to that 

process.

Throughout this document, the term ‘indicator’ refers 

to the elements of environmental composition, structure and 

function that sustain biological and ecological systems (Karr, 

1981; Noss, 1990; Dale and Beyeler, 2001). ‘Attributes’ 

are characteristics of those elements that are amenable to 

measurement, and therefore to being monitored.

Legal Mandates Directing Management of the 

NWRS in Alaska

A fundamental purpose for monitoring of managed lands 

is to support management decisions, which are made to meet 

legislated mandates. Management of Alaska NWRs is guided 

by the Alaska National Interest Lands Conservation Act of 

1980 (ANILCA), which recognizes the distinctive setting 

of these 16 refuges and gives them unique purposes. As a 

group, they are to be managed to preserve a wider range of 

characteristics than other U.S. refuges, namely “significant 

natural, scenic, historical, archeological, geological, scientific, 

wilderness, cultural, recreational and wildlife values.” 

[ANILCA §101 (a)]. Perhaps in recognition of possibilities 

afforded by their immense size, these refuges have the 

additional mandate to conserve natural landscapes, wildlife 

species dependent on vast, relatively undeveloped areas, 

and entire ecosystems. In recognition of the dependence of 

Alaskan native cultures and rural residents on harvest of 

natural resources, ANILCA also calls for refuge management 

to provide opportunities for subsistence use. ANILCA 

supersedes the National Wildlife Refuge System Improvement 

Act of 1997 (NWSRIA), if they should conflict (as stated in 

NWRSIA).

Continental/International Regional/State Ecoregional/LCC Land Unit

Statutory Mandates USFWS mandates 

(MMPA, ESA, MBPA)

ANILCA, ANCSA, 

AMBCC 

Secretarial Order Establishing legislation 

including ANILCA 

and original Executive 

Orders, Public 

Land Orders, and 

Proclamations

Management Decisions Budget allocation, special 

initiatives, flyway 

harvest regulations

Land acquisition, budget 

allocation, initiatives

Information needs 

across agencies

Harvest limits, GMUs, 

predator management, 

refuge land use decisions

Tactical Information 

Needs

International Rusty 

Blackbird Technical 

Group investigating 

severe, unexplained 

range-wide decline

Distribution of migratory 

bird nesting habitat, 

resource inventories, 

for example, rusty 

blackbirds, marine 

mammals

Resource inventories, 

for example, rusty 

blackbirds, marine 

mammals

Size of caribou population 

sufficient to allow 

opportunity for 

subsistence; refuge 

resource inventories, 

for example, rusty 

blackbirds, marine 

mammals

Strategic Information 

Needs

Partners in Flight trilateral 

plan, Circumpolar 

Assessment of Flora 

and Fauna, Phenology

Changes in distribution of 

migratory bird nesting 

habitat

Climate-change effects 

on resources

Climate-change effects on 

resources

Monitoring Objectives Understand status, trend, 

distribution, and 

phenology of migratory 

birds, marine mammals

Trends in statewide 

wetland distribution 

Monitor health of 

eelgrass

Determine caribou 

population abundance 

in Alaska Peninsula/ 

Becharof NWRs

Table 1. Examples of statutory mandates, management decisions, information needs, and monitoring objectives that potentially affect 

USFWS at four spatial scales. 

[Abbreviations: AMBCC, Alaska Migratory Bird Co-management Council; ANCSA, Alaska Native Claims Settlement Act ; ANILCA, Alaska National Interest 

Lands Conservation Act; ESA, Endangered Species Act; MBPA, Migratory Bird Protection Act; MMPA, Migratory Mammal Protection Act; GMU, Game 

Management Unit]
Chapter 1 7

In addition to clarifying the general management goals, 

ANILCA also defines the purposes of each of Alaska’s NWRs. 

Generally stated, the act established each refuge to: conserve 

populations of wildlife including, but not limited to, a refugespecific list of species or species groups; fulfill international 

treaty obligations with respect to fish and wildlife; provide 

for subsistence uses (except Kenai NWR); and ensure 

necessary water quality and quantity within each refuge. The 

statutory mandate to provide opportunities for subsistence 

harvest is unique in the NWRS to Alaska, and the statutory 

listing of water quality and quantity is the legal basis for 

reserved federal water rights within Alaska refuges. Several 

refuges have additional purposes related to reindeer grazing, 

education, research, and boat access to large rivers.

ANILCA also requires that refuges publish and obtain 

public feedback on Comprehensive Conservation Plans 

(CCPs) at intervals not longer than 15 years. These plans 

describe how each refuge will fulfill its legal mandates 

within this time frame. The comprehensive plan is supported 

by step-down plans, which provide details for how specific 

management goals will be achieved, as needed, for each 

refuge. Example topics for step-down plans include fisheries 

management, wildlife inventory and monitoring, land 

protection, and fire management. Collectively, these CCPs 

define the approach each refuge will take to the full range of 

management decisions it will likely face.

Management of the entire NWRS (referred to as ‘the 

System’ in the relevant legislation), is guided by the National 

Wildlife Refuge System Administration Act of 1966 as 

amended by the NWRSIA. This law states:

The mission of the System is to administer a national 

network of lands and waters for the conservation, 

management, and where appropriate, restoration 

of the fish, wildlife, and plant resources and their 

habitats within the United States for the benefit of 

present and future generations.

Although putting ‘wildlife first’, other language in 

this law also states that wildlife-dependent recreational 

uses are the priority general-public uses of the System and 

shall receive priority consideration in refuge planning and 

management as long as they are compatible with conserving 

wildlife. It also requires managers to ensure that the biological 

integrity, diversity and environmental health of the System are 

maintained.

Finally, refuges are subject to other federal laws and 

treaties that address wildlife, and environmental and cultural 

protection. Examples of national and Alaska-specific laws 

include the Endangered Species Act (ESA, 1973), the Marine 

Mammal Protection Act of 1972 (MMPA), Migratory Bird 

Treaty Act of 1918 (MBTA), the Clean Water Act of 1977 

(CWA), the Wilderness Act of 1964, the Coastal Zone 

Management Act of 1972, the Antiquities Act of 1976, and the 

Alaska Native Claims Settlement Act (ANCSA), as amended. 

The need for management to be based on inventory and 

monitoring is identified throughout legislative directives. 

The NWSRIA states that “in administering the System, the 

Secretary shall monitor the status and trends of fish, wildlife, 

and plants in each refuge.” ANILCA calls for a report to 

Congress every three years, which should include results 

of monitoring of subsistence use and the status of fish and 

wildlife populations subject to subsistence use. The policy 

on biological integrity (USFWS Manual Part 601 Chapter 3) 

states that refuge managers should assess current status of 

refuge resources through baseline vegetation and population 

surveys and should assess the effectiveness of management 

by comparing the results to desired outcomes. Using desired 

outcomes to assess management effectiveness is essentially 

the monitoring step in adaptive management (Holling, 

1973, 1978; Williams, 1997; Nichols and Williams, 2006; 

Williams and others, 2007). The refuge planning policy 

(USFWS Manual Part 602) states that CCPs should be 

based on scientific literature and should identify conditions 

and trends of resources including habitats and wildlife. The 

monitoring policy for NWRS is detailed in USFWS Manual 

Part 701 Chapter 2, and a new draft calls for refuges to 

develop inventory and monitoring step-down plans to provide 

biologically and statistically robust data on trends of selected 

species and species groups in an ecosystem context.

Evolution of Perspectives on Management of the 

NWRS

Historically, refuges were established and managed for 

conservation of specific species or taxonomic groups and 

administered relatively independently (National Wildlife 

Refuge System Administration Act, 1966). The concepts of 

“trust species” and “trust resources” are terms commonly 

used by the USFWS to indicate species and resources 

statutorily subject to Federal management by the Service (for 

example, via the ESA, MBTA, refuge enabling legislation). 

They generally encompass migratory birds, threatened and 

endangered species, anadromous fish, some marine mammals, 

and refuge lands and waters. In the U.S., fish and wildlife 

populations generally are a state responsibility; thus the 

USFWS (and the National Oceanographic and Atmospheric 

Administration – National Marine Fisheries Service) are 

unique among federal land-management agencies in having 

special statutory responsibilities for many species. 

This focus on individual species or species groups has 

steadily broadened to encompass other resources over time. 

For the first time in 1997, the NWRSIA gave the refuge 

system an organic act and a system-wide mission. This 

legislation set overall management direction of the NWRS, 

which emphasized wildlife, habitats, biological integrity 

and diversity, and environmental health. For Alaska refuges 

in particular, ANILCA called for management of natural 
8 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

landscapes and entire ecosystems, including cultural and 

many other values (see above). Moreover, the spatial scale 

of management was expanded by the policy regarding 

biological integrity (NWRSIA), which emphasized taking a 

broader spatial view when determining goals for population 

sizes. For example, landscape patterns such as flyways 

should be the basis for managing migratory birds. Finally, the 

prospect of climate change has created an impetus to manage 

all Department of Interior lands from a landscape-level 

perspective based on “Landscape Conservation Cooperatives” 

(Secretarial Order 3226, 2009; LCCs). LCCs are defined 

as science-based cooperative management programs at 

the ecoregional or regional scale (SHC EOC 2009; see 

http://www.fws.gov/science/SHC/lcc.html). This mandate 

recognizes that climate change will have impacts on broadscale processes such as wildlife migration patterns, hydrology, 

phenology, spread of invasive species, risk of wildfire, and 

pattern of permafrost thaw that extend beyond the boundaries 

of individual management units. This is especially true at 

high-northern latitudes, where contemporary changes in 

climatic parameters have been more pronounced, and where 

climate change is predicted to have the most dramatic and 

imminent effects (IPCC, 2007). Therefore, management 

responses must be coordinated at an unprecedented spatial 

scale. 

The recognition that refuge management must add an 

ecoregional dimension and take a comprehensive view of 

refuge resources also requires that refuge monitoring include 

an ecoregional and comprehensive perspective. Development 

of an appropriate monitoring framework to meet these needs 

should be informed by an evaluation of current monitoring 

efforts and lessons learned from other broad-scale monitoring 

programs.

2010 – A New National Monitoring Program for 

the NWRS

The impetus to develop long-term ecological monitoring 

for Alaska NWRs resulted from the increasing awareness that 

climate change is strongly influencing high-northern-latitude 

ecosystems. Alaska refuges began collaborating with USGS in 

2005 to explore the potential consequences of climate change 

(for example, Climate Change Forum for Alaska, February 

2007) and design an ecoregionally scaled monitoring program 

(that is, Forum on Ecoregional Monitoring for NWRS and 

other Public Lands across Alaska, April 2009). Immediately 

after the Ecoregional Forum, the USFWS Alaska Region 

Chief of Refuges proposed to the national NWRS leadership 

team that a small group of biologists be detailed to develop 

a national I&M strategy for refuges. The Core Team for 

NWRS I&M was chartered in June 2009 with an Executive 

Oversight Committee. Both teams met in August 2009, and 

the Core Team subsequently devoted most of the autumn 

2009 to development of an I&M Framework for the NWRS. 

Eventually, a Technical Review Committee will be asked for 

critical input.

In September 2009, the USFWS published Rising to the 

Challenge – Strategic Plan for Responding to Accelerating 

Climate Change (USFWS, 2009). This document included an 

objective of developing ‘monitoring and research partnerships’ 

through an I&M strategy for refuges. Shortly thereafter, the 

next budget for the DOI included 20 million dollars over 

2 years to fund USFWS to develop the aforementioned 

ecoregionally based and cross-programmatic science support 

units called Land Conservation Cooperatives. The DOI 

FY2010 budget also included 12 million dollars for the NWRS 

to develop a national I&M program on refuges. The refuge 

I&M program is being designed to support the agency’s 

broader strategies to mitigate the effect of climate change on 

fish, wildlife, and plant populations. Furthermore, these efforts 

are encouraged to use an ecoregional perspective, as directed 

by the Secretary of the Interior (Ken Salazar) in an Executive 

Order adopting Landscape Conservation Cooperatives and 

expanding the concept to a Department-wide initiative 

(Secretarial Order 3226, 2009). 

As of December 2009, the Refuge Core Team for I & M 

had developed an internal draft document entitled Operational 

Blueprint for Inventories and Monitoring on National Wildlife 

Refuges for FY 2010 and 2011 and a draft Strategic Plan for 

Inventory and Monitoring on NWRS targeting subsequent 

years. These plans are scheduled for release to the public 

in 2010. In the meantime, Region 7 (Alaska) Refuges have 

been authorized to hire two database managers and a regional 

refuge coordinator for I&M as part of the national USFWS 

monitoring program organized around LCCs.

Climate change is viewed by many as a major concern 

regarding natural resources in Alaska. This contrasts with the 

expectation that land-use change from human activities such 

as agriculture, forestry, and other forms of development will 

have a larger effect on species’ survival at lower latitudes, 

especially in the short-term. However, several short-term 

change agents also have been identified for polar and boreal 

regions. These include pollution in the form of airborne 

nitrogen and phosphorus from agriculture elsewhere, and 

over-exploitation of polar areas (Millennium Ecosystem 

Assessment, 2005). Although concerns about climate change 

may have precipitated the development of a broad-scale 

monitoring program for Alaska NWRs, these other potential 

changes should not be overlooked (Murphy and Weiss, 1992; 

Hulme, 2005; Root and Schneider, 2006; Thomas and others, 

2006).
Chapter 2 9

Chapter 2. Programmatic and 

Monitoring Objectives for Alaska 

NWRs

Multiple sets of objectives are required to underpin the 

development of a monitoring program (fig. 1). We describe 

types of objectives; their roles and importance; and potential 

programmatic and monitoring objectives to underpin 

monitoring of refuges in Alaska.

Role of Objectives in Developing Monitoring

At the highest level, programmatic objectives state 

what the program strives to achieve. They derive from the 

agency information needs and the agency context (Chapter 1), 

which in turn reflect the resources for which the agency 

is responsible, the nature of the responsibility, available 

management tools as defined by statute, and relationships 

with the public. Agency context also includes the agency 

administrative structure and the feasibility of application of 

available management tools. In addition to being driven by 

agency context, agency information needs in Alaska are driven 

by need to understand the effects of climate change. 

The purpose of programmatic objectives is to guide 

decisions regarding program strategy and structure (fig. 1), 

rather than identify what specifically should be monitored. 

Programmatic strategy refers to such decisions as the types of 

questions, spatial scale, and quality of information that will be 

collected. It reflects determinations of the audience for, and 

purpose of, the information. Programmatic structure refers to 

the staffing plan, organization chart, and funding allocation, 

which determine where responsibilities, capabilities, and 

authority for decisions reside in the organization and on 

the ground. Examples of decisions regarding programmatic 

structure made by a number of broad-scale monitoring 

programs are presented in Chapter 3.

Monitoring objectives derive from the programmatic 

objectives and specifically reflect the information needs 

of the agency (fig. 1). These objectives describe what 

should be monitored in very general terms. Refinement of 

these objectives results in measurable objectives (that is, 

monitoring questions), which are further refined to identify 

specific indicators and attributes, the survey design describing 

where and how often to monitor, and how data will be 

collected, managed, analyzed, and reported. Developing 

measurable objectives will be discussed in detail in Chapter 4.

Programmatic Objectives for Alaska NWRs

The Alaska NWR monitoring program will be embedded 

within the national I&M program, which is being developed 

concurrently. The draft programmatic objectives for the 

national program include (from draft Strategic Plan for 

Inventory and Monitoring on NWRS):

Figure 1. Conceptual framework describing relationships among three types of monitoring 

objectives and various aspects of monitoring-program structure.

1. Meet the Refuge System’s 

legal mandate to monitor 

the status and trends of 

fish, wildlife, and plant 

populations on refuges; 

collect and manage 

information needed 

to maintain biological 

integrity, biological 

diversity, and environmental 

health; and preserve the 

character of designated 

Wilderness within the 

System.

2. Advance fish and wildlife 

conservation at refuge and 

broader landscape scales in 

an adaptive-management 

cycle by providing scientific 

information that supports 

conservation planning and 

design, guides learning 

through evaluation of 

conservation delivery, and 

provides hypotheses to drive 

research.

MONITORING PROGRAM

Agency Context

Agency Information Needs

Programmatic Strategy

• Types of Questions (e.g., 

adaptive management, 

protection accountability, 

single resource)

• Spatial Scale of Results

• Information Quality (e.g., 

statistical power)

• Etc.

Programmatic Objectives

Programmatic Structure

• Where responsibilities reside

• Where capabilities reside

• Where authority for decisions

resides

Monitoring Objectives

Monitoring Design

• Indicators & attributes

• Survey Design

• Data collection, 

management, reporting

Measurable Objectives

(monitoring questions)
10 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

3. Implement monitoring of fish, wildlife, and plants, 

physical resources, and ecological processes to reduce 

uncertainty related to impacts of climate change and other 

stressors, provide early warning of changing conditions, 

and guide development of management actions that 

facilitate adaptation to climate change.

4. Synthesize, interpret, and report on the condition of fish, 

wildlife, plants, and habitats conserved by the Refuge 

System in a manner that documents the contributions of 

the System within the context of the larger conservation 

estate and clearly communicates its value to the American 

public.

5. Enhance effectiveness and reduce costs by coordinating 

and integrating monitoring of natural resources at 

landscape scales through collaboration with other Service 

programs, agencies, and organizations.

Several considerations affect how these national 

objectives might be applied in Alaska. First, the geographic 

context for Alaska refuges includes the vast areal extent of 

individual refuges, few roads, and a matrix of large blocks 

of protected lands managed by multiple agencies with 

interspersed private lands. This context will constrain what 

constitute feasible monitoring methods, afford extensive 

opportunities for collaboration with other agencies, and 

define relationships between USFWS and the rest of the 

conservation community. Second, the vast land base, together 

with relatively few financial resources and personnel, and 

the mandate to protect ecosystem processes, means that 

management options are limited largely to protection, with 

very little practice of manipulative habitat management. 

This makes application of the adaptive-management cycle 

for identifying monitoring topics less straightforward than in 

cases of active management. Third, many Alaska refuges have 

subsistence-dependent resident human populations whose 

singular focus on particular resources may be in conflict with 

the need to protect entire ecosystems. Finally, the extreme 

weather conditions hamper monitoring efforts, even as the 

relatively rapid rate of climate change at northern latitudes 

intensifies the need for monitoring.

These objectives express the programmatic goals of 

monitoring, which reflect management information needs 

(for example, meet legal mandate to monitor, achieve adaptive management, collaborate with other agencies, etc.) and 

will determine how the national monitoring program will be 

structured. Instead of identifying specific ecosystem components that should be monitored, they indicate broad categories 

of resources, including fish, wildlife, plants, habitats, and 

ecological processes. Decisions regarding which elements 

within these broad categories should be monitored will be 

found in the monitoring objectives and will reflect the national 

programmatic goals and also refuge and regional resources, 

responsibilities, and information needs. Monitoring data will 

be combined with other considerations (for example, societal 

impacts) to lead to management decisions.

Monitoring Objectives for Alaska NWRs

The statutes and purposes of the Alaska NWRs have 

several logical consequences with respect to monitoring 

objectives. First, there are information needs that require 

monitoring at multiple spatial scales: statewide, ecoregional, 

and unit-specific. Second, better understanding of water 

quality and quantity is important not only because of ANILCA 

statutes, but also because USFWS’ neighbors also are invested 

in monitoring indicators of water quality and quantity, thereby 

creating opportunities for collaboration. Third, resources 

subject to subsistence use are of critical management concern 

and responsibility. Finally, better understanding of ecological 

health and ecosystem integrity, including biodiversity, is 

needed to inform management decisions. 

The Service must decide which aspects of these topics 

are most important for them to understand in order to meet 

management goals. Potential refined objectives that could 

guide development of a monitoring framework include:

• Determine trends in population size of species subject 

to subsistence use.

• Determine whether intact ecosystems and natural 

processes are being conserved within and across 

refuges, especially in response to climate change.

• Determine trends in populations of focal species, 

which are determined by the agency and are a subset of 

‘trust’ species plus other priority species (for example, 

species especially sensitive to climate change).

• Determine trends in water quality and quantity relative 

to legal standards and levels necessary for ecosystem 

function.

These objectives are derived from ANILCA legal 

mandates and express the most general information needs. 

There may be refuge-specific, ecoregional, statewide, and in 

some cases, international aspects to all of these objectives 

(table 1). Consideration of multiple spatial scales and the 

information needs at each will lead to further refinement of the 

monitoring objectives (table 1, last row) and eventually the 

development of measurable objectives and specific monitoring 

protocols.

The monitoring objectives listed above also reflect 

a range of temporal scales underlying the management 

concern. Some objectives express immediate management 

information needs (for example, populations of species subject 

to subsistence use) while others relate to future information 

needs (for example, conservation of ecosystems and processes 

in the face of climate change, Martin and others, 2009). 

The immediate needs may be more amenable to a tactical, 

adaptive-management approach. In contrast, the longer-term 

needs may require a strategic approach. It is important to 

prevent the immediate needs from monopolizing monitoring 

resources to the point of leaving the agency unprepared for 

addressing future changes. 
Chapter 3 11

Chapter 3. Developing Monitoring 

Program Strategy and Structure

Many broad-scale monitoring programs have been 

developed around the world. Based largely on examples 

presented at the Forum on Ecoregional Monitoring for the 

NWRS and other Public Lands across Alaska, held in April 

2009, we summarize lessons learned regarding the structure 

and development of monitoring programs in general. Then we 

discuss how some lessons can be applied to Alaska NWRs in 

particular. Finally, while program structure is a policy issue to 

be determined by USFWS, we outline decisions that must be 

made to determine the structure.

Lessons Learned from Other Large-Scale 

Monitoring Programs

The fundamental challenge for monitoring programs 

is to maintain consistency in both funding commitment and 

methods across many repetitions of data collection (Cauglan 

and Oakley, 2001). Threats to consistency include changes 

in personnel, in topics of interest, and in user groups; and 

competition with short-term urgent needs for resources. 

Support within the organization can be maintained only if 

monitoring results are useful and relevant, which means that 

they must address specific management information needs 

in a timely fashion and at the proper spatial scale. Several 

potential purposes of monitoring include assessing the 

outcome of management actions, verifying compliance with 

legal obligations, providing early warning before unacceptable 

effects occur, and providing information to influence policy 

made by other agencies (Noss, 1990; Dale and Beyeler, 2001; 

Niemi and McDonald, 2004). Specific trade-offs made in 

the design of a monitoring program that affect the cost and 

usefulness of the program include:

• Scope of indicators – the breadth and depth of 

ecosystem components included. For example, a 

monitoring program may address ecosystem health 

broadly or focus narrowly on water quality. In terms of 

depth, the same amount of monitoring resources can 

be distributed to learn a little about a lot of things or to 

learn a lot about a few things.

• Statistical confidence – acquiring high statistical 

confidence in the veracity of an observed trend 

often requires more time and sampling effort than 

that needed to obtain an early warning of the trend. 

Obtaining a high level of confidence may delay 

the delivery of a firm conclusion, but strengthens 

the justification for action. The level of confidence 

required must be evaluated in light of the potential 

costs of action versus inaction (Field and others, 2004; 

Reynolds in press).

• Spatial resolution – a sample intended to describe a 

large area may not be collected at a high enough spatial 

density to adequately describe any subregion within 

the larger area.

• Timeframe of information need – the information needs 

of management span the range from immediate and 

tactical to long-term and strategic. Tactical information 

needs inform imminent decisions; strategic information 

needs provide understanding of ecosystem function, 

provide early warning of system changes, and enable 

the agency to anticipate the need for management 

actions.

• Autonomy of individual management units (if 

applicable) – allowing complete local autonomy 

means that data collected using methods that answer 

locally relevant questions in one unit may not be easily 

synthesized with data from other units collected to 

address different local questions, thus preventing a 

broader view of conditions; however, without local 

autonomy, local staff cannot be expected to support 

monitoring with labor and local funds or to support the 

agency’s investment in monitoring.

Examples of how extant broad-scale monitoring 

programs addressed these trade-offs were presented at 

the Forum on Ecoregional Monitoring for the NWRS and 

other Public Lands across Alaska, held in April, 2009, in 

Anchorage. The goal of the Forum was to learn from the 

experiences of other programs to inform the development of a 

statewide monitoring program by staff of the Alaska NWRs. 

Most of the programs that were presented are summarized 

in appendixes 1-7. We supplement these programs with a 

description of the USFWS Waterfowl Breeding Population and 

Habitat Survey (WBPHS). A summary of how each program 

allocated resources to the first four dimensions above is found 

in table 2.

The seven programs and the USFWS Waterfowl Breeding 

Population and Habitat Survey can be grouped into four 

categories:

1. Surveillance Monitoring, National Parks: [U.S. National 

Park Service (NPS I&M; Appendix 1), and Parks Canada 

Agency (PCA; Appendix 2)]. These two agencies share 

nationally distributed units of federal land managed 

primarily through protection, and monitoring is guided 

by broad goals such as (a) describing status and trends of 

ecologic integrity (PCA) and (b) providing broad-based 

understanding of park resources (NPS I&M). These 

programs recognize both the need to address park-level 

issues and that efficiency can be gained by developing 

and implementing standardized monitoring across groups 

of parks. In the case of PCA, the parks were grouped 

ecoregionally. NPS also grouped parks into networks 

somewhat ecoregionally, but groupings mainly reflected 

administrative rather than ecological concerns. Both 

developed a national structure for classifying indicators, 
12 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

and PCA developed a framework for summarizing 

status of attributes at the national level. This framework 

produces a qualitative summary of the status (good, 

fair, poor) and trend (increasing, stable, decreasing) of 

numerous attributes to describe the biodiversity and 

ecological function of various habitat-based strata. 

Although the assessments are qualitative, they are based 

on quantitative thresholds to define categories of status 

(sensu Parrish and others, 2003). These assessments 

enable monitoring to be closely linked to management 

by clearly indicating management success. The PCA 

approach demonstrates how to allow local autonomy in 

choosing attributes, methods, and a sample frame, while 

retaining the ability to create national assessments of 

resource status.

Challenges for these monitoring programs include 

difficulty in narrowing their open-ended objectives 

and scope to a fiscally feasible list of indicators. Both 

programs wrestle with sustaining financial support 

for the tremendous amount of work required by these 

comprehensively oriented programs. Although both 

programs realize that they have a role as a benchmark 

for comparison with altered environments, PCA also 

sees a need for strengthening the current linkage to park 

management, possibly by coupling monitoring to adaptive 

management.

2. Targeted-Resource Monitoring at National Extents

[Forest Inventory and Assessment (FIA; appendix 3), 

National Aquatic Resources Survey (NARS; appendix 4), 

and United Kingdom Countryside Survey (UKCS; 

appendix 5)]. These three programs monitor national 

samples of selected resources. The FIA and NARS 

programs target relatively narrow resource domains 

(forests and aquatic resources of the USA, respectively), 

although the UKCS has a broader resource domain (rural 

United Kingdom) but a focused set of measurements. 

All three have national-scale sample frames that are 

probabilistic and spatially balanced, enabling quantitative 

assessments of resources at regional and national scales. 

However, the sample densities are sparse enough that 

none of the programs can answer questions at scales finer 

than the multiple-county level (or country level in the case 

of the UKCS). All three have government funding, have 

a national and/or regional administrative structure, and 

address national-scale information needs. 

In a unique collaboration, data collected from the FIA 

sample grid of forest plots in Kenai NWR have been 

supplemented by an inventory of breeding landbirds, 

vascular and non-vascular plants on non-forested plots, 

arthropods, and soundscapes (Long-term Ecological 

Monitoring Program, LTEMP; Morton and others, 2009). 

The inventory is planned to be repeated so that it will 

be possible to assess changes in species distribution and 

abundance at Kenai NWR; after an inventory is repeated, 

it can begin to be considered monitoring. Integration with 

FIA ensures that LTEMP achieves some cost-efficiencies 

for data collection, and has a probabilistic sampling 

strategy. Furthermore, the increased breadth of indicators 

allows for species-habitat modeling and other spatial 

analyses (Morton and others, 2009) of those resources 

well represented by a systematic sampling grid (for 

example, common species). However, this program has 

the same limitations as do all grid samples. Specifically, 

rare communities are often inadequately sampled 

and common communities are over-sampled for most 

objectives of a comprehensive inventory. This can make 

grid samples of questionable value for creating efficient 

and effective inventories. 

