United States

Department

of Agriculture

Forest Service

Rocky Mountain

Research Station

General Technical

Report RMRS-GTR-161

September 2005

Strategies for Monitoring

Terrestrial Animals and

Habitats

Richard Holthausen, Raymond L. Czaplewski,

Don DeLorenzo, Greg Hayward, Winifred B. Kessler,

Pat Manley, Kevin S. McKelvey, Douglas S. Powell,

Leonard F. Ruggiero, Michael K. Schwartz,

Bea Van Horne, Christina D. Vojta
The Authors _____________________________________

Richard Holthausen: Washington Office, Watershed, Fish and Wildlife, Flagstaff, AZ

Raymond L. Czaplewski: Rocky Mountain Research Station, Fort Collins, CO

Don DeLorenzo: Southwestern Region, Albuquerque, NM

Greg Hayward: Rocky Mountain Region, Denver, CO

Winifred B. Kessler: Alaska Region, Juneau, AK

Pat Manley: Pacific Southwest Research Station, Sierra Nevada Research Center, Davis, CA

Kevin S. McKelvey: Rocky Mountain Research Station, Missoula, MT

Douglas S. Powell: Washington Office, Ecosystem Management Coordination, Washington, DC

Leonard F. Ruggiero: Rocky Mountain Research Station, Missoula, MT

Michael K. Schwartz: Rocky Mountain Research Station, Missoula, MT

Bea Van Horne: Washington Office, Wildlife, Fish, Water, and Air Research, Washington, DC

Christina D. Vojta: Washington Office, Watershed, Fish and Wildlife, Flagstaff, AZ

Holthausen, Richard; Czaplewski, Raymond L.; DeLorenzo, Don; Hayward, Greg; Kessler,

Winifred B.; Manley, Pat; McKelvey, Kevin S.; Powell, Douglas S.; Ruggiero, Leonard F.;

Schwartz, Michael K.; Van Horne, Bea; Vojta, Christina D. 2005. Strategies for monitoring

terrestrial animals and habitats. Gen. Tech. Rep. RMRS-GTR-161. Fort Collins, CO: U.S.

Department of Agriculture, Forest Service, Rocky Mountain Research Station. 34 p.

Abstract ________________________________________

This General Technical Report (GTR) addresses monitoring strategies for terrestrial animals

and habitats. It focuses on monitoring associated with National Forest Management Act planning

and is intended to apply primarily to monitoring efforts that are broader than individual National

Forests. Primary topics covered in the GTR are monitoring requirements; ongoing monitoring

programs; key monitoring questions and measures; balancing three necessary and complementary forms of monitoring (targeted, cause-and-effect, and context); sampling design and statistical

considerations; use of the data that result from monitoring; and organizational and operational

considerations in the development and implementation of monitoring programs. The GTR

concludes with a series of recommendations for the ongoing improvement of monitoring of

terrestrial animals and their habitat.

You may order additional copies of this publication by sending your

mailing information in label form through one of the following media.

Please specify the publication title and number.

Telephone (970) 498-1392

FAX (970) 498-1396

E-mail rschneider@fs.fed.us

Web site http://www.fs.fed.us/rm

Mailing Address Publications Distribution

Rocky Mountain Research Station

240 West Prospect Road

Fort Collins, CO 80526
Contents

Page

Preface ..................................................................................................................iii

Executive Summary .............................................................................................. iv

Chapter 1 Background........................................................................................... 1

Monitoring Under the National Forest Management Act...................................... 1

Current Wildlife and Habitat Monitoring ............................................................... 1

Overview of existing monitoring activities and programs

for terrestrial species................................................................................. 1

Habitat monitoring—the FIA program............................................................. 2

The utility of existing programs....................................................................... 3

The need for improvement to existing monitoring programs .......................... 4

Chapter 2 Questions and Measures ..................................................................... 5

Monitoring Questions ........................................................................................... 5

Selection of Ecosystem Elements to Monitor ...................................................... 6

Selection of Measures for the Ecosystem Elements ........................................... 8

Population and community measures ............................................................ 8

Habitat measures ........................................................................................... 8

Chapter 3 Creating an Integrated Monitoring Program .................................... 11

Categories of Monitoring.................................................................................... 11

Targeted monitoring ..................................................................................... 11

Cause-and-effect monitoring ........................................................................ 11

Context monitoring ....................................................................................... 12

Strengths of Different Monitoring Types ............................................................ 12

Targeted monitoring ..................................................................................... 12

Cause-and-effect monitoring ........................................................................ 12

 Context monitoring ...................................................................................... 13

Balancing Components in a Comprehensive Monitoring Program .................... 13

A Case Example to Illustrate Targeted, Cause-and-Effect, and

Context Monitoring and Their Relationships ................................................ 15

Chapter 4 Sampling Design and Statistical Considerations

 and Guidelines ............................................................................................ 17

Ecological and Management Context ................................................................ 17

Scale Issues ...................................................................................................... 17

Strategies for Monitoring Terrestrial

Animals and Habitats

Richard Holthausen, Raymond L. Czaplewski, Don DeLorenzo, Greg Hayward,

Winifred B. Kessler, Pat Manley, Kevin S. McKelvey, Douglas S. Powell,

Leonard F. Ruggiero, Michael K. Schwartz, Bea Van Horne, Christina D. Vojta

i
Resonable Expectations of Monitoring Programs.............................................. 18

Variability over time ...................................................................................... 18

Timeframe of inference ................................................................................ 18

Geographic area of inference ....................................................................... 19

Sample Design .................................................................................................. 19

Sampling Adequacy ........................................................................................... 20

Review Process ................................................................................................. 20

Chapter 5 Applying Monitoring to Managment ................................................. 23

Adaptive Management ....................................................................................... 23

Evaluation of Targeted, Context, and Cause-and-Effect Data........................... 23

Linkage of Habitat and Population Monitoring ................................................... 24

Chapter 6 Organizational Considerations ......................................................... 27

Effective Organizational Structure and Roles .................................................... 27

Current situation ........................................................................................... 27

Desired condition and organization .............................................................. 27

Operational Strategies ....................................................................................... 30

Partnerships....................................................................................................... 31

International Association of Fish and Wildlife Agencies (IAFWA) ................ 31

State agencies.............................................................................................. 31

BLM, NPS, DOD, and Tribes........................................................................ 31

USGS ........................................................................................................... 32

NatureServe ................................................................................................. 32

Other NGOs ................................................................................................. 32

Volunteers .................................................................................................... 32

Chapter 7 Critical Elements for Successful Monitoring ................................... 33

Literature Cited .................................................................................................. 33

ii
Preface _______________________________

The original version of this report was prepared at the request of

Forest Service Regional Directors of wildlife who wanted a team to

provide recommendations for monitoring terrestrial animals and species on National Forests and Grasslands. This General Technical

Report (GTR) was developed from that internal report. It focuses on

monitoring associated with National Forest Management Act planning

and is intended to apply primarily to monitoring efforts whose scope is

broader than individual National Forests. Much of the GTR focuses on

the Forest Service’s organization and programs. However, the concepts described for making critical choices in monitoring programs and

efficiently combining different forms of monitoring should be broadly

applicable within other organizations.

iii
EXECUTIVE SUMMARY

Monitoring of terrestrial animals and their habitats on

National Forests and Grasslands is motivated largely by

the National Forest Management Act (NFMA) and regulations implementing the act. Regulations that were issued

in 1982 required monitoring of Management Indicator

Species (MIS) and their habitats, determination of the

relationship between populations and habitat, and determination of the effects of management. New

regulations published in 2005 contain only a general

requirement for monitoring indicators of ecological

sustainability but do not contain specific wildlife monitoring requirements. The increased flexibility in the new

regulations will not necessarily eliminate monitoring of

animal populations, but they should allow us to reconsider the question of what monitoring information will be

most useful to inform needed adjustments to management plans over both the short and long term.

Monitoring for terrestrial animals on National Forests

and Grasslands has been problematic. At the level of

individual Forests and Grasslands, monitoring efforts

are frequently marked by inadequate design and insufficient funds to reliably detect trends. Terrestrial animal

monitoring efforts that address multiple Forests tend to

be better designed and funded. However, these tend to

be focused on Federally listed or otherwise highly visible

species, and just three of these efforts account for nearly

$4 million in annual budget.

In order for monitoring to be useful in adaptive management, monitoring must be able to distinguish the

effects of local activities (e.g., management of a single

National Forest) from broad-scale effects such as those

that might result from disease or climatic patterns. It must

also provide information on causes of trends. Without

such information, managers will not be able to properly

interpret trends or know what actions to take to alter

unfavorable trends. With those considerations in mind,

we suggest that monitoring programs for terrestrial animals and their habitats be designed to answer the following

five questions:

1. Are species, habitat, and community objectives

being achieved consistent with outcomes anticipated in

Forest plans?

2. Are species, habitats, and communities responding

to specific management activities and the effects of those

activities as anticipated in Forest plans?

3. What are the status and trends of species, habitats,

and communities of concern and interest for which there

are not specific anticipated outcomes in Forest plans

(e.g., invasives, some sensitive species, species or groups

of special interest)?

4. What are the status and trends of broader measures

of biological diversity and ecosystem change for which

there are not specific anticipated outcomes in Forest

plans?

5. What are the mechanisms underlying change in

habitats and communities, and species responses to

changes in ecological conditions?

Questions 1, 2, 3, and 5 focus on species, habitats

and communities that are considered of concern or

interest in Forest plans. However, in most cases it will

not be possible to monitor all such species. We suggest

criteria to narrow the list of species to be monitored, but

even after application of the criteria there are likely to

be too many candidates for monitoring. Further

prioritization may be accomplished by using ecological

modeling and by focusing on legal obligations and species at highest risk.

In order to respond to the monitoring questions, three

separate types of monitoring are needed:

• Targeted—monitors the condition and response to

management of species and habitats that are identified as being of concern or interest

• Cause-and-effect—investigates the mechanisms that

underlie habitat and species response to management and other forms of disturbance

• Context—monitors a broad array of ecosystem components at multiple scales without specific reference

to influences of ongoing management

Creating balanced programs incorporating all three

types of monitoring within realistic budgets will be a

significant challenge. We suggest that this balancing be

done at the Regional or higher level rather than at the

scale of individual Forests so that appropriate consideration is given to monitoring that must be conducted

across broad spatial extents. Assigning priorities at the

Regional or higher scale should also result in greater

consideration of the need for context and cause-andeffect monitoring. Appropriate balance among the three

types of monitoring will be influenced by the state of

knowledge of species and their habitats within an area,

and the levels of risk to those species and habitats.

All monitoring must be designed to comply with the

Data Quality Act. Monitoring programs must use best

available science; employ sound statistical methods with

effect size and power appropriate to the objective; identify sources of error; provide for quality assurance in data

collection; and be subjected to peer review.

Modification of some facets of the current Forest Service organizational structure could be considered in

order to improve effectiveness of our monitoring programs. We suggest that the Regions be given a larger

role in the coordination of monitoring of terrestrial animals, and that such coordination would require some

new dedicated positions. We also suggest that new

funding mechanisms are needed to provide a reliable

source of funds for multi-Forest efforts. Monitoring should

be a collaborative effort between National Forest Systems (NFS) and Research and Development (R&D),

iv
requiring a careful definition of roles and innovative,

collaborative relationships. Partnerships and inter-agency

coordination should play a much larger role in the future

in monitoring of terrestrial animals and their habitats.

The report concludes with the following recommendations:

Make a national commitment to improve monitoring of

terrestrial animals and their habitats.

Ensure that all monitoring contributes to adaptive management by exploring both the causes for trends and

alternative scenarios that could reverse unfavorable

trends.

Ensure that all monitoring complies with USDA Data

Quality Guidelines.

Implement Regional monitoring strategies that integrate

habitat and population monitoring. Monitoring habitat

alone will rarely be sufficient for adaptive management

because habitat relationships are not well understood

and may not be predictable.

Adopt and integrate three types of monitoring (context,

targeted, and cause-and-effect).

Use sound ecological principles and risk assessment to

prioritize and design monitoring activities.

Recognize that monitoring is multi-scalar. Coordinate

across ecological and administrative scales, with emphasis on the role of the Regions.

Establish appropriate roles and coordination for NFS

and R&D from the Washington Office through Forest

levels.

Provide adequate staffing, skills, and funding structures

to accomplish monitoring objectives.

Use partnerships and interagency coordination to accomplish monitoring objectives.

Ensure that individuals and teams responsible for monitoring, development, and oversight have appropriate

skills.

v

USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 1

Monitoring Under the National

Forest Management Act __________

The issue of wildlife monitoring on National Forest

System (NFS) lands has been problematic for decades, at

least since the development of regulations (Federal Register, 1982, Vol. 47, No. 190, 43037-43052) for the

National Forest Management Act (NFMA) in 1982.

Those regulations required monitoring at the scale of the

plan area (generally a single National Forest or Grassland), focused monitoring on a set of Management

Indicator Species (MIS)1

, and required that changes in

population be related to changes in habitats. The 1982

regulations sparked ongoing debates over the choice of

MIS, the appropriate scale for monitoring, the utility of

population monitoring, the need for statistical reliability

in data, responsibilities of the Forest Service and other

agencies, and the ability to relate population changes to

habitat changes resulting from management. Monitoring

was frequently the target of both legal challenges and

scientific criticisms.

