Adaptive Management

The U.S. Department of the Interior

Technical Guide

Adaptive Management Working Group

Chair: Olivia Barton Ferriter

Director, Conservation, Partnerships & Management Policy

Lead Authors

Byron K. Williams, Robert C. Szaro, and Carl D. Shapiro

Other Contributors

Robert Adamcik, Mary Boatman, Sarah Bransom,

Jeremy Casterson, John Fay, Scott Florence,

Douglas Growitz, Caroline Hermans, Fred A. Johnson, James Kendall,

Dennis Kubly, Michael Mayer, Susan Moyer, Malka Pattison,

Randall Peterson, Laura van Riper, Michael Runge, Robert Snow,

Christine Turner, and Rich Whitley

Book Design

Vitmary Rodriguez
U.S. Department of the Interior

For more information on the Technical Guide, please visit: 

http://www.doi.gov/initiatives/AdaptiveManagement/

2009 edition—updated (first edition—2007)

Suggested citation: 

Williams, B. K., R. C. Szaro, and C. D. Shapiro. 2009. 

Adaptive Management: The U.S. Department of the Interior 

Technical Guide. Adaptive Management Working Group, U.S. 

Department of the Interior, Washington, DC. 

International Standard Book Number: 978-1-4133-2478-7

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

U.S. Government.
Preface

The Department of the Interior (DOI) Adaptive Management Working Group (AMWG) sponsored the development of this technical guide to clearly and consistently define adaptive management and describe conditions for its 

implementation. AMWG membership includes representatives from across DOI’s bureaus and offices.

A writing team of resource managers, technical experts, and other specialists worked with AMWG to address 

four basic questions concerning adaptive management: (1) What is adaptive management? (2) When should it be used? 

(3) How should it be implemented? (4) How can its success be recognized and measured? These questions were used 

to organize both the writing effort and the structure of the guide itself, with individual chapters addressing each of the 

questions. 

The authors sought to describe adaptive management at an appropriate level of technical detail, while remaining 

focused on its definition, operational components, and conditions in which it applies. A key challenge was to provide 

sufficient detail for clarification, while limiting the length and complexity of the document. 

The authors gratefully acknowledge the efforts by the many people who participated in developing this guide, 

including Maryanne Bach, Donna Brewer, Tara Conrad, John Dennis, Mike Ferguson, Larry Finfer, Gary Fraser, Ken 

Havran, Jacob Hoogland, Rick Lemon, Kim Magraw, Chris Pease, Steve Tyson, Ben Tuggle, John Vitello, Suzanne 

Weedman, and Tom Weimer. The authors also thank the people who provided valuable comments as reviewers, 

including Charles Baxter, Robert Fisher, Scott Florence, Clint Moore, Roger Sayre, and Brent Uilenberg. 

i
ii
Contents

Preface............................................................................................................................................................. i

Problem-Scoping Key for Adaptive Management.......................................................................................... iv

Executive Summary......................................................................................................................................... v

CHAPTER 1: WHAT IS ADAPTIVE MANAGEMENT?.................................................................................. 1

1.1. Decision making and natural resource management......................................................................................... 2

1.2. Operational definition of adaptive management............................................................................................... 4

CHAPTER 2: WHEN SHOULD ADAPTIVE MANAGEMENT BE USED?..................................................... 9

2.1. Conditions that warrant an adaptive management approach.............................................................................. 9

2.2. Institutional context for adaptive management................................................................................................. 13

2.3. Limitations of adaptive management.............................................................................................................. 15

2.4. Benefits and challenges in using adaptive management.................................................................................... 17

CHAPTER 3: HOW SHOULD ADAPTIVE MANAGEMENT BE IMPLEMENTED?..................................... 21

3.1. Operational sequence for adaptive management............................................................................................... 21

3.2. Legal considerations when applying adaptive management............................................................................... 38

CHAPTER 4: WHEN IS ADAPTIVE MANAGEMENT SUCCESSFUL?......................................................... 49

4.1. Recognizing success in adaptive management................................................................................................. 49

4.2. Key questions for successful implementation.................................................................................................. 53

CHAPTER 5: OTHER OPERATIONAL ISSUES............................................................................................. 59