Approach Program Information is needed to assess Scope of 

resources

Timeframe Spatial 

scale

Statistical 

confidence

Adaptive Management WBPHS Effectiveness of specific management 

action & specific resource status

Limited Tactical Broad High

Targeted Resource FIA Effectiveness of national policy Limited Strategic Broad High

NARS Effectiveness of national and state policy Limited Strategic Broad High

UKCS Effectiveness of national policy Limited Strategic Broad High

LTEMP Effectiveness of protection Intermediate Strategic Intermediate High

Integrative EMAN Resource status Broad Strategic Broad Low

CBMP Resource status Broad Strategic Broad Low

Surveillance NPS Effectiveness of protection Broad Strategic Narrow High

Broad Low

PCA Effectiveness of protection Broad Strategic Narrow High

Broad Low

Table 2. Summary of characteristics of broad-scale monitoring programs along several dimensions of resource allocation. 

[Abbreviations: CBMP, Circumpolar Biodiversity Monitoring Program; EMAN, Environmental Monitoring and Assessment Network;FIA, Forest Inventory 

and Assessment; LTEMP, Long-term Ecological Monitoring Program; NPS, National Park Service; PCA, Parks Canada Agency; UKCS, United Kingdom 

Countrywide Survey; WBPHS, Waterfowl Breeding Population and Habitat Survey. NPS and PCA sample some indicators at larger spatial scales than others]
Chapter 3 13

3. Integrative Monitoring Programs: [Circumpolar 

Biodiversity Monitoring Program (CBMP; appendix 6), 

and the Environmental Monitoring and Assessment 

Network of Canada (EMAN; appendix 7)]. These 

programs are dependent on data collected by others. The 

programs add value to these data by synthesizing results 

across indicators and across broad spatial extents. They 

try to standardize protocols, data analysis, and reporting 

across space and time, in general to inform high-level 

policy makers. The data summaries are qualitative and 

provide early warning, but the lack of statistical rigor 

provides relatively weak justification for action to address 

threatened resources. Nevertheless, ‘weight of the 

evidence’ arguments are recognized as valuable means 

to integrate across locally independent programs such as 

NPS and PCA.

4. Adaptive Management [USFWS Waterfowl Breeding 

Population and Habitat Survey (WBPHS)]. This program 

was not presented at the April 2009 Forum, but provides 

an excellent example of using monitoring data to support 

adaptive management. Each year, hunting regulations are 

set to achieve the objectives of maximizing cumulative 

harvest of waterfowl over the long term while maintaining 

populations above a specific number (Nichols and 

Williams, 2006). An aerial survey is used to compare the 

population size each spring with the predictions from 

several models; these predictions are based on population 

size and harvest level in the previous year. The models 

represent different hypotheses about the combinations 

of factors that determine response of bird populations to 

harvest (for example, two hypotheses regarding effects 

of hunting mortality on annual population survival, and 

two other hypotheses involving density dependence). 

Confidence in each model is expressed by the weight 

garnered by each model. In turn, each model’s weight 

reflects the fit of the model to the observed data over the 

years, as well as parsimony (namely, models with more 

variables are penalized). In this example, monitoring 

results are used to assess the status of the population, 

model the outcome of potential harvest limits, set the 

harvest limits, and evaluate the relative support for the 

competing models. Ideally, this process leads to more 

effective assignment of harvest limits, thereby achieving 

agency goals. 

***

Certain elements necessary for an effective broadscale monitoring program were identified in all programs. 

These include the need for: a structure that reflects the types 

of management decisions required, clearly defined goals 

and objectives (Noon and others, 1999; Busch and Trexler, 

2003; Niemi and McDonald, 2004), a carefully constructed 

sample design (Cochran, 1977), and as much standardization 

of protocols as feasible. All agree that data management, 

analysis, and reporting must be timely (Palmer, 2003) and that 

these require a significant part of the budget (33 percent, NPS; 

20 percent, FIA). They also identified the need to monitor at a 

hierarchy of spatial scales for program efficiency. Above all, 

these programs required an extensive initial effort to develop 

detailed objectives at several levels of specificity (for example, 

from national overarching to network-wide to indicatorspecific objectives) and at appropriate temporal and spatial 

scales. Moreover, detailed planning and significant investment 

in data-collection protocols and data management – including 

plans for data processing, archiving, analysis, and reporting – 

are essential before data collection occurs.

The need to closely link monitoring to management 

decisions (Noon and others, 1999; Noon, 2003; Niemi and 

McDonald, 2004) is another lesson learned from monitoring 

experience. Management of natural areas usually takes one 

of two forms: active manipulations (for example, habitat 

restoration), which generates tactical information needs 

regarding the effectiveness of the action; or protection (for 

example, prohibit motor vehicle use), which generates 

strategic information needs regarding system status. The 

threat of human activities to conserved lands in recent times 

has motivated the institution of “surveillance” monitoring 

programs, which attempt to detect the results of those threats. 

This type of monitoring program has been criticized as 

an inefficient use of agency resources that could be used 

elsewhere (Nichols and Williams, 2006), or as ineffective 

because it does not logically inform management decisions 

(Lyons and others, 2008). Consequently, some recommend 

that monitoring be applied in an adaptive-management 

process in which monitoring is used strictly to evaluate the 

effectiveness of management actions (Williams and others, 

2007; Lyons and others, 2008). Examples of appropriate 

scenarios usually involve an objective to change something 

(for example, maximize the population size of a given 

species) and an action to meet that objective (for example, 

create additional habitat in some specific way; see WBPHS 

description above). 

The adaptive management approach is well suited to 

address tactical information needs, but is harder to apply 

when the management action consists of protection to achieve 

resource conservation, as is generally the case in national 

parks and the Alaska NWRs. However, as already noted, 

success using an adaptive-management approach to address 

these strategic needs can be achieved using quantitative 

thresholds to define whether attributes indicate good, fair, or 

poor condition of resources. Critical to this is a clear statement 

of desired conditions – the management target. An example of 

a criterion related to extent of forest fires might be to compare 

annual area burned with the 50-yr average and conclude 

that good is within 15 percent, fair is within 15-30 percent, 

and poor is more than 30 percent above or below the longterm average. Using these thresholds, success or failure of 

management can be clearly and objectively evaluated (Timko 

and Innes, 2009). These thresholds are often difficult to define, 

but they are an important step in developing a monitoring 

program for protected areas. 
14 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Monitoring Principles for Potential Application 

to Alaska NWRs

The NWRS in Alaska has features in common with the 

agencies whose monitoring programs were presented at the 

(2009) Forum on Ecoregional Monitoring for the NWRS 

and other Public Lands across Alaska. As with the U.S. and 

Canadian systems of national parks, the NWRS in Alaska 

is composed of individual protected areas with a sweeping 

mandate to conserve landscapes and biodiversity. Furthermore, 

management is based primarily on protection rather than on 

specific active-management actions. In common with NARS, 

FIA, and UKCS, the NWRS in Alaska also is responsible for 

the abundance and quality of specific resources (that is, water 

and specific wildlife species) that have spatial extents that are 

larger than individual management units. Like the integrative monitoring programs, the NWRS in Alaska has interests 

in (but not responsibility for) synthesizing monitoring data 

collected by others, either by neighboring agencies or in other 

parts of the ranges of migratory species, which may be continents away. Lessons learned from other large-scale monitoring particularly relevant to the NWRS monitoring program in 

Alaska are:

• Program commitment and relevance. Maintaining a 

long-term monitoring program will require a sustained 

financial commitment by the Service. Achieving 

sustained support requires regular reporting of results 

and champions of the program at multiple political 

and administrative levels. These, in turn, are all aided 

by having clear objectives and an organizational 

commitment to efficiency and effectiveness of the 

program as a whole (Caughlan and Oakley, 2001).

• Linkage to management. Monitoring results 

that provide relevant information that is clearly 

communicated to management will usefully inform 

management decisions and provide early warning of 

upcoming management issues.

• Adaptive monitoring. Information needs will vary 

as resource condition responds to changes in system 

drivers, as the political and social climate fluctuates, 

and as monitoring and research generate knowledge 

(Ringold and others, 1996; Lindenmayer and Likens, 

2009). Additionally, the existence and feasibility of 

monitoring tools will change with new technology. 

Maintaining flexibility, especially for resources 

dedicated to tactical information needs (Ringold and 

others, 1996), will enable timely response to changing 

conditions.

• Collaboration for efficiency. Collaboration with other 

agencies, and with national and international programs, 

especially for treaty species, will extend the utility 

of the NWRS program of monitoring in Alaska by 

contributing to the description of a larger context, even 

if data can only be combined qualitatively. 

• Context for monitoring design and interpretation. 

Ecosystem conceptual models are simply diagrams 

describing relationships among the components and 

processes constituting the system. Because they 

identify important elements and articulate hypotheses 

regarding system function, conceptual and quantitative 

models (usually less available) are useful tools for 

planning monitoring, developing consensus around 

appropriate indicators, linking monitoring to adaptive 

management, and learning from monitoring results 

(Maddox and others, 1999; Fancy and others, 2009). 

Development of refuge-specific and ecoregional 

conceptual models has been initiated for Alaska 

NWRs.

• Spatial scales. A multi-scaled monitoring program 

will monitor some indicators at statewide or coarser 

resolutions, some at the ecoregional level, and some 

at the refuge level (tables 3 and 11) to put refuge 

resources into the larger contexts needed to manage 

them in an era of global-scale environmental change. 

Consequently, refuge-specific monitoring plans will 

be most effective if embedded within an ecoregional 

and statewide monitoring framework, such that results 

can contribute to, and be interpreted in, an ecoregional 

context. A multi-scale program can be best facilitated 

by a regional or statewide planning staff.

• Temporal scales. Some monitoring objectives meet 

short-term, tactical needs, whereas others meet longterm, strategic needs. Recognizing these differences 

will result in appropriate resources being applied in an 

appropriate sample design for the appropriate amount 

of time to any given objective.

• Survey and monitoring designs. Probabilistic sample 

designs are necessary for extrapolating monitoring 

results from the sample to an entire population or 

domain. It is not efficient to try to design one sample 

frame to answer all questions, given the diversity 

of topics and spatial scales reflected in potential 

monitoring objectives for refuges in Alaska (see 

tables 1 and 3). That is, various abiotic and biotic 

processes and components occur at differing spatial 

scales and asynchronously with other components, 

such that it is not possible to have a single “silverbullet” design that is optimal for monitoring 

everything, everywhere. Designs can be modified 

to reflect a spatially restricted target domain or for 

specific objectives of the monitoring question (Niemi 

and McDonald, 2004).
Chapter 3 15

Potential Monitoring Program Structure for 

Alaska NWRs

The structure of the monitoring program for Alaska 

NWRs is a policy decision to be made by the USFWS, in 

concert with development of the structure of the nationallevel monitoring program and the evolution of the LCCs. In 

terms of agency structure (that is, land management units 

with significant local autonomy), the refuge system is most 

like NPS and PCA, and can learn from the successes and 

shortcomings of their monitoring programs. We can list some 

important decisions and considerations:

• What is the question? A monitoring program whose 

structure is guided by clear objectives will allocate 

program resources, capabilities, and responsibilities 

at the appropriate organization levels and physical 

locations to efficiently meet agency information needs.

• Where do the responsibilities reside? In other words, 

who is accountable and how is accountability 

measured? Specifically, it must be determined which 

position in the organizational structure is responsible 

to produce each of the products of monitoring, 

including: data collection (and perhaps data acquisition 

from other agencies), quality assurance, analysis, 

archiving, as well as reporting. There are also required 

outputs from planning, notably protocols, and support 

functions such as GIS, database and analytical support. 

Consideration also may be given to accommodate 

the additional burden on current administrators, 

especially in the realms of hiring, contracting, and 

budget tracking. Many monitoring programs hire 

a few positions that require highly technical skills 

(for example, GIS, database management) to cover 

broad spatial and thematic domains while assigning 

implementation of the many phases of monitoring and 

reporting to many people at local levels.

• Where does the accountability reside? In other words, 

what is the governance structure? People may have 

the responsibility to complete various tasks, but 

unless they answer to someone for whom completing 

those tasks is a high priority, the tasks may be 

neglected in favor of other pressing needs. Based 

on experiences with a variety of structures used by 

different networks, NPS I&M has determined that the 

most effective governance structure includes: network 

coordinators who are directly supervised by a regional 

program manager rather than a park superintendent; 

who supervise the monitoring staff; and who are 

accountable to a Board of Directors, which includes 

superintendents of many or all parks in the network 

(John Gross, National Park Service, written commun., 

2010).

• Where do the capabilities reside? Decisions regarding 

where responsibilities reside will affect where staff 

members are physically located and who supervises 

them. 

SPATIAL SCALE

Information Need Refuge Ecoregion State/International

Natural diversity, biological 

integrity, and ecosystem 

health

Distribution and abundance of 

species and communities within 

refuges; any ecosystem process 

(for example, pollination, erosion 

control, herbivory, nutrient 

cycling)

Distribution and abundance 

of species and communities 

with ecoregional ranges (for 

example, Griffith and others, 

2002)

Integration of ecoregional data, and 

data from other parts of species’ 

ranges

Stressors Off-road vehicles Climate change, species-specific 

diseases

Climate change, air pollution, 

marine harvest

Subsistence resources Berries, wood, small furbearers Species with home ranges 

outside of refuge

Species with range outside of 

ecoregion (for example, salmon)

Water quality and quantity Aspects (for example, acidity, 

turbidity) subject to legal 

requirements

Integration of data Integration of data

Species subject to treaty 

obligations and named in 

refuge purposes

Aleutian Shield fern, species with 

limited geographic ranges

Species with ecoregional home 

ranges

Species with statewide and broader 

home ranges

Table 3. Examples of monitoring topics and analyses relating to the purposes of refuges dictated by Alaska National Interest 

Lands Conservation Act and the Refuge Improvement Act, at multiple spatial scales relevant to Alaska National Wildlife Refuges. 
16 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

• Where do the decisions reside? In other words, who 

has the authority to make various decisions? These 

will include such decisions as budget allocation, 

prioritization of monitoring objectives, hiring, 

acceptance of protocols, and many others. Within NPS 

I&M, the national program has authority to allocate 

money among its 32 networks and approve compliance 

with steps in the planning process (including structure 

and content of planning documents and protocols). 

Decisions about choice of monitoring indicators and 

allocation of funding to each indicator are made at the 

network level. In contrast, FIA and NARS make all 

decisions at the national or regional levels.

Further Considerations

• Measures of accountability at every level of the 

monitoring-program structure will ensure that no level 

becomes a bottleneck in the production of information 

from monitoring.

• Alternative ways to infuse insights from monitoring 

results into management decision processes (for 

example, Interdisciplinary Teams of USFWS, in 

addition to traditional line authority) will better ensure 

that the right information reaches the right people at 

the right time and in the right format.

• Carefully considered funding priorities at each step will 

ensure limited resources are efficiently used. At the 

moment, national monitoring funds are being evenly 

distributed among USFWS regions, so priorities are 

not needed. At the local level, however, priorities may 

need to be set regarding distribution of funds among 

LCCs or refuges within regions, and then to protocols 

at the regional, ecoregional and refuge levels.

• Existing agency culture and organization will drive 

many of these decisions about monitoring program 

structure. New agency features include the efforts to 

design a national monitoring program and the newly 

forming LCC offices. LCCs also have a mandate to 

engage in monitoring, so there is an opportunity to 

create synergy.

• Protecting funding from alternative uses will help 

preserve program integrity over the long term. NPS 

I&M has achieved this by having dedicated funds 

and high levels of accountability at all levels from the 

national office to the park, insuring that the money be 

spent only on monitoring. 

Importance of a Hierarchical Monitoring Plan

Monitoring objectives are hierarchical in both time and 

space. Specifically, there are short-, medium-, and long-term 

needs for decisions and understanding; and refuge, ecoregional, regional, and broader spatial scales of resource distribution 

and effects of system drivers. Addressing these needs can be 

best accomplished by a hierarchical monitoring plan. The 

objectives will naturally motivate spatially hierarchical sample 

frames so that locally collected data can be put in a larger 

spatial context to answer questions at broader spatial scales. 

Short- and long-term questions will require that the temporal 

dimension be considered in funding allocation. 
Chapter 4 17

Chapter 4. Identifying Monitoring 

Indicators

Once a monitoring program structure is in place, efforts 

will focus on determining monitoring objectives and refining 

them to create measureable objectives, which specify indicators. Given that management staff of Alaska NWRs has both 

strategic and tactical information needs, we discuss how to 

choose indicators of ecological integrity for strategic needs, 

and how to choose indicators of effectiveness of management 

actions to address tactical needs. We also list potential indicators that come from consideration of ANILCA, and of conceptual models of refuges and ecoregions. Finally, we address options and approaches to prioritizing the inevitably lengthy list 

of indicators including the importance of incorporating cost.

Developing Measurable Objectives

Setting monitoring objectives for a broad-scale, multifaceted monitoring program is a critically important step in 

program development, as it directly informs all subsequent 

steps in program development and implementation (Noon 

and others, 1999; Noon, 2003; Niemi and McDonald, 2004; 

Keeney and Gregory, 2005). The process of developing 

monitoring objectives is one of refining broad statements 

of information needs (such as the potential objectives for 

Alaska refuges given in Chapter 2), which results from close 

collaboration with decision- and policy-makers (Noon and 

others, 1999; Dale and Beyeler, 2001; Noon, 2003; Niemi 

and McDonald, 2004). The process is based on the purposes 

and guiding legislation associated with individual refuges 

and the USFWS system at regional and national scales, as 

detailed in Chapter 1. Specifically, it is necessary to consider 

the context of all factors that will affect management decisions 

(in addition to science), what trends and triggers will support 

management decisions, and the conceptual basis for indicators. 

The first level of refinement results from considering how 

these factors vary in space and time, and will usually identify 

specific indicators. Further refinement must proceed until 

objectives are specific and detailed enough to provide clear 

guidance regarding: selection of the temporal and spatial 

monitoring domains, relative importance of understanding 

trend vs. status (and thus nature of the sampling re-visit 

strategy), attributes of interest, level of sampling needed to 

detect changes with a selected level of confidence, subset of 

relevant options for methods that may be appropriate, and the 

suite of analytical approaches needed to address the questions. 

These highly refined objectives are ‘measurable objectives’. 

A hypothetical example regarding tactical monitoring to 

assess effectiveness of management actions to influence the 

population size of a caribou herd follows:

Alaska NWR Monitoring Objective: Determine 

whether population levels of species subject to subsistence use 

are above the minimum required to allow subsistence use.

Refined Monitoring Objective: Determine whether 

removing predators for a 4-year period will increase the 

size of the caribou population to a level that supports some 

subsistence harvest.

Further Refined Monitoring Objective: Determine 

whether removing predators from caribou calving grounds for 

a four-year period will increase the number of caribou adults 

to a level that supports some subsistence harvest.

Measureable Objective: Determine whether the 

population of the (name) caribou herd exceeds (number 

determined to be adequate to support subsistence harvest) 

adults in (season) at (place) following 4 years of predator 

removal within (specified) confidence limits.

Developing a measurable objective from a monitoring 

objective is a highly iterative process. Budget constraints 

may dictate that the ultimately desired information is not 

feasibly obtained, so that the objective may need to be revised 

to reflect the minimum information required to meet the 

information needs of managers. Measurable objectives should 

be developed in collaboration between managers, refuge 

biologists and scientists, to aid in translating management 

questions to strategies for effective data collection (Stokols 

and others, 2008).

Strategic Versus Tactical Monitoring Needs

As previously noted, managers of Alaska NWRs undertake both passive (protective) and active (manipulative) management actions. An approach in this situation is to develop a 

two-part monitoring program (Timko and Innes, 2009), to both 

(1) address the strategic information need for status and trends 

of ecological integrity, and (2) to address the tactical information need to assist managers in assessing the effectiveness of 

management actions.

Choosing Indicators of Ecological Integrity for 

Strategic Needs

Monitoring ecological integrity is a daunting goal. 

Ecological integrity has been described as having three 

components: indicators of biodiversity, ecosystem processes, 

and stressors (Woodley, 1993; Parks Canada Agency, 2005). 

Monitoring of biological diversity must pay attention to all 

levels of ecological organization, according to Noss (1990). 

Notwithstanding this guidance, few protected areas have 

established systems to assess whether they are protecting 

biodiversity (Yoccoz and others, 2001; Parrish and others, 

2003; Hockings and others, 2004). To provide more-specific 

direction, a global framework has been promoted by the IUCN 

World Commission on Protected Areas to help managers of 

protected areas develop effective monitoring of conservation 

efforts (Hockings, 2003; Hockings and others, 2003). The 

framework recommends that the biological diversity of a 
18 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

region can be represented by a limited number of ecological 

communities or ecosystems (Noss and Cooperrider, 1994; 

Poiani and others, 2000), plus a selection of species with 

unique ecological requirements not captured by those 

communities or ecosystems. Key ecological attributes used 

by The Nature Conservancy (TNC) to measure success 

in protected areas include biological composition, biotic 

interactions and processes, environmental regimes and 

constraints, and landscape structure and architecture (Parrish 

and others, 2003). According to the TNC guidance, attributes 

for assessing these indicators can be determined using 

conceptual models to describe the ecology of the indicator, 

thereby identifying characteristics that determine the longterm persistence of the indicator (Parrish and others, 2003). 

Linkage of monitoring to management and the effectiveness 

of conservation depends on establishing the limits of an 

acceptable range for each attribute (Parrish and others, 2003). 

These are determined by considering the range within which 

each attribute represents ensured persistence of the indicator. A 

weakness of this approach is the need for a fairly sophisticated 

understanding of system function.

 Monitoring of ecological integrity can also be focused 

around changes that are anticipated with contemporary climate 

change (see table 4) and might be addressed by changes in 

Polar Bering Coast Interior Alaska North Pacific Coast

• Altered management of 

harvested species by other 

agencies

• Altered distribution of 

invasive species (relating 

to species’ detection and 

control)

• Altered water quality and 

quantity

• Effects on biological 

diversity (and legal and 

statutory ramifications

• Change in plant and animal 

community composition and 

structure

• Drying of wetlands

• Changes in amount and 

timing of precipitation

• Alterations to terrestrial 

hydrology

• Changes in the types, levels 

and spatial distribution of 

anthropogenic activities

• Altered fire regimes 

• Changes in diversity and 

distribution of invasive 

species

• Altered subsistence 

management (population 

sizes, reproduction, and 

demography; harvest 

regulations; phenology)

• Effects on rare and declining 

species and habitats (that 

is, needs to identify losses, 

determine conservation 

actions)

• Alterations to water quality 

and quantity (including 

management of upstream 

activities)

• Effects on species covered 

by treaties (for which 

broad-scale coordination is 

essential)

• Altered phenology (a 

phenomenon better 

understood in terrestrial 

ecosystems)

• Altered water quality, 

especially melting of glaciers, 

surface water flow, water 

chemistry, and timing and 

quantity of fresh water 

entering marine systems (and 

consequent local effects on 

salinity)

• Altered animal-community 

dynamics (terrestrial and 

marine), due to species’ 

differential responses to 

climate change

• Changes in ocean dynamics 

(upwellings, acidification, 

altered currents, impacts on 

marine food webs, nutrient 

flows, effects on seabirds)

• Change in plant community 

composition and structure

• Alterations to migratory and 

invasive species

Table 4. Consequences of climate change that are of greatest concern to land managers within each of four ecoregions within 

Alaska, as identified at the (April 2009) Forum on Ecoregional Monitoring.
Chapter 4 19

management philosophy, policy, or actions, once they are 

detected. Examples of climate-related information needs to 

which monitoring may contribute include:

• Understanding the effects of extreme-weather events, 

and consequences of extreme levels of a particular 

ecosystem component or process. 

• Understanding species’ current habitat associations and 

conservation status, to forecast future distributions and 

set conservation priorities, based on current and future 

vulnerability to climate change and other stressors. 

This also has implications for habitat-management 

decisions, and the potential acquisition of conservation 

easements.

• Re-defining natural diversity – for example, if 

moose were present 60 years ago but have increased 

dramatically in density, what is the appropriate density 

of moose to sustain as a target? It is necessary to 

acknowledge that most management targets can now 

no longer be considered static through time (Morgan 

and others, 1994; Kessler, 2010).

• Determining when the forecasted conservation status 

is so poor that cost to conserve a species may be 

infeasible. This has ramifications for complying with 

the Endangered Species Act and other legislation.

• Informing education and outreach efforts, both 

internally and externally – under increased levels of 

uncertainty associated with climate change. These 

efforts should honestly and explicitly acknowledge that 

uncertainty.

• Determining the limits of natural diversity, and the 

range of environmental health and integrity conditions 

that are permissible without resulting in unacceptable 

levels of species or habitat degradation. This informs 

the decision regarding when managers may want to 

intervene. 

Because it is challenging to select indicators of biological 

integrity, it is important to consider published guidance. 

Based partly on compiling the suggestions of others, Noss 

(1990:357-358) has suggested that: 

“Ideally, an indicator should be [Cook, 1976; Sheehan, 

1984; Munn, 1988]:

(1) sufficiently sensitive to provide an early warning of 

changes;

(2) distributed over a broad geographical area, or otherwise widely applicable;

(3) capable of providing a continuous assessment over a 

wide range of stress;

(4) relatively independent of sample size;

(5) easy and cost-effective to measure, collect, assay, 

and/or calculate;

(6) able to differentiate between natural cycles or trends 

and those induced by anthropogenic stress; and

(7) relevant to ecologically significant phenomena.”

Dale and Beyeler (2001) further suggested that indicators 

should: respond to stress in a predictable manner; predict 

changes that can be averted by management actions; be 

integrative; and have a known response to disturbances, 

anthropogenic stresses, and changes over time. Few, if any, 

indicators meet all of these criteria, but all indicators should 

be linked to ecosystem function through conceptual models 

(Busch and Trexler, 2003). 

Choosing Indicators of Effectiveness of 

Management Actions to Address Tactical Needs

Some have advocated monitoring the effectiveness of 

management actions in the context of structured decision 

making, of which adaptive management is a subset (Nichols 

and Williams, 2006; Lyons and others, 2008). There are three 

roles for monitoring in this iterative process, including: (1) 

providing data for state-dependent decisions (for example, 

given the state of the harvested population, how much harvest 

will be allowed?), (2) evaluating management performance 

(for example, did harvest restrictions result in expected 

productivity?), and (3) facilitating improved management 

through learning (for example, which of the hypotheses 

regarding species response was most accurate?). Choosing 

indicators for adaptive management or other forms of 

structured decisions is driven by the specific management 

decision needed and the requirements of the models, which 

represent different hypotheses, used to predict the outcomes of 

the decision.

Although active management is not commonly 

undertaken currently in most refuges in Alaska, the 

following are some potential management actions that may 

be appropriately evaluated in an adaptive-management 

framework:

• Creating and maintaining habitat – fire suppression, 

prescribed fire, planting trees along streamsides, 

habitat enhancement, habitat protection or 

conservation.

• Managing people – regulatory actions will affect 

most of the change (for example, road closures, 

permitting of other anthropogenic activities such as 

overflights); the exact manner in which these actions 

are implemented may evolve, given that resource 

distributions will shift in the future.

• Setting of harvest dates, bag limits, and acceptable age 

and gender of harvest, by type of harvest equipment 

(bow vs. rifle vs. muzzle-loader), for both subsistence 

and sport (or non-federally qualified) harvesters.

• Allocation of water rights, or permitting of upstream 

anthropogenic activities that may affect water quality 

or quantity.