New NFMA regulations published in 2005 (Federal

Register, 2005, Vol. 70, No. 3, 1055-1061) require monitoring of indicators of ecological sustainability. While

terrestrial animals and their habitats may be included

within the set of indicators chosen by a Forest, the

regulations do not contain specific wildlife monitoring

requirements. These regulations also require that National Forests and Grasslands establish Environmental

Management Systems (EMS), which are a set of processes and practices that enable an organization to track

and manage its environmental impacts2

. EMS will require monitoring, but the form of that monitoring is not

clear. During the transition from the old to the new

regulations, National Forests that continue to operate

under the 1982 regulations will be allowed to satisfy MIS

monitoring requirements through consideration of habitat and not populations.

While the requirements in the NFMA regulation are a

key consideration in the development of monitoring

plans, it is impossible to second guess what these requirements will be in the future. So, while the requirements

deserve consideration, we also need to ask a much more

fundamental question: what monitoring information will

allow us to make needed adjustments to management

plans over both the short term and long term? Focus on

this question will be more valuable over the long term

than trying to second guess future changes in regulations.

Current Wildlife and Habitat

Monitoring _____________________

Overview of existing monitoring activities

and programs for terrestrial species

On Forest Service System lands, approximately 700

species of terrestrial vertebrates and 500 invertebrates

have one or more designations as federally listed, regionally sensitive, or Forest management indicator species,

but only around 30 species are monitored with consistently funded monitoring programs, either at the

multi-Forest level (table 1) or at the level of the individual

national Forest or grassland (table 2). Of these, only 14

monitoring programs are funded by NFS at $100,000 or

greater, while other programs operate on $30,000 to

$80,000 annually. Funding of terrestrial animal species

monitoring tends to be disproportionately allocated to a

few high profile species. For example, the Forest Service

contribution to the annual monitoring budget for northern spotted owls and red-cockaded woodpeckers is $1 to

1.5 million per year for each species, including administration, data analysis, and reports (table 1). The Forest

Service contribution to grizzly bear monitoring is

$250,000 annually through normal appropriations plus

an additional $1.1 million Congressional earmark for

FY04. These funds do not include the contributions of

other monitoring partners, most of which are federal or

state agencies.

In addition to monitoring programs for individual

species, long-term avian monitoring programs exist in

several Forest Service Regions (table 3). These multispecies bird monitoring programs, often called “landbird”

Chapter 1

Background

1

MIS are defined in the 1982 regulations (36 CFR 219.19) as “species...

selected because their population changes are believed to indicate the effects

of management activities”. 2

http://www.iso-14001.org.uk/iso-14004.htm
2 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

Table 1—Forest Service FY04 contributions to monitoring programs for terrestrial species at multi-forest or

regional scales. Expenditures are approximate within 10% of the actual.

Species Federal status Regions involved NFS FY04 contribution$

Northern Spotted Owl T 5,6 1,620,000

Grizzly Bear, 1-yr Congressional earmk T 1 1,100,000

Red-cockaded Woodpecker E 8,9 1,000,000

Carnivores (Sierra Nevada) C (fisher) 5 550,000

California Spotted Owl 5 450,000

Marbled Murrelet T 6 400,000

Yosemite Toad and Yellow-legged Frog Both C 5 314,000

Grizzly Bear (standard program) T 1,2,4,6 250,000

Birds and Burns Network 1,2,4,6 234,000

Southwest Willow Flycatcher E 3 150,000

Willow Flycatcher (California) 5 115,000

Mexican Spotted Owl T 3 80,000

Chiricahua Leopard Frog T 4 80,000

Pileated and white-headed woodpecker 4 60,000

Amphibian inventory (Montana) 1 50,000

Bats (Oregon bat grid) 6 40,000

Spotted Frog C 4 36,000

Kirtland’s Warbler E 9 30,000

Canada Goose: Dusky and Vancouver 10 30,000

Black Swift 2, 3, 4,10 Not available

Boreal Toad C 2,3,4 Not available

Black-tailed Prairie Dog C 2 Not available

Table 2—Forest-level monitoring programs for terrestrial species where the NFS contribution is $50,000 or

greater for FY04. Estimates are within 10% of the actual.

Species Federal status Region Forest FY04 contribution$

Multiple Species 1 Idaho Panhandle 500,000

Multiple Species (MSIM) 5 Tahoe 400,000

Northern Goshawk 3 Kaibab 300,000

Northern Goshawk 4 Dixie 60,000

Northern Goshawk 10 Tongass 75,000

Mexican Spotted Owl T 3 Lincoln 250,000

Canada Lynx T 9 Superior 125,000

Indiana Bat* E 9 Monongahela 100,000

Chiricahua Leopard Frog T 3 Coronado 80,000

Riparian birds 5 Tahoe 55,000

Northern Flying Squirrel E 9 Monongahela 50,000

*Most forests with Indiana bat conduct project clearance work only.

monitoring, have been in place for two to 12 years, and

annual costs, including administration, data analysis,

and reports, are between $15,000 and $250,000.

Habitat monitoring—the FIA program

The Forest Inventory and Analysis (FIA) program is

the nation’s coast-to-coast forest inventory program and

has been in continuous operation since 1930. FIA is

primarily designed as a continuous forest census. Plots

are permanently marked and revisited on a 10-year cycle.

FIA also has current and future potential for the inventory

and monitoring of wildlife habitat, and it is therefore

included here as an on going monitoring program. The

FIA program is managed by Forest Service Research and

Development (R&D) and when fully funded, the program costs $72 million annually.

The current FIA sample design consists of a systematic

hexagonal grid across all ownerships in the United States,

with each hexagon containing approximately 6000 ac

(2360 ha). The inventory program consists of three
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 3

phases. Phase 1 is a remote sensing phase aimed at

classifying the land into forest and non-forest and obtaining spatial data such as fragmentation, urbanization, and

distance variables. Phase 2 provides the bulk of information and consists of field data collected at one randomly

located point within each hexagon. Vegetation structure

and composition are measured at a cluster of plots associated with this sample point. At the present time,

non-forest points are only sampled as necessary to quantify rates of land use change, and field measurements are

not used to develop detailed information on non-forest

vegetation. Phase 3 of data collection is conducted at a

relatively small subset of the grid points (approximately

6%) and consists of an extended suite of ecological data

including full forest-vegetation inventory, tree and crown

condition, soil data, lichen diversity, measures of coarse

woody debris, and ozone damage. From all three phases,

FIA generates reports on the status and trends in forest

conditions and makes the raw data available to NFS for

site-specific analysis and interpretation. Many Regions

rely on FIA points as training data for generating

vegetation maps for Forest and project planning, and

they also measure non-forest sites with FIA Phase 2

protocols to complete their vegetation databases. The

FIA program is implemented in cooperation with a

variety of partners including State forestry agencies and

private landowners who grant access to non-federal

lands for data collection purposes.

The utility of existing programs

Most of the current wildlife population monitoring

programs are intended to produce simple trend data for

individual species. The best examples of these programs

are those directed at federally listed species. Under these

programs, data are generally collected by multiple agencies and landowners and given directly to the Fish and

Wildlife Service or to a university. The receiving agency

or university takes responsibility for collating and analyzing the data across all ownerships within the range of

the species, and then distributing reports. Forest Service

units benefit from the reports by incorporating recent

trends into project and Forest plans. Red-cockaded woodpecker monitoring is an example of such a program. Each

National Forest has a budget for collecting data and the

results are compiled by the Fish and Wildlife Service

with those of other landowners across the range of the

woodpecker.

The “landbird” (table 3) monitoring programs represent the only multiple-species monitoring for terrestrial

vertebrates currently in place in NFS. Unfortunately each

of these programs uses a different design, so it is difficult

to aggregate or compare data between programs. Nevertheless, the data have proven valuable for the National

Forests. In many cases, these regional programs provide

the only capability for determining avian population

trends for the National Forests. The Northern Rockies

Landbird Monitoring Program has been underway for 12

years, and preliminary trends are available for approximately 60 species. The Songbird Monitoring in the Great

Lakes program also has 12 years of data and has done

trend analyses for 66 species. Both programs post trend

information on the web, so that it is available for Forest

planning and other applications. Other landbird programs are of shorter duration and have not yet evaluated

trends. Due to methodological issues, the reliability of

some generated trend data has been questioned (Ellingson

and Lukacs 2003, Hutto and Young 2003).

FIA data have been used in numerous ways to provide

broad scale context for assessing status and trends of

wildlife habitat (Rudis 2004). Barnes (1979) gleaned

information from FIA on foliage structure, browse/mast

availability, and snag/wolf tree density to assess habitat

Table 3—National Forest System landbird monitoring programs that are multi-Forest or

regional in scope.

Program Started Annual cost

Fire and Fire Surrogates (bird monitoring portion) 2000 400,000

Birds and Burns 2002 234,000

Northern Region Landbird Monitoring Program 1994 200,000

Monitoring Colorado Birds 1998 200,000

Monitoring Wyoming Birds 2003 200,000

Southern Region Neotrop and Resident Landbirds 1996 250,000

Songbird Monitoring in the Great Lakes 1991 55,000

Late-successional Forest Birds in the Pacific NW 1994 15,000

Prairie bird monitoring 2001 35,000

Nevada Bird Count 2002 140,000

MAPS in Pacific Northwest Region 1994 70,000
4 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

of gray squirrels in Ohio and Pennsylvania. Brooks and

others (1986) evaluated changes in white-tailed deer

habitat in Maine from the 1950s to the 1980s, and

similarly, Brooks (1990) evaluated raptor habitat

changes for the same time period across the 11 northeastern states, using cover type, successional stage, and

land ownership data from FIA. Flather and others (1989)

used FIA along with a number of other broad scale

information sources to create models predicting changes

in white-tailed deer and turkey habitat in the southern

United States. O’Brien (1990) conducted bird point counts

at FIA points in Arizona and correlated bird numbers

with FIA forest structure variables. Ohmann and others

(1994) assessed the characteristics and density of snags

for primary cavity-nesting birds using FIA data from

nonfederal forest lands in Oregon and Washington.

Chojnacky and Dick (2000) used FIA data to calculate

stand density measures for assessing habitat of Mexican

spotted owl in New Mexico.

The need for improvement to existing

monitoring programs

Several patterns emerge from these ongoing, broadscale monitoring programs. They are strongly directed

toward high-profile species, with the bulk of funds going

to three federally listed species. Currently there are no

population monitoring programs for any MIS that are as

intensive as the monitoring efforts for federally listed or

candidate species.

Taxonomically, these broad-scale monitoring programs focus primarily on birds (tables 1, 2, and 3).

There is very little monitoring of mammals, except

where these species are federally listed (grizzly bear,

lynx) or candidates for listing (fisher). The Forest Service relies heavily on state agencies for data on game

birds and mammals. There are few instances of amphibian monitoring, either for groups of species or for single

species. There are no substantial monitoring programs

for reptiles or invertebrates.

In addition to the broad-scale monitoring programs,

there are examples of monitoring activities at the scale of

individual National Forests. Some of these programs are

well-designed, but most share common pitfalls. First,

many of the individual Forest programs lack well-stated

objectives. Frequently, the programs simply aim to verify

that a species still occurs where it was found in previous

years. This is sometimes called persistence monitoring,

but the area or population of inference is unknown, and

the resulting data are of limited use for informing management decisions.

Other pitfalls are a lack of sampling design and a lack

of involvement of statisticians. Although many of these

monitoring programs have an explicit protocol for data

collection, the vast majority have no overall protocol for

sample design. Plots are frequently placed in the best

available habitat for a species, with no effort to randomize or to sample systematically. The sampling frame is

not clearly specified, which makes it difficult or impossible to identify an area of inference. Many monitoring

programs produce data that cannot be effectively evaluated because flawed statistical designs limit the ability to

test hypotheses or quantify confidence limits.

Many Forest Service monitoring activities fail to involve Forest Service Research and Development (R&D)

and therefore miss opportunities to gain enhanced knowledge about observed trends. Ideally, long-term trend

monitoring could be associated with specific research

projects that investigate possible explanations for observed trends.

Current wildlife and habitat monitoring programs need

to be improved in order to provide high quality information for decisions made by land managers. Improvements

are needed in monitoring design, coordination, and implementation. Based on our review of current Forest Service

monitoring activities, the most successful monitoring

programs have the following characteristics:

1. They have clearly stated objectives and a statistically sound sample design and have involved the research

community and statisticians from their inception.

2. Monitoring is conducted in conjunction with related research studies to investigate potential causes of

observed trends.

3. Successful monitoring programs effectively utilize partnerships for funding, political leverage, research

expertise, and field assistance.

4. Data are collected under written protocol, by trained

personnel, with established controls for data quality.

5. Costs of data management and analysis are included in the monitoring costs, with data management

performed at frequent intervals and data analysis conducted at the end of each data collection period.

6. Data and results are made available through published reports or websites.

7. Programs encompass large geographic areas,

which makes the results applicable at a scale that is

meaningful for populations of species with broad ranges.

Because of their broad geographic extent, these programs also attract more partners and therefore benefit

from secure funding. There are many examples of

successful small scale monitoring programs, but too

often, small scale programs fail due to lack of consistent

funds, inadequate statistical support, and inappropriate

spatial extent for the monitoring question and species of

interest.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 5

This chapter describes strategic planning of monitoring for terrestrial animal species and habitats. The process

begins with identification of key monitoring questions to

be addressed. Those questions help determine which

biological elements (populations, species, communities,

habitats) will be monitored. The monitoring questions,

combined with logistical considerations, also drive the

selection of specific measures (presence/absence, abundance, etc.) that will be monitored for each of the elements.