5.1. Uses of information in natural resource management....................................................................................... 59

5.2. Accounting for uncertainty in adaptive management........................................................................................ 61

5.3. The measurement of learning......................................................................................................................... 62

5.4. Learning organizations.................................................................................................................................. 62

5.5. Realistic expectations for adaptive management.............................................................................................. 63

CONCLUDING REMARKS............................................................................................................................. 65

References........................................................................................................................................................ 66

Key Terms......................................................................................................................................................... 71

iii
Problem-Scoping Key for Adaptive Management

 The following key can help in dissecting a particular management problem and determining whether adaptive 

management is an appropriate approach to decision making. If the answer to any question in the key is negative, then an 

approach other than adaptive management is likely to be more appropriate. 

1. Is some kind of management decision to be made? 

 (see Sections 1.1, 2.1, 2.3, 3.1, and 5.5)

 No – decision analysis and monitoring are unnecessary when no decision options exist.

 Yes – go to step 2.

2. Can stakeholders be engaged?

 (see Sections 1.1, 1.2, 2.1, 3.1, and 4.2)

 No – without active stakeholder involvement an adaptive management process is unlikely to be effective.

 Yes – go to step 3.

3. Can management objective(s) be stated explicitly? 

 (see Sections 1.2, 2.1, 2.2, 2.3, 3.1, 4.2 and 5.1)

 No – adaptive management is not possible if objectives are not identified. 

 Yes – go to step 4.

4. Is decision making confounded by uncertainty about potential management impacts? 

 (see Sections 1.1, 1.2, 2.1, 3.1, 4.1, 4.2 and 5.2)

 No – in the absence of uncertainty adaptive management is not needed.

 Yes – go to step 5.

5. Can resource relationships and management impacts be represented in models?

 (see Sections 1.2, 3.1, 4.2, and 5.1)

 No – adaptive management cannot proceed without the predictions generated by models.

 Yes – go to step 6.

6. Can monitoring be designed to inform decision making?

 (see Sections 2.1, 2.3, 3.1, and 4.2)

 No – in the absence of targeted monitoring it is not possible to reduce uncertainty and improve management. 

 Yes – go to step 7.

7. Can progress be measured in achieving management objectives?

 (see Sections 1.1, 3.1, 4.1, and 4.2)

 No – adaptive management is not feasible if progress in understanding and improving management is 

 unrecognizable. 

 Yes – go to step 8.

8. Can management actions be adjusted in response to what has been learned?

 (see Sections 1.2, 2.1, 3.1, 4.1, 4.2, 5.3, and 5.4)

 No – adaptive management is not possible without the flexibility to adjust management strategies.

 Yes – go to step 9.

9. Does the whole process fit within the appropriate legal framework? 

 (see Sections 2.3, 2.4, 3.2, 4.1, and 4.2)

 No – adaptive management should not proceed absent full compliance with the relevant laws, regulations, 

 and authorities. 

 Yes – all of the basic conditions are met, and adaptive management is appropriate for this problem. 

iv
Executive Summary

The purpose of this technical guide is to present an operational definition of adaptive management, identify the 

conditions in which adaptive management should be considered, and describe the process of using adaptive management for managing natural resources. The guide is not an exhaustive discussion of adaptive management, nor does it 

include detailed specifications for individual projects. However, it should aid U.S. Department of the Interior (DOI) 

managers and practitioners in determining when and how to apply adaptive management. 

Adaptive management is framed within the context of structured decision making, with an emphasis on uncertainty 

about resource responses to management actions and the value of reducing that uncertainty to improve management. 

Though learning plays a key role in adaptive management, it is seen here as a means to an end, namely good management, and not an end in itself. The operational definition used in the guide is adopted from the National Research 

Council, which characterizes adaptive management as an iterative learning process producing improved understanding 

and improved management over time:

Adaptive management [is a decision process that] promotes flexible decision making that can be 

adjusted in the face of uncertainties as outcomes from management actions and other events become 

better understood. Careful monitoring of these outcomes both advances scientific understanding and 

helps adjust policies or operations as part of an iterative learning process. Adaptive management also 

recognizes the importance of natural variability in contributing to ecological resilience and productivity. 