• Predator control, and resulting ecological cascades.
20 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Implementing a monitoring program can itself be seen 

as taking a management action. Knowledge gained from the 

monitoring program should be used to iteratively refine the 

monitoring design, in what has been termed ‘adaptive monitoring’ (Ringold and others, 1996; Lindenmayer and Likens, 

2009). This could be accomplished by implementing the 

plan in pilot areas, or by using monitoring results to refine 

ecosystem models, thereby focusing attention on the mostinformative indicators. An outcome to be avoided, however, is 

the loss of long-term continuity of comparable data (Ringold 

and others, 1996).

Potential Monitoring Indicators Suggested by 

ANILCA

In addition to protecting water quality and quantity, 

providing for subsistence resources, and ensuring that treaty 

obligations are met, ANILCA identifies species and resources 

that constitute refuge purposes (table 5). These are not the only 

resources that concern refuge managers, but the list can be 

used to identify some common interests (see fig. 3 for location 

of ecoregions mentioned):

Migratory birds – statewide, but especially 

waterfowl in Interior Alaska and shorebirds for 

refuges with Arctic, Bering Sea, and North Pacific 

coastlines 

Caribou – statewide

Moose – especially in Interior Alaska

Furbearers – especially in Interior Alaska

Bears – especially polar bears in the Polar 

ecoregion, and brown bears on the North Pacific 

Coast

Salmon – especially in coastal refuges and Interior 

Alaska.

Potential program-level monitoring objectives for 

these resources are given in Chapter 2. While these species 

have complex dynamics and require long-term monitoring 

to be accurately understood, management tends to require 

immediate, tactical information regarding the species.

Table 5. Species, taxonomic groups and resource categories listed in refuge purposes identified in ANILCA. 

[Terminology was not used consistently among refuges, so that a higher taxonomic group might be listed for one refuge and a species within that 

taxonomic group might be listed for another. Resources are grouped by category and refuges are grouped by ecoregion. Arctic and Selawik NWRs 

each appear in two columns because a large proportion of each refuge occurs in two ecoregions]

Polar Interior Alaska Bering Coast North Pacific Coast Arctic Arctic Innoko Kanuti Kenai Koyukuk Nowitna Selawik Tetlin Yukon Flats Selawik Togiak Yukon Delta Alaska Maritime Alaska Peninsula Becharof Izembek Kodiak

Birds

Black brant X

Canada goose X

Canvas back X X

Emperor goose X

Non-migratory birds X

Marine birds X X X

Migratory birds X X X X X X X X X X X X X X X X X X

Peregrine falcon X X X

Raptors X X

Sea Birds X

Shorebirds X X X X X

Snow goose X X

Trumpeter swan X

Waterfowl X X X X X X X X X

Whistling swan X

White-fronted goose X X X
Chapter 4 21

Polar Interior Alaska Bering Coast North Pacific Coast Arctic Arctic Innoko Kanuti Kenai Koyukuk Nowitna Selawik Tetlin Yukon Flats Selawik Togiak Yukon Delta Alaska Maritime Alaska Peninsula Becharof Izembek Kodiak

Terrestrial Mammals

Bears X X X

Brown bear X X X X

Black bear X

Caribou X X X X X X X X X X X X

Dall sheep X X X X

Furbearers X X X X X X X

Grizzly bear X X

Large Mammals X

Marten X

Moose X X X X X X X X

Mountain goat X

Muskox X X X

Other Mammals X X

Polar bear X

Wolverine X X X X

Wolf X X X X

Marine

Marine Mammals X X X X X X

Marine Resources X

Sea lion X

Sea otter X

Fish

Arctic char X X

Dolly varden X

Fish X X

Grayling X X

Northern pike X

Salmon X X X X X X X X X X X X X

Sheefish X X X

Table 5. Species, taxonomic groups and resource categories listed in refuge purposes identified in ANILCA.—Continued

[Terminology was not used consistently among refuges, so that a higher taxonomic group might be listed for one refuge and a species within that 

taxonomic group might be listed for another. Resources are grouped by category and refuges are grouped by ecoregion. Arctic and Selawik NWRs 

each appear in two columns because a large proportion of each refuge occurs in two ecoregions]
22 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Potential Monitoring Indicators Suggested by 

Conceptual Models

A preliminary list of potential indicators of ecosystem 

integrity comes from the ecoregional workgroups at the Forum 

on Ecoregional Monitoring for the NWRS and other Public 

Lands across Alaska (tables 4 and 6). These indicators are 

based on ecoregional conceptual models that describe the (1) 

processes and distribution patterns that emerge more clearly 

at broader spatial extents, and (2) potential effects of climate 

change on natural resources of Alaska NWRs. Concerns varied 

by ecoregion, but generally fell into the following categories:

Water quality and quantity – including hydrology; 

and wetland distribution and abundance

Biological diversity and community structure – 

including distribution and abundance of invasive 

species, rare species and habitats, and migratory 

species

Species with legal mandates – including subsistence 

and harvested species, and species associated with 

treaty obligations or other statutory mandates

Fire regime – especially in Interior Alaska

Phenology – specifically, the potential loss of 

synchrony across trophic levels

Ocean dynamics – for refuges with coastlines

Many of these potential indicators relate to the programlevel objective (Chapter 2) of determining whether intact 

ecosystems and natural processes are being protected. Specific 

information needs for them will tend to be met by strategic, 

long-term monitoring. 

Prioritization of Monitoring Objectives and 

Indicators

When addressing issues as broad as the management 

purview of the NWRS in Alaska, it is inevitable that more 

objectives and indicators will be identified than can possibly 

be monitored. Basically, at every point when decisions are 

made about the distribution of resources (that is, funds and 

personnel), some sort of prioritization process must occur. 

This will involve identifying selection criteria and applying 

them. The more transparent and objective the process, the less 

contentious the decision is likely to be. 

We have described (Chapter 2) the need for developing 

a series of iteratively more highly-refined monitoring 

objectives that are derived from program-level objectives. 

Agency management must decide at which levels to prioritize 

these objectives. For example, the most general monitoring 

objectives (Chapter 2) might be prioritized based on the 

importance of strategic versus tactical information needs, the 

public visibility of various issues, etc. The purpose of this 

prioritization might be to determine the relative allocation of 

funds among them. Within each of these broad objectives, it 

will likely be necessary to prioritize sub-objectives. In most 

monitoring programs prioritizing sub-objectives is done using 

indicators rather than formally stated objectives. For example, 

what are the priority subsistence or focal species? What are the 

priority indicators of ecosystem health? Prioritizing indicators 

has been an effective approach, but program staff of the 

Alaska NWRs might consider developing different selection 

criteria for each program-level objective. For example, the 

criteria for determining where and how to monitor water 

quality are likely different than are the criteria for identifying 

priority focal species. Developing different criteria for each 

objective and applying them to appropriate potential indicators 

would alleviate the tendency of most prioritization processes 

to compare unrelated indicators using vague criteria. However, 

no prioritization process is perfect, because they all suffer 

from the following pitfalls: 

• Items to be prioritized must have equivalent scope 

(for example, ‘forest processes’ will rank higher than 

‘decomposition’ as an indicator because it is more 

inclusive; however, it is too general to be useful for 

selecting particular attributes to measure).

• Respondents tend to rank highly those topics about 

which they are familiar and knowledgeable.

• No list of criteria can take into consideration all 

concerns and issues.

• The uncertainty about how climate will change 

and how ecosystems will respond complicates 

prioritization.

• There is no good way to include cost as a factor early 

in the prioritization process, because any monitoring 

objective can be addressed with a variety of budgets, 

depending on the choice of attributes, and intensity 

and domain of sampling. Laying out all of the options 

for all of the potential indicators is usually too onerous 

until the list of indicators has been reduced. However, 

budgetary limitations must be considered when 

designing a monitoring program as discussed below.

• A monitoring program should amount to more than the 

sum of its parts, but it is difficult to evaluate the entire 

program by prioritizing individual components.

Several methods can be used to prioritize monitoring 

objectives and indicators. No method is perfect and it should 

be realized from the outset that subjectivity will necessarily be 

applied to the list that emerges from a prioritization process. 

Nevertheless, a formal process is an effective tool to reduce 

the list of potential objectives and indicators to a manageable 

number. 
Chapter 4

23

Table 6. List of potential monitoring indicators suggested by ecoregional-scale conceptual models. [These models feature ecosystem components and processes that span broad spatial extents, and thus would inform organization and interpretation of monitoring at ecoregional resolutions]

Polar Bering Coast Interior Alaska North Pacific Coast

Air and Climate

Climate Climate Climate Climate

CO2 levels (release by melting permafrost, 

fires; sequestration by plant growth)

Sea ice distribution, phenologyShorefast ice distribution, phenology

Sea ice distribution, phenologyShorefast ice distribution, phenology

Sea ice distribution, phenology

Beaufort Gyre Ocean currents North Pacific current

Geology 

and SoilsMarine-derived nutrients (chemistry) Marine-derived nutrients (chemistry) Marine-derived nutrients (chemistry) Permafrost distribution and melting Isostatic rebound Volcanism

Water 

quality and 

quantity

Freshwater Aspects of Kuskokwim River water River flow and flood riskLake drying Aspects of Yukon, Kobuk Rivers River-ice breakup Marine conditions (pollutants, 

acidification, climatic influence

Marine conditions Marine conditions

Biological Integrity

Beluga whales and other migratory marine 

mammals

Migratory birds Migratory birds Migratory birds Marine food webs

Anadromous fishes Anadromous fishes

Caribou herds (Western Arctic, 

Central Arctic, Porcupine)

Caribou herds (Western Arctic, Mulchatna) Caribou herds (Western Arctic, Forty-mile, 

Porcupine, Mulchatna)

Phenology (insects, sea ice, vegetation 

green-up, migratory birds)

Phenology (ice, vegetation, migratory 

birds)

Phenology (insects, river ice, vegetation 

green-up, migratory birds, fire season)

Phenology (Whale migrations, 

vegetation green-up, migratory birds)

Anthropogenic 

stressorsHarvest of migratory animals Harvest of migratory animals Harvest of migratory animals Harvest of migratory animals (marine, terrestrial) Fire management Fire management Fire management Fire management Industrial activities Oil and gas development
24 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Delphi Process. This is a group decision-making process 

in which participants are not required to interact directly. 

Working independently eliminates some of the possibly 

negative aspects of group interactions in which some voices 

can dominate the group, the discussion can ramble, or the 

desired number of respondents can be too unwieldy for 

a discussion. Also, it can be conducted electronically, so 

that travel is unnecessary (Delbecq and others, 1975). This 

process was used effectively by Oliver (2002) to identify 

indicators of vegetation condition in low-gradient, open forest 

and woodlands of Australia. A preliminary list of indicators 

categorized by composition, structure, and function was 

provided to vegetation experts. The experts were provided 

background on program objectives and asked to add to the 

list. In some cases, a Delphi process can be iterative until a 

consensus is reached. In the Oliver (2002) example, they used 

one process to identify indicators and planned to use a second 

phase to prioritize them. Delphi processes are most often used 

to obtain input from experts, but can also be useful when 

respondents are distant, as is the case among refuge biologists 

in Alaska. Negative aspects include the large amount of 

administration needed and the fact that the process may work 

best for generating ideas rather than setting priorities (Oliver, 

2002).

Weighted Criteria. Several similar prioritization methods 

can be used to generate a list of criteria and then score all 

indicators according to how well they meet the criteria. 

Scores accumulated across all criteria are used to rank the 

indicators. The methods differ in the scale used for ranking, 

the complexity of the structure of the criteria (that is, how 

many hierarchical levels are allowed) and the complexity of 

the calculations needed to score the indicators. Examples of 

criteria might include how well an indicator can provide early 

warning of unacceptable change, or how closely it is linked to 

a management decision.

Prioritization Matrices. This method uses a two-way 

matrix to first compare the relative importance of pairs of 

criteria, where ‘importance’ must be defined. The matrix is 

used to develop weights for the criteria. Next, each indicator 

is compared to each of the other indicators relative to each 

criterion. The outcome is a ranked list of the indicators 

in which the relative importance of the criteria has been 

incorporated (Anjard, 1995; Wang and others, 1998). This 

method has the advantage that only pairwise comparisons need 

to be made simultaneously to rank a long list of items. Even 

though this process can be conducted using a spreadsheet, if 

there are many indicators and criteria, the many permutations 

of all the possible pair-wise combinations make full 

implementation of this method very tedious.

Analytical Hierarchy Process. This method allows for 

a hierarchical structure to describe priorities. In other words, 

there can be sub-criteria within criteria. The user makes pairwise comparisons among indicators, but the computation of 

rank involves calculus; hence, it requires specific software 

that uses algorithms that are opaque to the user. However, it 

provides satisfactory results and has been used for inventory 

and monitoring program planning (Schmoldt and others, 1994; 

Peterson and others, 1994).

Simple Multi-Attribute Ranking Technique (SMART). This 

is a simple and robust ranking method. Instead of comparing 

indicators to each other, all are rated on a standard scale (for 

example, 0-100) for each criterion (Ralls and Starfield, 1995; 

Goodwin and Wright, 2009). Thus, indicators are rated relative 

to their position on the scale, not by which one is higher than 

the other (when in fact they may not be very different). Scores 

for indicators can be weighted by the importance of each 

criterion to calculate a final rank.

NPS I&M Process. The NPS program advocates a hybrid 

system in which criteria are developed and weighted and a 

scoring system is defined. Subsequently, each indicator is rated 

(by both resource managers and research scientists) for each 

criterion and the final score is weighted by the importance of 

each criterion (see Suggestions for Prioritizing Vital Signs at 

http://science.nature.nps.gov/monitor/). It can be conducted in 

one round or two rounds. If using two rounds, the first round 

is used to prioritize indicators and a second round is used to 

prioritize attributes. This allows for different criteria to be 

used for each round (see appendix 8 for example criteria). It 

also may be advantageous to develop different criteria for each 

spatial extent and for indicators of ecosystem integrity versus 

adaptive management. If the NPS approach is adopted, criteria 

used by USFWS should reflect the differences in objectives 

of the monitoring programs for the two agencies. Sources 

of potential criteria include Noon (2003), Mueller and Lenz 

(2006), Patten (2006), and Niemeijer and de Groot (2008).
Chapter 4 25

The ranking process should not be the final word 

regarding the choice of indicators and attributes (Fancy and 

others, 2009). One likely outcome is that some indicators will 

receive very different ranks, depending on the expertise of the 

respondent. These discrepancies can be addressed in a group 

setting where very high or very low ranks can be defended, 

ideally with the help of conceptual models, hopefully leading 

to consensus. 

Even if there is consensus around the ranks of individual 

indicators, none of these ranking methods addresses the fact 

that no monitoring indicator possesses all of the desirable 

properties; consequently, a set of complementary indicators 

are needed to create an effective monitoring program (Noss, 

1990; Niemi and McDonald, 2004). In other words, a 

monitoring program is more than the sum of its parts and the 

value of an indicator is contingent on what else is included in 

the set. An approach to evaluating sets of indicators based on 

their inter-relationships has been proposed by Neimeijer and 

de Groot (2008). They explain the use of causal networks to 

facilitate the identification of the most relevant indicators for 

addressing a specific objective.

Ultimately, the final list of indicators will also be based 

on an evaluation of each indicator for: the value of unique 

information it provides; cost in relation to range of inference; 

partnership opportunities; availability of methods, expertise, 

and facilities; practicality; clarity of linkage to management 

issue; and negotiations with refuge biologists and managers. 

As was pointed out by Dr. T. Barrett (presentation Day 1 

http://alasks.usgs.gov/science/biology/ecomonitoring), good 

leadership is required to navigate this process. 

Incorporating Cost Considerations into Indicator 

Selection

There will always be more to monitor than the budget 

will allow, and the program will be sustained only if it is 

creating value when both budgetary and opportunity costs 

are considered. Therefore it is necessary to choose individual 

indicators and design the overall monitoring program to 

be cost-effective (Caughlan and Oakley, 2001). In terms of 

individual indicators, there are several means to achieving 

cost-effectiveness:

• Monitor only those attributes that answer a specific 

objective (U.S. Environmental Protection Agency, 

1995).

• Replace costly attributes with easily measured 

surrogates (Burbidge, 1991; MacDonald and others, 

1991; Silsbee and Peterson, 1993).

• Use a carefully designed sample frame that avoids 

wasteful over-sampling and inconclusive undersampling (see Chapter 5).

In terms of the overall monitoring program, it is 

especially important to consider cost in the design phase, and 

then check the program’s financial feasibility in the testing 

and implementation phases (Caughlan and Oakley, 2001; see 

table 15). Tools that can be used to evaluate cost-effectiveness 

include a cost-benefit (when benefits can be quantified) or a 

cost-effectiveness (when benefits are intangible) analysis to 

compare elements in the monitoring program. Both methods 

essentially express a measure of benefit (monetary or nonmonetary) per unit of cost (Saaty, 1980; Loomis and Walsh, 

1997). However, the challenge of valuing outcomes from 

monitoring when they are often intangible (for example, 

provide early-warning, clarify species status, etc.) and 

manifest over long time periods is not insignificant. An 

alternative perspective is to consider the relative costs among 

indicators of not monitoring each.

Another tool for incorporating cost into indicator 

selection and program design is to consider three levels of 

budget (Caughlan and Oakley, 2001). Tier 1 assumes the 

lowest level of anticipated funding, and may consist of 

existing budgets and staff; tier 2 assumes a moderate level 

of program funding; and tier 3 assumes that additional, 

possibly one-time, funding becomes available. If protocols 

for individual indicators and the program as a whole include 

strategies for each level of funding, the program will be 

flexible to most scenarios. Planners should anticipate that 

annual costs of monitoring will increase faster (especially due 

to cost-of-living adjustments to pay) than the budget available 

to pay for them.
26 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Chapter 5. Sample Design 

Considerations

Although staff members of the Alaska NWRs are 

several steps away from articulating ecoregional monitoring 

objectives, we can anticipate some of the options and 

constraints that will contribute to determining sample designs. 

Once measurement objectives are determined from the 

monitoring objectives, sample-design considerations include 

several factors that determine which class of sample frame 

is appropriate. We discuss how decisions regarding sample 

design will be influenced by the specific context of Alaska, and 

how some of the inherent constraints can be alleviated through 

collaboration with partners. Finally, we provide examples of 

sample designs appropriate to potential monitoring questions 

for Alaska NWRs.

Design Considerations

The primary requirement for designing a sample frame 

for any particular indicator is a very specifically stated 

objective for monitoring that indicator (Noon and others, 

1999; Noon, 2003; Niemi and McDonald, 2004). Frequently, 

the identification and framing of a question is the most 

difficult task faced during the design of monitoring programs 

(Silsbee and Peterson, 1993; Pastorok and others, 1997). If 

the monitoring questions are poorly developed, no amount of 

sophisticated analysis will produce the needed information. 

Therefore, it is critically important that researchers and 

managers work together to identify and frame the questions 

that will drive the development of monitoring questions.

Our discussion in Chapter 4 suggests that it is likely that 

there will generally be both tactical and strategic monitoring 

needs. Tactical needs will tend to be shorter-term, of 

smaller spatial scale, and possibly amenable to an adaptivemanagement approach. In contrast, strategic needs will tend to 

be longer-term, possibly of ecoregional or broader scale, and 

concerned with the effectiveness of protective management. 

Based on these conclusions, we can describe the fundamental 

decisions that must be made and some options that are 

available for sample design. 

In general, factors that affect the monitoring design 

include: 

• Desired domain of inference (that is, to what spatial 

areas and time periods should results be applicable?).

• Availability of mechanistic or other models to extend 

results. 

• Spatial resolution(s) at which the indicator occurs or 

acts across the landscape (which determines where 

independence of samples effectively occurs).

• Available methods for measurement, and the expertise 

required to conduct them.

• Relative time and costs associated with travel to each 

site, performance of sampling, and processing of 

samples (for example, chemical analyses).

• Degree of confidence in monitoring results, or the 

minimum level of change that is desired to be detected 

with a given level of certainty.

• Existing designs in use in adjacent jurisdictions, if 

comparability and collaboration with those efforts is of 

importance.

• Available budget.

Based on the evaluation of these factors, the first decision 

regards the sampling strategy. Specifically, there are three 

main types of options to consider: index (reference sites), 

census (comprehensive), and probabilistic samples. All have 

an appropriate role in monitoring.

Index sites have been used to monitor numerous resources across protected areas of Alaska for several decades (for 

example, weather stations, stream gages). Such sites have been 

non-randomly selected, and results from their sampling cannot 

be justifiably extrapolated beyond the individual collection of 

points from which the results were derived, except through use 

of model-based inference. The value of continuing to monitor 

at these sites typically derives from lower monitoring costs 

associated with their usually higher accessibility, and more 

importantly from the long time-series that allow for long-term 

perspectives on trend, albeit at only one or a few points that 

do not represent any larger domain. In cases in which models 

have been developed in an attempt to extend results, there 

may be benefits to adding sites to improve the accuracy of the 

model (for example, high-elevation validation is often weak 

for weather models).

Comprehensive sampling – that is, a census – is 

measurement of every member of a population. Given the 

vastness of even each ecoregion within Alaska, censuses (for 

example, via remote sensing) will likely be feasible only 

within smaller domains (such as a particular refuge) or at a 

coarse resolution of information.

Probabilistic sampling is appropriate when the goal is to 

apply results from a subset (that is, a sample) of a population 

to make inferences about an entire domain of interest. Besides 

allowing for defensible inference, probabilistic samples also 

enable unbiased estimates of status and trend of an indicator, 

as well as of the associated measure of uncertainty with each 

estimate. They furthermore allow appropriate use of inferential 

statistics to analyze and interpret status and trend. This type 

of sampling will likely be the most appropriate method for 

sampling many indicators proposed by staff of Alaska NWRs, 

especially those whose status and trend must be estimated over 

refuge-wide, ecoregional, and larger spatial scales.

Sample size is determined by the desired level 

of statistical power, which indicates the probability of 

committing a Type II error. A Type II error entails concluding 

that no change has happened when, in fact, it has. This 

contrasts with a Type I error, important to null-hypothesis 
Chapter 5 27

testing, of concluding that a change has occurred when, in 

fact, is has not. In a monitoring context, Type II errors are 

potentially more costly than Type I errors (Peterman, 1990; 

Fairweather, 1991). While a Type I error may trigger an 

unnecessary response, it will likely be recognized quickly 

and result in only short-term costs. In contrast, a Type II error 

has the potential to result in irreparable damage to resources. 

Prospective (a priori) power analyses of sampling designs can 

insure that adequate sample size is used (Steidl and others, 

1997; Legg and Nagy, 2006).

Among the many types of probabilistic samples, simple 

random, cluster, and systematic sampling are the most 

commonly used (Lohr, 1999; table 7). In simple random 

sampling, each point is randomly selected from the whole 

sampling domain, independent of the locations of all other 

points. These samples often occur in a somewhat clumped 

spatial distribution, especially at relatively small sample sizes. 

In systematic sampling, sample points are evenly spaced 

across the entire domain, often on a grid after a random 

start. A potential weakness is that the grid spacing may be 

in synchrony with naturally occurring patterns, such that 

only ridges or valleys are sampled, for example. This would 

provide a biased representation of the domain. A grid sample 

also has the potential to miss rare elements entirely, especially 

at small sample sizes. Cluster sampling begins with a random 

or systematic sample of points and at each point a cluster of 

samples is taken (for example, subplots on a transect). Cluster 

sampling is conducted to (a) improve the precision of each 

point estimate (which represents a cluster of subsamples), and 

(b) quantify uncertainty around that point estimate (Sarndal 

and others, 1992). Cluster sampling is an effective sampling 

design especially when (a) elements of the target population 

occur naturally in clusters or groups (for example, caribou 

and colony-nesting birds, anglers in boats), or (b) the cost of 

obtaining observations increases markedly as the distance 

separating the sample units increases. If the same total 

number of plots is sampled across designs, however, cluster 

sampling typically results in lower precision. Generalized 

Random Tesselation Stratified designs (GRTS; Stevens and 

Olson, 1999, 2003, 2004) involve a spatially balanced random 

sample. The approach was developed as part of EMAP and it 

overcomes the tendency of simple random samples to clump 

spatially. Furthermore, it does not distribute points in a regular 

pattern, and thereby avoids the complicated computation of 

variance involved with systematic sampling.

Any of these sample types (that is, simple random, 

cluster, or systematic) can be distributed probabilistically 

throughout the sampled domain using equal-probability, 

stratified, or unequal-probability sampling (Lohr, 1999; table 

8; fig. 2). In equal-probability sampling, all areas are equally 

likely to be selected. In stratified sampling, the domain is 

divided into relatively homogeneous areas called strata. Equalprobability sampling is often used within strata; the selection 

probabilities and sample densities can be different for different 

strata. With unequal-probability sampling, the probability of 

selection and sample density can vary continuously across 

the domain. Stratified sampling is a special case of unequalprobability sampling in which probabilities of selection 

differ among strata. Finally, especially in cases in which a 

particular variable (for example, elevation, latitude, distance 

from water) is known to account for much of the variation in 

an indicator’s values, arranging sample units across gradients 

can be a valuable design approach to quantify the range of 

trajectories that sites may experience through time. Such 

approaches explicitly acknowledge that contemporary climate 

change is not the only driver influencing resource condition; 

rather, climate change will typically interact with other factors 

to affect ecological resources (Thomas and others, 2006; Root 

and Schneider, 2006; Rowe, 2007). 

Pros Cons

Simple Random • Simple and has straight-forward statistical 

properties

• The distribution is often clumped, especially at small sample sizes

Cluster • Most useful when travel costs among sites 

are high

• Produces more-accurate point estimates

• Degrees of freedom for analysis are based on the number of sites 

(that is, plot clusters) rather than the number of plots (that is, 

requires sampling more plots than with other sampling designs)

Systematic • Spreads sample evenly in space; avoids 

biases associated with small-sample-size 

random sampling

• Under-samples rare resources and over-samples common ones

• Produces bias if spacing corresponds to any environmental 

gradient or periodicity

• Can be difficult to compute variance due to lack of randomness in 

sample

Table 7. Characteristics of simple random, cluster, and systematic sampling methods, in the context of long-term ecological 

monitoring.
28 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Pros Cons

Equal- probability • Simple to implement

• All areas are equally important

• Emphasizes importance of common 

ecosystem components or processes

•

• Can be inefficient

• Provides little information on less-common ecosystem 

components or processes

Stratified • Sample density can be increased, within some 

strata, to provide adequate sample size for 

less-common species

• Selection probabilities can be designed to 

reflect site accessibility, to increase overall 

sample size

•

• More complicated analysis than for equal-probability 

sampling

• Membership of sites within strata must remain fixed forever, 

although one can switch to unequal probability sampling, 

which will allow for changes in membership

•

Unequal-probability • It has the advantages of stratification without 

need to define discrete strata

• One can add samples without regard to the 

initial strata

• Probability of selection can vary according to 

any suite of constraints

• More complex analysis than for stratified sampling

• One must keep track of the selection probabilities

•

Table 8. Advantages and disadvantages of equal-probability, stratified, and unequal-probability sampling designs, in the context of 

long-term ecological monitoring.

SAMPLE TYPE

Simple Random

SAMPLE DISTRIBUTION

Equal

Probability

Stratified

(mid stratum

sampled more

Intensively)

Unequal 

Probability

(gradient of 

sampling 

intensity from 

top bottom)

Cluster Systematic

Figure 2. Primary methods and strategies for distributing samples (from Jenkins and 

others, 2003).
Chapter 5 29

Besides distributing sampling through space, decisions 

must be made about how to distribute sampling through 

time (for example, across years), which is also known as 

the re-visit strategy. Though it may be desirable to revisit 

every site on every sampling occasion, this is rarely feasible, 

especially for samples covering large areas. Panel designs 

are an alternative distribution of site visits through time that 

allow for the allocation of groups of sites (that is, panels) to 

specific re-visit schedules such that not all sites are re-visited 

every year (table 9). The specific schedules and allocation of 

plots to them depend upon the relative perceived importance 

of several factors. First, greater numbers of re-visits to the 

same site(s) provides improved understanding of trend at those 

site(s); whereas the larger the number of sites visited in any 

one year (and across the cycle of all sites sampled), the better 

is the understanding of an indicator’s status within the domain 

during the year (or cycle). Second, the greater the inter-annual 

variability in a given indicator, the more important it is to 

have repeat sampling at sites to precisely estimate longterm trend. In highly variable environments, sampling often 

occurs in two to four successive years, rather than just one 

year within a cycle (tables 9B and 9C). Finally, if all sites are 

very costly to access from the monitoring office but travel 

among sites is relatively less costly, then sampling of all or 

most sites in fewer years is recommended (table 9A). The 

rotating-panel re-visit design (table 9C) represents a balance 

between understanding trend and status. A final consideration 

is that of monitoring-induced alteration of the target resource 

(for example, trampling of vegetation, disturbance of the 

nesting process for shorebirds); in cases where alteration is 

unavoidable to accurately measure condition of the target, 

less-frequent visits to sample points are worth considering.