Monitoring Questions ____________

The general goal and requirement for conservation of

species and ecosystems on National Forests and Grasslands is provided in the NFMA, which directs Forest and

Grassland units to “provide for diversity of plant and

animal communities based on the suitability and capability of the specific land area in order to meet overall

multiple-use objectives.” The NFMA regulations, Forest

Service directive system, and regulations implementing

the Endangered Species Act (ESA) provide additional

guidance for achieving this general goal. The objectives

for monitoring should reflect both the general goal of

providing diversity and the specific requirements for

species contained in regulations and directives. Based on

these requirements, the National Center for Ecological

Analysis and Synthesis articulated three general objectives for monitoring of terrestrial animals in the National

Forests and Grasslands (Andelman and others 2001).

These are to:

• Improve our knowledge of the effects of ongoing

management activities on species and the ecological

conditions that support them. There are two components to this objective. The first is to determine the

effect of individual management actions on species

and their habitats, and the second is to determine the

cumulative effect of combined management actions

and natural processes under a given plan on species

and habitats. As a practical matter, this objective is

likely to be focused on particular species identified

to be of interest or concern.

• Provide a more complete understanding of species

and system dynamics in order to facilitate adaptive

Chapter 2

Questions and Measures

management. Understanding the effects of ongoing

management is an important part of a monitoring

program but will not in itself provide the information

needed to effectively modify management. To effectively modify management, we require

information on the mechanisms underlying management effects on species and habitats.

• Improve our knowledge of the status of a broad array

of species and the ecological conditions that support

them. Status of species is affected by many factors in

addition to Forest Service management and conditions on National Forests and Grasslands.

Information on the status of a broad array of species

provides better understanding of the influences of

National Forest System lands and other ownerships on species, overall diversity, and which species

should be considered of concern. This information

is necessary to establish whether all species that

ought to be considered of concern are identified in

Forest plans.

Based on these objectives, we articulated five primary

monitoring questions for terrestrial animal species and

their habitats. While the questions are general in nature

and would be useful in any natural resource management

situation, they are stated below in a form that relates

directly to NFMA plans:

1. Are species, habitat, and community objectives

being achieved consistent with outcomes anticipated in

plans?

This question is directed at those species, habitats,

and communities that are identified as being of concern

or interest in Forest plans, and for which specific outcomes are stated or implied. These outcomes may be

quite general (e.g., maintain breeding populations in

every fourth-order watershed) or very specific (e.g.,

maintain over time four snags per acre >20 inches dbh

in managed areas). Translation of outcomes into measurable terms is necessary for meaningful monitoring

under this question.

2. Are species, habitats, and communities responding

to specific management activities and the effects of those

activities as anticipated in plans?
6 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

As with question 1, this question is directed at those

species, habitats, and communities that are identified as

being of concern or interest in Forest plans, and for which

specific outcomes are stated or implied. However, the

question here is not whether overall outcomes are being

achieved as in question 1. Rather, here we are asking if

specific management activities are having the effects that

were anticipated. For example, if certain nest sites are

buffered from recreation activities during the breeding

season, we might ask if those sites have higher reproductive success than sites that are not protected from recreation

activities.

3. What are the status and trends of species, habitats,

and communities of concern and interest for which there

are not specific anticipated outcomes in the Forest plan?

This question addresses species, habitats, or communities that are identified to be of concern or interest, but for

which no specific outcomes are stated. These might

include invasive species, some sensitive species which

are not individually addressed, and some species that are

noted to be of special interest but are not the subject of

individual outcomes. As an example there may be a

general goal in the plan to reduce the rate of spread of

invasive species but no specific objective for individual

species.

4. What are the status and trends of broader measures

of biological diversity and ecosystem change for which

there are not specific anticipated outcomes in the Forest

plan?

The intent here is to look at a broader array of species,

habitats, and communities than is addressed in questions

1-3. This will provide information on issues such as

diversity and broad changes in distributional patterns that

may result from the ongoing effects of multiple stressors.

This would include unexpected changes in species not

tracked under the other monitoring questions.

5. What are the mechanisms underlying change in

habitats and communities, and species responses to

changes in ecological conditions?

This question looks at actual mechanisms underlying

changes in habitats, communities, and species. As an

example, we could ask what effect the composition,

structure, and landscape pattern of habitats have on

reproductive and/or survival rates of a species. Studies

designed to look at underlying mechanisms may be

considered by some to be “research” rather than “monitoring.” Regardless of the term used, such studies require

designs that look at controls and treatments, with alternative treatments as a desirable feature.

Selection of Ecosystem Elements to

Monitor ________________________

The first step in moving from a series of broad questions to a feasible monitoring program is to determine

those ecosystem elements (e.g., communities, habitats,

species) that will be selected for monitoring under each

of the monitoring questions. Once the elements are

chosen, then specific characteristics of those elements

(e.g., number, spatial extent, vital rates) are identified as

measures, and monitoring designs are developed to provide estimates of those measures. The next two sections

provide guidance for the selection of ecosystem elements

and measures.

Selection of elements to be monitored requires consideration of information regarding management issues as

well as information about the elements under consideration. The following types of knowledge are important to

the selection of elements.

• The dominant management issues faced by the land

manager.

• The major uncertainties associated with the most

important management issues.

• The dominant biological taxa that are deemed important by society and/or are ecologically associated

with critical uncertainties.

• The characteristics of species that will determine

whether they will effectively reflect change in the

environment. In particular an understanding of the

response of the taxa to directional change in the

environment and whether:

o response to change is expected to occur in a

predictable direction over the range of expected

environmental change.

o response is expected to be large (significant)

and measurable relative to the environmental

variation.

o background variation in the species population

dynamics are not likely to obscure any directional signal.

o the time lag between environmental change and

change in the species will be short and constant

across time. That is, it is important to detect

changes before it is too late to correct observed

problems.

o species detectability is adequate to allow effective determination of trends.

The following criteria describe ecosystem elements

that should be selected for monitoring under each of the

monitoring questions. Application of these criteria would
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 7

narrow the list of elements that might be selected under

each monitoring question, but that list will likely still

contain more elements than can be addressed with limited monitoring resources. Further prioritization of these

elements will almost always be necessary. One approach

would be to set priorities by first meeting legal obligations, then focusing on elements at high risk that might be

strongly influenced by management, and then elements

that have direct or indirect effects on many other elements. Ecosystem modeling may help focus on those

elements that are most likely to be strongly influenced by

ongoing ecological processes and management, or that

are likely to have strong influences on other elements.

For example, modeling would help identify species that

will be both negatively and positively influenced by

widespread fuel reduction projects.

Preliminary selection criteria follow for each of the

five monitoring questions.

1. Are species, habitat, and community

objectives being achieved consistent with

outcomes anticipated in plans?

Criteria for species to be monitored

• Species at risk/of concern for which there is enough

knowledge to make projections in the Forest plan.

• Species of social/economic interest for which objectives are established in the Forest plan.

• Species that play a significant role in maintaining the

structure and processes of dominant ecosystems

affected by management.

• Species that are strongly affected by management.

• Species selected under surrogate concepts to help

establish conservation approaches in the Forest plan.

• Exotics that are thought to have a strong ecological

influence (for example, on disturbance processes or

on other species).

Criteria for habitats and communities to be

monitored

• All habitats and communities (including their composition, structure, distribution, and landscape

pattern) for which desired conditions and objectives

are established as part of the broad ecosystem approach adopted in the Forest plan.

• Habitats and communities that are at risk/of concern

or of interest and for which there is enough knowledge to make projections in the Forest plan. These

would include rare/unique/irreplaceable habitats and

communities and other habitats and communities

that support high levels of biodiversity.

2. Are species, habitats, and communities

responding to specific management

activities and the effects of those

activities as anticipated in plans?

The criteria for species, habitats, and communities to be

monitored under question 2 are the same as under question

1, except that (1) more emphasis is given here to those

species, habitats and communities that are most responsive to dominant management activities and effects, and

(2) monitoring focuses on species, habitats and communities for which there is greatest risk and uncertainty.

3. What are the status and trends of

species, habitats, and communities of

concern and interest for which there are

not specific anticipated outcomes in the

Forest plan (e.g., exotics, some sensitive

species, species of special interest)?

Criteria for species, habitats and communities to be

monitored under question 3 are similar to those for

question 1. However, those addressed under question 3

are not individually addressed in the Forest plans and are

likely to be less well known.

4. What are the status and trends of

broader measures of biological diversity

and ecosystem change for which there are

not specific anticipated outcomes in the

Forest plan?

Criteria for species to be monitored

• Individual species and groups of species that, taken

together, serve as indicators of broad patterns of

diversity and response to management and other

changes in ecological conditions.

Criteria for habitats and communities to be

monitored

• Most important elements to be monitored are already included under questions 1, 2, and 3. However,

it might also be important to provide for direct

measures of ecosystem processes (e.g., hydrology,

nutrient cycling) under this question.

5. What are the mechanisms underlying

change in habitats and communities, and

species responses to changes in

ecological conditions?

Studies to determine underlying causes of change will

likely be intensive and expensive. Thus, they should be
8 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

directed at key ecosystem elements that are at high risk,

that have significant impact on overall systems, and/or

whose response to management is highly uncertain.

These broad criteria should be considered in conjunction

with the specific species, habitat, and community criteria

given below.

Criteria for species to be monitored

• Species of concern.

• Species that play a significant role in maintaining the

structure and processes of dominant ecosystems

affected by management.

• Species selected under surrogate concepts to help

establish conservation approaches in the Forest plan.

• Exotics that are thought to have a strong ecological

influence (for example, on disturbance processes or

on other species).

Criteria for habitats and communities to be

monitored

• Habitats and communities (including their composition, structure, distribution, and landscape pattern)

whose response to management is uncertain.

• Habitats and communities that are at risk/of concern.

Selection of Measures for the

Ecosystem Elements ____________

Once the elements (species, communities, habitats)

that are to be monitored are selected, we must determine

the appropriate measure to respond to the monitoring

objective. Below we discuss population, community,

and habitat measures. If several different measures are

appropriate in any given application, priority should be

given to measures that are commonly used, easily employed, have standard methods for collection, relate most

closely to the issue motivating monitoring, and are least

expensive to measure.

Population and community measures

We categorize monitoring measures into two groups—

population measures and community measures.

Population measures are those that would be applied to

individual species, while community measures apply to

multiple species within a community. It is critical to

distinguish between population and community measures and to understand the strengths and weaknesses of

each. Population measures are known to be sensitive to

change, while community measures are quite insensitive. However, community measures by definition

integrate over multiple species and thus may be more

meaningful in some circumstances. Table 4 lists the

pluses and minuses of five categories of population

measures: (1) presence / absence, (2) abundance or

density, (3) vital rates, (4) range distribution, and (5)

genetic measures; as well as two categories of community measures: (1) diversity and (2) integrity.

When selecting population measures, there is often a

choice between direct measures and indices. Examples

of direct measures would include estimates of population

numbers, or estimates of vital rates from direct observations such as clutch size and adult survival. In contrast,

indices are measures that may be correlated with population size or vital rates but are not direct observations of

those parameters. Track and scat counts are common

examples of indices. In general using direct measures of

population parameters is preferred. However, given the

logistic difficulty and cost prohibitive nature of direct

measures, indices may be usable alternatives (Caughley

1977, McKelvey and Pearson 2001). If indices are used,

their inherent weaknesses must be understood. For broadscale monitoring, the relationships between indices and

the parameters they represent must be predictable across

space and time; for example, a good index would be one

that increases in a predictable way as the numbers of a

species increases. It is important to understand any systematic bias in indices. For example, pellet counts for

deer are highest in the areas in which they defecate and

may not accurately represent overall patterns of habitat

use. It is also important to understand the mechanistic

relationship between an index and the parameter it represents, and factors that might cause that relationship to

vary. For example, snowshoe hare scats should provide

a better index of population size than habitat condition.

More hares should produce more scats whereas the

relationship between habitat and population may be

strongly influenced by exogenous factors such as weather.

However, even scat numbers should be interpreted with

caution. Scat counts can be affected by decomposition

rates and variation in diet in addition to population

density.

Habitat measures

Species respond to habitat quality, quantity, and configuration at multiple scales. Most habitat measures are

designed to assess vegetation composition and structure within a stand or patch and result in a quantitative

measure of habitat quality within that area. In addition

to responding to the quality of habitat at discrete sites,

many species also respond to the configuration of habitat

over larger areas. Additional measures are needed to

characterize and monitor this configuration including

measures such as patch size, patch density, edge density,

and nearest neighbor distance.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 9

Table 4—Population and community measures that may be employed in a monitoring program.

Population measures:

1) Presence/Absence

General description of approach: Sample to determine presence of an organism at sample points. Demonstrating presence requires

only concrete proof of the species’ existence at a location, while demonstrating absence requires knowledge of the probability of

detecting the organism given its presence. P / A detection methods at plots can be effective as long as the probability of detecting

an animal (given that it is present) is constant through time or can be estimated based on field data.

2) Abundance or Density

General description of approach: Abundance and density can be formally estimated using a class of well-developed techniques, or

it can be monitored indirectly through an index related to abundance (Lebreton and others 1992; Pollock and others 1990; Otis and

others 1978). Formal estimates can range from the simple Lincoln Peterson index with only three parameters, to complex models

that account for other environmental, social, time, demographic, and location parameters. Typically the cost of obtaining an

abundance estimate increases proportionally to the number of parameters estimated; likewise precision is often gained proportionate

to cost and can approach a plateau where incremental improvements in precision become increasingly expensive. Because these

measures can be expensive, abundance is often inferred through an index. Density is simply abundance per area; however,

estimates of density are complicated by the need to estimate the effective area being sampled.