It is not a ‘trial and error’ process, but rather emphasizes learning while doing. Adaptive management 

does not represent an end in itself, but rather a means to more effective decisions and enhanced benefits. 

Its true measure is in how well it helps meet environmental, social, and economic goals, increases 

scientific knowledge, and reduces tensions among stakeholders.

Adaptive management as defined here involves ongoing, real-time learning and knowledge creation, both in a 

substantive sense and in terms of the adaptive process itself. It is described in what follows in a series of 9 steps, as 

summarized in section 4.1, involving stakeholder involvement, management objectives, management alternatives, 

predictive models, monitoring plans, decision making, monitoring responses to management, assessment, and adjustment to management actions. An adaptive approach actively engages stakeholders in all phases of a project over its 

timeframe, facilitating mutual learning and reinforcing the commitment to learning-based management. Adaptive 

management in DOI is implemented within a legal context that includes statutory authorities such as the National 

Environmental Policy Act (NEPA), the Endangered Species Act, and the Federal Advisory Committee Act.

For many important problems now facing the resource management community, adaptive management holds great 

promise in reducing the uncertainties that limit the effective management of natural resource systems. For many conservation and management problems, utilizing management itself in an experimental context may be the only feasible way 

to gain the system understanding needed to improve management. 

Though it is commonly thought that an adaptive approach can produce results quickly at low cost, the opposite is 

more likely to be true. An initial investment of time and effort will increase the likelihood of better decision making and 

resource stewardship in the future, but patience, flexibility, and support are needed over the life of an adaptive management project. For these reasons it is important to carefully consider the potential use of an adaptive approach, and to 

engage in careful planning and evaluation when adaptive management is used.

v

 

Adaptive management is a systematic approach 

for improving resource management by learning from 

management outcomes (1). Its origin can be traced back 

to ideas of scientific management pioneered by Frederick 

Taylor in the early 1900s (2,3). Various perspectives 

on adaptive management are rooted in parallel concepts 

found in business (total quality management and learning 

organizations [4]), experimental science (hypothesis 

testing [5]), systems theory (feedback control [6]), 

and industrial ecology (7). The concept has attracted 

attention as a means of linking learning with policy and 

implementation (8,9). Although the idea of learning from 

experience and modifying subsequent behavior in light of 

that experience has long been reported in the literature, 

the specific idea of adaptive management as a strategy for 

natural resource management can be traced to the seminal 

work of Holling (10), Walters (11), and Lee (12).

Adaptive management as described here is 

infrequently implemented, even though many resource 

planning documents call for it and numerous resource 

managers refer to it (13). It is thought by many that 

merely by monitoring activities and occasionally 

changing them, one is doing adaptive management. 

Contrary to this commonly held belief, adaptive management is much more than simply tracking and changing 

management direction in the face of failed policies, 

and, in fact, such a tactic could actually be maladaptive 

(14). An adaptive approach involves exploring alternative ways to meet management objectives, predicting 

the outcomes of alternatives based on the current state 

of knowledge, implementing one or more of these 

alternatives, monitoring to learn about the impacts of 

management actions, and then using the results to update 

knowledge and adjust management actions (15). Adaptive 

management focuses on learning and adapting, through 

partnerships of managers, scientists, and other stakeholders who learn together how to create and maintain 

sustainable resource systems (3).

The purpose of this technical guide is to present an 

operational definition of adaptive management, identify 

the conditions in which adaptive management should be 

considered, and describe the process of using adaptive 

management for managing natural resources. The guide is

not an exhaustive discussion of adaptive management, 

nor does it include detailed specifications for individual 

projects. However, it should aid both U.S. Department of 

Interior (DOI) managers and practitioners in determining 

when and how to apply adaptive management.

Chapter 1: What is Adaptive Management?

Examples of decision making in natural resource 

management include the control of water releases 

from a dam, direct manipulation of plant or 

animal populations through harvesting, stocking, 

or transplanting, and manipulations of ecosystems 

through chemical or physical changes to habitats.