Table 9. Allocation of visits to 20 hypothetical sites, across 5 years of monitoring. In each re-visit strategy, there are a total of 40 

site-visits. A) presents the case in which all visits occur in 2 years; a more-extreme case of optimizing understanding status within a 

given domain would be to sample 40 sites all in one year. B) represents, for this hypothetical time period and available number of visits, 

a strategy that maximizes understanding of trend, at a random sample of 8 sites. C) represents a rotating-panel design, which balances 

understanding of status and trend.

A B C

2010 2011 2012 2013 2014 2010 2011 2012 2013 2014 2010 2011 2012 2013 2014

Site # Site # Site #

1 X X 1 X X X X X 1 X X

2 X X 2 2 X X

3 X X 3 X X X X X 3 X X

4 X X 4 4 X X

5 X X 5 5 X X

6 X X 6 X X X X X 6 X X

7 X X 7 X X X X X 7 X X

8 X X 8 8 X X

9 X X 9 9 X X

10 X X 10 10 X X

11 X X 11 X X X X X 11 X X

12 X X 12 12 X X

13 X X 13 X X X X X 13 X X

14 X X 14 14 X X

15 X X 15 15 X X

16 X X 16 16 X X

17 X X 17 X X X X X 17 X X

18 X X 18 18 X X

19 X X 19 X X X X X 19 X X

20 X X 20 20 X X
30 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Determining Sampling Domains in Alaska

Conducting monitoring and research in the remote, 

relatively undisturbed ecosystems of protected areas in Alaska 

involves numerous constraints. These sampling constraints 

include: typically high transport costs due to lack of any roads 

in most refuges; harsh, unpredictable weather for much of the 

year; short day lengths during winter and adjoining seasons; 

inaccessibility of some resources during periods of snow and 

ice cover; short growing seasons; and impassability of some 

portions of the landscape (due to cliffs, crevassed glaciers, 

large water bodies, etc.). Especially for strategic monitoring 

objectives, thoughtfully designed broader-scale monitoring has 

several advantages over purely local-scale monitoring, which 

include: (a) encompassing a greater range of variability in the 

factors that influence the variable or phenomenon of interest; 

(b) increased sample size, when sampling is performed using 

compatible methods and design across units, allowing for a 

more-powerful ability to detect broad-scale trend (all other 

things, especially variability, being equal); (c) expansion of the 

sampled area to broaden the area of understanding and inference; and (d) possible illumination of hierarchical, cross-scale, 

or non-linear emergent dynamics. 

In particular, there are several characteristics that affect 

the domain in which resources will be sampled. First are 

safety, logistical (that is, weather- and travel-related), and 

fiscal constraints. Unless these can be mitigated by combining 

monitoring with other existing work of the USFWS or its 

collaborators, sampling must either: (a) rely on a smaller 

sample size, (b) define the domain of inference as areas 

within an accessible distance from points of access (for 

example, boat docks, appropriate shorelines, water bodies 

that can accommodate float-equipped planes, flat areas where 

a propeller plane can land), or (c) monitoring fewer natural 

resources, more comprehensively. To adequately define the 

sampling frame to which results have inference, accessibility 

must be a quantitative criterion, such as within 2 km of 

any road or a threshold value in a GIS-based Path Distance 

Analysis (Thompson and others, in press).

In addition, domains may be dictated by ANILCA 

purposes or the nature of the indicator. For example, 

monitoring results for water quality and quantity, a key 

resource for many waterbirds and whose protection is one 

of four guiding purposes for all refuges in Alaska, are most 

informative if considered in the watershed context even if 

investigated at smaller than watershed resolutions. This is 

because smaller-order headwaters are unavoidably connected 

to higher-order rivers that pass through refuges. Similarly, 

species that are mentioned in treaties between the U.S. and 

other nations (for example, salmon, sea otters, Northern 

fur seals, migratory birds) are mandated by ANILCA to be 

managed and monitored at those international extents. Not 

coincidentally, most of these species travel across vast areas 

during their lifetime, and their survivorship and reproductive 

success depend upon habitat conditions that they experience 

at those very broad spatial extents. In similar fashion, 

indicators such as climate-related or landcover metrics are best 

understood and interpreted at extents beyond that of individual 

management units, due simply to the nature of the phenomena 

and drivers underlying those metrics. For example, because of 

shifts in distributions of both species and permafrost, as well 

as the landscape mosaic of water-body drying and creation via 

melting, contemporary climate change provides strong impetus 

to design, implement, and interpret monitoring at ecoregional 

or broader scales. In contrast, trends in other indicators such 

as narrowly distributed plants and insects or unique, rare 

habitat types will likely be interpretable only at more-localized 

extents such as that of an individual management unit. 

Potential Benefits of Collaboration

Collaboration with other agencies offers a means to 

alleviate some of the constraints on conducting monitoring 

in Alaska. For example, close collaboration with neighbors 

allows for the assessment of complementarity among 

monitoring efforts, subsequently allowing synergy in 

understanding by (a) filling in gaps that are not monitored 

by neighboring landowners, and (b) increasing total sample 

size, for resources that are shared. In addition to the statistical 

advantages of such collaboration, staffing can become 

more specialized when shared; resources such as aircraft 

can be utilized more cost-effectively; and numerous socioeconomic benefits accrue, as evidenced in a growing number 

of conservation efforts across jurisdictions and international 

boundaries (Mittermeier and others, 2005). In Alaska, nearly 

every refuge abuts conservation lands administered by other 

federal agencies (table 10, fig. 4), and Tetlin NWR is part 

of the world’s largest contiguous protected-area complex, 

which also includes portions of British Columbia and Yukon 

Territory (Mittermeier and others, 2005). Profound differences 

in monitoring objectives for adjacent jurisdictions tracking the 

same resource rightfully prescribe some tailoring of methods 

or the suite of attributes measured; nonetheless, compromises 

that still allow comparability across the landscape are often 

possible.

 For resources monitored across broad spatial extents 

yet at finer resolutions, hierarchical organization of sampling 

allows for results to be obtained for multiple areas (and 

thus, diverse stakeholders at refuge to international scales; 

Raudenbush and Bryk, 2002). For example, the systematic 

sampling designs of FIA and NARS allow provision of results 

at county, state, regional, and national extents; however, 

sample size within individual management units (even those 

as extensive as Alaska NWRs) is typically too limited to 

make robust inference about resource status within the unit, 

especially if the sample is stratified into different soil types 
Chapter 5 31

or vegetative communities. To address this need, managers 

have often elected to collect samples or make measurements 

at sampling points using the same methods and systematic 

grid (for example, LTEMP in Kenai NWR; Morton and others, 

2009), but increase the density of sample points within each 

grid cell to provide results that have greater power to detect 

change within such smaller extents. In contrast to nested 

and hierarchical sampling, sampling of some indicators (for 

example, citizen monitoring) may not be nested within (nor 

co-located with) frameworks for other resources.

Applying Design Considerations to Monitoring 

for Alaskan NWRs

Given this suite of considerations, we have listed one or 

two strategies (table 12) that could be employed to address 

examples of potential monitoring questions for each indicator 

listed in table 11. (These are examples of the potential 

questions and indicators that may result from a careful 

indicator-selection process based on management information 

needs.) Note that even within a given extent, highly divergent 

designs may be appropriate to assess status and trend of the 

different target resources. In addition to the spatial designs, 

table 12 also contains possible re-visit strategies that could be 

used to allocate monitoring effort through time. See table 9

for examples of how sampling of units through time can be 

distributed to maximize understanding of status, trend, or 

a balance between the two. Strikingly, there may be very 

different optimal re-visit strategies across indicators, even 

among indicators organized at the same extent (for example, 

statewide, or ecoregional). Note that many other options 

for spatial and temporal allocation of effort may also be 

appropriate. The ‘best’ approach for any indicator depends 

strongly on the nature of the monitoring question being asked, 

as well as (among other things) the technical resources to 

analyze the data. Ultimately, selection of monitoring designs 

reflects tradeoffs among a suite of design considerations. 

Determining the importance and consequences of various 

choices requires collaboration among field biologists and 

technicians, biometricians, and decision-makers, as well as 

communication and sufficient lead time to thoughtfully design 

and implement monitoring, in a manner that solidly meets 

objectives.

Ecoregion Unit Agency

Polar National Petroleum Reserve BLM

Dalton Highway Corridor BLM

Alaska Maritime NWR FWS

Arctic NWR FWS

Cape Krusenstern NM NPS

Gates of the Arctic NP NPS

Kobuk Valley NP NPS

Noatak NP NPS

Interior Alaska White Mountains NRA BLM

Steese NCA BLM

BLM units BLM

Arctic NWR FWS

Innoko NWR FWS

Kanuti NWR FWS

Kenai NWR FWS

Koyukuk NWR FWS

Nowitna NWR FWS

Selawik NWR FWS

Tetlin NWR FWS

Yukon Flats NWR FWS

Cape Krusenstern NM NPS

Denali NP NPS

Kobuk Valley NP NPS

Lake Clark NP NPS

Noatak NP NPS

Wrangell-St. Elias NP NPS

Bering Coast Wood Tikchik State Park Alaska

BLM unit BLM

Becharof NWR FWS

Selawik NWR FWS

Togiak NWR FWS

Yukon Delta NWR FWS

Bering Land Bridge NP NPS

North Pacific 

Coast

Annette Is. Indian Reservation BIA

BLM unit BLM

Alaska Maritime NWR FWS

Alaska Peninsula NWR FWS

Becharof NWR FWS

Izembek NWR FWS

Kenai NWR FWS

Chugach National Forest FS

Tongass National Forest FS

Table 10. Federal and state lands in Alaska by ecoregion. 

[Abbreviations: BIA, Bureau of Indian Affairs; BLM, Bureau of Land 

Management;USFWS, U.S. Fish and Wildlife Service; NCA, National 

Conservation Area; NP, National Park; NHP, National Historical Park; NM, 

National Monument; NRA, National Recreation Area; NPS, National Park 

Service; FS, U.S. Forest Service]
32 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Indicator(s) Notes

State-wide Extent

Climate Accumulate data from existing weather stations and climate networks; supplement by filling 

gaps that will improve climate models at various extents; attributes include temperature, 

precipitation, snow depth, snow-water equivalent, freeze-thaw events, length of growing 

season

Air quality, precipitation chemistry Accumulate data from existing air-quality stations; fill gaps to improve model accuracy

Landcover Include attributes of vegetation mosaic, distribution of water bodies, glaciers, sea ice; create a 

seamless map every 5–7 years (perhaps with panel design) using satellite imagery, groundtruthing, or maybe a systematic grid of ground plots; collaborate with FIA

Phenology Is already being done by others; surrogate for other species’ dynamics; example attributes 

include vegetation greening and browning using NDVI, ice-out and ice-in, and other 

metrics organized by the National Phenological Network (for example, budburst, arrival of 

migrants, first nesting dates)

Water quality and quantity Most cost-effective to organize at statewide extent, but may need to parameterize at 

ecoregional or finer resolution; includes wetlands, riparian areas, and lentic systems

Deformities and contaminants in 

organisms

Bird beaks, amphibians; contaminants in seabirds, other taxa

Ecoregional Extent

Habitat mosaics Composition of habitat types important to primary monitoring entities in the ecoregion (for 

example, as determinants of distributions of species monitored by those entities)

Migratory species Includes birds, large mammals (ungulates, carnivores, anadromous fishes, and marine 

species)

Permafrost-related events and 

resources

Example attributes: thermokarst, filling and draining of lakes and wetlands

Shoreline changes May need local-scale normalization

Invasive species

Other landscape processes Examples: fire and subsequent succession

Refuge Extent

Subsistence resources Examples: plant parts, animals

Ecological keystones, ecosystem 

engineers, or key landscape 

modifiers

Examples: sea otters, beavers, moose, and (cyclically) lagomorphs

Local stressors and responses Examples: roads, snow-machine use, non-subsistence harvest, localized sites of recreation, 

etc.

Refuge-significant species not 

covered at ecoregional extent

Examples include species in refuges purposes and other statutes with home ranges smaller 

than the refuge (for example, furbearers)

Special plant and animal 

communities

Examples; Eelgrass, rare habitat, endemic or narrowly distributed animals

Table 11. A potential suite of indicators for which monitoring, assessment and interpretation may occur at state-wide, ecoregional and 

refuge-specific extents within Alaska.

[ Note that for all metrics except invasive species, we have only listed each indicator at the broadest extent at which results might be usefully summarized. 

The criterion for deciding to consider an indicator at the state-wide or ecoregional extent was whether one would want a state-wide or ecoregional map for that 

indicator, for regulatory, conservation, management, or other management decisions. Abbreviations: NDVI = Normalized Difference Vegetation Index, FIA = 

Forest Inventory and Assessment]
Chapter 5

33

Table 12. Examples of monitoring designs and temporal re-visit strategies that could be used to guide monitoring of indicators listed in table 11.[Note that individual indicators have from 1-4 example questions with which they are associated, as indicated by the letters in the second-leftmost column. Note that although we have tried to illustrate the intimate connection between the monitoring question and both the monitoring design and re-visit strategy, space limitations have precluded us from explicitly specifying the specific spatial and temporal domains associated each monitoring question, which will be necessary for each indicator, before program development can begin. Some indicators are so inclusive that we could not provide a meaningfully comprehensive set of examples to illustrate connection of question(s) with spatial design and temporal strategy. Abbreviations: LiDAR = Light Detection and Ranging, BBS = Breeding Bird Survey, SPOT = Satellite Pour l ́Observation de la Terre, IKONOS is not an acronym]

Indicator(s) Monitoring Design Temporal (re-visit) strategy

State-wide Extent

Climate Collection of index sites with time series of varying antiquity and continuity Continuous data collection (recorded or summarized at sub-hourly, hourly, 

sub-daily, daily, monthly, seasonally, and annually)

Air quality, precipitation chemistry Collection of index sites with time series of varying antiquity and continuity Continuous data collection (recorded or summarized at sub-daily, daily, 

monthly, seasonally, and annually)

Land cover Patchwork of strips of locally censused area; re-sample across years at several 

index strips (randomly selected, initially), to quantify inter-annual effects

State divided into 5-7 randomly selected samples of strips; rotating-panel 

design

Phenology Varies by attribute; probably a collection of volunteer locations, for many 

attributes; most sites likely to be in easily-accessible locations, for easy revisits

Re-visits daily or weekly, within range of target date (varying by indicator)

Water quality and quantity Gage stations are a network of index sites; seasonal chemistry should be sampled 

across gradients of remoteness

Continuous data collection (recorded or summarized at sub-hourly, hourly, 

sub-daily, daily, monthly, seasonally, and annually)

Deformities and contaminants in organisms Opportunistic, in the midst of other research and monitoring projects Contingent upon existing study designs

Ecoregional Extent

Habitat mosaics Obtain Landsat or other remotely sensed imagery; supplement with ground-based 

sampling or finer-resolution imagery (for example, SPOT, LiDAR, IKONOS), to validate

Ecoregion (or interested management units) divided into 5-7 randomly 

selected samples of strips; rotating-panel design

Migratory species Across gradients of remoteness (at least occasionally); maintenance of existing 

BBS route time-series

Annually, within target season (migrant arrival, breeding , rutting, premigration)

Permafrost-related events and resources Opportunistic, in the midst of other research and monitoring projects; use these 

to inform subsequent monitoring designs; stratified random sampling across gradients at least several km away from big population centers (for example, heat sources); sample across elevations and aspects; use Landsat imagery as a coarse-resolution census

Opportunistic sampling varies by project; Censuses: ecoregions divided 

into 5-7 randomly selected samples of strips; rotating-panel design

Shoreline changes Stratified random sampling Split-panel design (to balance understanding of status and trend)Invasive species Divided effort: smaller effort in systematic or random sampling (stratified by 

accessibility); greater effort at most-likely vectors (for example, trailheads) of invasion and known population sites

Annually, within target season

Other landscape processes Opportunistic, depending on where events occur (mapping) Annually, within target season; split-panel design (to balance 

understanding of status and trend)

Refuge extent

Subsistence resources Most effort at most-likely locations (for example, near population centers, 

trailheads, roadsides) of likely and known harvest or collecting sites

Annually, within target season; split-panel design

Ecological keystones, ecosystem engineers, 

or key landscape modifiers

Local stressors and responses Most effort at most-likely locations (for example, near population centers, 

trailheads, roadsides) of likely and known transportation corridors and recreation sites

Annually, within target season

Refuge-significant species not covered at 

ecoregional extent

Varies by indicator Varies by indicator

Special plant and animal communities Varies by indicator Split-panel design (to balance understanding of status and trend)
34 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Chapter 6. Building Blocks for Alaska 

NWRs Monitoring Program

Some building blocks are already in place for developing a monitoring program for Alaska NWRs. These include 

refuge-specific and ecoregional conceptual models and the rationale for that ecoregional structure. Additionally, inventories 

and monitoring are currently occurring in and around refuges. 

These monitoring projects are being conducted by refuge staff, 

other divisions of USFWS, and other agencies. Inadequacies 

in inventory data have already been identified and prioritized. Finally, current staff members already have some of the 

needed technical capabilities to conduct monitoring.

Conceptual Models

Conceptual models inform monitoring programs 

in a number of ways, including summarizing important 

ecosystem components and processes as well as facilitating 

communication, discussion, and debate about the nature of 

the system and important management issues. This process 

can lead to hypotheses regarding future changes, likely results 

of alternative management actions, and identification of 

monitoring indicators. Ultimately, conceptual models can help 

managers and scientists interpret monitoring results. Recently, 

staffs of the 16 National Wildlife Refuges in Alaska created 

a conceptual model of their refuge and the landscape context 

to support development of long-term ecological monitoring. 

Models include prominent ecosystem components, drivers, 

and processes by which components are linked or altered. 

Ecoregional models were then developed to describe 

linkages among refuges sharing the same broadly-defined 

climate. Ecoregional boundaries are derived from the 32 

unified ecoregions of Alaska, which are hierarchically nested 

into eight Level-1 groups, and further into four terrestrial 

ecoregions for modeling (Polar, Interior Alaska, Bering Coast, 

and North Pacific Coast; see below). Conceptual models were 

also developed for adjacent marine areas, designated as the 

North Pacific, Bering Sea and Polar Marine Ecoregions. The 

process of developing and refining monitoring objectives will 

include further refinement of the conceptual models so they 

provide more detail about specific resources and processes 

within ecosystems. 

The process of conceptual model development for 

the system to be monitored, and the discussion that leads 

to acceptance of these models by everyone involved in the 

monitoring program is critical to engendering agreement 

about how the system operates (National Research Council, 

1995; Busch and Trexler, 2003). Without this process, there 

can be a tendency to simply adopt approaches favored by a 

subset of experts, or to work from lists of potential indicators 

without adequate consideration of their ecological role 

and connections. By hypothesizing which indicators might 

represent pivotal stressors, drivers, or responses, these models 

may provide the basis for indicator selection. Because they 

are a mechanism for integrating often highly sophisticated, 

but disparate, views about the ecosystem, they can support the 

prioritization process, which seeks to identify the most fruitful 

set of indicators to monitor.

Ecoregional Structure

Ecoregions define areas with common ecological 

components and processes, and therefore could be used to 

describe regions with the potential for common monitoring 

objectives (Busch and Trexler, 2003). Classifying ecoregions 

is complicated by the difficulty of determining strict categories 

for natural systems characterized by multivariate gradients. 

Consequently, there are multiple ways to define ecoregions, 

reflecting differences in the parameters considered and their 

relative weights. Moreover, the fact that different levels of 

discrimination are possible leads to classifications that are 

commonly hierarchical, with smaller spatial units grouped 

into larger ones by increasing the range of variability used 

to define a class (Nowacki and others, 2001; Omernik, 1987; 

Bailey, 1995). Notwithstanding the complexity and ambiguity 

of ecoregional boundaries, an ecoregional classification is a 

useful tool for organizing monitoring and putting local results 

into a larger context.

Nowacki and others (2002) attempted to unify the 

extant ecoregional maps of Alaska (Gallant and others, 1995; 

Nowacki and Brock, 1995) of Alaska by combining them 

and using additional data to resolve discrepancies. This map 

was the basis for delineation of ecoregions for organizing 

conceptual models of Alaska NWRs. Meanwhile, the national 

NWRS has been organizing management according to 

Landscape Conservation Cooperatives (LCCS), which are 

ecoregions defined by Bird Conservation Regions (BCRs). 

Because the BCRs were developed with a priority on bird 

distributions, they differ somewhat from the ecoregions based 

on the work of Nowacki and others (2002) (figs. 3 and 4). 

Both have ecoregions bordering on the Arctic Sea, Bering Sea, 

and northern Pacific Ocean, plus an interior region. The only 

significant difference relevant to the grouping of refuges is 

that the BCR map includes the Alaska Peninsula and Kodiak 

Island with western Alaska, whereas the Nowacki-based 

map included the Alaska Peninsula and Kodiak Island with 

southern Alaska. However, it has also been determined that 

there is insufficient staff in Alaska to separately administer 

the five BCRs in Alaska. Consequently, they may be grouped 

in the Northern Alaska LCC (NAK-LCC), including Arctic 

plus Northwestern Interior Forest, and the Southern Alaska 

LCC (SAK-LCC) including Aleutian/Bering Sea and Western 

Alaska. The North Pacific LCC will be administered by 

Region 1. In this case, the Alaska Peninsula and Kodiak Island 

will be grouped with both western and southern Alaska in the 

SAK-LCC. However, this structure is still in flux.
Chapter 6

35

Figure02_Boundaries of Alaska NWRs in relation to Bird Conservation Region (BCR) boundaries

160°E 170°E 170°W 180° 150°W 160°W 140°W 130°W 120°W 70°N 65°N

60°N55°N50°N

Bird Conservation Region (BCR) boundaries 

(color indicates region) 

Alaska Maritime Alaska Peninsula Arctic Becharof Innoko Izembek Kanuti Kenai 

12345678

Kodiak Koyukuk Nowitna Selawik Tetlin Togiak Yukon Delta Yukon Flats

9

10111213141516

National Wildlife Refuges—All outlines in 

black except Alaska Maritime in red.

Arctic

Arctic

Aleutian/

Bering

Sea

Aleutian/Bering

Sea

Northwestern

Interior Forest

North Pacific

Western

Alaska

EXPLANATION

0 100 200 300 400 500 Miles0 100 200 300 400 500 Kilometers

Figure 3. Boundaries of Alaska National Wildlife Refuges in relation to Bird Conservation Region (BCR) boundaries.
36 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Figure04_Refuges and Ecoregions

160°E 170°E 170°W 180° 150°W 160°W 140°W 130°W 120°W 70°N 65°N

60°N55°N50°N

0 100 200 300 400 500 Miles0 100 200 300 400 500 Kilometers

CANADA

ALASKA

2

2

2

3

4

5

5

6

7

8

9

10

11

12

13

14

15

15

16
Chapter 6

37

Figure01_Refuges and Ecoregions Explanation Keep with map on facing pages

BOREAL

Bering Taiga

Ahklun MountainsBristol Bay LowlandsNulato HillsYukon-Kuskokwim Delta

Intermontane Boreal

Davidson MountainsKobuk Ridges and ValleysKuskokwim MountainsNorth Olgivie MountainsRay MountainsTanana-Kuskokwim LowlandsYukon-Old Crow BasinYukon River LowlandsYukon-Tanana Uplands

Alaska Range Transition

Alaska RangeCook Inlet BasinCopper River BasinLime Hills

POLAR

Arctic Tundra

Beaufort Coastal PlainBrooks FoothillsBrooks Range

Bering Tundra

Bering Sea IslandsKotzebue Sound LowlandsSeward Peninsula

MARITIME

Aleutian Meadows

Alaska PeninsulaAleutian Islands

Coastal Rainforests

Alexander ArchipelagoBoundary RangesChugach-St. Elias MountainsGulf of Alaska CoastKodiak Island

Coastal Mountains Transition

Kluane RangeWrangell Mountains

EXPLANATION

Ecoregions—from Nowacki and others, 2001. Ecoregions are organized into major 

bioclimatic groups. 

Alaska Maritime Alaska Peninsula Arctic Becharof Innoko Izembek Kanuti Kenai Kodiak Koyukuk Nowitna Selawik Tetlin Togiak Yukon Delta Yukon Flats

123456789

10111213141516

National Wildlife Refuges—All outlines in 

black except Alaska Maritime in red.

Figure 4. Boundaries of Alaska National Wildlife Refuges, in relation to ecoregions based on Nowacki and others (2001).
38 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

The National Park Service has also grouped land 

management units in Alaska for purposes of organizing 

monitoring (fig. 5). Only the Southeast Alaska Network falls 

completely in one Nowacki-based ecoregion or LCC. The 

Central Alaska Network falls mainly in the interior ecoregions 

of the two other two classifications, but also has significant 

area in the north Pacific ecoregions. The Southwest Alaska 

Network occupies the Alaska Peninsula, but the Lake Clark 

National Park and Preserve is in the interior ecoregion. Finally, 

the Arctic Network falls mainly in the Polar (Nowacki-based 

system) and Arctic (BCR system) with the exception of Bering 

Land Bridge National Preserve, which lies in western Alaska. 

Given how much cooperation already occurs between refuges 

and national parks, it is unlikely that the discrepancies in 

ecoregional groupings will prevent further collaboration.

The Bureau of Land Management, U.S. Forest Service, 

other federal agencies and the State of Alaska have significant 

land holdings throughout Alaska. Their location relative to 

refuges is detailed in table 10.

Existing Inventories and Current Monitoring on 

Alaska NWRs

Inventories of natural resources have been conducted 

by various agencies throughout Alaska over a long period. 

An effort to enter all of the information, or even a summary 

covering what, when, how and who, would benefit all 

agencies. Having a current and historic record of resource 

distribution would provide an important context to assess 

future trends. Alaska refuges could begin to create this 

database by compiling the many inventories that have 

occurred on refuge lands. In fact, the Arctic NWR already 

does this by contributing the results of studies to North Slope 

Science Initiative and the Arctic LCC.

 In fiscal year 2010, the refuge program in Alaska 

developed an assessment of the work effort expended by the 

refuge field stations and their staff on biological surveys and 

studies. Analysis of these results is pending. Ultimately, this 

annual survey will be a useful tool in tracking inventory and 

monitoring efforts on refuges. 

In addition to current efforts by refuges themselves, other 

monitoring efforts are being conducted in and around these 

areas by other agencies. The following three sections of this 

chapter, as well as appendixes 9-11, describe much, but not all, 

of what is being done. We were able to gather more complete 

information from some agencies than others. Nevertheless, 

these summaries provide some guidance regarding potential 

sources of collaboration with refuges. Lists of other agencies 

that are monitoring indicators that may be of interest to 

USFWS are provided in table 13. 
Chapter 6

39

160°E 170°E 170°W 180° 150°W 160°W 140°W 130°W 120°W 70°N 65°N

60°N55°N50°N

2

2

1

2

3

4

5

5

6

7

8

9

10

11

12

13

14

15

15

16

Alaska Maritime Alaska Peninsula Arctic Becharof Innoko Izembek Kanuti Kenai 

Ecoregions—from Nowacki and others, 2001. 

12345678

Kodiak Koyukuk Nowitna Selawik Tetlin Togiak Yukon Delta Yukon Flats

9

10111213141516

National Wildlife Refuges—All outlines in 

black except Alaska Maritime in red.