3) Vital Rates

General description of approach: Vital rates are age-specific birth and death rates or emigration/immigration rates. Here we will only

address birth and death (in rare cases, immigration and emigration will be of direct interest and appropriate literature should be

consulted to examine the use of these measures). Techniques are available for both estimates of vital rates and indices of those rates.

Vital rates are a cornerstone of population viability analysis and an understanding of vital rates provides insight into population status

(Beissinger and McCullough 2002, Franklin and others 2004). Depending on life history, monitoring of vital rates often provides a

better measure of trend than measures of abundance. Furthermore, understanding how vital rates change in response to

management provides insight into potential mediation or mitigation, although demography is also influenced by factors such as

weather (Raphael and others 1996) that are beyond the control of managers. Demographic sensitivity or elasticity analysis can aid

in identifying the appropriate vital rate to monitor.

4) Range Distribution Measures

General description of approach: Geographic range is estimated through either presence/absence measures or through collaboration

with other monitoring systems (such as Breeding Bird Survey) that allow the spatial extent of the species occupied range to be tracked

over time. Sometimes the goal of monitoring will be to determine whether the range of a species is expanding, contracting, or

remaining relatively constant. This is often the case with exotic or endangered species, where the goal may be to compare the current

geographic range to historic distributions. Some theory would suggest that geographic range is relatively sensitive to population

status and therefore a species’ distribution may provide an effective indication of status (Maurer 1994).

5) Genetic Measures

General description of approach: It is important to distinguish between the use of genetics as a tool to bolster other monitoring efforts

(e.g., to verify presence/absence of a species) and the use of genetic parameters as measures in and of themselves. For instance,

determining the presence of a species and subsequently counting the number of unique individuals from scat or hair (non-invasive

genetic sampling) surveys exemplifies how genetics can add to current monitoring practices. In addition to this function of providing

defensible monitoring results, there are several genetic parameters that can serve as measures on their own. The three direct genetic

parameters most likely to be of practical value will be: (a) change in allelic diversity in the population over time, (b) detection of a

genetic population bottleneck, and (c) change in effective population size estimated from changes in gene frequencies across time.

Community Measures:

1) Diversity Measures

General description of approach: Species diversity is expressed through measures of species richness and species evenness.

Species richness may be based on repeated measures of species composition (e.g. presence/absence of taxa). Species evenness

requires abundance data. Measures of species diversity have been employed in research settings to examine particular questions

in community and ecosystem ecology. However, in a management setting it is difficult to determine relationships between measures

of diversity and specific management problems. Challenges include identifying the taxa groups to monitor (e.g. groups identified by

trophic relationships, functional relationships, taxonomic relationships, etc.), the choice of diversity index, and interpretation of

results. These challenges have limited the utility of these measures in resource management monitoring.

2) Integrity Measures

General description of approach: Karr and Dudley (1981) define biological integrity as the “capability of supporting and maintaining

a balanced, integrated, adaptive community of organisms having a species composition, diversity, and functional organization

comparable to that of the natural habitat of the region.” The concept of biological integrity has evolved in response to perceived flaws

in the biological diversity measures. Estimating biological integrity requires asking if conditions on the landscape today are similar

to conditions present at a specific instance in history or to a nearby “natural” baseline habitat. Because this measure would rely on

comparing a measure of diversity across space or time, it is subject to the same difficulties described for diversity measures.
10 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 11

In discussing monitoring approaches that would be

needed to respond to the five key monitoring questions,

we found it useful to define three types of monitoring:

targeted, context, and cause-and-effect (figure 1). This

section describes each type of monitoring, discusses the

strengths of each, and provides guidance on relative

levels of emphasis that would go into each type of

monitoring in different situations. It explores how the

three types of monitoring can work together and concludes with a description of the integration of population

and habitat data.

Categories of Monitoring _________

Targeted monitoring

Monitoring that looks directly at effects of management is the subject of the 1982 NFMA regulations and is

also the primary type of monitoring required in EMS. In

this document we refer to this first type of monitoring as

TARGETED monitoring. Targeted monitoring is done

to answer a specific question about a population, habitat

Chapter 3

Creating an Integrated Monitoring Program

Targeted

Monitors the condition and response to

management of species and

habitats that are identified as being

of concern or interest

Context

Monitors a broad array

 of ecosystem components

at multiple scales without 

specific reference to

influences of ongoing 

management

Cause-and-Effect

Investigates the mechanisms that

underlie habitat and species response

to management and other

forms of disturbance 

Figure 1—Three types of monitoring described in this report.

feature, or species group of interest. We use targeted

monitoring to determine whether the Forest plan objectives for a species are being met and whether management

actions are having expected effects. For example, we

may monitor to determine whether marten populations

decline in areas of forest thinning as would be predicted

by understandings of marten habitat use.

Targeted monitoring would be used to directly address

monitoring questions 1, 2, and 3.

Cause-and-effect monitoring

Targeted monitoring, as described above, informs us

concerning trends in specific ecosystem elements and

whether anticipated effects are occurring. However, it

generally does not inform us about the causes of observed

trends and what alternative management strategies we

should pursue if effects are not as anticipated. To better

understand how management should be changed, we

need to understand actual mechanisms underlying changes

in habitats, communities, and species. Monitoring designed to look at underlying mechanisms generally
12 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

requires designs that include controls and alternative

treatments. We refer to this second type of monitoring as

CAUSE-AND-EFFECT monitoring. Cause-and-effect

monitoring directly addresses monitoring question 5.

Context monitoring

In addition to direct monitoring of Forest plans and

monitoring of underlying mechanisms, another less obvious form of monitoring may also be very important.

CONTEXT monitoring is intended to look at a broad

array of ecosystem components without specific reference to those components that are expected to be affected

by current management activities. Over the long term,

such monitoring may be extremely important in allowing

us to look at (1) cumulative effects of various types of

activities on ecosystems; (2) effects that result from the

interaction of our activities with broader changes (e.g.,

global climate change); and (3) effects on ecosystem

components that we had not expected to be influenced by

our management (Karieva and Wennergren 1995, Tilman

and others 1994). For Forest plan monitoring, it provides

a context within which the results of targeted monitoring

can be evaluated. Context monitoring addresses monitoring question 4 and provides background information

that will aid in the interpretation of the other monitoring

questions.

Strengths of Different Monitoring

Types _________________________

Targeted monitoring

The following are primary strengths of targeted

monitoring:

• It is focused on indicators that are selected because

of risk, concern, or interest.

• It can be focused on elements that are most likely to

change.

• It can be tied directly to management objectives.

• Because of its focus, it is relatively efficient and cost

effective.

• It has a high probability of detecting targeted changes.

Targeted monitoring directly examines change in selected measures (e.g., population size) for a particular

species, habitat, community, or ecosystem. Properly implemented, targeted monitoring meets requirements of

the 1982 administrative rules promulgated under NFMA.

Targeted monitoring allows flexibility in the selection

of indicators for which technically reliable and costeffective monitoring methods exist, and that are expected

to be sensitive to management actions. However, the

implied assumption that observed changes are directly

due to management activities is also the weakness of

targeted monitoring. Unless trend data collected in a

targeted monitoring program are evaluated in light of

regional or global trends (context), changes may be

erroneously attributed to a management activity. For

example, the decline of lynx on a Forest may, or may not,

be due to a particular management activity. Rather, the

trend may be due to global climate changes or to a natural

decline due to population cycling. Therefore, while targeted monitoring is well suited to tracking the trends of

specific indicators, such as MIS, unless the results can be

placed within a broader context, proper interpretation of

these results is impossible. Full understanding of causes

of change also requires cause-and-effect monitoring.

Cause-and-effect monitoring

The following are primary strengths of cause-andeffect monitoring:

• It allows investigation of assumptions used in land/

resource planning models.

• It can be focused on ecosystem elements that are of

greatest interest or concern.

• It leads to greater understanding of mechanisms

underlying patterns.

• These understandings can be used to modify

management.

• It may provide predictive capability, allowing management to refine future choices.

Cause-and-effect monitoring provides understanding

of the causal mechanisms underlying observed trends.

Such understanding is necessary so that managers will

know what actions to take to change unfavorable trends.

Cause-and-effect monitoring integrates monitoring with

research. Historically, the determination of cause-andeffect has been delegated to separate research efforts. In

many cases this may still be the best approach, but a tie

between standard time-series monitoring and research

provides special opportunities to improve understanding

and to develop mechanistic understanding of trends at

spatial and temporal scales larger than generally can be

achieved through separate research efforts.

Generally, research is only weakly coupled to management activities. Therefore, research that is directly

applicable to current activities in the area where an

unfavorable trend has been observed is often lacking. If,

upon observation of an unfavorable trend, a highly directed research program is initiated, the subsequent results

will likely take substantial time to produce. Frequently,

the lag between the results of directed research and the

need to take action leads to actions being taken prior to
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 13

completion of the research. Management actions therefore often do not benefit from ongoing research and lack

the defensibility associated with relevant, peer reviewed

information. Ideally, with cause-and-effect monitoring,

we build experimental design into the management itself

and monitor consequences of specific management actions. Because the research and management occur

simultaneously and in the same areas, data obtained will

be directly pertinent and the development of causal

understandings will be expedited. When cause-and-effect monitoring data are available, not only can

management effectively monitor the important element

of interest, but management also has knowledge to change

the response of the element. As an example, cause-andeffect monitoring led to an understanding that nest sites

are the limiting factor for red-cockaded woodpeckers,

thus allowing Forests to focus on the maintenance of nest

sites and restoration of appropriate conditions within

those sites.

The results of cause-and-effect monitoring help identify relationships and often provide the information

necessary to alter management in order to reverse unfavorable trends. As a stand alone monitoring strategy, it

does not provide information on status and trends of

indicators, and so it would not meet agency monitoring

obligations.

Context monitoring

The following are primary strengths of context

monitoring:

• It is not restricted to selected ecosystem elements.

• It provides status and change information on a wide

range of species and habitats.

• It allows detection of unanticipated changes in species and systems.

• It may reflect trends within entire communities of

organisms, and allow relatively direct inference to

diversity.

• It provides additional context for the interpretation

of targeted or cause-and-effect monitoring results.

Context monitoring for terrestrial animals obtains information on population and habitat conditions across

broad regions and scales for a variety of species. It is most

likely to be based on the application of “omnibus”

sampling methods such as breeding bird counts that

detect many species simultaneously. The sampling frame

and sample density are set based on objectives of detecting as many species as is economically feasible rather

than detecting a single species with specific power.

Because of the lack of targeting, the data that results for

individual species must generally be viewed at broad

scales and over long time periods in order to detect

statistically reliable trends. For example, a context monitoring effort could be tailored to provide adequate status

and trend information at a regional scale over a 10-year

timeframe. When the data from context monitoring are

evaluated at these spatial and temporal scales, they can

provide scientifically reliable trend data for many species

(Manley and others 2004), including some species of

concern and interest. Therefore, while they may not

provide information to directly evaluate individual management actions, these data can (1) provide a context

within which targeted and cause-and-effect monitoring

results can be evaluated and interpreted and (2) provide

monitoring data on diversity by generating information

on broad changes in communities and their component

species over time.

Balancing Components in a

Comprehensive Monitoring

Program _______________________

The three types of monitoring are complementary.

Each has its own strengths and weaknesses, and each will

be most suited to answer particular questions. A program

employing all three types of monitoring will be most

effective in meeting short- and long-term information

needs. All three approaches should be integrated into

coordinated monitoring strategies. The appropriate balance among the three will depend on a number of factors.

Choices about the balance among the three types of

monitoring must be context dependent. We suggest that

the balance and priorities of the three monitoring types be

established at Regional or higher levels so that appropriate consideration is given to the many monitoring

programs that must be conducted across broad spatial

extents and institutional boundaries. Assigning priorities

at the Regional or higher level will also result in greater

consideration of the need for context and cause-andeffect monitoring. At the Forest or District levels,

short-term, targeted monitoring needs generally appear

most critical.

Figure 2 illustrates how those choices might be made.

It provides a framework for managers to evaluate the

relative emphasis that would be given to different types

of monitoring given the state of knowledge of species,

habitat, and communities in a system and levels of risk

to those species, habitats, and communities. For example, if we know little about a species, its habitat,

community, or ecosystem, it is unlikely that a proper

target can be chosen for effective monitoring. If risk is

also deemed low, as might be the case in areas with little

management activity (figure 2, lower left quadrant),
14 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

context monitoring would be emphasized. If there were

adequate knowledge to know both that elements were at

risk, and how those elements might respond to management, then targeted monitoring would predominate

(figure 2, upper right quadrant). If risk were somewhat

lower, but knowledge well-developed, context monitoring might predominate with the objective of detecting

broad trends and unanticipated changes (figure 2, lower

right quadrant). If knowledge were poor but risk deemed

high, it would be appropriate to allocate significant

resources to all three types of monitoring (figure 2,

upper left quadrant). In almost all situations, the key

decision to be made is level of emphasis to be given to

each type of monitoring rather than selecting one type

of monitoring to the exclusion of the others.

In an idealized situation, the design of the three monitoring types and the understanding developed from them

would be synergistic. Context monitoring would be employed to track trends for many species about which we

know little, detect unanticipated change, and track broadscale trends. These trends would be used as part of the

basis for judging significance of targeted monitoring

results, as well as identifying populations or habitats that

warrant targeted or cause-and-effect monitoring in the

future.