1

1
1.1. Decision Making and Natural 

 Resource Management

A context for resource management involves a decision making environment characterized by multiple (often 

competing) management objectives, constrained management authorities and capabilities, dynamic ecological and 

physical systems, and uncertain responses to management 

actions. Management thus involves not only predicting 

how ecological or physical systems are likely to respond 

to interventions, but also identifying what management 

options are available, what outcomes are desired, how 

much risk can be tolerated, and how best to choose among 

a set of alternative actions. The challenge confronting 

managers is to make “good” decisions in this complex 

environment, recognizing that the quality of decision 

making in the face of uncertainty should be judged by 

the decision making process as well as progress towards 

desired outcomes.

A common problem in natural resources management 

involves a temporal sequence of decisions, in which the 

best action at each decision point depends on the state 

of the managed system. Because management actions at 

each point in time can influence change in the resource 

system from that time forward, the goal of management 

is to prescribe objective-driven strategies that account for 

both the current and future impacts of decisions. A key 

issue is how best to choose management actions, recognizing that the most appropriate management strategy is 

obscured by limited understanding. 

Often the uncertainty about management impacts 

is expressed as disagreements among stakeholders who 

have differing views about the direction and magnitude of 

resource change in response to management. An adaptive 

approach explicitly articulates these viewpoints, incorporates them into the decision making process, and uses 

management itself to help identify the most appropriate 

view about resource dynamics. In this way, understanding 

of the resource can be enhanced over time, and management can be improved.

Examples of this kind of decision problem include 

the control of water releases from a dam, direct manipulation of plant or animal populations through harvesting, 

stocking, or transplanting, and manipulations of ecosystems through chemical or physical changes to habitats.

The following management issues exemplify sequential 

decision making in natural resources in the face of 

uncertainty:

• In a newly established meta-population of wolves, how 

 many animals (if any) should be relocated periodically 

 to maximize the probability that the meta-population 

 will persist over the long term?

• What amount and timing of water release from a dam 

 will maintain downstream water quality, water quantity, 

 and living resources, including people and communities?

• How can an area be managed to minimize the impacts of 

 recreational use on flora and fauna?

• When and how much should water levels be raised or 

 lowered in an impoundment to maximize abundance and 

 availability of invertebrates for foraging shorebirds?

• How can plant communities in an area be managed so

 as to protect and sustain archeological resources in the

 area at minimum cost?

• How much forest should be cut each year as part of a 

 pine regeneration program to maximize old-growth pine 

 for use by red-cockaded woodpeckers?

• How can fuel loads be decreased while minimizing 

 effects on forested ecosystems?

• Should annual hunting-season regulations be restrictive 

 or moderate to maximize the longterm cumulative 

 harvest of mallards?

• How much and how often should herbicide be applied to 

 minimize the proliferation of the invasive plant hydrilla 

 in a group of southern lakes?

• In what order should patches of isolated bull trout 

 habitat be reconnected in a network of tributaries to 

 maximize the probability of population persistence while 

 minimizing costs?

• When and where should prescribed burns be used in a 

 collection of management units to maximize the prob-

 ability that Florida scrub-jays will persist at a refuge 

 over the long term?

2
Management of problems like these increasingly 

involves a systems approach with explicit and agreedupon objectives, management alternatives, and analytical 

approaches that can identify the most appropriate 

management strategies. Adaptive management exemplifies such an approach; however, its focus is not only on 

making good decisions in the present, but also on gaining 

experience and knowledge so that future management 

decisions can be improved.

Adaptive management as an example

of structured decision making 

The move toward accountability and explicitness 

in natural resource management has led to a growing 

need for a more structured approach to decision making. 

Improved clarity about key elements in a decision making 

process can help decision makers focus attention on 

what, why, and how actions will be taken. Activities in 

a structured approach to decision making include the 

following:

• Engaging the relevant stakeholders in the decision 

 making process

• Identifying the problem to be addressed

• Specifying objectives and tradeoffs that capture the 

 values of stakeholders

• Identifying the range of decision alternatives from 

 which actions are to be selected

• Specifying assumptions about resource structures 

 and functions

• Projecting the consequences of alternative actions

• Identifying key uncertainties

• Measuring risk tolerance for potential consequences 

 of decisions

• Accounting for future impacts of present decisions

• Accounting for legal guidelines and constraints

In the ensuing chapters it will be clear that adaptive 

management is itself a structured approach to decision 

making, in that it includes the key elements listed above. 