Polar

Polar

National Park Units: NP = National Park, 

NMon. = National Monument, Pres. = National Preserve

Bering

Coast

Interior

Alaska

North Pacific Coast

EXPLANATION

0 100 200 300 400 500 Miles0 100 200 300 400 500 Kilometers

Kobuk

I&M Networks

Noatak Pres.

Gates of the Arctic

NP and Pres.

Yukon-Charley

Rivers Pres.

Wrangell-St.Elias

NP and Pres.

Glacier Bay

NP and Pres.

Kobuk Valley NP

Cape Krusenstern

NMon.

Bering Land

Bridge Pres.

Lake Clark

NP and Pres.

Aniakchak NMon.

and Pres.

Katmai NP

and Pres.

Kenai Fjords NP

Denali NP

and Pres.

Figure 5. Comparison among Nowacki-based ecoregions, boundaries of Alaska NWRs and NPS units grouped by the four I&M networks in Alaska. Nowackibased ecoregions are denoted by shading as in Fig. 4; NPS I&M networks are identified by ovals. ALAG, SITK, and KLGO (all in the North Pacific Coast 

ecoregion; abbreviations as in appendix 12) are not indicated, in this figure. 
40 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners Indicator(s) Other entities monitoring the indicator Other collaborating entities that consider the indicator part of their monitoring program

State-wide Extent

Climate NWS, NOAA, NPS-ARCN, NPS-CAKN, NPS-SWAN, NPSSEAN, PCA BLM, ADF&G, NPS-ARCN, NPS-CAKN, NPS-SWAN, NPS- SEANAir quality, precipitation chemistry NPS-ARCN, NPS-SWAN, NPS-SEAN, USFS NPS-CAKNLandcover NPS-CAKN, NPS-SWAN, NPS-SEAN, USFS, PCA BLM, ADF&GPhenology Various public and private entities, PCA, NPS National Phenological Network-USAWater quality and quantity NPS-CAKN, NPS-SWAN, NPS-SEAN NPS-ARCN (future)Deformities and contaminants in organisms USGS-ASC, USFS

Ecoregional Extent

Habitat mosaics BLM Wildlife, ADF&G, USFS, PCAMigratory species Boreal Partners in Flight, CARMA, ADF&G, USGS-ASC, BLM, 

NPS-ARCN, NPS, CAKN, USFWS Migratory Birds

NPS-SWAN (collaborator), NPS-SEAN (future), ALMS, BBS

Permafrost-related events and resources NPS-ARCN, NPS-CAKN, USGS-ASC NPS-ARCN, NPS-CAKNShoreline changes NPS-ARCN, NPS-SWAN, USGS-ASC, PCAInvasive species NPS-SWAN (collaborator), NPS-ARCN (future), NPS-CAKN 

(future), NPS-SEAN (future)

Other landscape processes BLM, USFS USFWS Regional Office

Refuge Extent

Subsistence resources BLM, USFWS OSM, USGS-ASC (fishes, ungulates), USFWS 

Fisheries

Ecological keystones, ecosystem engineers, 

or key landscape modifiers

ADF&G, BLM

Local stressors and responses Individual refuges, NPS-ARCN, NPS-CAKN, NPS-SWAN, 

NPS-SEAN, BLM, PCA

BLM

Refuge-significant species not covered at 

ecoregional extent

Individual refuges, USGS-ASC, NPS-ARCN, NPS-CAKN, NPSSWAN, NPS-SEAN, BLM, PCA

Special plant and animal communities Individual refuges, USGS-ASC

Table 13. Entities within or adjacent to Alaska that perform monitoring of indicators in table 11, and those that participate collaboratively, but are not the lead in monitoring of each indicator (including entities that may monitor the indicator in the future).[ ADF&G = Alaska Dept. of Fish & Game; ASC = Alaska Science Center; ARCN = Arctic I&M Network; CAKN = Central Alaska I&M Network; NOAA = National Oceanographic and Atmospheric Administration; NWS = National Weather Service; PCA = Parks Canada Agency; SEAN = Southeast Alaska I&M Network; SWAN = Southwest Alaska I&M Network; USFS = U.S. Forest Service]
Chapter 6 41

Ecological Monitoring on Refuges in 

Collaboration with Other Agencies

Although most monitoring within Alaska NWRs occurs 

independently of other refuges, several monitoring efforts span 

broader extents and encompass several refuges (appendix 9). 

Most of the monitoring of large-bodied mammals undertaken 

on refuges is conducted by, or in collaboration with, the 

Alaska Department of Fish and Game (ADF&G). Caribou, 

and black and grizzly bears, are monitored aerially based on 

survey units (caribou) or line transects (bears). ADF&G also 

occasionally monitors wolves and wolverines (appendix 9).

 Two programs monitor birds extensively in Alaska, 

the Breeding Bird Survey (BBS) and the Alaska Landbird 

Monitoring Survey (ALMS). BBS is a national, road-based 

program and many refuges have at least one BBS route on or 

near the refuge. The system of BBS routes in Alaska has had 

enough routes to be meaningful since 1993. Currently there 

are 142 routes in Alaska, some of which use motor boats to 

supplement the little area accessible via the state’s sparse 

road system. The ALMS program was also established to 

supplement BBS by tracking bird species and abundances 

in roadless areas. It was launched in 2003, and the initial 

sample came from Interior and North Pacific Rainforest Bird 

Conservation Units (appendix 9).

 Several programs monitor plants in Alaska. These 

include, among others, the U.S. Forest Service Forest 

Inventory and Analysis Program (FIA, appendix 3, 11), the 

USGS eelgrass and macroalgae monitoring program, Global 

Observation Research Initiative in Alpine Environments 

(GLORIA) and the International Tundra Experiment (ITEX). 

The FIA program has been implemented in southeast and 

south-central Alaska using methods of the national program, 

which covers all U.S. forested lands. It features a spatiallybalanced sample with 10 percent of the plots measured 

annually. Data collection is focused on trees, with additional 

vegetation metrics measured on a 1/16 subsample. Eelgrass 

and macroalgae monitoring was initiated by USGS in 2009. 

Sampled areas included embayments in or adjacent to four 

Alaska NWRs (Izembek, Togiak, Alaska Peninsula-Becharof, 

and Yukon Delta). Vegetation monitoring also is performed 

by the U.S. National Park Service and the Bureau of Land 

Management (appendix 19).

Monitoring Efforts by Other USFWS Programs

Various treaties and legislative acts require USFWS to 

monitor a number of species, all of which are important to 

various refuges (appendix 10). Refuges already collaborate 

with most of these efforts and have the potential to 

augment sampling for the benefit of the refuge and for the 

larger USFWS program. The USFWS Marine Mammals 

Management Office monitors the status and trends of polar 

bear, Northern sea otter, and Pacific walrus populations in all 

Alaska marine habitats, and performs a census of subsistence 

harvest. The information directly applies to the eight coastal 

refuges. In addition, the Office is beginning to monitor 

interactions between polar bears and humans (appendix 10).

USFWS monitors key fish populations in collaboration 

with the Alaska Department of Fish and Game and the refuges. 

Although the monitoring program meets high standards of 

sample design and data collection and analysis, the large area 

of the State, as well as logistic and budgetary constraints 

have limited the effectiveness of the program. Consequently, 

the effort has been insufficient to meet the information 

needs, and data have not been readily available to decisionmakers. Monitoring developed for the Alaska NWRs has an 

opportunity to help fill this gap.

The Migratory Birds Branch of USFWS monitors 

seabirds, waterfowl, raptors, and shorebirds. Seabird 

monitoring consists of counting individuals at index sites 

located approximately every 500 miles along the coast, as 

well as kittiwake monitoring in Prince William Sound in 

response to the Exxon Valdez oil spill. Abundance, trend, and 

distribution of waterfowl are monitored in the spring using 

aerial transects, both on and off refuges. Raptor monitoring 

is limited to bald eagles, mainly on the southern coast of the 

State. Shorebird monitoring is dependent on “soft” money, 

so is conducted inconsistently. Status and trend of multiple 

shorebird species is monitored via a standardized protocol 

(PRISM). The effort began in 2002 and occurs irregularly 

at Canning River, near Arctic NWR, near Barrow and near 

Prudhoe Bay, and on the Yukon River Delta. Additionally, 

more-intensive demographic investigations track attributes 

such as nest success, site fidelity, and adult survival at a 

limited number of sites (see appendix 10). 

Monitoring by Other Agencies with Relevance 

to the Alaska NWRs

U.S. Forest Service’s Forest Inventory and Analysis (FIA) 

program – The FIA program in Alaska is part of a national 

program that monitors status and change of all U.S. forest 

lands (http://www.fia.fs.fed.us; appendix 3). In Southeast 

and South-central Alaska, the program uses the national 

design: a spatially-balanced probability sample of field plots 

across all lands and use of spatially-complete remote sensing 

data for stratification (appendix 11). Field sample points are 

randomly divided into 10 panels, with one panel measured 

each year using a boat/helicopter combination that travels 

from Ketchikan to Kodiak. The program covers 15 million 

ha, and the sample contains about 5,620 plots on land (2,200 

forested plots). The national FIA program currently operates 

in all states and territories of the U.S. with the exception 

of Wyoming and the remainder of Alaska. If funded, the 

program proposed for the remainder of Alaska will have a 

reduced sampling intensity, some modifications to the design 

and indicators, and incorporation of LiDAR data. Indicators 

monitored by the FIA program are generally reported at the 

ecoregion, survey unit, state, or national level. Status and 
42 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

change of a variety of forest indicators are reported, as listed 

in appendix 8. On a 1/16th subsample of plots, additional 

indicators include suites of variables for down woody debris, 

vegetation diversity, crown conditions, lichens, and soils. 

U.S. National Park Service’s Inventory and Monitoring 

(I&M) program – Five overarching objectives guide the 

program nationally (appendix 1), and suites of stepped-down 

objectives analogously guide each of the four I&M networks 

within Alaska (see http://science.nature.nps.gov/im/units/akro/

index.cfm and links). Each network chose, via a carefully 

orchestrated process, a group of about 20 to 30 ‘Vital sign’ 

indicators, which are organized under the themes of Air and 

Climate, Geology and Soils, Water, Biological Integrity, 

Human Use, and Landscapes. I&M networks consider their 

constituent park units as their primary clients, but interface 

with a diversity of other stakeholders and audiences. A 

summary of the I&M effort at the national level is given 

in appendix 1. As illustrated in appendix 12, the suites of 

indicators monitored in each park and network in Alaska 

represent a balance between comparability across space 

and acknowledging the unique resources and management 

priorities of each park.

Bureau of Land Management (BLM) – As with Forest 

Service lands, BLM lands are administered under a multipleuse mandate. Ecological monitoring in BLM occurs within 

Fisheries, Wildlife, Cultural, Recreation, and Vegetation 

programs (appendix 11). Species groups include cliff-nesting 

raptors; eiders; game mammals; breeding and migrating birds; 

polar bears; subsistence-use (for example, salmon, northern 

pike), recreationally important, unique and resident fish. 

Across Alaska, BLM works through NRCS to collect soils 

information in a few regions, and data on snow-depth and 

snow-water equivalent in specific areas that are part of NRCS’ 

regional networks. There is no cultural or paleontological 

information collected that is not site- or project-specific; it will 

thus be difficult to organize this information at ecoregional or 

statewide extents.

Priorities for Baseline Information Needs

One clear message expressed by participants at the 

Forum on Ecoregional Monitoring was that most USFWS 

refuges within Alaska lack baseline data on many biotic and 

(especially) abiotic components. Addressing this deficit would 

provide managers fundamental information regarding exactly 

what resources they have to protect. Relative to supporting 

monitoring this information would: (a) provide a baseline 

against which to measure refuge-wide and ecoregional-scale 

change and (b) inform analysis, interpretation, and forecasting 

of numerous other monitored indicators, and (c) provide a 

basis for spatial stratification that may be needed to distribute 

samples.

This message was not new; in fact, by 2004, the National 

Wildlife Refuge System had already developed “guidelines 

and core baseline biotic data standards for inventories that 

include the types of information every unit of the National 

Wildlife Refuge System should have on its resources.” 

(USFWS Baseline Inventory Team 2004:3). In addition to 

identifying the minimum inventory data needed for every 

refuge and determining the spatial scales most appropriate 

for data collection and presentation, the 2004 document 

also provided standardizing guidelines for realizing the 

inventories and suggested standards for reviewing products. 

The minimum set of inventories included GIS data layers 

for abiotic (topography, hydrography, soils, boundaries, and 

manmade features) and, biotic features (vegetation mapping 

and National Wetland Inventory data), and aerial photography. 

In contrast to refuges in the contiguous U.S., for which 

these data layers exist free of cost via other sources, many 

Alaskan refuges have never had comparable inventories of 

their resources. Species lists of vertebrate fauna and flora, as 

well as supplemental data on resources of special interest (for 

example, Threatened and Endangered species) were among the 

highest priorities, after the minimum set.

Although some at the Forum on Ecoregional Monitoring 

for the NWRS and other Public Lands across Alaska have 

espoused considering these informational products as onetime “baseline” inventories, their value will increase the more 

times that they are repeated. Furthermore, in the particularly 

unpredictable environment created by climate dynamics, 

a ‘baseline’ may be better defined by a few snapshots or 

estimates than by a sample at a single point in time. That is, 

historical range of variability is no longer dependable as a 

paradigm, because targets will likely shift through time.

To obtain a cross-disciplinary assessment of the value of 

various pieces of spatially explicit information for inventory 

and monitoring purposes, Forum participants were randomly 

distributed into four groups while balancing regional and 

discipline affiliations to assess and prioritize inventory 

needs for refuges in Alaska (table 14). The groups identified 

a number of abiotic (permafrost, landform, bathymetry, 

climatology, traditional ecological knowledge), and biotic 

inventories (rapid biodiversity assays) that were not part of 

the 2004 list but would be particularly valuable for refuges in 

Alaska. Although not shown in table 14, other needs that were 

communicated included spatially explicit layers of fire history, 

future-fire projections, and LANDSAT vegetation mapping. 

None of these was listed in the 2004 document, although 

National Vegetation Classification System (NVSC) data were 

recommended for creating a vegetation map.
Chapter 6 43

Technical Capabilities/Staffing

Technical capacities that must be brought to bear in 

ecological monitoring are diverse and varied. In most cases, 

moving forward without possessing these capacities within 

the I&M workforce or securing a collaboration to otherwise 

access these skill sets can create a bottleneck that dramatically 

slows the productivity of the entire monitoring process. 

These capacities include expertise in statistical analysis, 

Geographic Information Systems (GIS) analysis, remote 

sensing, database management and programming, and the 

disciplinary expertise required to write, review, and implement 

protocols (that is, ‘-ologists’) in addition to the fundamental 

need for administrative support. Disciplinary expertise is 

especially important for resources (for example, glaciers, 

insect identification) for which refuges within an ecoregion 

may not possess specific experience and knowledge. Not all 

positions need to be filled at all sites, but it is desirable that 

the capability be available somewhere. Short-term, intensive 

needs may be met by consultants, especially for statistics, or 

by other agencies (for example, USGS). 

Currently two positions are dedicated to data 

management and analysis in the Alaska NWRs: a biometrician 

in the Regional Office and a database programmer at Kenai 

NWR. In addition, Alaska Maritime NWR is trying to hire 

an individual who specializes in databases. While there are 

also individuals using these skill sets in other parts of the 

refuge system, the current investment in data management 

is lower than the approximately 30 percent of program 

funding dedicated by many ongoing monitoring programs (for 

example, USFS Forest Inventory and Analysis, NPS Inventory 

and Monitoring programs). These resources are needed 

because developing an active constituency and sustaining 

support for monitoring programs involve timely reporting 

of synthesized and interpreted information, which requires 

technical resources. Note that the 30 percent budgeted in most 

programs excludes the initial effort to develop and refine 

primary objectives, monitoring designs, methods used, and 

analysis-support tools. 

Many of these points are recognized by the leadership 

of USFWS and were expressed at two breakout sessions held 

for managers at the Forum on Ecoregional Monitoring for the 

NWRS and other Public Lands in Alaska (appendix 13). 

Rank Overall Group 1 Group 2 Group 3 Group 4

1 High-resolution imagery 

(1,1,1,3)

Abiotic Suite (DEM,

soils, etc.)

High-resolution imagery High-resolution 

imagery

Topographic and 

aerial imagery 

2 Abiotic Suite (1,2,3,3) (Rapid) biodiversity 

assay

(Rapid) biodiversity assay Abiotic (soils, landform, 

permafrost, etc.)

Water

3 Water (2,3,4,4) High-resolution 

imagery

Abiotic Suite (DEM, 

bathymetry, 

climatology)

Hydrology, vegetation 

maps, and rapid 

biodiversity assay

Soils

4 Biodiversity Assay (2,2,3,-) Water quality and 

quantity

Water quality and quantity Human component; 

traditional ecological 

knowledge

Vegetation

Table 14. The top four priorities for inventory needs for National Wildlife Refuges in Alaska, as determined by each of four multidisciplinary, multi-affiliation groups at the (April 2009) Forum on Ecoregional Monitoring. 

[The overall average rank of the four highest-priority inventories appears in the leftmost column]
44 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Chapter 7. Road Map for Developing 

Monitoring Plan

To aid visualization of the road ahead, we consolidate the 

process of developing a monitoring plan into a list of steps, 

both sequential and concurrent, and a rough estimate of the 

time required for each. We also provide a rough draft of a potential monitoring program in broad terms, based on the legal, 

environmental, and managerial context of Alaska NWRs and 

considerations for developing a monitoring program described 

above.

Steps Required to Implement Monitoring

In practice, most broad-scale monitoring programs at 

regional, national, and international scales have required 

about a decade to become fully functional. The many steps or 

activities required to develop such programs and the estimated amount of time required to complete each of those 

activities are listed in table 15. It is clear that the process of 

monitoring program development requires much forethought, 

and continued vigilance to ensure that deadlines are met and 

progress develops as envisioned. Each of the listed activities 

could easily be more fully described by a list of sub-activities 

Activity Typical duration

Begin to hire staff for broad-scale Monitoring Center: Coordinator, Data Manager 4-15 mos

Perform inventories of resources present in management areas (especially within target domains) 1-several yrs

Amalgamate information from existing monitoring programs within the sphere of influence of the target 

domains(s)

6-24 mos

Summarize resources, processes, drivers, and gradients existing within focal area 9-18 mos

Create conceptual models that link prominent resources, processes, structure, and stressors via defined 

interactions/links

6-12 mos

Develop and refine objectives for the Monitoring Center (and other levels, as appropriate) 1-6 mos

Identify more-comprehensive list of potential indicators 1-4 mos

Decide upon method to prioritize indicators; obtain input on priorities from researchers and managers 3-9 mos

Select initial list of indicators to be monitored in short and longer terms (tiered, to accommodate various funding 

levels)

2-6 mos

Write comprehensive monitoring plan covering objectives, conceptual models and all decisions regarding 

indicators

18-36 mos

Hire disciplinary Specialists to lead monitoring program(s) for related indicator(s) 6-15 mos

Develop objectives/questions for each indicator 1-2 mos

Develop sampling design and protocols for each indicator 6-18 mos

Obtain external peer-review of objectives/questions, sampling design, and protocols 6-18 mos

Pilot test methods and protocol and protocol revision 1-4 yrs

Begin full implementation of monitoring 5-7 yrs

Review progress of monitoring for each indicator Every 3-5 yrs

Produce annual reports for indictors Annually

Create synthetic report to summarize, interpret and communicate findings of monitoring; multiple formats may 

be needed to address different audiences

Every 5-7 yrs

Table 15. A roughly sequential list of activities that are typically accomplished in the development of an integrative, long-term 

program of monitoring natural resources across broad spatial scales.
Chapter 7 45

that are required as steps to achieving the completion of that 

activity's overarching objectives. For example, external peer 

review of many of the most-technical intermediate products in 

the process, especially without dedicated funding, can require 

non-trivial amounts of extra time. Although a summing of the 

duration for each activity could provide a 'ballpark' estimate 

for the upper and lower bounds of time required for the entire 

process, two facts complicate estimation of the sum: (a) 

multiple activities can occur simultaneously, thereby lowering the total estimate; and, more commonly, (b) the estimates 

for duration assume that work on the monitoring program is 

both the dominant priority for all staff members and continues 

without interruption in personnel. 

The process of developing a monitoring program is well 

documented by the U.S. NPS I&M program (http://science.

nature.nps.gov/im/monitor/). In addition to many reports with 

useful ideas about all aspects of monitoring, the site provides 

the monitoring plans from all NPS networks including the four 

in Alaska (Arctic Network, ARCN; Central Alaska Network, 

CAKN; Southeast Alaska Network, SEAN; and Southwest 

Alaska Network, SWAN). Good examples of layout and production also include plans from the Greater Yellowstone Network (GRYN) and the Mojave Network (MOJN) (John Gross, 

NPS I&M Program, oral commun., 2010.). Good examples of 

data-management plans include those from the National Capital Network (NCRN), the Southeast Coast Network (SECN), 

and the Southeast Alaska Network (SEAN) (Margaret Beer, 

NPS I&M Program written comm.). All can be found fairly 

easily on the national website. 

Outline of Monitoring Plan

Tables 11 and 12 present one possible version of a multifaceted, multi-scale monitoring program for USFWS refuges 

in Alaska that relies upon a number of key characteristics to 

increase the likelihood of its long-term success. As stated 

previously, this is merely illustrative of what may result 

from an indicator selection process reflecting management 

information needs. The brief notes regarding potential 

temporal and spatial monitoring strategy are not meant to 

underestimate the tremendous amount of work that must 

be invested in determining these. They are merely meant to 

suggest a range of possibilities and to illustrate how they may 

vary with monitoring question.

This plan has several notable features. First, it 

acknowledges that different ecological resources vary on 

different spatial and temporal resolutions, and that their 

dynamics and trend are most logically and efficiently 

monitored organizationally at different extents. Second, it 

accommodates and blends with the wealth of monitoring 

efforts that are already occurring in and adjacent to refuges 

across Alaska; at least some of these efforts may be best 

performed only at local (refuge-specific) extents, from 

biological and analytical standpoints. Third, it allows for 

collaboration with other entities performing ecological 

monitoring within Alaska, and helps fill gaps in things that are 

not already being monitored, thereby creating synergy across 

entities via a discipline-oriented (rather than spatial) GAP 

analysis. Fourth, the suite of metrics and attributes reflects 

the laws and statutes that guide management philosophies 

and actions on refuges of Alaska. Fifth, the suite of indicators 

include numerous monitoring targets that numerous 

constituencies in Alaska and broader publics care about, due 

to their charisma, elevated conservation status, or ability to 

effect dramatic changes on the landscape. This interest and 

‘investment’ in those species’ status and trends may serve as 

another impetus to retain support for the monitoring program. 

Sixth, although the hypothetical plan includes charismatic 

elements, it also includes metrics such as water quality, 

invasive species, land cover, and other abiotic measures. 

Seventh, humans are considered an integral part of the natural 

landscape, and human needs for sustenance and transportation 

are explicitly acknowledged. Finally, the plan considers not 

only contemporary climate change, but a suite of potential 

drivers of resource condition and trend, in a stressor-based 

paradigm, as part of analysis and interpretation (Roux and 

others, 1999; Dubé and Munkittrick, 2001). Although climatic 

influences will be a pervasive and strong driver of ecological 

dynamics for many years to come, long-term monitoring 

must be responsive to all sources that cause variability in the 

condition of that resource.

 It is important to note that although ecosystem function 

is one of the three fundamental aspects of biological diversity 

(other than composition and structure; Noss, 1990; Niemi 

and McDonald, 2004) and will likely increase in importance 

over time due to its intimate connection with provision 

of ecosystem services (for example, clean water, flood 

attenuation, prevention of erosion), it is largely absent from 

table 11. Because ecosystem function is often poorly linked to 

biodiversity (Schwartz and others, 2000; Hector and others, 

2001), monitoring biological diversity with the assumption 

that it will be a surrogate for ecosystem functioning is 

untenable. Thus, although it is comparatively difficult to 

develop measurable attributes as proxies of ecosystem 

function, we suggest further consideration of ecosystemfunction indicators.
46 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Chapter 8. Conclusions

In this document, we have reviewed multiple broadscale ecological monitoring programs and shown that careful 

planning is the foundation of a good monitoring program. 

Because of the complexity and the number of people 

necessarily involved, the planning and design processes 

can take much longer than expected. The refuge system 

in Alaska has taken major steps in this process through 

meetings with staff and the creation of refuge-scale and 

ecoregional conceptual models. Other building blocks 

include existing monitoring conducted by the refuges, other 

branches of USFWS, and other agencies. Some programlevel decisions are being made at the national level, but 

many regional, ecoregional, and refuge-scale decisions will 

have to be made and other steps will be required before 

protocols for monitoring specific indicators are completed. 

These steps include selection of indicators, prioritization 

of alternatives, and developing sampling frames based on 

design considerations that are appropriate for the desired 

results. Despite the challenges, Alaska NWRs are on the path 

to developing an effective ecoregionally based monitoring 

program that will meet information needs at several spatial 

scales and organizational levels. 

Decisions regarding monitoring must be driven by 

carefully articulated objectives, and several tiers of objectives 

must be developed. First, programmatic objectives reflect the 

audience and purpose of the monitoring data, and state what 

the program strives to achieve. These objectives may or may 

not specify particular resources to monitor, but instead guide 

decisions regarding program strategy and structure, such as 

types of questions, spatial scale, and allocation of personnel 

and funds. Monitoring objectives form the second tier of 

objectives. They derive from the programmatic objectives, and 

describe what should be monitored in general terms. Finally, 

measurable objectives (or monitoring questions) specify 

specific indicators and monitored attributes in sufficient detail 

to determine a spatial and temporal survey design, as well 

as sampling methods that will be used. Careful attention to 

objectives insures that the resources allocated to monitoring 

will indeed meet the information needs of the agency.

An important conclusion of this report is that the 

management context of Alaska NWRs, (that is, relevant 

statutes, logistical constraints, potential threats to resources, 

etc.) results in both strategic and tactical monitoring 

needs. Tactical information relates to the effectiveness of 

active management actions to natural resources within the 

ecosystem (for example, habitat restoration, harvest limits 

on game species), whereas strategic information relates 

to the effectiveness of passive protection of ecosystem 

integrity. Tactical information needs can be met with the 

standard adaptive-management approach where indicators are 

specified by the nature and purpose of a management action. 

Strategic information needs, which usually require describing 

ecosystem status and trend, are more difficult to identify and 

are based on current understanding of ecosystem structure, 

composition, and function. Because these two needs require 

different approaches to identifying indicators, and often 

different temporal and spatial scales for trend detection and 

inference, it makes sense to address them separately at every 

stage of program development. Nonetheless, both types of 

monitoring, as well as inventories, will achieve maximum 

utility when they are explicitly tied to management decisions 

and actions, in some way.

 We also emphasize the utility of using hierarchical 

structures throughout the development and implementation 

of monitoring. Hierarchical structures are especially useful 

for an agency with vast landholdings that are embedded in a 

matrix of other federal lands and are facing a variety of threats 

acting over a range of time frames. The result is a hierarchy 

of information needs in time (strategic, tactical) and space 

(international, regional, ecoregional, refuge; table 1). Coarser 

information is often sufficient to meet information needs at 

larger spatial scales and longer time frames, while finer detail 

is more likely required at smaller spatial scales and more 

immediately. Moreover, protected resources are organized 

on the landscape according to a hierarchy of ecoregional 

delineations. The hierarchy of needs and spatial structure 

can be appropriately met by hierarchical organization of 

objectives, conceptual models, and program structure. 

The management context of Alaska NWRs requires that 

several challenges be met throughout the development of a 

monitoring program. Perhaps the most difficult challenge 

is to maintain enough flexibility to both address strategic 

and tactical needs, yet also address unforeseen future needs. 