Appropriate subjects for targeted monitoring would be

selected based on information from context monitoring,

information from other sources, knowledge of anticipated

management, and ecological modeling. Targeted monitoring would be focused on appropriate indicators and on

key locations where effects were anticipated to occur. It

would not necessarily always focus on Forest-level status

and trends, but would instead look for trends at the most

appropriate geographic scale. This might be larger than

a single Forest, or be some subdivision of a Forest

depending on the question being asked. Where possible,

targeted monitoring would use the same sampling techniques as were employed for context monitoring and

simply represent an increase in sampling intensity for the

selected locations. This would maximize the synergy

between targeted and context monitoring. Frequently,

however, targeted monitoring would be needed precisely

because the techniques used for context monitoring performed poorly for particular species. In other cases, the

specific measure identified for targeted monitoring would

be different from the measure chosen for context

monitoring, thus requiring different sampling techniques. In all situations, however, it is expected that

context monitoring would make some contribution to

needed targeted monitoring. The level of that contribution will depend on the number of species identified

for targeted monitoring and the effectiveness of context monitoring techniques in detecting those species

(figure 3).

Cause-and-effect monitoring should be linked to targeted

monitoring, if possible by conducting cause-and-effect

and targeted monitoring in the same geographic area and

timeframe. The subjects for cause-and-effect monitoring

should be a subset of those that are being tracked through

targeted monitoring. The highest priorities for causeand-effect monitoring should be those ecosystem elements

(species, habitats, and communities) that are expected to

be strongly influenced by management decisions, and for

which management intervention is possible. Priorities

for cause-and-effect monitoring will likely shift over

time. Some indicators may be subject only to targeted

monitoring for a period of time while we attempt to better

understand their status. Based on the results of initial

targeted monitoring, these might subsequently be dropped

from monitoring programs or be subjected to more intense cause-and-effect monitoring. If cause-and-effect

monitoring is successful in determining causal relationships for an indicator, the cause-and-effect portion of a

monitoring program for that indicator might be terminated, with targeted monitoring continuing. In this way,

cause-and-effect monitoring becomes part of a fluid

monitoring program that can be periodically adjusted to

reflect updated priorities.

Where context monitoring deals with broad scale

variables such as major vegetation types, these may be

Dominant Monitoring Approach

Risk

State of Knowledge

Low

Low

High

High

CTE

Cte

cTe

Cte

C = Context, T = Targeted, E = Cause and Effect

Figure 2—Graphic showing how risk and state of

knowledge could influence relative emphasis among

monitoring types. Uppercase letters indicate greater

emphasis.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 15

correlated with variables included in targeted or causeand-effect monitoring. If these relationships can be

established, results from context monitoring may be used

to extend the spatial extent of inference of more localized

targeted and cause-and-effect monitoring within the area

of the context monitoring. Without this extension, the

spatial and temporal scope of inference of targeted and

cause-and-effect monitoring may be very limited. By

working iteratively among the three types of monitoring,

it is possible to extend the inference of targeted and

cause-and-effect monitoring results, making them considerably more useful to management.

A Case Example to Illustrate

Targeted, Cause-and-Effect, and

Context Monitoring and Their

Relationships___________________

The purpose of this example is to describe how targeted, cause-and-effect and context monitoring interact

in a specific situation involving wildlife and habitat

Figure 3—Two possible scenarios for relationships among species subject to context

and targeted monitoring.

management on a National Forest. The example focuses

on the Sitka black-tailed deer, a featured species in the

Tongass Land Management Plan with high subsistence,

recreation, and ecological values.

Information Need 1: What is the population level of

deer on Prince of Wales Island, and what is the population trend through time? This information is required to

properly regulate the harvest of deer on the island to

ensure that hunting demand is provided for without

unnecessarily restricting other users. This requires targeted monitoring focused in a specific area (Prince of

Wales Island) and on a specific management question

(what is the population level of deer, and how does it

change year to year?).

Information Need 2: How defensible are the deerhabitat relationships contained in the Tongass Land

Management Plan? This information is required to test

and validate the assumptions, models, and management

hypotheses used to address deer concerns and objectives in the plan. For example, it was assumed that as

cutover forest areas reached canopy closure, understory

Species detected 

with context 

monitoring

Targeted 

species

Species detected 

with context 

monitoring

Targeted 

species

Scenario 1: A small set of species at risk and of concern have been identified, and context monitoring will

provide useful information for only a few of these species, thus the contribution of context monitoring to

targeted monitoring is limited.

Scenario 2: A large number of species are considered at risk or of concern and interest, many of them are

considered low to moderate risk, and context monitoring is deemed an adequate and effective approach to

monitoring many of them. The contribution of context monitoring to the objectives of targeted monitoring are

substantial.
16 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

vegetation would decline with a subsequent reduction

in carrying capacity for deer. It was predicted that this

effect could be mitigated by thinning treatments to slow

the process of canopy closure. This requires causeand-effect monitoring, carried out as administrative

studies and demonstration projects, to test and validate

the predicted relationships.

Information Need 3: If trends in deer and habitat

relationships are not as predicted in the plan, is this

because: (1) our models and assumptions are faulty, or

(2) background change, unrelated to our management

actions, is confounding the results? For the past 25 years

or so, Sitka black-tailed deer experts have assumed that

periodic severe (deep snow) winters exert an over-riding

control on deer populations. Based on past climate data,

such winters are assumed to occur every decade or so. In

deer-habitat models for Sitka black-tailed deer, snowfall

figures prominently in determinations of habitat quality

and availability. In Alaska today, however, there is

mounting evidence of a warming trend, which affects the

probability and frequency of severe winter events, which

in turn affects dynamics of the deer population and its

habitat. Context monitoring that assesses Region-wide

changes to deer populations is essential to sort out the

effects of background change (e.g., milder winters) from

the effects associated with local management actions

designed to affect habitat.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 17

Once the monitoring questions, elements, measures

and approaches are determined, several specific design

and statistical considerations must be addressed. This

chapter highlights key considerations for creating a successful monitoring program. These include the ecological

and management context within which monitoring will

occur, appropriate scale, limitations, statistical/design

consideration, and appropriate levels of review.

Ecological and Management

Context ________________________

In developing monitoring recommendations at a national level, it’s important to acknowledge ecological

and management situations that differ greatly across the

National Forests and Grasslands. Primary differences

can be described in the following areas:

• Levels of management activity—National Forests

and Grasslands differ greatly in both historical and

current levels of management. Forests in the northeast and southeast were generally highly disturbed

during the first period of European settlement beginning in the 1600s, and most of the eastern forest has

developed as secondary regeneration. Heavy disturbance occurred later in western forests, with major

levels of timber harvest not occurring until the mid20th century in many areas. Some western forests

have still not been subject to significant management disturbance, although they may have been

changed by fire protection, grazing, etc. Current levels of management activity also differ greatly and

may influence judgments about necessary levels of

monitoring activities. Where Forests and Grasslands

have not been significantly disturbed, conditions are

similar to the natural range of variation, and major

management actions are not proposed, less intensive

monitoring may be appropriate.

• Geographic continuity—In some Regions, National

Forests and Grasslands tend to be isolated and embedded in a matrix of lands of other ownerships

(private, state, other federal agency). This is the

dominant pattern in the eastern Regions. Western

Chapter 4

Sampling Design and Statistical

Considerations and Guidelines

Regions generally have Forests that are more contiguous to each other. The extent of geographic

continuity of NFS lands and partnerships with other

agencies will affect sampling design considerations,

sample size needs, and the importance of collaborative efforts across multiple ownerships.

• Ongoing monitoring programs—Some Regions participate in broad-scale, cooperative monitoring efforts

for selected taxa. The costs and data implications of

restructuring an existing, long-term program must

be carefully weighed against the potential benefits

associated with a new monitoring approach.

Scale Issues____________________

Legal and social structures will often dictate a primary

scale of inference for monitoring programs—for NFMA

under the 1982 regulations, it is the National Forest.

However, status and change monitoring defined by administrative boundaries—project, District, or Forest—will

generally have limited utility to inform management. To

improve the utility of monitoring, it should be conducted

at ecologically meaningful scales that may not match

administrative boundaries. For many species this will

mean monitoring at the scale of multiple National Forests

because the geographic range of the species extends over

large geographic areas (e.g., bioregions). Broad-scale,

multi-Forest monitoring strategies can still meet obligations for monitoring at the Forest scale if they are conducted

at ecologically meaningful scales and designed such that

Forest subsets can be evaluated to determine if they are

consistent with larger scale trends. Some legally mandated

monitoring (e.g., biological opinions issued by the U.S.

Fish and Wildlife Service) may require inference at the

scale of individual projects, potentially limiting its broader

utility. However, ongoing programs of scale-appropriate

monitoring may reduce the need for isolated, projectspecific monitoring.

Effectiveness of monitoring can often be improved by

collecting information at multiple scales through a nested

hierarchical system. Multi-scale information aids the

understanding of patterns. For example, assume that a
18 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

Forest has planned to increase elk numbers on the Forest.

A number of actions are taken to improve elk habitat

(e.g., planting grass, closing roads). Of course, the Forest

will be engaged in many other management activities not

directed at elk, but that have the potential to affect habitat

conditions, such as timber harvest and fuel treatments. A

single-scale approach might be to monitor elk numbers at

the Forest level. From a planning and legal standpoint,

this is the scale of interest in terms of meeting desired

conditions. However, measured at this scale, the relationship between elk trends and management actions on the

Forest is unknown. Trends could be going up or down

due to weather, successional trends within the Forest,

hunting patterns on surrounding private land, or a wide

variety of other factors, many of which are beyond the

scope or the control of Forest management. Thus, additional monitoring at broader scales can provide context

for Forest-level patterns. Likewise, monitoring at scales

smaller than the Forest might also enhance understanding. For example, monitoring on an individual district

with an active road-closure program might reveal differences between district-level and Forest-wide elk habitat

use.

Reasonable Expectations of

Monitoring Programs ____________

A key consideration in the development of monitoring programs is recognition of limitations of any

monitoring effort. Monitoring programs are designed to

provide meaningful information, but our knowledge will

always be imperfect due to the inherent variability and

complexity of ecosystems, the rarity and low detectability of many species, the speed at which lost opportunities

become irretrievable, funding constraints, and the inherent limits in our knowledge of ecosystems.

Understanding these limitations will help us develop

reasonable expectations regarding the information that

a monitoring program can provide, and the reliability of

that information.

Variability over time

The inherent variability in ecosystems makes it difficult to distinguish annual fluctuations in species

abundance from meaningful trends. Most species alter

one or more aspects of life history in response to variations in temperature, precipitation, or other climatic

factors. Not only does this change the population dynamics of the individual species, but it also affects the

relationship of that species to other species that act as

competitors, predators, or prey. The level of variability in

populations, even for species of long-lived vertebrates,

can be surprisingly high. According to Pimm (1991, as

cited in Lande 2002), the abundance of unexploited

populations of vertebrates can vary 20 to 80% or more

through time. This level of variation makes the results of

short-term monitoring programs questionable and significantly influences the interpretation of early results

from long-term monitoring programs.

Variability that takes the form of cyclic patterns can

also confound our ability to observe trends. As an example, consider snowshoe hares that undergo a stable

10-year population cycle. While an increase or decrease

in hares could be detected across a fairly short period of

time, it would take at least 20 years to see the 10-year

oscillation, several more decades to determine that the

dynamics were, in fact, cyclic, and several more yet to

determine whether anything unusual was occurring outside the expected range of oscillation. Thus, it should be

anticipated that perhaps 50 years might pass before

trends were understood in a way that allowed legitimate

evaluation of current dynamics.

Development of causal understandings along with

status and trend information will likely decrease the

amount of time necessary for evaluation of monitoring

data. However, the parameters involved in causal relationships may also be subject to intrinsic variability and

non-linear patterns. So, development of causal relationships may also require a substantial period of monitoring.

Timeframe of inference

The complexity of ecosystems limits our interpretation

of the population status and trend data that monitoring

provides. We can document changes that happened during the years the data were collected, but we cannot

predict changes that might occur in the future. Projection

may be reliable for short periods of time, but the reliability rapidly degrades as we push the projection further into

the future. Furthermore, the shorter the period of monitoring, the less reliable the projection that is made from

the resulting data. When data are only available from a

short period of monitoring, the only possible projection

is linear. When data are collected over a longer period,

the functional form of the pattern may become apparent

and its reliability across space and time evaluated.

Since plant community trends are generally less variable than the population dynamics of animals, it should

be possible to forecast habitat data more reliably than

population data. Such projections would make use of our

understanding of ecological processes and the relationship of these processes to climate. Nevertheless, long-term

forecasting is limited by our knowledge of the effects of
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 19

factors such as global climate change and the spread of

invasive species.

Geographic area of inference

We must also consider geographic limitations to monitoring information. The geographic area over which we

can draw inferences from any data set, including monitoring data, is dictated by the area within and the process

by which sample sites are selected (sampling frame). If

sites selected for status and change monitoring are selected in a systematic or randomized manner within a

given National Forest, then data from that sample can be

used to make inferences about status and change on the

National Forest. Extrapolation of these monitoring results from one Forest to another, however, is tenuous.

Our confidence in such an extrapolation may be increased slightly by carefully describing the ecological

and management situation in which the data are collected

and extrapolating results only to similar situations. However, such extrapolations will always be weakened by

inevitable dissimilarities between situations. One of the

strengths of context monitoring is that it is implemented

using similar methodologies across broad spatial scales

and over time so there is less need for extrapolation of

data.

Sample Design _________________

Two key components of a credible monitoring program are protocols for data collection and an overall

sample design. A protocol establishes how data are to be

collected at each sample point, while the overall design

determines where the samples will be located and the

timing of data collection. National Forests and Grasslands frequently ensure that their monitoring programs

use a prescribed field protocol, but it is rare that the field

methods are embedded within an explicitly stated randomized sample design. Without a randomized sample

design, it is not possible to determine whether the monitoring data are representative of an entire area of interest,

or only certain aspects of it, such as certain habitats or

management situations. When data are collected without

a randomized sample design, there is no valid basis for

making inferences from the sample to the population of

interest, and there also is no valid basis for assessing

precision of the estimated population parameters.