The distinguishing features of adaptive management are 

its emphasis on sequential decision making in the face of 

uncertainty and the opportunity for improved management as learning about system processes accumulates 

over time.

Embracing uncertainty

Making a sequence of good management decisions is 

more difficult in the presence of uncertainty, an inherent 

and pervasive feature of managing ecological systems 

(16,17). Uncertainties arise with incomplete control of 

management actions, errors in measurement and sampling 

variation, environmental variability, and an incomplete 

understanding of system dynamics (see Section 5.2). 

These uncertainties potentially degrade management 

performance and contribute to acrimony in the decision 

making process.

Perhaps not surprisingly, managers have sometimes been reluctant to acknowledge uncertainty in 

environmental assessments and management strategies 

(18). Often there is a perception that asserting certainty 

as to management impacts is more convincing, and 

acknowledging uncertainty increases the likelihood that 

recommended actions will be ignored. Acknowledgement 

of uncertain management outcomes is sometimes seen as 

an invitation for confrontation among different interest 

groups, resulting in an inability to reach timely agreement 

on a proposed action. 

Adaptive management forces stakeholders to confront 

unresolved uncertainties that can significantly influence 

management performance. An adaptive approach provides 

a framework for making good decisions in the face of 

critical uncertainties, and a formal process for reducing 

uncertainties so that management performance can be 

improved over time.

3
4

1.2. Operational Definition of 

 Adaptive Management

For the U.S. Department of the Interior to effectively 

implement adaptive management in a consistent and 

coherent manner across all bureaus, an operational definition is needed that will be applicable for all of DOI. The 

definition used in this technical guide is adopted from the

National Research Council (19):

Adaptive management [is a decision process that] 

promotes flexible decision making that can be 

adjusted in the face of uncertainties as outcomes 

from management actions and other events become 

better understood. Careful monitoring of these 

outcomes both advances scientific understanding 

and helps adjust policies or operations as part of 

an iterative learning process. Adaptive management also recognizes the importance of natural var 

ability in contributing to ecological resilience and 

productivity. It is not a ‘trial and error’ process, but 

rather emphasizes learning while doing. Adaptive 

management does not represent an end in itself, 

but rather a means to more effective decisions and 

enhanced benefits. Its true measure is in how well 

it helps meet environmental, social, and economic 

goals, increases scientific knowledge, and reduces 

tensions among stakeholders.

1.1 Key Points

Resource management involves decision making in 

an environment of multiple management objectives, 

constrained management authorities and capabilities, 

dynamic resource systems, and uncertain responses to 

management actions.

Resource management increasingly involves the 

articulation of objectives and management options 

and the use of analytical techniques to identify 

optimal management strategies.

Adaptive management is a structured approach to 

decision making that emphasizes accountability and 

explicitness in decision making.

Adaptive management is useful when there is 

substantial uncertainty regarding the most appropriate 

strategy for managing natural resources.









This definition gives special emphasis to uncertainty 

about management impacts, iterative learning to reduce 

uncertainty, and improved management as a result of 

learning. Key points in the definition are discussed in 

more detail below:

Adaptive management openly acknowledges uncertainty 

about how ecological systems function and how they 

respond to management actions (20,21). However, adaptive management is not a random trial-and-error process. 

Instead, it involves formulating the resource problem, 

developing conceptual models based on specific assumptions about the structure and function of the resource 

system, and identifying actions that might be used to 

resolve the problem. Through the monitoring of outcomes 

following management interventions, adaptive management promotes improved understanding about which 

actions work, and why.

Adaptive management is designed to improve understanding of how a system works, so as to achieve 

management objectives (20,21). Models are used in 

adaptive management to embed hypotheses about system 

behaviors and enable managers to predict the impacts of 

their activities. These predictions are the basis for learning later on. Once activities are implemented, the testing 

of underlying model assumptions against monitoring data 

provides the foundation for learning and the improvement 

of management based on what is learned.