Flexibility is extremely difficult to sustain, given the rigidity 

and uncertainty of annual federal budgets. Moreover, 

monitoring decisions usually require an arduous process of 

negotiation and compromise among agency staff and are 

therefore not easy to alter. Another important challenge is to 

achieve collaboration among refuges and with other agencies 

to accomplish monitoring goals. Collaboration can be difficult, 

especially among agencies, because different entities are 

likely to have different objectives for monitoring the same 

resource, as a function of different mandates and other factors. 

Consequently, attributes and sample frames monitored by 

one agency may be inadequate to meet the information needs 

of another agency. Nevertheless, the potential savings in 

staff time and funds means that exploring opportunities for 

collaboration is worthwhile. A final challenge is to realize that 

the information needs are so great and the costs of acquiring 

it so high, that it will not be possible to monitor anything in 

great detail. It is important to remember that the monitoring 

program is meant primarily to indicate change and thereby 

trigger a management action, which might include research 

efforts to better understand what is happening. 
Acknowledgments 47

Effective data management is required to produce highquality data that is appropriately analyzed and effectively 

communicated. Because data management pervades the 

monitoring process, planning for and funding these activities 

are crucial for a successful monitoring program. It is 

sometimes hard to accept that the costs of monitoring are 

greater than the costs of simply collecting data, but unless 

the data are reported and archived for future uses, the effort 

to collect them was wasted. These costs are not trivial; 

they can constitute from one-fifth to fully one-third of the 

entire monitoring budget. However, the rise of ecoregional 

monitoring represents a landmark opportunity for a sea change 

in USFWS monitoring efforts across Alaska, wherein the 

amount of information learned and the number of individuals 

better informed can be maximized at every opportunity.

Despite the complexity of the process and inevitable 

challenges, staff members of the Alaska NWRs have an 

invaluable opportunity to use lessons from the experiences of 

other agencies to develop a successful monitoring program. 

The required steps begin with hiring leadership staff and 

developing programmatic and monitoring objectives. 

Choosing and prioritizing indicators and attributes with the 

help of conceptual models are the next steps, followed by 

developing protocols and the data-management infrastructure 

to ensure that results are produced and communicated. Along 

the way, documentation of plans, decisions, and protocols 

will enable internal and external scientific peer-review and 

review by Service management staff, thereby ensuring that all 

scientific and management implications have been considered. 

The benefits of investing in the careful, thorough development 

of a monitoring program include creation of an endeavor 

that persists through time while providing status-and-trends 

information to support the agency decision-making process. 

While this process must integrate multiple social and scientific 

considerations to evaluate the need for and consequences of 

management actions, adequate information regarding resource 

condition is indispensible. 

Acknowledgments

This report is a product of a Science Support Partnership 

(SSP) project involving collaboration between the Alaska 

Regional office of the U.S. Fish and Wildlife Service 

(USFWS) and the U.S. Geological Survey. This project was 

originally conceived and developed by Karen Oakley (USGSASC) and Eric Taylor (USFWS). Page Spencer (USFWS 

Acting Regional Refuge Biologist, 2006), Joel Reynolds 

(Regional Biometrician), and Danielle Jerry (USFWS Chief 

of Realty and Natural Resources) hosted a discussion of 

the SSP proposal at the 2006 Refuge Biologist Workshop, 

which helped refine the scope of the project. This report 

reflects the contributions of many individuals to the ”Forum 

on Ecoregional Monitoring for the National Wildlife Refuge 

System and Other Public Lands Across Alaska” held in 

Anchorage and Girdwood during April 14-16, 2009. 

Staff of the USFWS Alaska Regional Office, including 

Danielle Jerry, Joel Reynolds, and John Martin, helped to 

plan and implement the meeting. Patrick Lieske provided 

substantial logistical assistance. 

Speakers featured on Day 1 of the Forum, who 

introduced the essential aspects of existing long-term 

monitoring programs, included Donald McLennan 

(Parks Canada Agency), John Gross (NPS), Michael Gill 

(Circumpolar Biodiversity Monitoring Program, Environment 

Canada), Tara Barrett (USFS-FIA), John Morton (Kenai 

NWR, USFWS), Christian Torgersen (USGS Forest and 

Rangeland Ecosystem Science Center), Tony Olsen (EPA), 

Terry Chapin (University of Alaska, Fairbanks), Kelly 

Redmond (Desert Research Institute), Melinda Knutson 

(USFWS), and WilliamThompson (NPS I&M). Furthermore, 

Torre Jorgenson (Alaska Ecoscience) provided an overview 

of effects of contemporary climate change that have been 

predicted and already evidenced.

Staff of the U.S. Geological Survey Alaska Science 

Center (USGS-ASC), including Karen Oakley, Anthony 

DeGange, Carl Markon, and Leslie Holland-Bartels provided 

valuable leadership support of the Forum. Cheri Yoesting, 

Julie Hammonds, and Christy Severtson of USGS-ASC were 

instrumental in facilitating various aspects of the Forum, 

including the web page. 

Facilitation of the four ecoregional work groups at the 

Forum was provided by Catherine Curby, Nancy Swanton, 

Warren Keogh, Dom Watts, and Melinda Knutson. Cynthia 

Bouck, John Martin, Kelly Walton, Steven Talbot, and Patrick 

Lieske served as Recorders. 

Many of the state’s USFWS Refuge Managers and 

other regional and leadership staff attended the April 2009 

meeting. This presence represents a significant commitment 

by the refuges and USFWS to actively pursue coordinated 

approaches to performing broad-scale monitoring in a costeffective and meaningful manner. USFWS leadership included 

Todd Logan, Michael Boylan, Robert Adamcik, Melinda 

Knutson, and Andrew Loranger.

Finally, subsequent to the (April 2009) Forum, numerous 

individuals were instrumental in providing information for 

this document, and edits to information contained herein. 

In addition, numerous individuals from USFWS, NPS, and 

each of the other long-term monitoring programs featured 

in appendixes 3-12 provided information for, or editing 

of, those appendices. Those individuals included James 

Lawler, Michael Shephard, Brendan Moynahan, and Maggie 

MacCluskie (NPS I&M). 
48 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

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52 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

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Appendix 1 53

Appendix 1. Summary of National Park Service Inventory and Monitoring 

Program 

(Based on presentation by John Gross at the Forum on Ecoregional Monitoring for the NWRS 

and other Public Lands across Alaska [http://Alaska.usgs.gov/science/biology/ecomonitoring], 

Fancy and others, 2009, and the program website [http://science.nature.nps.gov/im/monitor])

The mission of the National Park Service is “to promote and regulate the use of national parks ... 

which purpose is to conserve the scenery and the natural and historic objects and the wild life 

therein and to provide for the enjoyment of the same in such manner and by such means as will 

leave them unimpaired for the enjoyment of future generations.” National Park Service Organic 

Act, 16 U.S.C.1. 

Agency Mission

The National Park Service is a nationally distributed collection of fairly autonomous park units, 

having unique specific purposes stated in the establishing legislation for each. 

Agency Structure

Objectives for Monitoring

• Determine the status and trends in selected indicators of the condition of park ecosystems 

to allow managers to make better informed decisions and to work more effectively with 

other agencies and individuals for the benefit of park resources. 

• Provide early warning of abnormal conditions of selected resources to help develop 

effective mitigation measures and reduce costs of management.

• Provide data to better understand the dynamic nature and condition of park ecosystems 

and to provide reference points for comparison with other, altered environments. 

• Provide data to meet certain legal and congressional mandates related to natural resource 

protection and visitor enjoyment. 

• Provide a means of measuring progress toward performance goals. 

The parks with significant natural (as opposed to cultural) resources are grouped into 32 

geographically related networks of parks to facilitate collaboration, information sharing and 

economies of scale. Each network shares core funding and a professional staff to design and 

implement the monitoring program. Profession staff includes a network coordinator, data 

manager, quantitative ecologist, and sometimes GIS support. A national staff sets the overall 

program objectives (quoted above); sets standards for monitoring plan content and the timeline 

for completion; sets standards for protocol content; and evaluates programs. National program 

direction is facilitated by regional coordinators. Specific monitoring objectives and decisions 

about indicators and attributes are set at the park level.

Monitoring Program Administrative Structure

The program strives to identify a small set of information-rich attributes that will indicate the 

‘health’ of park resources and to provide early warning of conditions that require management 

Monitoring Program Approach
54 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

action. These ‘Vital Signs’ are defined as a subset of all physical, chemical and biological 

elements and processes of park ecosystems and the information obtained from them is expected 

to have application for management decisions, research, education and promoting public 

understanding. 

Pillars of the I&M effort include: thorough assessment of existing resources and previous 

monitoring efforts, creation of conceptual models that describe ecosystem dynamics (Gross 

2003), creation of protocols that facilitate repeatability of monitoring through time and through 

staff turnover (Oakley and others, 2003), creation and maintenance of databases that archive 

collected data that have been carefully quality-checked, rapid and regular availability of 

monitoring results through various communication avenues (for example, online, annual reports, 

podcasts, summary briefs for managers), and connection to management (Fancy and others, 

2009). 

National parks are managed to promote visitor enjoyment and to protect natural resources from 

damage. Consequently, active management to achieve biological outcomes is minimal. 

Monitoring objectives reflect this situation by aiming to provide understanding of ecosystem 

function and early warning of changes rather than having an adaptive management role. The goal 

is to provide managers with the knowledge necessary to respond effectively when needed, and to 

alert them to the need as early as possible. Predictions of where to expect change, and therefore 

where to invest monitoring resources, are based on ecosystem conceptual models. 

Linkage between Monitoring and Management

Networks were given a fair amount of autonomy to determine their structure, especially 

regarding whether network staff would be full time network employees or part time network and 

part time park employees. The table below describes the most common situation.

Administrative Location of Decisions

 

ADMINISTRATIVE LEVEL

FUNCTION PARK NETWORK NATIONAL

General Guidance X

Detailed Planning

 Specific Objectives X

 Attribute Selection X

 Survey Design X

 Choice of Methods X

 Data Management Plan X

Program Implementation

 Data Collection X X

 Data Management X

 Data Analysis X

 Reporting/Dissemination X

Program Administration

 Program Revision X

 Funding Allocation X X
Appendix 1 55

The primary audience of monitoring results is at the park level: park managers and planners, 

natural resource specialists, interpreters and scientists working at the park level. The secondary 

audience is the public, Congress and the Office of Management and Budget. 

Audience for Monitoring Results

Fancy, S.G., Gross, J.E., and Carter, S.L., 2009, Monitoring the condition of natural resources in 

U.S. national parks: Environmental Monitoring and Assessment, v. 151, p. 61–174. 

References Cited

Gross, J.E., 2003, Developing conceptual models for monitoring programs, in Developing 

Conceptual Models of Relevant Ecosystem Components: Washington, D.C., National Park 

Service website, accessed October 26, 2010 at 

http://science.nature.nps.gov/im/monitor/ConceptualModels.cfm. 

Oakley, K.L., Thomas, L.P., and Fancy, S.G., 2003, Guidelines for long-term monitoring 

protocols: Wildlife Society Bulletin, v. 31, p. 1000–1003. 
56 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Appendix 2. Summary of Inventory and Monitoring Program of Parks 

Canada Agency

(Based on presentation by Don McLennan at Ecoregional Monitoring for the NWRS and other 

Public Lands across Alaska [http://Alaska.usgs.gov/science/biology/ecomonitoring] and the 

program website [http://www.pc.gc.ca/progs/np-pn/])

“On behalf of the people of Canada we protect and present nationally significant examples of 

Canada’s natural and heritage, and foster public understanding, appreciation and enjoyment in 

ways that ensure the ecological and commemorative integrity of these places for present and 

future generations.”

Agency Mission

Agency

Parks Canada Agency consists of 42 national parks and national park reserves, which have been 

grouped into six bioregions (Pacific, Montane, Interior Plains, Great Lakes, Atlantic-Quebec, and 

Northern and Arctic groups).

Structure

The objective of the monitoring program is to measure changes in ecological integrity of parks: 

Objectives for Monitoring

• to assess the effectiveness of management

• to increase the understanding of ecosystem change

• to find areas where future research is needed

• to serve as ‘ecological baselines’ to which non-protected areas can be compared.

Ecological integrity is a condition that is determined to be characteristic of its natural region and 

likely to persist, including abiotic components and the composition and abundance of native 

species and biological communities, rates of change and supporting processes. 

The National Ecological Integrity Monitoring Committee provides general guidance and 

evaluates park monitoring plans. 

Monitoring Program Administrative Structure

Two levels of questions drive the monitoring approach: 

Monitoring Program Approach

What is the state of park ecological integrity? 

How do our management actions affect park ecological integrity? 

To answer these questions, the program strives to develop core indicators that are relevant to 

parks but can be summarized regionally and nationally. Indicators of ecological integrity are 

ecosystems (for example, forest, tundra) within bioregions. Measures (attributes) are grouped by 

biodiversity, ecosystem functions and stressors, and are collected at the spatial scales of plots and 

remote sensing. Landscape-scale metrics of ecological integrity in development for arctic 

national parks in Canada include:
Appendix 2 57

Tundra ecosystems

• Change in area of tundra ecotypes 

• Change in tundra vegetation biomass/Leaf Area Index 

• Change in tundra growing season length 

• Change in tundra snow phenology 

Freshwater ecosystems

• Change in lake ice phenology 

• Change in river ice phenology 

• Change in lake surface area 

Wetlands ecosystems

• Change in area of wetland ecotypes 

• Change in wetland physiognomy/structure 

• Change in wetland vegetation biomass/LAI 

• Change in wetland snow phenology 

Coastal ecosystems

• Change in area of coastal ecotypes 

• Change in biomass/LAI of coastal ecotypes 

• Change in sea ice phenology 

• Change in rate of shoreline erosion 

• Change in sea surface temperatures 

Forest ecosystems

• Change in area of forest ecotypes 

• Change in forest vegetation biomass/LAI 

• Change in forest growing season length 

• Change in forest snow phenology 

Results are communicated with simple graphics that indicate whether a given attribute can be 

described as having impaired, fair, or good condition. The process of setting thresholds to define 

levels of condition is also the process of setting management goals and indicating management 

success. These are used to assess fulfillment of management objectives through park 

management plans which are reviewed and updated every 5 years.

Linkage between Monitoring and Management
58 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Administrative Location of Decisions

ADMINISTRATIVE LEVEL

FUNCTION PARK BIOREGIONAL NATIONAL

General Guidance X

Detailed Planning

 Specific Objectives X X X

 Attribute Selection X

 Survey Design X

 Choice of Methods X

 Data Management Plan X

Program Implementation

 Data Collection X

 Data Management X

 Data Analysis X

 Reporting/Dissemination X X

Program Administration

 Program Revision X

 Funding Allocation X

The audience for monitoring results is park management and the public through State of the Park 

Reports and visitor education.

Audience for Monitoring Results
Appendix 3 59

Appendix 3. Summary of Forest Inventory and Assessment Program 

(Based on presentation by Tara Barrett at the Forum on Ecoregional Monitoring for the NWRS 

and other Public Lands across Alaska [http://Alaska.usgs.gov/science/biology/ecomonitoring], 

USDA Forest Service (2007), and the program website [http://fia.fs.fed.us])

The mission of the U.S. Forest Service is to “sustain that health, diversity and productivity of the 

National’s forests and grasslands to meet the needs of present and future generations.” 

Agency Mission

The U.S. Forest Service is composed of nationally distributed national forest units. 

Agency Structure

The fundamental objective of the program is to “make and keep current a comprehensive 

inventory and analysis of the present and prospective conditions of and requirements for the 

renewable resources of the forest and rangelands of the United States.” Recent legislation further 

instructed the FIA program to establish an enhanced program to inventory and analyze public 

and private forests and their resources including 

Objectives for Monitoring

• an annual inventory of each State every year

• a 5-year report for each State

• national standards and definitions for reporting 

• provisions to ensure protection of private-property rights

• a process for employing remote sensing, global positioning systems, and other advanced 

technologies. 

The monitoring is directed and funded nationally but it is implemented operationally at the 

regional level. Regions are composed of several states. Data are compiled on an annual basis and 

made available on line within 6 months of collection. Complete State-level analytical reports are 

completed every 5 years. Experts in various technical areas who develop methods and 

approaches needed to implement the program form “Technical Bands”.

Monitoring Program Administrative Structure
60 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

The attributes described under monitoring objectives are measured in a rotating panel design of 

10 percent, 15 percent or 20 percent of plots per year, depending on region, of a systematic grid 

of plots (Bechtold and Patterson 2005). Special designs are being developed for interior Alaska, 

the Caribbean and Pacific Islands. The design for attribute selection is hierarchical with a 

consistent core set of field measurements collected the same way across all U.S. forested lands, 

paid for with federal funding. Regions may add additional attributes to be paid for with federal 

and shared funding. Other attributes may be added locally to address local needs and provide 

data for special studies, to be paid for by clients. Core attributes measured or derived for every 

plot include: 

Monitoring Program Approach

• above-ground carbon

• fire effects, post-fire succession

• stand age, species composition, stand structure (height, layering) 

• species distribution, size, and health of trees 

• total tree growth, regeneration, mortality, and harvest 

• tree volume and biomass; wood production and utilization rates by various products 

• tree diseases, insects, and other damages

• invasive plants 

• soils (O’Neill and others, 2005), understory vegetation (Schulz and others, 2009), tree 

crown conditions (Zarnoch and others, 2004, Schomaker and others, 2007), coarse woody 

debris (Woodall and Monleon 2007), and lichen community composition (for example, 

Jovan and McCune 2005) on a 1/16th subsample of monitoring plots (that is, on all Phase 

3 plots). 

Summary statistics calculated by state or nationally include:

• forest area and location, by owner, by reserve status, and by forest type 

Several other additional indicators exist:

• Harvest and utilization: Mill survey of each state occurs every 5 to 10 years. 

• National woodland owner survey: Information collected includes reasons for owning 

forest, how land is used and managed, concerns and issues, sources of information, future 

intentions, and demographics. 

• Ozone damage: This is a special set of plots across the U.S. used to monitor ozone 

damage of vegetation – there are only 4 plots in Alaska and no damage has been found in 

those plots. 

Most forests of the United States are actively managed to provide a supply of forest products (the 

major exception being national parks and designated Wilderness). The data from this monitoring 

program informs public and private forest managers, as well as state and federal policy makers, 

about the statewide and national condition of forests as a basis for decisions regarding harvest 

levels, fire management, and other issues.

Linkage between Monitoring and Management
Appendix 3 61

 

Administrative Location of Decisions

ADMINISTRATIVE LEVEL

FUNCTION LOCAL REGIONAL NATIONAL

General Guidance X

Detailed Planning

 Specific Objectives X X X

 Attribute Selection X X X

 Survey Design X

 Choice of Methods X

 Data Management Plan X

Program Implementation

 Data Collection X

 Data Management X

 Data Analysis X

 Reporting/Dissemination X

Program Administration

 Program Revision X

 Funding Allocation X

The primary audiences for monitoring results are national and state policy makers with 

responsibility for forest management, and Congress.

Audience for Monitoring Results

Bechtold, W.A., and Patterson, P.L., eds., 2005, The enhanced Forest Inventory and Analysis 

program—national sampling design and estimation procedures: Asheville, N.C., U.S. 

Department of Agriculture, Forest Service, Southern Research Stations, General Technical 

Report SRS-80, 85 pp. 

References Cited

Jovan, S., and McCune, B., 2005, Air-quality bioindication in the greater central valley of 

California, with epiphytic macrolichen communities: Ecological applications, v. 15, p. 1712–

1726. 

O’Neill, K.P., Amacher, M.C., Perry, C.H., 2005, Soils as an indicator of forest health—a guide 

to the collection, analysis, and interpretation of soil indicator data in the Forest Inventory and 

Analysis program: St. Paul, Minn., U.S. Department of Agriculture, Forest Service, North 

Central Research Station, General Technical Report NC-258, 53 p. 

Schomaker, M.E., Zarnoch, S.J., Bechtold, W.A., Latelle, D.J., Burkman, W.G., and Cox, S.M.,

2007, Crown Condition Classification—A Guide to Data Collection and Analysis: Asheville, 

N.C., U.S. Department of Agriculture, Forest Service, Southern Research Station, General

Technical Report SRS-102, 78 p.

Schulz, B.K., Bechtold, W.A., and Zarnoch, S.J., 2009, Sampling and estimation procedures for 

the vegetation diversity and structure indicator: Portland, Oreg., U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research Station, General Technical Report 

PNW-GTR-781. 
62 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

U.S. Department of Agriculture, 2007, Forest inventory and analysis strategic plan—a history of 

success, a dynamic future: Washington, D.C., U.S. Department of Agriculture, Forest Service 

Report FS-865. 

Woodall, C.W., and Monleon, V.J., 2007, Sampling protocol, estimation, and analysis 

procedures for the down woody materials indicator of the FIA program: Washington, D.C., 

U.S. Department of Agriculture, Forest Service, Northern Research Station, General Technical 

Report NRS-22. 

Zarnoch, S.J., Bechtold, W.A., and Stolte, K.W., 2004, Using crown condition variables as 

indicators of forest health: Canadian Journal of Forest Research, v. 34, p. 1057–1070. 
Appendix 4 63

Appendix 4. Summary of National Aquatic Resources Surveys 

(Based on presentation by Tony Olsen at Forum on Ecoregional Monitoring for NWRS and other 

Public Lands across Alaska [http://Alaska.usgs.gov/science/biology/ecomonitoring], and the 

program website [http://www.epa.gov/owow/monitoring/nationalsurveys.html])

The mission of the Environmental Protection Agency (EPA) is “to protect human health and to 

safeguard the environment – air, water and land – upon which life depends.” EPA leads the 

nation’s environmental science, research, education and assessment efforts. 

Agency Mission

The EPA consists of a national office, 10 regional offices, and 12 laboratories. 

Agency Structure

The National Aquatic Resources Surveys (NARS) is the institutionalized monitoring program 

resulting from the monitoring tools developed by the Environmental Monitoring and Assessment 

Program (EMAP). The objectives of the program are to “report on core indicators of water 

condition using standardized field and laboratory methods.” Specific questions include 

Objectives for Monitoring

• What is the extent of waters that support healthy ecosystems, recreation and fish 

consumption? 

• How widespread are water quality problems?

• Is water quality improving?

• Are we investing in restoration and protection wisely? 

EPA provides federal funds to states to monitor the condition of waters across the nation. 

Funding is contingent on states using a statistically valid survey design, that they use at least 

some of an identified set of core attributes, and that they achieve a minimum level of statistical 

confidence in the results. States are allowed to use national or state methods, and use any 

temporal sampling frame as long as the results can be aggregated for a state-scale survey. States 

report results to EPA; EPA will create a national summary. EPA regional offices provide 

technical assistance to states. EPA recognizes that the unique nature of the land and waters in 

Alaska mean that more time may be required to meet program requirements.

Monitoring Program Administrative Structure

The EMAP program pioneered the development of General Randomized Tesselation Stratified 

sampling (GRTS) for establishing spatially balanced random sample frames for monitoring. 

Monitoring attributes measured at GRTS-selected plots were developed by EMAP to effectively 

and efficiently describe water quality. Core indicators are expected to be measured at each plot 

over the long term; supplemental data may be collected short term to meet special needs; 

research indicator studies may also be conducted to pilot new indicators. 

Monitoring Program Approach
64 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Results are presented in simple graphics describing whether individual attributes are good, fair or 

poor by region. Producing these summaries requires that monitoring objectives for attributes be 

stated in precise quantitative terms, and thresholds must be established to categorize results into 

good, fair or poor. Therefore, there is a clear assessment about whether management of the 

nation’s waters is effective in protecting water quality.

Linkage between Monitoring and Management

 

Administrative Location of Decisions

ADMINISTRATIVE LEVEL

FUNCTION STATE/TRIBES REGIONAL NATIONAL

General Guidance X

Detailed Planning

 Specific Objectives X X

 Attribute Selection X X

 Survey Design X

 Choice of Methods X

 Data Management Plan X

Program Implementation

 Data Collection X

 Data Management X

 Data Analysis X X

 Reporting/Dissemination X

Program Administration

 Program Revision X

 Funding Allocation X

The primary audiences for monitoring results describing the conditions of the nation’s waters are 

the public and Congress. Results also measure the performance of EPA protection and 

restoration programs. 

Audience for Monitoring Results
Appendix 5 65

Appendix 5. Summary of United Kingdom Countryside Survey 

(Based on presentation by Christian Torgersen at Forum on Ecoregional Monitoring for NWRS 

and other Public Lands across Alaska [http://Alaska.usgs.gov/science/biology/ecomonitoring], 

Kugler and others, (2009), and the program website [http://www.countrysidesurvey.org.uk])

Agency Mission

“The Natural Environment Research Council delivers independent research, survey, training and 

knowledge transfer in the environmental sciences, to advance knowledge of planet Earth as a 

complex, interacting system. Our vision is to advance knowledge and understanding of the Earth 

and its environments to help secure a sustainable future for the planet and its people.” 

The NERC national office funds research in universities and its own centers. Four centers are 

owned by NERC and five are collaborative with universities or other institutions. 

Agency Structure

The mission of the Countryside Survey is to provide scientifically reliable evidence about the 

state or ‘health’ of the United Kingdom’s countryside and to identify change and rate of change 

in resources. Specific objectives change with every survey and reflect the resources available. In 

2007, the objectives included: 

Objectives for Monitoring

• To record and report on the amount and condition of widespread habitats, landscape 

features, vegetation, land cover, soils and freshwaters. 

• To assess changes in the countryside and improve our understanding of the causes and 

processes of change, by comparison with data from earlier surveys.

• To collect, store and analyze data in ways that optimize the integration of Countryside 

Survey data through time and make it compatible with other data sources. 

• To provide access to data and interpreted results that underpin a range of policy and 

science needs for major environmental zones and landscape types in the UK, Great 

Britain, England, Scotland, Wales and Northern Ireland. 

• To contribute to the development of an integrated assessment of the drivers and pressures 

of change and better understand their effects on the UK countryside and their 

implications for ecosystem goods and services. 

The Countryside Survey is conducted by the Natural Environment and Research Council’s 

Center for Ecology and Hydrology with funding from NERC and a partnership of other 

government agencies, led by the Department for Environment, Food and Rural Affairs. The 

project is divided into Work Packages, which are managed and undertaken by highly trained 

teams. Work Packages address such topics as Landcover mapping, soils, reporting, filed surveys, 

informatics, etc. Surveys have been conducted in 1978, 1984, 1990, 1998, 2000 and 2007. 

Monitoring Program Administrative Structure
66 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Surveys consist of a national landcover map based on remote sensing plus a random sample of a 

systematic grid of 1-km squares distributed across all non-urban landscapes and stratified by 

habitat type. Each 1-km square is mapped according to broadly defined priority habitats, linear, 

and point features. Multiple subsamples are taken to describe vegetation, streams, pond and soils. 

Plots are documented with georeferenced photographs. 

Monitoring Program Approach

The program reports percentage change from the 1978 baseline for attributes by habitat type as a 

means to inform government policy-makers and the public regarding biodiversity, natural 

environment, sustainable agriculture, environmental stewardship, water resources, sustainable 

forestry, soil protection, urban development, air quality and climate change. 

Linkage between Monitoring and Management

Administrative Location of Decisions

 

ADMINSTRATIVE LEVEL

FUNCTION LOCAL NATIONAL

General Guidance X

Detailed Planning

 Specific Objectives X

 Attribute Selection X

 Survey Design X

 Choice of Methods X

 Data Management Plan X

Program Implementation

 Data Collection X

 Data Management X

 Data Analysis X

 Reporting/Dissemination X

Program Administration

 Program Revision X

 Funding Allocation X

The primary audience is policy makers in the governments of Great Britain, and the public. 

Audience for Monitoring Results

Kugler, T.A., Torgersen, C.E., Benjamin, S.P., Gelfenbaum, G.R., Woodward, A., Torregrosa, 

A., and Fuentes, T., 2009, Integrated Landscape Monitoring: Lessons Learned from Four 

National Programs. Unpublished manuscript. 