For every specific monitoring plan, a sample design

should be selected that best meets the monitoring objectives. Samples must provide for an unbiased representation

of the population of interest. For context monitoring, the

sampling frame must include all cover types within the

desired area of inference, and the sample design must

provide for good spatial dispersion of samples across the

sampling frame. The sampling frame for targeted monitoring should represent all potential habitats for the

species throughout the area of inference. Even habitats

thought to have low potential to support a species should

be included in sampling in order to avoid biasing the

resulting estimate. For cause-and-effect monitoring, the

sample design will, in most cases, be based on treatment

and control blocks, and include replicates (that is, multiple blocks in which management actions occur and

similar blocks where no actions are taken). For all types

of monitoring, the sample size must be adequate to detect

the desired degree of change (“effect size”) with the

desired level of confidence.

The sample design for individual species monitoring

must also take into account specific aspects of a species’

life history and habitats so that data collection can be

optimized and results properly interpreted. Examples

include home range size, territoriality (or conversely,

social clumping), seasonal use patterns, and natural population fluctuations. Home range size and territoriality (or

social clumping) influence plot size and the spacing

between plots within the sampling frame, as well as

interpretations of habitat use patterns. Seasonal use patterns could determine the optimal time of year for detecting

a species, interpreting fluctuations within a season related to the appearance of young of the year, and

interpreting observed occurrence or habitat use data. For

context monitoring of multiple species, the sample design should include sampling several times over the

potential sampling season so that data are not biased

toward early or late seasonal species, and the timing of

sampling should either be simultaneous across all plots,

or randomized such that certain habitats and areas are not

preferentially sampled either early or late in the season.

The magnitude of change that we desire to detect also

drives the design of a monitoring program. Monitoring

plans should specify the amount of change that is considered to be ecologically significant or otherwise deemed

appropriate as an evaluation checkpoint or threshold.

Natural population fluctuations must be considered when

specifying a desired effect size. For example, if a 20%

change in population is within the range of normal

fluctuations, it may not be necessary to detect a 20%

change in population for management purposes. A larger

effect size and hence, smaller sample size, might be

adequate.

Many sources of error affect the reliability of monitoring data, decreasing the precision of estimates and making

it more difficult to reliably detect changes over time. For

count and presence/absence data, one of the primary
20 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

sources of error within and among sample periods is the

detection probability, which is affected by observer variability, habitat conditions, animal behavior, and detection

methods. Estimates of probability of detection can be

obtained with well-designed monitoring protocols

(MacKenzie and others 2002, Royle and Nichols 2003,

Tyre and others 2003).

Although monitoring requirements and information

needs exist at the scale of individual National Forests, it

is often financially or technically infeasible to obtain the

precision and power necessary to detect ecologically

meaningful changes in population parameters in a landscape of 1-2 million acres. For many purposes it is more

appropriate to design monitoring such that temporal

changes can be evaluated over a range of spatial scales,

so that changes indicated weakly at the Forest scale can

be placed in the context of more precise estimates obtained over broader spatial extents. For some monitoring

programs it is also advantageous to design monitoring in

a manner that allows data points to be aggregated by a

variety of features (strata), such as within a species range,

by habitat types, or by type of disturbance (management

or natural) so that the data can have maximum utility for

a variety of applications. When developing multi-scale

monitoring it is critical that measurement methods and

quality control standards be standardized across the

hierarchy and that the formal linkages among data collected at various spatial scales be incorporated statistically

into the overall sample design.

A sample design is not only the heart of every monitoring program, but it also aids in ensuring that the program

meets data quality standards. Forest Service monitoring

programs will be both more defensible and more efficient

if each has a sample design that is specific to the monitoring objectives and natural history of targeted species.

Finally, many sampling design options exist for obtaining samples with a known probability, but a good rule of

thumb for monitoring programs is to keep the design as

simple as possible. The fewer assumptions one has to

make in a sampling design, the more robust it is likely to

be over time. Risks can be reduced by early consultation

with statisticians experienced in sample surveys of populations and habitats.

Sampling Adequacy _____________

Monitoring programs need to be concerned with missing important changes (type II error), as well as falsely

concluding that a change has taken place (type I error).

Estimates of sample size adequacy should be based on

objectives for both statistical power (associated with

type II error) and precision (associated with type I

error). Given the short duration of most planning periods

(10-15 years) during which population and habitat change

must be assessed, precision and power are critical considerations and need to be set high. In the case of targeted

monitoring, monitoring should be designed to detect

ecologically important effect sizes based on species and

plan specific considerations. In most situations, this

would translate into power and precision of at least 80%

for whatever time period and spatial area is being assessed (e.g., 5, 10, 15 year period). For context monitoring,

these same levels of power and precision should be used

to assess which species will be adequately sampled by

proposed omnibus sampling procedures. If power and

precision are lower than these levels, the observed trends

form a weak basis for understanding patterns of change

and informing management decisions.

When presence/absence data are used, sample sizes

needed to reach a given power and precision are generally higher than they would be if abundance data were

used. However, abundance data are more expensive to

collect than presence/absence data. Cost comparisons

should be conducted for context and targeted monitoring

to evaluate the relative efficacy of obtaining presence/

absence and abundance data for various taxa. Regardless

of the type of data collected, monitoring efforts that do

not meet these minimum precision and power objectives

are not likely to yield useful information on population

change.

Review Process _________________

The need for a review process is crucial to ensure that

data quality standards are met and that limited monitoring funds are being used as effectively as possible. To

that end, we recommend a three-part review process that

consists of: (1) an internal agency review after the monitoring design has been developed; (2) an external review

after recommendations from the internal review have

been incorporated into the design; and (3) periodic supplemental internal reviews to recommend changes in the

direction of the monitoring program if needed. We recommend at least one additional formal review four to five

years into the monitoring effort.

The internal agency review should consist of a formal

review by a Regional team comprised of Regional staff,

Station scientists, Forest Supervisors, and species experts.

The purpose of this review would be to ensure that the

monitoring objectives are clear, the sample design and

indicators are sufficient to support the stated objectives,

the proposed analytical methods are sound, the implementation is feasible given the topography and available staff,

and the monitoring program has incorporated, to the extent
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 21

possible, existing relevant information from previous research or monitoring in the proposed monitoring area. An

additional technical review could be done by the Statistical

Advisory Group of the Inventory and Monitoring Institute

(IMI).

The external review should be coordinated by the

Regional office, in partnership with a Forest Service

Research Station, which would be responsible for contacting relevant experts for the monitoring program

under review. At a minimum, the Regional office should

contact personnel at USGS Wildlife Research Center

(Patuxent), representatives of all partners in the monitoring effort, and other agency personnel within or near

the proposed monitoring program geographic area, such

as NPS, BLM, or tribal personnel. The external review

should also include university faculty with expertise in

biometrics, the relevant species, and the relevant ecosystems. The purpose of this review would be to meet

the standards of the U.S. Department of Agriculture

Quality of Information Guidelines3

, ensure that all

affected parties are adequately informed, and gain advice from qualified persons to improve the design as

needed.

Additional reviews should be undertaken over the

course of any monitoring program, but as mentioned

above, we recommend that at least one additional formal

review be incorporated into the review process. The

second internal review, conducted after the monitoring

program has been in place for a few years, could be

carried out by the same groups of people that conducted

the initial internal review. This review would ensure that

the monitoring program is on the right trajectory for

meeting the stated objectives, that data are being entered

into the Natural Resource Information System (NRIS),

data analysis is underway, and the analytical methods are

still appropriate. The review will also provide an opportunity to modify sampling schemes if the present sampling

scheme could not be met for logistical reasons. For large,

sustained monitoring programs, the use of a standing

statistical monitoring group may be helpful.

3 The Department of Agriculture issued revised departmental guidelines

for quality of information in 2003 (http://www.ocio.usda.gov/qi_guide/

index.html). The guidelines generally call for scientific information released

by the Department to be peer reviewed, transparent, and reproducible

according to accepted scientific standards. Guidelines are provided for

statistical data and for data used in regulatory processes. It is likely that

monitoring data would fall under both sets of guidelines.
22 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 23

For monitoring to be useful in management decisionmaking, there must be a formalized adaptive management

framework that directs the analysis, evaluation, reporting, and response to monitoring results. This chapter

discusses key considerations for adaptive management

and analysis of monitoring data in the context of Forest

Service management.

Adaptive Management ___________

Adaptive management is the process of designing

management actions to gain knowledge about critical

uncertainties in our models of management outcomes

and to help us choose between alternative models (Walters

and Holling 1990). The important difference between

trial-and-error learning and adaptive management is that,

with the latter, uncertainties that could lead to unforeseen

and perhaps irreversible outcomes are explicitly identified. By identifying the uncertainties and then creating

management actions so that outcomes can be measured,

the resulting actions yield knowledge, even when the

outcome is different from what was predicted (Lee 1993).

Targeted, cause-and-effect, and context monitoring

should be used in combination to gain knowledge about

uncertainties associated with our management. Targeted

monitoring focuses on uncertainties about the outcomes

of management. Cause-and-effect monitoring focuses on

uncertainties about the mechanisms by which proposed

management, or other possible manipulations, affects

species and habitats. Context monitoring focuses on

uncertainties concerning the larger context within which

proposed management will take place. As an example,

we could look at management for white-headed woodpeckers in ponderosa pine forests. Large ponderosa pine

snags are considered vital for populations of whiteheaded woodpeckers, and guidelines have been

established for their retention in fuel treatment areas.

Targeted monitoring could be conducted to determine if

desired densities of white-headed woodpeckers were

maintained in areas that were treated according to these

guidelines. At the same time, cause-and-effect monitoring could be established to look at the effects of varying

densities of snags, live trees, and logs on woodpecker

reproduction. Context monitoring could be used to

Chapter 5

Applying Monitoring to Management

determine if broad scale changes in populations of several woodpecker species were occurring in correlation

with management treatments or other influences such as

pine mortality. Comparison of treated and untreated

landscapes might also be possible through context monitoring. The combination of these three types of monitoring

would provide clear information for any necessary modification of management. Identifying the key areas of

uncertainty would help determine appropriate emphasis

in the monitoring program.

Evaluation of Targeted, Context, and

Cause-and-Effect Data ___________

The evaluation of management outcomes and the timely

use of new information by decision makers are critical

components of the adaptive management process. Monitoring data are neutral—they simply paint a picture. It is

land managers and scientists who must determine how

monitoring data are interpreted to represent success,

concern, or failure in meeting management objectives.

Periodically, the data from targeted, context, and causeand-effect monitoring programs must be evaluated both

separately and together to determine if desired conditions

are being met and whether specific knowledge gaps have

been sufficiently filled to adjust or reaffirm management

actions. The evaluation of targeted and context monitoring data should be based on pre-selected “threshold” or

“trigger point” values that represent desired or undesirable conditions for each measure. For cause-and-effect

monitoring, evaluation should focus on values that represent ecologically significant levels of response by

species or habitat conditions to management actions.

The terms “thresholds” and “trigger points” are often

used to indicate parameter values of concern and cause

for action, but the evaluation of monitoring results should

also recognize when desired conditions are being met.

Thus, we suggest that a more neutral term, “evaluation

checkpoints,” be used. Checkpoints can be based on a

variety of consideration, including ecological thresholds, management direction, and legal requirements.

Well-developed checkpoints provide a strong foundation for a considered management response to monitoring
24 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

results. Ideally, pre-negotiated management responses to

checkpoints would be described in the monitoring plan,

but this rarely occurs. More commonly, the appropriate

management response is determined after the checkpoint

is exceeded. The periodicity of monitoring reports is

important since evaluations are likely to take place only

when reports are generated.

At the Forest or Regional scales, any problems in a

monitoring program can be spotted by producing annual

reports outlining planned and actual activities (i.e., how

well sampling conformed to the study plan, number of

sites sampled, data collected) and presenting a simple

summary of results. At 5 to 10 year intervals, it is

desirable to conduct detailed data analysis and generate

reports for the purposes of evaluating the need for change

in either management or the monitoring program. Comprehensive evaluations should include summarization

and interpretation of monitoring results at the multiForest or Regional scale to ensure that misleading small

scale patterns of stasis or change are not mistaken as

reliable, sending management in the wrong direction.

The 2005 regulations implementing NFMA require evaluations every 5 years. A mix of managers and scientists, as

well as collaborators and partners, should be involved in

the interpretation of monitoring results at these 5-year

time steps and together generate recommendations for

appropriate actions by decision makers.

Linkage of Habitat and Population

Monitoring _____________________

The Forest Service responsibility for wildlife conservation is to provide ecological conditions that are capable

of supporting wildlife populations to meet stated objectives. Monitoring information can be used to check our

progress toward achieving desired conditions and better

define the relationship between populations and ecological conditions, and subsequently refine our notion of the

desired conditions toward which we should be managing. The importance of the relationship between

population dynamics and ecological conditions was recognized in the 1982 regulation implementing NFMA,

which required that changes in population be related to

changes in habitat condition. While this specific requirement is eliminated from the 2005 regulations, there are

still requirements to monitor “the degree to which onthe-ground management is maintaining or making

progress toward the desired conditions and objectives for

the plan” (36 CFR 219.6 (b)(2)(iii). In the remainder of

this discussion we use the term “habitat” instead of

“ecological conditions,” but it is intended in the sense of

the full suite of conditions that influence wildlife

populations.

Because of the complexities inherent in monitoring

animal populations, it is often proposed that we monitor

only habitat rather than monitoring both habitat and

populations. However, habitat monitoring alone has limited usefulness in predicting wildlife populations for

several reasons:

• Our understanding of wildlife-habitat relationships

is poor for most species.

• Wildlife species may be affected by properties of the

larger landscape, outside the area being measured.

• The habitat variables measured may be chosen for

logistical reasons rather than because they are the

best indicators of ecological conditions for targeted

species. For instance, red-cockaded woodpecker

populations are known to be strongly influenced by

the availability of nest cavities, yet nest cavities are

not likely to be assessed in a general habitat monitoring scheme.

• The disturbance history (e.g. fire, timber harvest) of

an area may influence population size, especially

where wildlife species are not mobile and/or where

populations are fragmented.

• Current disturbances, such as recreational use, may

not affect the physical features of an area but can

limit or exclude occupancy by species sensitive to

human presence.

• The wildlife species of concern may be influenced

by population size of other prey, predator, mutualistic, or competitor wildlife species.

• Population-limiting processes may occur elsewhere

for migratory or seasonally mobile species.

• Intrinsic factors, such as disease or parasites, may

cause declines in wildlife species that are not predicted by habitat. The general amphibian decline of

the past several decades is a good example in which

population changes would have been poorly predicted by habitat monitoring alone.

In a limited number of situations it may be appropriate

to monitor only habitat and project population responses

to that habitat. For example, tracking proportions of

gross habitat types, as from satellite imagery, may be

useful for habitat specialists and species whose distribution or abundance is generally limited by habitat. To be

useful, it must be possible to remotely sense an attribute

of the habitat that limits the species. For example, early

successional stages of forested habitats are usually easily

detected with satellite imagery, and a loss of earlysuccessional habitat will inevitably produce a decline in

a broad suite of species associated with early succession.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 25

For species that are not in decline and whose population

levels have been demonstrated to be strongly tied to

habitat, this information may suffice. However, for the

many reasons listed in the bullets above, a more informed

understanding requires us to effectively relate population

data to habitat data.

Where habitat and population data are being collected

to refine our understanding of their relationship, several

factors must be considered:

• Effects of external influences on populations, such

as those mentioned above, are likely to introduce

variability into the habitat/population relationship.

• Collection of habitat data must be consistent with the

spatial scale at which species respond to habitat.

• Different levels of habitat data specificity may be

needed for collection with different population

measures:

o Predictions of presence/absence for wildlife

can be based on broad and correlative habitat

variables;

o Predictions of population change should be based

on variables closely tied to factors inducing

population change; and

o Predictions for survival and reproduction should

be based on habitat attributes thought to directly

influence survival and reproduction, e.g., food

availability.

Considerations for relating populations and habitat

differ among the three monitoring types.

In context monitoring, species population parameters

tend to be those that are easiest to collect (e.g., presence/

absence), and the same sample points tend to be used for

multiple taxa. Statistical habitat relationships can be

generated by correlating either the number of organisms

or the presence of organisms with the collected habitat

variables. For some taxa, appropriate habitat data may

consist of major vegetation types close to the sample

point. For example, presence/absence of bird species

with small home ranges may be correlated with major

vegetation types within 0.1 miles of the sample point.

Correlations may be enhanced by including variables

representing understory structure and composition in

addition to the major vegetation type. However, for other

taxa such as mammals with large home ranges, this area

may be too small for appropriate population-habitat

correlations. For still other taxa such as amphibians and

some small mammals, knowledge of very localized and

specific features such as logs may be needed to produce

meaningful correlations. Finally, for some taxa, we do

not know a priori the scale at which habitat data must be

collected for correlation with population data. So, multiscale habitat data will likely be required in order to

develop population-habitat correlations for multi-species

context monitoring.

Determining habitat variables to be collected in conjunction with targeted monitoring is likely simpler because

it is directed at individual species or species groups in

particular situations. For example, targeted monitoring

of habitat conditions specific to the species at various

scales would be clearly identified and monitored spatially and temporally coincident with population

monitoring. Cause-and-effect monitoring also has clearly

identified species, areas of interest, management activities, and predicted population and habitat responses. For

both targeted and cause-and-effect monitoring it is important that wildlife and habitat observations are

co-located within home-ranges of the targeted species.

Selection of habitat variables should be based on conditions known or suspected to influence wildlife populations.

Existing habitat relationships models are one way to

identify the key habitat and limiting variables.
26 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 27

Implementation of effective monitoring that is useful

in meeting Forest Service management goals requires

changes in organization and investment patterns. In this

chapter we describe what needs to be changed, strategic

decisions that need to be made in order to design and

implement these changes, and partnerships that can be

strengthened to lower costs and increase benefits of

monitoring expenditures across land management

organizations.

Effective Organizational Structure

and Roles ______________________

Current situation

Organizations within the Forest Service are not currently structured to facilitate effective design and

implementation of programs to monitor terrestrial animals. With the exception of the multi-Forest monitoring

programs reviewed in Chapter 1, each National Forest

and Grassland is encouraged to conduct independent

monitoring programs, but these units are not adequately

staffed to carry out comprehensive monitoring. It is

assumed that Forest and District personnel are sufficiently trained to design rigorous monitoring programs,

and that these same personnel, with additional temporary

staff, are able to implement the monitoring programs.

There is the expectation that monitoring data can be

collected in addition to the accomplishment of other

normal duties and fire response duties. In reality,

monitoring usually is the first activity to be dropped

when other priorities compete for biologists’ time. As

a result, monitoring efforts vary in intensity and quality from Forest to Forest, fluctuate annually, and are

often short-lived.

Moreover, the current structure does not provide the

level of statistical expertise that Forest and District

biologists need in order to design a monitoring program.

As a result, monitoring designs are frequently flawed to

the extent that data are unusable or only weak statistical

inferences can be made. In many cases, small initial

changes in the sampling protocol could have produced

robust results. The lack of statistical training or access to

statisticians also severely restricts data analysis, with the

Chapter 6

Organizational Considerations

outcome that data may be collected for years and never

evaluated. The current structure does not generally provide Regional oversight of Forest monitoring programs,

so adjacent National Forests and Grasslands develop

different approaches to monitoring the same species, and

frequently, trends are not comparable between planning

units. Moreover, it is difficult for National Forests to

orchestrate multi-Forest monitoring efforts, even when

such efforts would provide ecologically meaningful data

for Forest planning purposes.

The current organizational structure also does not

promote collaboration between NFS and R&D, so opportunities to integrate cause-and-effect studies with National

Forest management are lost. Moreover, Research Stations may not be aware of the information needs of

nearby National Forests, and so they miss opportunities

to develop testable hypotheses that would directly benefit the National Forests. In some cases, joint efforts

between NFS and R&D are undertaken but ultimately fail

because treatments are altered, postponed, or canceled.

Desired condition and organization

The desired goal is to obtain information about terrestrial animals and their habitats that is meaningful for

Forest planning and enables the National Forests and

Grasslands to “provide for a diversity of plant and animal

communities” (NFMA). Ideally, this information would

be obtained through monitoring programs that occur at

the appropriate ecological scale, are reliably funded,

meet data quality standards, are consistent across planning units, and are strategically linked to specific research

questions. In order to achieve this condition, we propose

two changes in current organizational structure:

(1) strengthen Regional capability to provide leadership, coordination, and oversight of monitoring programs

and; (2) strengthen collaboration between NFS and R&D.

Regional Roles—National Forest monitoring programs

would benefit greatly if Regional capabilities were expanded to provide the necessary leadership and expertise

to obtain meaningful data. Regional offices could provide oversight of existing and proposed monitoring

programs, ensure consistency in data collection, identify

opportunities to integrate similar monitoring objectives
28 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

on adjacent Forests, and develop effective partnerships

with other agencies and organizations. With added staff,

Regional offices could also serve as a source of statistical

consultation, both for design of Forest monitoring programs and for assistance with data analysis procedures.

A key role of Regional offices should be coordination

of any monitoring of terrestrial animals that occurs at

multi-Forest or Regional scales. A coordinator should be

designated to oversee such programs with responsibility

for establishing the multi-Forest sampling frame, acquiring equipment and personnel, providing training to field

crews, serving as data steward, and ensuring that data

analyses are timely and that the results are made available

to all contributing National Forests and partners. This

coordination will require a dedicated position, either in

the Regional office or elsewhere (see Operational

Strategies).

New procedures to fund monitoring at the Regional

level should be developed. Currently, most Regions do

not have the ability to retain funds at the Regional level

for multi-Forest monitoring efforts. Most of the existing

multi-Forest monitoring programs were established when

off-the-top funding capabilities existed, whereas presently these programs are being pieced together from each

contributing National Forest. As a result, these programs

are constantly struggling for consistent funding and

sampling intensity from year to year. The ability to retain

off-the-top funds for monitoring should be reinstated at

the Regional level, because ultimately the National Forests would benefit from the efficiencies and quality of

information obtained through stable, long-term monitoring efforts.

Regional capabilities can also be strengthened by placing more emphasis on monitoring at the national level.

Although NFS is geographically too diverse to operate

most monitoring programs at the national scale, national

staff could play a significant role in promoting Regional

and Forest level monitoring programs. Nationally, the

responsibility is to develop policy related to terrestrial

animal monitoring, and to market the importance of

wildlife monitoring both within the agency and with

potential partners. National personnel, including the

Chief, should actively demonstrate the potential value

of wildlife monitoring to current agency missions, such

as the National Fire Plan and the current Off Highway

Vehicle (OHV) policy, and strive to build monitoring

direction into national regulations and policy regarding

Forest planning. National wildlife staff should build

alliances with the USGS Status and Trend Monitoring

Program, the USGS Wildlife Research Center, and other

partners as opportunities arise, and ensure that these

partnership opportunities are made available to the

Regions. Currently, these roles are not clearly identified

in the WO wildlife staff structure, so wildlife monitoring

is not receiving adequate attention nationally. By identifying national roles regarding policy development,

marketing, coordination, and partnerships, and ensuring

adequate staff to carry out these roles, Regional and

Forest level monitoring can be carried out with solid

agency support and commitment.

NFS and R&D Collaboration—Close collaboration

between NFS and R&D is needed to achieve the goals of

enhancing ecological knowledge and increasing understandings of cause-and-effect relationships. Currently,

NFS and R&D operate independently except for ad hoc

cooperative efforts. This independence is appropriate

given the distinct missions of each branch. Especially

germane is the critical need for independent science,

including freedom from the process of establishing policy

and consideration of concomitant political issues. Although this separation of missions is necessary in many

instances, it is also appropriate to formalize the notion

that collaboration within the agency can be useful in

response to certain natural resource management situations. Effective monitoring of management activities

constitutes one such situation. Collaboration between

R&D and NFS is necessary in response to certain monitoring problems. Such collaboration would in no way

compromise the independence of the two entities. Fieldlevel line officers from both branches should be assigned

the responsibility and authority to design and implement

collaborative activities.

Nationally, R&D can play a supportive role by assisting with the development and/or review of monitoring

protocols, communicating frequently with national NFS

staff regarding collaborative opportunities, and encouraging the Research Stations to build stronger linkages

between R&D projects and the information needs of

NFS. R&D should evaluate whether the current organization is sufficient to serve these roles effectively.

Currently, the National Wildlife Program Leader for

Research carries out these and other roles regarding

wildlife monitoring.

At the Station level, R&D involvement in Regional

and National Forest monitoring programs should be

greatly increased. R&D could play key roles in context,

targeted, and cause-and-effect studies as illustrated in

figure 4. NFS and R&D would collaboratively establish

priorities both for context monitoring (boxes on left)

and for targeted and cause-and-effect monitoring (boxes

on right). Researchers would then take the lead in

developing the sample design, selecting variables to

measure, and designing the field protocol. NFS would

implement context monitoring, whereas R&D would
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 29

conduct cause-and-effect monitoring, and both might be

involved with different types of targeted monitoring. Results of context monitoring stimulate further targeted

monitoring when thresholds of tolerable change are exceeded. Results of targeted monitoring and cause-and-effect

monitoring would be used to adjust or initiate management,

and adaptive management would continue until objectives

are reached and knowledge of the system is sufficient.

Stronger collaboration between NFS and R&D would

likely require additional staffing, since Station scientists

are already fully committed to carrying out research project

assignments. Stations and Regional offices should consider a doctoral-level shared position per Research Station

with primary duties focused on monitoring. A shared

position could prove to be an effective way to develop

the integration recommended in this report between

context, targeted, and cause-and-effect monitoring.

At the National Forest level, Forest line officers and

Station project leaders can collaboratively identify a

suite of monitoring questions that relate to specific

management actions and research strategies. Together,

managers and scientists can design and lay out management treatments that implement appropriate

experimental design. Results and subsequent analyses

would serve to address the initial monitoring questions

while simultaneously providing the basis for scientists

to advance the ecological understanding needed for

informed management.

Figure 4—The collaborative roles of R&D and NFS in

terrestrial animal monitoring.