Reference Cited
Appendix 6 67

Appendix 6. Summary of Circumpolar Biodiversity Monitoring Program 

(Based on presentation by Mike Gill at Forum on Ecoregional Monitoring for NWRS and other 

Public Lands across Alaska [http://Alaska.usgs.gov/science/biology/ecomonitoring], and the 

program website [http://cbmp.arcticportal.org/])

The Arctic Council was formed by the Ottawa Declaration of 1996 to create a “high level 

intergovernmental forum to provide a means for promoting cooperation, coordination and 

interaction among Arctic states, with the involvement of Arctic Indigenous communities and 

other Arctic inhabitants on common Arctic issues, in particular issues of sustainable 

development and environmental protection in the Arctic.” 

Agency Mission

The Arctic Council includes Working Groups on various topics, including Conservation of 

Arctic Flora and Fauna (CAFF), which are responsible for executing the programs and policies 

mandated by Arctic Council Ministers. The Working Groups have supporting scientific and 

technical Expert Groups. 

Agency Structure

The Circumpolar Biodiversity Monitoring Program (CMBP) was initiated by the CAFF working 

group of the Arctic Council. The mission of CBMP is “to facilitate the conservation of biological 

diversity in the Arctic and the sustainable use of the region’s natural resources by:

Objectives for Monitoring

• harmonizing and enhancing Arctic monitoring efforts, thereby improving our ability to 

detect and understand significant trends, and 

• reporting to and communicating with both key decision makers and stakeholders, thereby 

enabling the effective conservation and adaptation responses to changes in Arctic 

biodiversity. 

Fundamentally, the goal is to build a collaborative framework for Arctic biodiversity monitoring. 

The program does not administer monitoring. 

Monitoring Program Administrative Structure

CBMP takes an ecosystem-based approach to aggregating monitoring data by integrating 

information on land, water and living resources in a geographic region. The CBMP is 

incorporating the ecosystem-based approach primarily through the establishment of five 

integrated, cross-disciplinary Expert Monitoring Groups representing the Arctic’s major systems: 

marine, freshwater, coastal, terrestrial fauna and terrestrial vegetation. These monitoring groups 

are supported by the coordination of a “network of networks”, drawing on existing species, 

habitat and site-based monitoring networks. The CBMP is assuming the role of coordinator for 

the networks by supporting monitoring standardization across networks and providing valueadded services in the areas of data management, communications, reporting and decisionmaking. 

Monitoring Program Approach
68 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

The primary linkage with management is through providing information to the Arctic Council. 

Linkage between Monitoring and Management

Administrative Location of Decisions

 

ADMINISTRATIVE LEVEL

FUNCTION LOCAL NATIONAL ARCTIC-WIDE

General Guidance X

Detailed Planning

 Specific Objectives X

 Attribute Selection X X

 Survey Design X

 Choice of Methods X X

 Data Management Plan X

Program Implementation

 Data Collection X

 Data Management X X

 Data Analysis X X

 Reporting/Dissemination X X

Program Administration

 Program Revision X

 Funding Allocation X

Audiences include members of Arctic Council governments, Permanent Participants, local Arctic 

residents, other global and regional shareholders with the goal of enabling policy-making 

decisions. 

Audience for Monitoring Results
Appendix 7 69

Appendix 7. Summary of Environmental Monitoring and Assessment 

Network 

(EMAN; based on presentation by Christian Torgersen at Forum on Ecoregional Monitoring for 

NWRS and other Public Lands across Alaska 

[http://Alaska.usgs.gov/science/biology/ecomonitoring] and the program website [http://emanrese.ca/eman/])

The mission of Environment Canada is “to preserve and enhance the quality of the natural 

environment; conserve Canada’s renewable resources’ conserve and protect Canada’s water 

resources; forecast weather and environmental changes; enforce rules relating to boundary 

waters; and coordinate environmental policies and programs for the federal government.” 

Agency Mission

Environment Canada has a national office and 100 community offices. 

Agency Structure

EMAN’s main role is one of coordination, as it does not have the resources to operate its own 

sites or fund monitoring and research. EMAN must rely on information and cooperation from 

other agencies, in order to better deliver information to decision-makers, demonstrate the 

relevance of ecosystem monitoring and maintain a range of long-term integrated monitoring 

sites. 

Objectives for Monitoring

EMAN was established with the following four objectives: 

• to provide a national perspective on how Canadian ecosystem are being affected by 

multitude of stresses on the environment; 

• to provide scientifically defensible rationales for pollution control and resource 

management policies; 

• to evaluate and report to Canadians on the effectiveness of resources management 

policies; and, 

• to identify new environmental issues at the earliest possible stage.

The program consists of a national Coordinating Office and seven regional leaders who are 

responsible for day-to-day organizational and scientific issues related to EMAN sites in their 

region. 

Monitoring Program Administrative Structure

As EMAN is not financially able to provide funding for monitoring and research, it must provide 

some other benefits for its partners in order to encourage participation in the network. EMAN 

does this through the development of products, services and programs that aid in ecological 

monitoring and assessment. These include monitoring protocols, metadata and databases, an 

annual national science meeting, early warning reporting and the coordination of two 

community-based monitoring programs. 

Monitoring Program Approach
70 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

EMAN strives to support effective management decisions and policy by providing coordinated 

reporting on environmental conditions at the national scale. 

Linkage between Monitoring and Management

Administrative Location of Decisions

 

ADMINISTRATIVE LEVEL

FUNCTION SITE NATIONAL

General Guidance X

Detailed Planning

 Specific Objectives X

 Attribute Selection X X

 Survey Design X

 Choice of Methods X

 Data Management Plan X

Program Implementation

 Data Collection X

 Data Management X

 Data Analysis X X

 Reporting/Dissemination X X

Program Administration

 Program Revision X

 Funding Allocation NA

The primary audiences for program information are the federal Minister of the Environment, the 

Canadian public and EMAN partners. 

Audience for Monitoring Results
Appendix 8 71

Appendix 8. Example Criteria and Weights for Ranking Indicators and 

Attributes (from Fancy and others, 2009)

Criterion 1: Management Significance (Weight – 40 percent) 

A useful ecological indicator must produce results that are clearly understood and 

accepted by park managers, other policy makers, research scientists, and the general public, all of 

whom are able to recognize the implications of the indicator’s results for protecting and 

managing the park’s natural resources. Ultimately, an indicator is useful only if it can provide 

information to support a management decision (including decisions by other agencies and 

organizations that benefit park resources) or to quantify the success of past decisions, For 

example, this may happen if:

• there is an obvious, direct application of the data to a key management decision, or for 

evaluating the effectiveness of past management decisions

• the measurements will produce results that are clearly understood and accepted by park 

managers, other policy makers, research scientists, and the general public, all of whom 

should be able to recognize the implications of the results for protecting and managing 

the park’s natural resources

• monitoring results are likely to provide early warning of resource impairment, and will 

save park resources and money if a problem is discovered early 

• in cases where data will be used primarily to influence external decisions, the decisions 

will affect key resources in the park, and there is a great potential for the park to 

influence the external decisions

• data are of high interest to the public 

• for species-level monitoring, involves species that are harvested, endemic, alien, species 

of special interest, or are threatened or endangered

• there is an obvious, direct application of the data to performance goals 

• contributes to increased understanding that ultimately leads to better management 

Criterion 2: Ecological Significance (Weight – 40 percent)

• there is a strong, defensible linkage between the indicator and the ecological function or 

critical resource it is intended to represent

• the resource being represented by the indicator has high ecological importance based on 

the conceptual model of the system and the supporting ecological literature 

• the indicator characterizes the state of unmeasured structural and compositional resources 

and system processes

• the indicator provides early warning of undesirable changes to important resources. It can 

signify an impending change in the ecological system

• the indicator reflects the functional status of one or more key ecosystem processes or the 

status of ecosystem properties that are clearly related to these ecosystem processes. 

[Note: replace the term ecosystem with landscape or population, as appropriate.] 

• the indicator reflects the capacity of key ecosystem processes to resist or recover from 

change induced by exposure to natural disturbances and/or anthropogenic stressors 
72 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Criterion 3: Legal/Policy Mandate (Weight – 20 percent) 

This criterion provides additional weight to a potential vital sign if a park is directed to 

monitor specific resources because of some binding legal or Congressional mandate, such as 

specific legislation and executive orders, or park enabling legislation. 

Fancy, S.G., Gross, J.E., and Carter, S.L., 2009, Monitoring the condition of natural resources in 

U.S. national parks: Environmental Monitoring and Assessment, v. 151, p. 161–174.

Reference Cited
Appendix 9 73

Appendix 9. Ecological Monitoring Across Refuges

Alaska Department of Fish & Game

Much of the monitoring of large-bodied mammals occurring in Alaskan NWRs is 

performed by, or in close collaboration with, the Alaska Department of Fish and Game 

(ADF&G). Principles that drive the ideal monitoring designs and implementation, statewide, are 

(1) explicit estimation of detectability (“sightability”) except in caribou monitoring, and (2) 

quantification of uncertainty in population-size estimates. Mark-resign and mark-recapture 

techniques are commonly used to assess detectability, but their accuracy and precision are 

vulnerable to unmodeled heterogeneity in recapture probabilities (Borchers and others, 2004). 

Caribou (Rangifer tarandus L.) monitoring is implemented in the most-consistent 

manner, across the state. It involves composition counts, to estimate sex and age-class ratios, as 

well as summer photo censuses, when animals are highly aggregated into groups. The latter 

method involves taking aerial photos of naturally occurring aggregations then counting 

individuals. Moose (Alces alces L.) monitoring most commonly takes one of two forms: surveys 

using Gasaway (1986) methods, or the VerHoef (2001, 2002) GSPE (GeoSpatial Population 

Estimator) approach. The latter method uses flights immediately before the planned survey to 

stratify sampled grid cells into high- and low-density grid cells. Both methods account for 

variable detectability, and are used in various places to better understand trend via annual revisits. The GSPE approach appears robust to some violations of model assumptions, and 

delineation of survey-area boundaries with GPS coordinates (rather than landmarks, which were 

previously used to delineate boundaries of Gasaway surveys) allows for more-rapid navigation to 

and within survey units. As a disadvantage, gridded cells typically encompass a heterogeneous 

mix of habitat elements important for the focal mammal species. GSPE is model-based and thus 

can accommodate more restrictions on sample composition, such as inclusion of index sites or 

other patterns that would compromise assumptions of simple random sampling. GSPE provides 

kriging of count data across the entire study area. 

ADF&G also monitors numerous terrestrial carnivore species. Black bears (Ursus 

americanus Pallas) and grizzly bears (Ursus arctos L.) are typically surveyed using aerial line 

transects (Becker and Quang 2009), and analyzed to account for assumptions about survey 

conditions that are normally violated. Mark-resight approaches are not commonly used for bears 

in Alaska, due to the high survey costs associated with their typically low densities and large 

number of replicate trials to accurately model heterogeneity. Wolves (Canis lupus L.) and 

wolverines (Gulo gulo L.) have been monitored using TIPS (transect-intercept probability 

sampling) or SUPE (sample-unit probability estimation) designs, although much less frequently 

than for ungulates. For example, the last extensive survey for wolves by ADF&G in an NWR 

occurred in 2002. Becker and others, (2004) describe the assumptions, implementation, analysis, 

variations, and advantages and disadvantages of the TIPS and SUPE methods. Re-visit strategies 

for carnivore surveys have not yet been systematically addressed, because few areas have been 

sampled twice using the same methods.

Breeding Bird Survey (BBS) http://www.pwrc.usgs.gov/BBS

Although most monitoring within USFWS refuges of Alaska occurs independently of 

other refuges, there are several monitoring efforts that span broader extents and encompass 
74 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

several refuges. For example, many refuges have one or more Breeding Bird Survey (BBS)

routes on or nearby refuge lands for which sampling is completed at least in part by USFWS 

biologists. The North American BBS is a continent-wide program designed to monitor the status 

and population trends of North America’s breeding birds at large spatial scales – from states and 

provinces, to the entire continent. The BBS is the most comprehensive avian survey in the 

continent; trends are estimated for over 420 bird species, including most landbirds breeding in 

the U.S. and Canada (Sauer and others, 2005). The program is based on a network of volunteer 

observers who conduct nearly 3,000 road-side surveys each year along predetermined routes in 

the United States and Canada (Figure A9.1). The program has been in existence since 1966, and 

is administered by the USGS in the United States and by the Canadian Wildlife Service in 

Canada.

Each roadside route is randomly assigned and consists of a 24.5-mi (39.2-km) stretch of 

secondary road with 50 stops spaced 0.5 mi (0.8 km) apart. At each of the 50 stops, the observer 

records the number of individuals of all bird species, either heard or seen, within 0.25 mi (0.4 

km) of the stop during a 3-min period. Routes are surveyed once a year (10-30 June in Alaska) 

by an observer that has good hearing and eyesight, can identify all birds in the region by sight 

and sound, and has completed the BBS on-line training program. The Alaska BBS has been most 

effective since 1993 when the number and consistency of routes surveyed annually was 

dramatically increased. As of 2009, ~70 routes are run each year, covering most of the 

appropriate road system in the state. The BBS is currently the only widely implemented 

monitoring program for landbirds in Alaska, and has a total of 142 routes that have been sampled 

for various lengths of time since 1968. Significant modifications to the program in Alaska 

include the collection of habitat data along most routes (Cotter and Andres 2000), the 

establishment of routes on rivers run by motorboat in areas without roads (Harwood 2002), and 

the non-random location of routes due to the limited number of appropriate roads in many 

portions of the state. The Alaska BBS does not cover the long-term sampling frame analyzed for 

trends (1966–present), so data are not currently included in the estimation of continent-wide 

trends (J.R. Sauer, U.S. Geological Survey, oral commun., 2009). Nonetheless, 15 years of 

consistent effort in Alaska has allowed for habitat relationships for 48 landbirds (Cotter and 

Andres 2000), and estimates of trends are available for >100 species across the state.
Appendix 9 75

0

10

20

30

40

50

60

70

80

90

687072747678808284868890929496980002040608

Year

Number of routes

 

Figure A9.1. Breeding Bird Survey (BBS) routes performed annually in Alaska, during 1968–2008. 
76 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Alaska Landbird Monitoring Survey (ALMS)

alaska.usgs.gov/science/biology/bpif/monitor/alms.php

Developed by Boreal Partners in Flight, ALMS is designed primarily to: (1) monitor 

population trends of landbirds across the vast roadless areas of Alaska and (2) model the 

distribution and abundance of birds relative to habitat, physiography, and other factors across the 

landscape. The program has been designed to complement the North American Breeding Bird 

Survey, which, by virtue of its restriction to roadsides, is greatly biased in Alaska and inadequate 

to estimate population trends because of the sparse road system in the state. Field protocols were 

developed and tested for ALMS over a 10-year period with the help of volunteer and agency 

biologists across Alaska. The program has been designed primarily to monitor passerines and 

other small landbirds during the breeding season; however, these surveys also gather valuable 

data for other groups of birds. Officially launched in 2003, ALMS is a statewide program in 

which cooperators conduct surveys on their own lands using a standardized methodology and a 

unified sampling design and pool their data for regional and statewide analyses. The sampling 

frame consists of a grid of 10-km by 10-km sampling blocks across mainland Alaska whose 

eastern boundary is aligned with the Alaska-Canada border (141° W). Within each sampling 

block is a mini-grid of 25 points (5 by 5) whose southwestern-most point is offset from the 

corner of the block by a randomly selected set vector. Sample points within each mini-grid are 

separated by 250 m in the Northern Pacific Rainforest and by 500 m in the other four Bird 

Conservation Regions (BCRs) in Alaska. These distances were selected to minimize travel 

distance between points while also minimizing the potential for double-counting the same 

individual birds at adjacent survey points. Within each sampling block, a minimum of 15 of the 

25 points must be available for surveying birds (that is, not in lakes, on glaciers, on terrain too 

unsafe to survey, etc.). 

The sampling design is a stratified random design. Broad strata are based on the 32 

Unified Ecoregions of Alaska (Nowacki and others, 2001), which in turn are substrata of the five 

BCRs (U. S. NABCI Committee 2000). Except in BCR1 (the Aleutian/Bering Sea Islands), the 

sampling frame subset selected for initial efforts consists of all blocks within federal and state 

resource lands. This subset has been divided into “readily accessible” and “less-accessible” strata 

based on time, cost, regulations, and safety to access, with the accessible stratum being the initial 

focus of the program. A sample of 200 blocks has been allocated proportional to the area of 

ecoregions and land management units. The initial statewide goal was to have an active sample 

of 100 blocks (50 per year) by year 2010, with efforts concentrated in BCR 4 (Interior) and BCR 

5 (North Pacific Rainforest) because of the high diversity of landbirds within those regions. Half 

of the blocks have been allocated to National Wildlife Refuges because of the large land mass 

they encompass relative to other federal and state resource lands. As of 2009, 65 of the targeted 

100 blocks statewide are being regularly surveyed. Among National Wildlife Refuges, however, 

only 13 of the allocated 50 blocks are being surveyed, although Tetlin NWR is surveying 6 more 

blocks than its allocated sample (table A9.1). 

Detailed protocols and data forms are provided in Handel and Cady (2004). Briefly, 

surveys consist of 10-minute point-transects during early morning at each of the points in the 

mini-grid; surveys can require 2–3 days to complete, depending on terrain. Trained observers 

record all birds seen or heard along with data on distance from the observer, behavior, time 

interval, weather, and habitat. Each survey is designed to be replicated every two years, with 

half of the samples surveyed in any given year. The sampling design and survey protocols have 

been selected to allow much flexibility in choice of analytical methods. Population trends from 
Appendix 9 77

ALMS data will be analyzed jointly with data from the roadside Breeding Bird Survey using 

hierarchical models (for example, Link and Sauer 2007). Distribution and abundance across the 

landscape can be modeled using designed-based approaches (for example, Handel and others, 

2009) or spatial hierarchical models (for example, Gorresen and others, 2009). Estimated total 

costs are $25–30K per crew per initial year, and $20K per crew in subsequent years. Total for 

entire program statewide is $250K for initial set-up, and $150K per subsequent year. 

Table A9.1. Number of sampling blocks targeted for ALMS program per refuge compared with number 

currently active and number still needed to meet statewide monitoring goals. Annual effort required is half 

of this level, since surveys are replicated every other year. 

National Wildlife Refuge Initial Target Active Still Needed

Alaska Maritime NWR 7 

4

3 

Alaska Peninsula/Becharof NWR 4 1 3

Arctic NWR 6 2 4

Innoko NWR 4 2 2

Izembek NWR 1 0 1

Kanuti NWR 2 2 0

Kenai NWR 2 1 1

Kodiak NWR 1 0 1

Koyukuk NWR 3 0 3

Nowitna NWR 2 0 2

Selawik NWR 2 0 2

Tetlin NWR 1 7 0

Togiak NWR 3 0 3

Yukon Delta NWR 6 0 6

Yukon Flats NWR 6 0 6

Total 50 19 37

Eelgrass monitoring in southwest Alaska 

USGS, in cooperation USFWS refuges, initiated a program to inventory and monitor 

eelgrass (Zostera marina L.) and macro-seaweeds in Alaska in 2009. Eelgrass plays an essential 

role in the health of estuarine and coastal ecosystems in the southern portion of Alaska (<65o N 

latitude), where it is a dominant marine plant species, a key primary producer, and a critical food 

resource and habitat for a rich diversity of plant and animal species. The monitoring program is 

focused on embayments in or adjacent to the four National Wildlife Refuges of southwestern 

Alaska: Izembek, Togiak, Alaska Peninsula-Becharof and Yukon Delta NWRs.

The monitoring program uses a hierarchical framework to characterize ecosystem status 

and trends while diagnosing causes of environmental change (NSTC 1997). The framework 

involves three levels of monitoring activity, integrated across spatial scales and sampling 

intensities. Level 1 consists of large-scale mapping and inventory of embayments using satellite 

and airborne remote-sensing capabilities to develop baseline maps of eelgrass distribution. 

Given that much of the eelgrass habitat has yet to be inventoried, Level 1 activities comprise a 

large portion of the initial effort. Level 2 consists of broad-scale boat surveys of the eelgrass 

and seaweed abundance and health by sampling a subset of points within each embayment, using 

a systematic sampling design with a random start (Lohr 1999). These surveys collect spatially 
78 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

explicit measurements of eelgrass health (for example, shoot morphometrics, density, abundance, 

epiphyte loads) during its peak biomass (mid-June to early August). Finally, Level 3 involves 

more-intensive monitoring of potential environmental parameters (for example, water 

temperature, turbidity, salinity, irradiance) at a few locations to assess how potential drivers 

influence eelgrass productivity and survival. Since the program’s inception, inventory and 

monitoring efforts have occurred in three embayments on two refuges (Izembek and Togiak), 

and are poised to expand to three more embayments on the other two refuges (Yukon Delta and 

Alaska Peninsula-Becharof) in summer 2010. 

Becker, E.F., Golden, H.N., and Gardner, C.L., 2004, Using probability sampling of animal 

tracks in snow to estimate population size, in Thompson, W.L., ed., Sampling Rare or Elusive 

Species—Concepts, Designs, and Techniques for Estimating Population Parameters: 

Washington, D.C., Island Press. 

References Cited

Borchers, D.L., Buckland, S.T., and Zucchini, W., 2004, Estimating animal abundance—closed 

populations: London, U.K., Springer-Verlag. 

Cotter, P. A., and Andres, B.A., 2000, Breeding bird habitat associations on the Alaska Breeding 

Bird Survey: Springfield, Virg., National Technical Information Service, USGS/BRD/ITR–

2000-0010. 

Gasaway, W.C., DuBois, S.D., Reed, D.J., and Harbo, S.J., 1986, Estimating moose population 

parameters from aerial surveys: Fairbanks, Alaska, Biological Paper 22, 108 p. 

Gorresen, P.M., McMillan, G.P., Camp, R.J., and Pratt, T.K., 2009, A spatial model of bird 

abundance as adjusted for detection probability: Ecography, v. 32, p. 291–298. 

Handel, C.M., and Cady, M.N., 2004, Alaska Landbird Monitoring Survey—Protocol for Setting 

Up and Conducting Point Count Surveys: Anchorage, Alaska, Boreal Partners in Flight, U.S. 

Geological Survey Alaska Science Center, accessed October 26, 2010, at 

http://alaska.usgs.gov/science/biology/bpif/monitor/alms/ALMSprotocol_2004.pdf. 

Handel, C.M., Swanson, S.A., Nigro, D.A., and Matsuoka, S.M., 2009, Estimation of avian 

population sizes and species richness across a boreal landscape in Alaska: Wilson Journal of 

Ornithology, v. 121, p. 528–547. 

Harwood, C. M., 2002, 2002 Lower Yukon River Watershed Breeding Bird Survey (BBS). 

Unpublished report, U.S. Fish and Wildlife Service, Yukon Delta National Wildlife Refuge.

Link, W.A., and Sauer, J.R., 2007, Seasonal components of avian population change—Joint 

analysis of two large-scale monitoring programs: Ecology, v. 88, p. 49–55. 

Lohr, S.L., 1999, Sampling: Design and Analysis: Pacific Grove, Calif., Duxbury Press. 

National Science and Technology Council [NSTC], 1997, Integrating the Nation’s environmental 

monitoring and research networks and programs—a proposed framework: Washington, D.C., 

The Environmental Monitoring Team, Committee on Environment and Natural Resources, 

National Science and Technology Council, 102 pp. 

Nowacki, G., Spencer, P., Fleming, M., Brock, T., and Jorgenson, T., 2001, Ecoregions of 

Alaska—2001: U.S. Geological Survey Open-File Report 02-297 [map] (also available at 

http://agdc.usgs.gov/data/usgs/erosafo/ecoreg/index.html).

Sauer, J.R., Hines, J.E., and Fallon, J., 2005, The North American Breeding Bird Survey, results, 

and analysis 1966-2004, Version 2005.2: Laurel, Md., .U.S. Geological Survey, Patuxent 

Wildlife Research Center website, accessed October 26, 2010 at http://www.mbrpwrc.usgs.gov/bbs/bbs.html. 
Appendix 9 79

U.S. North American Bird Conservation Initiative (NABCI), 2000, Bird Conservation Region 

Descriptions: Arlington, Virg, U.S. Fish and Wildlife Service. 

Ver Hoef, J.M., 2001, Predicting finite populations from spatially correlated data: Proceedings of 

the Section on Statistics and the Environment of the American Statistical Association, p. 93–

98. 

Ver Hoef, J.M., 2002, Sampling and geostatistics for spatial data: Ecoscience, v. 9, p. 152–161. 
80 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Appendix 10. Monitoring Efforts by USFWS Programs Other than NWRS

Marine Mammals Management

The USFWS Marine Mammals Management (MMM) Office in Alaska is responsible for 

conservation and management of polar bear, Northern sea otter, and Pacific walrus populations 

in all Alaska marine habitats, including in and near the eight National Wildlife Refuges in the 

state with a maritime border. Management of three sea otter, one walrus, and two polar bear 

stocks occurs at roughly ecoregional scales. Management mandates are largely specified by the 

Marine Mammals Protection Act of 1972 and the Endangered Species Act of 1973. MMM 

partners with the refuges, USGS, and others to assess status and trend of stocks using bestscience survey techniques and biological monitoring efforts. The Office is also committed to comanagement practices that incorporate both western-science and traditional-ecologicalknowledge perspectives in monitoring and managing these stocks. 

For the last 20 years, MMM has operated a Marking, Tagging, and Reporting Program 

(MTRP), which is intended to census subsistence harvest of all three species in Alaska and to 

forestall illegal trade of marine-mammal body parts. The MMM Office maintains a permanent 

network of about 150 ‘harvest taggers’ in 100 maritime communities and currently holds over 

47,000 harvest records across all three species. Taggers are local residents that work for MMM 

on a contractual basis to collect harvest information, which is used to satisfy the regulatory 

requirement that each harvested animal be reported within 30 days. Although the MTRP 

consistently under-reports actual subsistence harvest, it is a reliable harvest indexing system. 

The Office employs both formal and informal correction factors to estimate true harvest impacts. 

Two MMM biologists operate MTRP full-time with substantial support from part-time staff. In 

2009, MMM also began developing a Polar Bear-Human Information Management System 

(PBHIMS), which seeks to track and analyze polar bear/human conflicts for all circumpolar 

nations. There are over 80 variables in this database. One biologist in MMM has been assigned 

to operate the PBHIMS system for all jurisdictions in the geographic range of the polar bear, 

including Alaska. 

Fisheries 

Many of Alaska’s fish species have life histories that involve extensive migrations that 

range from hundreds to thousands of miles. As a consequence, effective fisheries management 

requires consistent and strategic population monitoring across these large geographic extents. 

Having sufficient baseline and time-series data is fundamental to conserving and managing 

Alaska’s fish species. The USFWS Fisheries Program in Alaska invests the majority of its 

human and fiscal resources in monitoring and assessing key fish populations in close 

collaboration with ADF&G, USFWS Refuges, and other natural-resource agencies. However, a 

persistent problem is that too few baseline and time-series (that is, trend) data exist for most 

aquatic resources in Alaska. The State’s large size, coupled with the logistical and budgetary 

constraints associated with conducting monitoring and assessment studies in remote areas, 

contribute to the paucity of baseline information necessary for making informed decisions. A 

major challenge is deciding where to use limited funding to monitor stock-specific and broadscale trends to support the conservation and management of Alaska’s fish populations. Another 

challenge is ensuring that existing fisheries data and expertise are incorporated into the 
Appendix 10 81

development of USFWS and external aquatic-resource conservation and management plans. In 

many cases, data are not readily available or easily accessible to those that need to use them for 

making decisions. 

The USFWS Fisheries Program in Alaska is highly mindful of the need to collect 

fisheries and aquatic habitat data in a consistent manner that will maximize its utility for 

management purposes. All fisheries monitoring projects are coordinated closely with ADF&G 

to insure data collection is standardized across jurisdictions. As a Fisheries Program policy, all 

projects must complete an Investigation Plan (IP) prior to conducting any field work. The IP 

must be approved by the Program’s regional Fisheries biometrician to insure appropriate sample 

sizes are considered, appropriate statistical methods have been outlined, and methods of data 

collection are consistent with primary fisheries and habitat databases. All approved fisheries 

projects are required to publish results in either professional journals or in the USFWS Alaska 

Fisheries Publication Series (http://alaska.fws.gov/fisheries/fish/reports.htm).