Conduct context

monitoring (NFS) Conduct targeted and

cause-and-effect

monitoring (R&D, NFS)

Select sampling frame,

sample design, 

variables to measure, 

field methods (R&D 

leads, NFS)

Determine species, 

communities, and 

locations for context

monitoring (NFS, R&D)

Evaluate data and

build models

(R&D) 

Determine priorities for 

targeted and causeeffect monitoring (NFS)

Evaluate causes of

population change

(R&D) 

Design and

implement new 

management 

(NFS)

Objective reached 

and knowledge

sufficient (NFS)

Select sampling frame,

sample design, variables

to measure, field methods

(R&D leads, NFS) 

Adaptive

management

Use hypotheses to identify

key processes, variables (R&D) 

Threshold of change exceeded
30 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

There are examples at both the National Forest and

Regional level of successful collaboration between NFS

and either R&D or university research. The Southern

Research Station has conducted a number of studies,

funded by the Ouachita National Forest and partners, on

the effects of different burn intensities and seasons on

wildlife species, which have aided National Forests in the

Southern Region to plan future prescribed burns. The

University of Montana has initiated four short term

cause-and-effect studies related to landbirds, funded by

the Northern Region: landscape factors affecting cowbird distribution (Young and Hutto 1999), effects of

partial-cut timber harvest (Hutto and Young 2002), effects of thinning and burning in ponderosa pine, and

effects of wildfire. Published results of the first two

studies are available for incorporation into relevant planning documents.

The Birds and Burns Network conducts targeted monitoring of prescribed fire to examine fire effects on

populations and habitats of wildlife in ponderosa pine

forests in eight states across the western United States.

The target wildlife species are cavity-nesting birds and

songbirds (also small mammals at selected locations).

This effort has been underway since 2002 and is funded

by several sources, including the Joint Fire Sciences

Program, several National Forests, the Intermountain

Region fire program, and the National Fire Plan. Similarly, Fire and Fire Surrogates was established in 2000 to

understand the effects of alternative methods for fuel

reduction and forest restoration. Funded by the Joint Fire

Sciences program, several National Forests, and numerous other collaborators, the Fire and Fire Surrogates

program consists of several long-term studies that use a

common experimental design on 13 sites nationwide.

Examples of wildlife monitoring projects include forest

birds, small mammals, herpetofauna, and two bat species

(the eastern red bat [Lasiurus borealis] and the eastern

pipistrelle [Pipistrellus subflavus]). This program has

fostered numerous collaborative research and monitoring studies of wildlife as well. While funded

independently, each of these projects benefits through an

existing experimental framework that includes replicated treatments, random selection of experimental units

of a minimum size, and reliable agreements with local

managers to insure the maintenance of site conditions

through time.

The Pacific Southwest Region has initiated a series of

cause-and-effect studies to monitor the effects of offhighway vehicle use on various resources. The Northern

Region has worked with R&D to design and implement

a DNA based presence/absence survey for multiple species that has led to advances in both science and

information pertinent to population management. The

Sierra Nevada carnivore study (table 1) is a new collaborative effort between the Pacific Southwest Region and

the Pacific Southwest Research Station that shows promise for close coordination between R&D and NFS in the

realm of monitoring.

Operational Strategies ___________

Multi-Forest and Regional monitoring programs require substantial coordination to provide for collection

and analysis of data with consistent quality and dissemination of reliable information. We propose two alternative

approaches for achieving the needed coordination, although other approaches may also exist.

The first approach is the “timber cruising” model,

where the design and data collection protocol are established at the Regional scale, and data collection and data

quality controls are implemented at the local scale. Under

this model, the Regional office would provide the structure for data quality control, while individual units would

be responsible for all aspects of implementing the field

work, including hiring and training of personnel and

performing field reviews of data collection standards.

Regional offices would need staff to oversee quality

control and collate and analyze incoming data, but the

bulk of funds would be dispersed to individual units.

The second approach is the FIA model, where a separate organizational structure is created for all aspects of

the monitoring program. The separate structure could

exist as part of NFS, as part of R&D, or through an

outsourcing contract at the national, Regional, or multiForest level. Under this model, this separate entity

provides the structure for data quality control and carries out all aspects of the monitoring program, from data

collection through report preparation. The information is

made regularly available to all benefiting Regions and

National Forests, for use in relevant planning documents.

The timber cruising model places more burdens on

Regional and National Forest programs to provide the

personnel for carrying out the program. At the same time,

it gives the Regional office and National Forests more

control over sample design and any alterations in data

collection that might be needed during the course of the

program. Maintaining high and consistent levels of effort

and quality across multiple administrative structures and

years is a critical issue under this model.

The FIA model relieves Regional offices and National

Forests from all aspects of monitoring while providing

the National Forests with high-quality, scientifically

independent information for land management planning purposes. Under this model, a completely separate,
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 31

dedicated organization is created and relies on special

funds. Because the organization is centralized, crews

generally are traveling resulting in additional expense

associated with travel. When this model is used for

animal monitoring, the timing of surveys is critical and

the need to deploy crews for simultaneous surveys across

large areas becomes an important consideration. The FIA

model provides a very direct way to maintain quality

control over time and space. However, this model might

give the Regional office and National Forests less control

over needed changes in the monitoring program unless

the separate entity is directly managed by the Regional

office, such as under a Regional contract.

The choice of models needs further consideration,

along with other potential strategies. It is likely that

different models would fit different situations. Given the

permanent staffing associated with the FIA model, this

approach would be most appropriate for monitoring

programs that are truly intended to be long-term in scope

with little variance in data collection methods. In contrast, programs with an intended time frame of 10-20

years might fit better under the “timber cruising” model.

For now, we simply raise the awareness of the need to

choose a specific strategy in order to ensure that multiForest and Regional monitoring programs have sufficient

coordination and sufficient controls of data quality.

Partnerships ___________________

Partnerships are essential to the success of wildlife

monitoring programs, especially multi-Forest and Regional programs. Virtually all of the current long-term

monitoring programs are built on partnerships that bring

funding, technical expertise, and/or political muscle to

the programs. The Forest Service must not only maintain

these partnerships but actively create new partnerships in

support of future monitoring programs.

The success of FIA is due in large part to support from

external partners, primarily the National Association of

State Foresters, the American Forest and Paper Association, the National Council for Air and Stream

Improvement, and the Society of American Foresters.

These external groups have been effective advocates

with Congressional appropriation staffs. Moreover, FIA

receives approximately $5,000,000 in partner contributions annually.

Wildlife staffs have an excellent history of building

partnerships at national, Regional, and Forest levels for

wildlife habitat restoration and enhancement projects,

but there are fewer examples of partnerships explicitly

created for wildlife monitoring. Some current and potential partnership opportunities are given here.

International Association of Fish and

Wildlife Agencies (IAFWA)

IAFWA has been a significant partner with the Forest

Service in the realm of habitat restoration and species

conservation. IAFWA is in a position to garner support

for broad scale monitoring programs, in the same way

that state forestry programs influence the funding of the

FIA program. In order to get IAFWA’s support, however, the Forest Service needs to demonstrate more than

a potpourri of local monitoring efforts. IAFWA needs to

see a well-planned monitoring design with broad applicability, that supports the states’ need for wildlife

information, and is practical, scientifically sound, and

field tested.

State agencies

Individual state game and fish agencies will continue to

be valuable partners in monitoring programs. The success of several landbird monitoring programs, most

notably Monitoring Colorado Birds, Songbird Monitoring in the Great Lakes Region, and Nevada Bird Count,

are due to strong partnerships with state agencies (Colorado Division of Wildlife, Minnesota Department of

Natural Resources, and Nevada Department of Wildlife).

The main contribution by state agencies is funding, and

states also provide expertise and protocols for data collection. Most states tend to be interested in broad scale

monitoring designs that can be implemented statewide.

Whereas IAFWA can provide the leverage for federal

funding across all states, individual state agencies provide the local contacts for developing joint monitoring

programs at Regional and multi-Forest levels. The funding for individual states will likely be from the State

Wildlife Grants program.

BLM, NPS, DOD, and Tribes

Tribal agencies and federal land management agencies

are crucial partners for context and targeted monitoring

programs. All broad scale monitoring efforts will require

partnerships with multiple landowners in order to provide a more complete and integrated monitoring effort. In

addition to providing a more complete sampling frame,

land management agencies can provide financial support

to mutually fund a person or entity (or university) to

coordinate data collection and management.

USGS

Partnership opportunities with USGS are currently

underutilized. USGS brings expertise in ecological classification and mapping, access to the largest landbird
32 USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005

monitoring database, the Breeding Bird Survey data, and

access to statistical expertise and data analysis tools.

Opportunities for partnerships exist with the Patuxent

Research Station, with the USGS Status and Trends of

Biological Resources program, and with individual USGS

coop units.

NatureServe

The Forest Service has an MOU with NatureServe that

addresses shared goals of inventory and assessments,

ecological classification and mapping, data sharing, and

technology development. NatureServe’s expansive database, along with habitat classification and mapping

capabilities, makes it an ideal partner for context monitoring. Currently, the Forest Service NRIS database

works best at the National Forest scale, but data sharing

with NatureServe could boost NRIS capability to display

and evaluate data at multi-Forest and Regional scales. A

key Forest Service contact in this partnership would be

the FAUNA development team.

Other NGOs

The Forest Service has many successful partnerships

with organizations that support conservation of game

birds and mammals (e.g., Rocky Mountain Elk Foundation, National Wild Turkey Federation, Northern Wild

Sheep and Goat Council). Although the focus of these

partnerships is habitat restoration, the organizations also

support monitoring programs for the targeted species.

The National Wildlife Federation and Defenders of Wildlife are partners to a number of monitoring programs for

federally listed species. Other potential partners include

the National Audubon Society, Partners in Amphibian

and Reptile Conservation, and various state-based conservation organizations.

Volunteers

There is significant opportunity to use volunteers to

assist with collection of monitoring data. When a monitoring program has a clearly established sample design

and field protocol, an effective data quality assurance

component, and adequate training and supervision, the

contributions of volunteers can be substantial. The Student Conservation Association provides college students

with conservation internships while providing agencies

with volunteers for the cost of per diem, and these

volunteers have been used in thousands of state and

federal projects across the country. The Citizen Science

Program is a successful partnership between Cornell

University and various agencies, using volunteers for

data collection. The Forest Service was a recent partner

in a Citizens Science Program project that looked at the

effects of recreation on a suite of nesting forest birds.

Cornell University took the lead with sample design

development, volunteer training, and data analysis.
USDA Forest Service Gen. Tech. Rep. RMRS-GTR-161. 2005 33

Current monitoring programs for terrestrial wildlife

and habitats do not provide all the information necessary

for adaptive management. Inadequacies in monitoring

programs are long-standing, not restricted to the Forest

Service, and difficult to resolve. In a 1993 report commissioned by then-Chief of the Forest Service Dale

Robertson (U.S. Forest Service 1993), the following

problems with monitoring programs were noted:

• Monitoring and evaluation is viewed as another

“new” program which will require more money,

more time, and more people-resources which are

already stressed.

• Monitoring and evaluation requirements often are

not based on clear objectives, do not address key

management questions or do not address key issues.

• There is no incentive for doing monitoring and

evaluation, and little or no perceived risk for not

doing it.

• Monitoring and evaluation is not recognized as an

integral part of target accomplishment.

• Monitoring and evaluation costs increase unit-costs

which can adversely affect budget allocations.

• There is a lack of integration and interdisciplinary

approach in monitoring and evaluation activities

resulting in duplication of efforts and redundant or

inconsistent data.

• Monitoring and evaluation techniques, methodologies, and philosophies vary widely resulting in

inconsistent findings and reporting methods that

affect our credibility.

• Effective teamwork within the Forest Service and

with other agencies, partners and public is not readily

apparent.

• Appropriate scientific methods frequently are not

used in conducting monitoring and evaluation.

While some progress has been made, it is telling that

many of the same concerns apply to today’s monitoring

programs. Monitoring is a complex issue that requires

the allocation of significant resources. There are clearly

no rapid or easy paths to effective monitoring, and it

takes a major commitment to improve monitoring. The

following are key recommendations for continuing

Chapter 7

Critical Elements for Successful Monitoring

improvement of monitoring of terrestrial animals and

their habitats:

• Make a national commitment to improve monitoring of terrestrial animals and their habitats.

• Ensure that all monitoring contributes to adaptive

management by exploring both the causes for trends

and alternative scenarios that could reverse unfavorable trends.

• Ensure that all monitoring complies with USDA

Data Quality Guidelines.

• Implement Regional monitoring strategies that integrate habitat and population monitoring. Monitoring

habitat alone will rarely be sufficient for adaptive

management because habitat relationships are not

well understood and may not be predictable.

• Adopt and integrate three types of monitoring (context, targeted, and cause-and-effect).

• Use sound ecological principles and risk assessment

to prioritize and design monitoring activities.

• Recognize that monitoring is multi-scalar. Coordinate across ecological and administrative scales,

with emphasis on the role of the Regions.

• Establish appropriate roles and coordination for

NFS and R&D from WO through Forest levels.

• Provide adequate staffing, skills, and funding structures to accomplish monitoring objectives.

• Use partnerships and interagency coordination to

accomplish monitoring objectives.

• Ensure that individuals and teams responsible for

monitoring, development, and oversight have appropriate skills.

Following these recommendations would allow the

Forest Service, in conjunction with partners and collaborators, to identify appropriate monitoring questions

and designs for terrestrial animals and habitats and

collect data needed for adaptive management over the

long-term.

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The Rocky Mountain Research Station develops scientific information and technology to improve management, protection, and use of

the forests and rangelands. Research is designed to meet the needs

of National Forest managers, Federal and State agencies, public and

private organizations, academic institutions, industry, and individuals.

Studies accelerate solutions to problems involving ecosystems,

range, forests, water, recreation, fire, resource inventory, land reclamation, community sustainability, forest engineering technology,

multiple use economics, wildlife and fish habitat, and forest insects

and diseases. Studies are conducted cooperatively, and applications

may be found worldwide.

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2150 Centre Avenue, Building A, Fort Collins, CO 80526

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