Migratory Birds

The Migratory Birds Management Division consists of two branches: Waterfowl and 

Non-Game. The Waterfowl group has biologists in field offices throughout the State. Within the 

Non-Game branch, there are lead biologists for Raptor, Waterfowl, Shorebird, Landbird, and 

Seabird groups. 

The Waterfowl Branch conducts surveys around Alaska to monitor abundance, trend, 

and distribution of waterbirds. Most surveys occur annually in springtime, to coincide with the 

breeding season. Other surveys are conducted on staging, molting, and wintering areas. 

Breeding-ground surveys follow a standard protocol (USFWS and Canadian Wildlife Service 

1987). Most survey areas are not stratified; however, where long-term distribution information 

is available, it is used to create designs stratified by bird density. Sampling effort is then 

optimally allocated within strata. Survey areas are typically sampled with systematically spaced 

strip transects. Multi-year surveys are designed with a rotating panel of transects with a different 

set flown annually (over a period of 4 years, for example). This allows pooling of multi-year 

data for finer-scale mapping of waterbird distribution. Most surveys do not incorporate 

correction for imperfect detectability; however, an independent-observer double-count technique 

(Seber, 1973; Magnussen and others, 1978; Pollock and Kendall, 1987; Graham and Bell, 1989) 

is used for some surveys, to correct for sightability. 

For seabirds, monitoring began in 1976 by Alaska Maritime NWR, and expanded in the 

1980s. Monitoring at colonies is achieved by repeat visits to a collection of index sites, which 

were originally established by selecting one large seabird colony within each ~500 miles of 

Alaska Maritime coastline. At each large colony, numerous count plots were non-randomly 

selected for establishment, and numbers of individuals in those plots are estimated by groundbased observers with binoculars during each survey. Additionally, censuses of kittiwake colonies 

in Prince William Sound were added after the Exxon Valdez oil spill in 1989. Seabird 

monitoring in Alaska: occurs during June-August; measures population trends, phenology, 

productivity, diets, and survival; and averages over 1,000 field person-days per year (for 

example, see Dragoo and others, 2009). 

Raptor monitoring has involved tracking trends of bald eagles (Haliaeetus leucocephalus

L.) across Alaska since 1967. The state is subdivided into five survey regions: Southeast Alaska, 

the North Gulf Coast, the Alaska Peninsula (including Kodiak), the Aleutian Islands, and the 

Interior; the intent is that one of these areas is surveyed each year, on a rotating basis. Most 
82 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

monitoring has focused on the south coast of the state (from Dixon Entrance to the tip of the 

Alaska Peninsula), where most bald eagles in Alaska occur. The vast Interior region has only 

been partially sampled once (along segments of some larger rivers), in 2006. The Aleutians have 

never been comprehensively surveyed due to costs (estimated at >$100,000.), but Byrd and 

Williams (1991) estimated ~400 pairs for the Aleutians in 1991. The other 3 areas have been 

surveyed more consistently. Data available from past surveys indicate that eagle numbers are 

stable in Alaska. There may be interest in increasing survey intensity in light of the new eagle 

permit program initiated in Nov. 2009 that will allow the take of eagles nationwide, due to the 

species’ delisting from the Endangered Species Act.

USFWS Migratory Birds’ monitoring of shorebirds depends heavily on availability of 

soft funding, thus effort varies dramatically across years. Monitoring of population status and 

trends occurs via a double-sample method, to quantify detectability (Bart and Earnst, 2002) and 

falls within the general hemispheric program designed to monitor shorebirds (Program for 

Regional and International Shorebird Monitoring, PRISM; Bart 2005, Skagen and others, 2004). 

Monitoring has been performed primarily along the North Slope of Alaska. Methods include a 

limited number of “intensive” plots (4 to 8 400-m × 400-m plots around established base camps) 

where intensive survey efforts (1 to 1 1⁄2 months) are conducted during June and July. A separate 

team performs rapid (1.25-hr) ground-based searches at many “rapid” plots located randomly 

over a much larger pre-set area of Arctic breeding habitat. There, the team records bird presence 

and abundance between 7-21 June, when shorebirds are most detectable. Base camps are not 

established randomly, due to financial constraints. PRISM was developed in 1998, and fully 

implemented starting in 2002. Separate and much more intensive demographic monitoring has 

also been conducted at Barrow during 2003-2009. At ground camps, focused monitoring obtains 

estimates of nest success, site fidelity, and adult survival. This program is poised to expand to a 

five-year effort at four Alaskan and three Canadian sites by collaborating with a whole host of 

NGOs and other federal agencies. 

Office of Subsistence Management (OSM) – alaska.fws.gov/asm/fis.cfm

The Fisheries Resource Monitoring Program (hereafter, Program) was established in 

2000 and is administered by the OSM. The Program employs a collaborative interagency, 

interdisciplinary approach to collect and apply information needed for subsistence fisheries 

management on Federal public lands in Alaska. To date, 325 projects have been funded that 

address research priorities identified by Regional Advisory Councils, management agencies, and 

local users. Annual budget is approximately $6.25 million dollars. Monitoring projects are 

developed through a biennial competitive request for proposals, and evaluated via an interagency 

technical peer-review process. Projects include investigations of stock status and trends, 

subsistence harvest and use patterns, and collection and analysis of traditional ecological 

knowledge. Project designs vary to address specific biological and social-science study 

objectives, ranging from basic census techniques to survey and sampling designs of varying 

complexity. Methods have included use of weirs, counting towers, sonar, mark-recapture, and 

telemetry to assess fish abundance and migration, sampling for genetic stock identification and 

other biological data, and surveys to obtain harvest, use, and traditional knowledge information. 

Although most projects address monitoring or research needs associated with salmon 

management, a significant commitment of funds also has been directed at resident (nonsalmonid) fish species (for example, whitefish species on the Yukon and Kuskokwim Rivers). 

All investigators are now being asked to consider examining or discussing climate-change effects 
Appendix 10 83

as part of their proposals. Investigators conducting long-term projects are encouraged to 

participate in a standardized air and water temperature monitoring program for which the OSM 

will provide calibrated temperature loggers and associated equipment, analysis and reporting 

services, and access to a temperature database.

Bart, J., and Earnst, S.L., 2002, Double sampling to estimate density and population trends in 

birds: Auk, v. 119, p. 36–45. 

References Cited

Bart, J., 2005, Monitoring abundance of bird populations: Auk, v. 122, p. 15–25. 

Dragoo, D.E., Byrd, G.V., and Irons, D.B., 2009, Breeding status, population trends, and diets of 

seabirds in Alaska, 2006: Homer, Alaska, U.S. Fish and Wildlife Service Report AMNWR 

09/05. 

Graham, A., and Bell, R., 1989, Investigating observer bias in aerial survey by simultaneous 

double-counts: Journal of Wildlife Management, v. 53, p. 1009–1016. 

Magnusson, W.E., Caughley, G.J., and Grigg, G.C., 1978, A double-survey estimate of 

population size from incomplete counts: Journal of Wildlife Management, v, 42, p. 174–176. 

Pollock, K.H. and Kendall, W.L., 1987, Visibility bias in aerial surveys–A review of procedures:

Journal of Wildlife Management, v. 51, p. 502–510. 

Seber, G.A.F., 1973, The estimation of animal abundance and related parameters: London, U.K.,

Charles Griffin and Co. 

Skagen, S. K., Bart, J., Andres, B., Brown, S., Donaldson, G., Harrington, B., Johnston, V., 

Jones, S.L., and Morrison, R.I.G., 2004, Monitoring the shorebirds of North America—

Towards a unified approach: Wader Study Group Bulletin, v. 100, p. 102–104. 

U.S. Fish and Wildlife Service and Canadian Wildlife Service, 1987, Standard operating 

procedures for aerial waterfowl breeding grounds and habitat surveys. Unpublished manual as 

revised, U.S. Fish and Wildlife Service, Laurel, MD. 
84 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Appendix 11. Monitoring in Alaska by Agencies Other than USFWS

Forest Inventory and Analysis

The FIA program in Alaska is part of a national program that monitors status and change 

of all U.S. forest lands (http://www.fia.fs.fed.us; appendix 4). In southeast and south-central 

Alaska, the program uses the national design: a spatially balanced probability sample of field 

plots across all lands and use of spatially complete remote sensing data for stratification. Field 

sample points are randomly divided into 10 panels, with one panel measured each year using a 

boat/helicopter combination that travels from Ketchikan to Kodiak. Approximately 18 crew 

people work in rotating shifts through the field season, which lasts from mid-May through midAugust. Data collection costs are approximately US$ 1.8 million yr-1, the land area within the 

southeast/south-central survey unit is 15 million ha, and the sample contains about 5620 plots on 

land (2200 forested plots). The national FIA program currently operates in all states and 

territories of the U.S. with the exception of Wyoming and the remainder of Alaska. If funded, the 

program proposed for the remainder of Alaska will have a reduced sampling intensity, some 

modifications to the design and indicators, and incorporation of LiDAR data. Indicators 

monitored by the FIA program are generally reported at the ecoregion, survey unit, state, or 

national level. Status and change of a variety of forest indicators are reported, as listed in 

appendix 8. On a 1/16th subsample of plots, additional indicators include suites of variables for 

down woody debris, vegetation diversity, crown conditions, lichens, and soils. Field-collected 

data and documentation are available from http://199.128.173.17/fiadb4-

downloads/datamart.html. 

U.S. National Park Service’s Inventory and Monitoring (I&M) program

Five overarching objectives guide the program nationally (appendix 6), and suites of 

stepped-down objectives analogously guide each of the four I&M networks within Alaska (see 

http://science.nature.nps.gov/im/units/akro/index.cfm and links). Each network has settled on a 

group of about 20 to 30 ‘Vital sign’ indicators, which are organized under the themes of Air and 

Climate, Geology and Soils, Water, Biological Integrity, Human Use, and Landscapes. I&M 

networks consider their constituent park units as their primary clients, but interface with a 

diversity of other stakeholders and audiences. Pillars of the I&M effort in Alaska and at the 

national level are described in appendix 1. As illustrated in appendix 14, the suites of indicators 

monitored in each park and network represent a balance between comparability across space and 

acknowledging the unique resources and management priorities of each park. 

Bureau of Land Management (BLM)

In contrast to other federal jurisdictions, BLM lands are administered under a multipleuse mandate. Ecological monitoring in BLM occurs within Fisheries, Wildlife, Cultural, 

Recreation, and Vegetation programs. Across Alaska, BLM works through NRCS to collect soils 

information in a few regions, and data on snow-depth and snow-water equivalent in specific 

areas that are part of NRCS’ regional networks. There is no cultural or paleontological 

information collected that is not site- or project-specific; it will thus be difficult to organize this 

information at ecoregional or statewide extents. 
Appendix 11 85

The Wildlife program monitors the following resources: a) occupancy and productivity of 

cliff-nesting raptors (Peregrine Falcon, Gyrfalcon, Rough-legged Hawk, Golden Eagle); b) 

population size, nesting, and distribution of Steller's and Spectacled eiders; c) population trends, 

distribution, habitat use, and subsistence harvest levels of game mammals (moose, caribou, Dall 

sheep, muskox); d) breeding birds (for example, BBS and ALMS routes); e) migrating birds (for 

example, banding stations); f) caribou habitat; g) snow depth; and h) polar bear summer on-shore 

habitat use (starting in 2010). These are mostly partnership projects (for example, with ADF&G, 

USFWS, USGS, etc). They use a variety of protocols and monitoring techniques, depending on 

the exact resource monitored, partners involved, and geographic location. 

The BLM Fisheries program is driven primarily by agency requirements under FLPMA 

(the goal of which is to understand the condition of public lands) and ANILCA (which mandates 

BLM to conduct research and monitoring of subsistence resources). Fulfilling these requirements 

is critical to insure that managers have the information necessary to make sound landmanagement decisions. Basic inventories utilize commonly accepted methods and techniques 

outlined in USFS and BLM manuals. Specifically, the Fisheries program utilizes basin-wide and 

representative-reach-based habitat surveys to quantify habitat conditions for baseline and 

monitoring studies. Population monitoring is based on electrofishing techniques, which range 

from cursory "spot shocking" for inventories to block-netted, triple-pass depletion techniques for 

more-quantitative assessments of fish community status. BLM also supports salmon escapement 

monitoring, involving the use of towers, weirs, and DIDSON (Dual-frequency IDentification 

SONar), and performs habitat use and delineation efforts for resident and anadromous species 

using radio telemetry. Study designs are variable and depend on the particular question being 

asked by managers. Less than half of the program’s work involves repeated monitoring at the 

same locations annually, given BLM's management responsibility over 277,000 km of streams 

and 4.14 million acres of lakes in Alaska. As such, much of the work involves first-time 

inventories that may not be re-sampled for >25 years. Repeated sites are generally associated 

with a specific project, such as the evaluation or monitoring of placer mining activities in certain 

areas. Increased emphasis is given to subsistence species, such as salmon and northern pike, in 

addition to recreationally important species. Other focal species include unique fish species or 

populations, such as the Kigluaik Mountain char and the Gulkana steelhead. In the future, the 

program expects an increasing emphasis on resident fish management, as a result of the Western 

Native Trout Initiative under the National Fish Habitat Action Plan. Specifically, the program 

strives to: a) determine the fish community composition on BLM-managed lands; b) determine 

the extent of anadromy on BLM-managed lands; c) determine the habitat quality (in-stream and 

riparian) for priority species (for salmonids, mostly); e) delineate critical habitats (spawning, 

overwintering, etc.) for priority species; f) quantify the effects of authorized land-use activities 

on fish populations and habitats; g) determine the effectiveness of mitigation and reclamation for 

BLM-authorized activities.
86 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Appendix 12. List of ecosystem components and processes monitored on 

U.S. National Park Service lands, within each of four Inventory and 

Monitoring Networks in Alaska. 

Using a medical analogy, NPS I&M tracks “Vital Signs” as indicators of ecosystem 

health. These vital signs are organized and listed under six broad “monitoring frameworks” in 

the far-left column. The Vital Signs and “Parks Where Monitored” columns are visually 

distinguished by row into one of three categories, as indicated in the legend (that is, bold ● for 

current I&M-led indicators, regular-font ○ for current monitoring led by other sources, and grey

italic + for most-likely future I&M monitoring). Parks in which the Vital-sign indicator is or will 

be monitored appear in the right-most columns; abbreviations for each park appear in the 

corresponding table header. 

Table A12.1. Vital signs of the Arctic Network. Park names given by column abbreviations: BELA = Bering 

Land Bridge National Preserve; CAKR = Cape Krusenstern National Monument; GAAR = Gates of the

Arctic National Park and Preserve; KOVA = Kobuk Valley National Park; NOAT = Noatak National 

Preserve. 

Legend:

● Vital signs for which the network will develop protocols and implement monitoring with funding from the vital 

signs or water quality monitoring program.

○ Vital signs that are currently being monitored long-term by a network park, another NPS program, or by another 

federal or state agency. The network will collaborate with these other monitoring efforts where appropriate but will 

not use vital signs or water quality monitoring program funds.

+ Vital signs for which monitoring will likely be done in the future but which cannot currently be implemented due 

to limited staff and funding.

Level-1 Category Level-2 Category Vital Sign

Parks Where Monitored BELA CAKR GAAR KOVA NOAT

Air and Climate

Air Quality Airborne Contaminants ● 

Weather and Climate Climate ● ● ● ● ●

Snowpack ● ● ● ● ●

Geology and Soils Geomorphology

Coastal Erosion ● ●

Sea Ice ○ ○ 

Permafrost ● ● ● ● ●

Water

Hydrology Surface Water Dynamics + + + + + 

Water Quality

Lake Communities and 

Ecosystems ● ● ● ● ●

Lagoon Communities and 

Ecosystems ● 

Stream Communities and 

Ecosystems ● ● ● ● ●

Biological Integrity Invasive Species Invasive/Exotic Species + + + + + 
Appendix 12 87

Focal Species or 

Communities

Land Birds ● ● ● ● ●

Yellow-billed Loons ● ●

Brown Bears ● ● ● ●

Dall's Sheep ● ● ●

Muskox ● ●

Caribou ○ ○ ○ ○ ○

Moose ○ ○ ○ ○ ○

Fish Assemblages + + + + +

Small Mammal Assemblages + + + + +

Terrestrial Vegetation and 

Soils ● ● ● ● ●

Human Use 

Consumptive Use Subsistence/Harvest ○ ○ ○ ○ ○

Point Source Human 

Effects Point Source Human Effects + + +

Landscapes 

Fire and Fuel 

Dynamics Fire Extent and Severity ○ ○ ○ ○ ○

Landscape Dynamics Landscape Patterns and 

Dynamics ● ● ● ● ●

Table A12.2. Vital signs of the Central Alaska Network. Park names given by column abbreviations: DENA

= Denali National Park and Preserve, WRST = Wrangell-St. Elias National Park and Preserve, and YUCH = 

Yukon-Charley Rivers National Preserve.

Level-1 Category Level-2 Category Vital Sign

Parks where Monitored DENA WRST YUCH

Air and Climate

Air Quality Air quality ○

Weather and Climate Climate ● ● ●

Snow pack ● ● ●

Geology and Soils 

Geomorphology Glaciers ● ● 

Permafrost ● ● ●

Subsurface Geologic 

Processes

Disturbance - volcanoes and 

tectonics + + + 

Water Hydrology Disturbance - Stream flooding ● ● ●

River/stream flow ● ● ●

Water Quality Water Quality ● ● ●

Biological Integrity

Invasive Species Disturbance - Exotic species + + + 

Infestations and Disease Insect Damage + + +

Focal Species or 

Communities

Freshwater fish ● ● ●

Passerines ● ● ●

Bald Eagle ● 

Golden Eagle ●
88 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Peregrine Falcon ●

Ptarmigan + + +

Moose ● ● ●

Sheep ○ ● ○

Small mammals ● + + 

Caribou ● ● ○

Snowshoe hare ● ● ●

Arctic ground squirrel + + +

Wolf ● + ●

Brown Bear + + +

Vegetation structure and 

composition ● ● ●

Subarctic steppe +

Human Use

Consumptive use Consumptive use ○ ○ ○

Point-Source Human 

Effects Human populations + + +

Human presence/use + + + 

Visitor and Recreation 

Use Trails + + +

Landscapes

Fire and Fuel Dynamics Disturbance - Fire occurrence 

and extent ○ ○ ○

Landscape Dynamics Land Cover ● ● ●

Plant phenology ○ ○ ○

Soundscape Soundscape ○ + +

Table A12.3. Vital signs of the Southwest Alaska Network. Park names given by column abbreviations: 

ALAG = Alagnak Wild River; ANIA = Aniakchak National Monument and Preserve; KATM = Katmai 

National Park & Preserve; KEFJ = Kenai Fjords National Park; LACL = Lake Clark National Park & 

Preserve.

Level-1 

Category Level-2 Category Vital Sign

Parks where Monitored ALAG ANIA KATM KEFJ LACL

Air and 

Climate

Air Quality Visibility and Particulate Matter ○ ● ○

Weather and Climate Weather and Climate ● ● ●

Geology and 

Soils

Geomorphology Glacier Extent ● ● ●

Geomorphic Coastal Change + + ● ●

Subsurface Geologic 

Processes Volcanic and Earthquake Activity ○ ○ ○ ○ ○

Water

Hydrology Surface Water Hydrology ● ● ● ● ●

Water Quality Freshwater Chemistry ● ● ● ● ●

Marine Water Chemistry ● ● ●
Appendix 12 89

Biological 

Integrity

Invasive Species Invasive/Exotic Species ○ ○ ○ ○ ○

Infestations and Disease Insect Outbreaks ○ ○ ○ ○

Focal Species or

Communities

Kelp and Seagrasses ● ●

Marine Intertidal Invertebrates ● ● ●

Resident Lake Fish ● ● ●

Salmon ○ ○ ○

Black Oystercatcher ● ●

Marine Birds ● ● ●

Bald Eagle + + ● ● ●

Brown Bear + + ● ●

Wolf + + +

Moose ● ●

Sea Otter ● ●

Caribou ○ ○

Harbor Seal ○ ○ ○

Vegetation Composition and 

Structure ● ● ● ● ●

Sensitive Vegetation Communities ● ● ●

Human Use Consumptive use Consumptive use ○ ○ ○ ○

Visitor and Recreation Use Visitor Use ○ ○ ○ ○ ○

Landscapes Landscape Dynamics Land Cover ● ● ● ● ●

Landscape Processes ● ● ● ● ●

Table A12.4. Vital signs of the Southeast Alaska Network. Park names given by column abbreviations:

GLBA = Glacier Bay National Park and Preserve; KLGO = Klondike Gold Rush National Historical Park; 

and SITK = Sitka National Historical Park.

Level-1 Category Level-2 Category Vital Sign

Parks where 

Monitored GLBA KLGO

SITK

Air and Climate Air Quality Airborne Contaminants ● ● ●

Visibility and Particulate Matter + + +

Weather and Climate Weather and Climate ● ● + 

Geology and Soils Geomorphology Glacier Dynamics ● ●

Water

Hydrology Streamflow ● ● ●

Water Quality

Oceanography ●

Freshwater Benthic Macroinvertebrates 

and Algae + + ●

Freshwater Water Quality ● ● ●

Freshwater Contaminants ● ● ●
90 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Marine Contaminants ● ○ ●

Biological Integrity 

Invasive Species Invasive/Exotic Animals + + + 

Invasive/Exotic Plants ○ ○ ○

Infestations and Disease Pests and Diseases + + + 

Focal Species or Communities

Bald Eagles + + + 

Bears + + + 

Biodiversity of Select Groups + + +

Breeding Land Birds Assemblages + + + 

Forage Fishes + +

Harbor Seals +

Intertidal Communities + + ●

Killer Whales +

Marine Predators ●

Salmonids + + + 

Ungulates +

Western Toads + ○

Wetland Communities + + + 

Humpback Whales ○

Steller Sea Lions +

At-risk Biota Kittlitz’s Murrelets ●

Human Use Consumptive Use Consumptive Uses + + +

Landscapes 

(Ecosystem Pattern 

and Processes)

Non-point-source Human 

Effects Human Uses and Modes of Access ○ ○ ○

Landscape Dynamics

Landform and Landcover ● ● ●

Phenology + + +

Plant Communities + + + 

Soundscape Airborne Sounds + + +

Underwater Sound ○
Appendix 13 91

Appendix 13. Notes from Manager’s Breakout Group at Forum on 

Ecoregional Monitoring for the NWRS and Other Public Lands across 

Alaska

The Manager Breakout Sessions

On Days 2 and 3 of the Forum, breakout sessions were held for managers. Managers were selfelected for this session based on a definition of ‘manager’ as a higher level supervisor 

responsible for the general direction of a larger work unit or land management area. Participants 

in the breakout session included the Alaska refuge chief, refuge and deputy managers, land 

managers for other agencies, regional or national office unit leaders (specifically invited because 

of their involvement with I & M programs), and regional office leaders of non-governmental 

organizations. Representatives included Canadians as well as Americans. Approximately 25 

managers attended the first session on Day 2 and about 15 on Day 2. Danielle Jerry was the 

facilitator for the manager breakout session. 

Issues Posed to the Managers

Three programmatic issues concerning ecoregional/statewide monitoring were posed to the 

managers and their recommendations sought on these issues. The facilitator listed the issues on a 

flip chart and started the session by briefly describing each of the issues. The listed issues 

focused an otherwise rather freewheeling conversation, which was cut short by time constraints 

on both days. 

• Agency cultural issues – recommendations for dealing with inherent USFWS/NWRS 

agency cultural issues when creating a new I&M program at the ecoregional and regional 

scales. 

• Accountability – recommendations for where and how to invest accountability for an 

I&M program when the work of the program is done at the refuge level, but the I & M 

questions and design may be largely focused at the ecoregional/regional level. The 

concern is that funding for the program could compete directly with other refuge 

programs in low-budget years.

• Science credibility – in 1993, DOI Secretary Bruce Babbitt administratively transferred 

the biological research arm of the USFWS from the agency to, at first, an independent 

agency and then ultimately to USGS, where it resides today. Although research by both 

USGS, universities, and the USFWS, itself, continues on refuge lands, the close 

interaction of research scientists and agency scientists and the science-based culture of 

the agency was affected in largely undetermined ways. The NWRS is largely a land 

management organization and managers within the agency often entering the 

management series early in their careers, rather than rising in the biological series.
92 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

Manager Recommendations, Day 2

At the time of the Forum, organizers had no anticipation of receiving funding in the near future 

to establish an ecoregional I & M program on refuge lands. As a result, managers first wanted to 

address the issue of building and selling the programmatic vision of why the NWRS needs an 

I&M program above the refuge-level. Recommendations from the managers on this issue follow. 

 - Build and sell the vision of an I&M Program. 

(1) All non-USFWS managers emphasized partnering as the first and most important step in 

building and selling the vision. The Forum and its organizers were praised for the conference and 

for inviting participants widely across agency, and international boundaries. 

(2) Cultivate I & M champions at all levels of the organization, but particularly at the highest 

level and in the budget arena. The NWRS needs an I&M marketing strategy. Ecoregional I&M 

means telling a different story that what we have been telling.

(3) To sell a vision locally, NWRS needs to translate performance measures into something that 

is actually meaningful to the agency.

(4) To sell a vision nationally, NWRS needs to use GPRA (Government Performance Results 

Act) effectively and tie new requests to agency performance measures.

(5) Be careful of the word ‘monitoring.’ It is has a long history of not being viewed well in our 

immediate-results based world. ‘Risk-based management’ is a better description. 

(6) Agency culture and mission is important. The NPS recognized their culture of strong and 

independent leadership at the Park level as an up-front obstacle in establishing an I&M program. 

As a result a decision was made early that at some organizational and administrative level of the 

Vital Signs program, the Parks managers would be told what to do or they would not be given 

funds. At the same time, it was also recognized that some levels (ecological indicators) needed

regional or local control. 

Manager Recommendations, Day 3 - agency culture, accountability, and scientific credibility.

(7) The USFWS has a broader, more complex mission than NPS which will make initiating an 

I&M program more difficult. The USFWS mission includes a land management program, the 

NWRS, as well as nationwide responsibility for migratory birds, endangered species, and interjurisdictional fisheries. The USFWS will have to address refuge and agency cultures in 

establishing a program. 

(8) USFWS management seemed very aware of agency cultural obstacles and the difficulty in 

overcoming them. Upon hearing this, a Parks Canada Agency representative suggested that 

USFWS refuges has a management vision and challenged the agency to examine if climate 

change alters this vision and if so how. 

(9) Personnel administratively dedicated to the I&M program are essential to move the program 

forward. A network coordinator and a database manager are the two key positions to be filled 

first. 

(10) Monitoring needs to be in addition to rather than in place of existing workloads. 

(11) A data base structure should be in place before monitoring begins. 

(12) At least one-third of the I&M budget should be dedicated to data management, analysis, and 

reporting. 
Appendix 13 93

(13) If possible, tie monitoring to management decisions. These locally important monitoring 

targets must be translated into performance measures recognized at the national level. 

(14) If data is not readily available to managers, it is irrelevant whether or not it is well-managed.

(15) Collaborate with partners and start by reviewing databases, protocols, and programs from 

other agencies for use by the USFWS. 

(16) And finally, managers really liked the NPS wedding cake model, where the lowest level 

represented data collected and analysis conducted at the refuge level. Each higher level of the 

cake represented a synthesis of data analysis for the ecoregional, regional, and national levels. 
94 Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners

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For more information concerning the research in this report, contact the 

Director, Alaska Science Center 

U.S. Geological Survey

4210 University Drive

Anchorage, Alaska 99508

http://alaska.usgs.gov
Woodward and Beever— Framework for Ecological Monitoring on Lands of Alaska National Wildlife Refuges and Their Partners—Open-File Report 2010–1300