Adaptive management is about taking action pursuant 

to desired outcomes (21). In adaptive management, the 

outcomes of decisions, assessed through followup monitoring, are compared against explicit predictions of those 

outcomes (20), with the comparative results fed back 

into decision making to produce more effective decision 

making (11,22,23,24). Actual and expected results can 

differ for many reasons: underlying assumptions are 

wrong, actions are poorly executed, environmental conditions have changed, monitoring is inadequate, or some 

combination of these problems. An adaptive approach 

helps isolate inadequacies in a management application, 

allowing adjustments to be made and management to be 

improved. 

Adaptive management requires the participation of 

stakeholders. Stakeholders include people and organizations who use, influence, and have an interest, or “stake,” 

in a given resource (25). Stakeholders should be involved 

early in the adaptive management cycle, to help assess 

the problem and design activities to solve it. Stakeholders 

also can help to implement and monitor those activities, 

and participate in the evaluation of results. Involvement 
Assess problem 

Design

Implement

Monitor

Evaluate

Adjust

Figure 1.1. Diagram of the adaptive management process.

5

of stakeholders from the beginning increases management 

effectiveness and the likelihood of achieving agreed-upon 

outcomes (25).

There are many definitions in the literature on 

adaptive management, but a common theme shared by 

them all is that adaptive management is a learning-based 

process (26). The definition used in this guide was chosen 

because it emphasizes the use of learning to improve 

management decisions and because it is germane to 

resource management in DOI.The sequence of activities 

shown in Fig. 1.1 is often used to characterize adaptive 

management. Additional structure can be incorporated 

into this sequence, by recognizing an embedded feedback 

loop of monitoring, evaluation, and management adjustments that focuses specifically on learning about the 

impacts of management. Multiple iterations of this loop 

may occur within each iteration of the overall cycle, 

accelerating learning about ecological process within the 

more comprehensive cycle that includes learning about 

the adaptive process itself (through periodic problem 

reassessment, design, and implementation). Learning at 

both levels is discussed in more detail in Section 3.1.
6

Other approaches to resource management 

Learning from the experience of management 

is certainly not a new idea, but the purposeful and 

systematic pursuit of knowledge as an explicit part of 

management has rarely been practiced. The term “adaptive management” has been used to describe a broad array 

of approaches that involve learning while doing, but the 

phrase is not always appropriate. For example, management by trial and error is sometimes described as adaptive 

management, but at best it is likely to be inefficient, and 

at worst it can retard the institutionalization of experience and learning. Nor should adaptive management be 

confused with conflict resolution, which focuses on negotiating tradeoffs among competing interests. Management 

approaches that primarily depend on expert opinion and 

advice for decision making are not by themselves adaptive. Finally, in the absence of additional structure in a 

decision making process, monitoring a managed resource 

system does not itself make an application adaptive. 

A great many resource systems are monitored in some 

manner, but in most cases the resulting data are not used 

systematically for learning and improvement in a context 

of objective-driven management. 

More formal approaches to decision making can 

be identified, depending on the amount of uncertainty 

facing managers and the capacity to influence the system 

being managed (Fig. 1.2). In an ideal situation in which 

system controllability is high and management impacts 

are predictable, formal optimal control approaches can be 

used to identify optimal management strategies. If one’s 

ability to control the system is limited, hedging strategies 

or scenario planning can be useful, depending on how 

well the effects of management can be predicted. As 

indicated in Fig. 1.2, adaptive management is appropriate 

if management can strongly influence the system but 

uncertainty about management impacts is high (27).

High

Low

Low High

Scenario 

Planning

Hedging

Adaptive 

Management

Optimal

Control

Uncertainty

Controllability

Figure 1.2. Approaches to decision making in a natural resource 

system. The appropriate approach depends on the influence 

decisions can have on system behavior and the amount of 

uncertainty about management impacts (27).
7

Adaptive management requires stated management 

objectives to guide decisions about what to try, and 

explicit assumptions about expected outcomes to compare 

against actual outcomes. It is important to know what the 

available management options and alternative assumptions are, in case the action that is tried does not work as 

expected. The linkages among management objectives, 

learning about the system, and adjusting direction based 

on what is learned distinguish adaptive management 

from a simple trial and error process. In the chapters that 

follow, we describe adaptive management formally in 

terms of objectives, management options, and models 

that embed alternative hypotheses about management 

responses. But in essence, adaptive management will be 

seen to be learning by doing, and adapting based on what 

is learned (28). A comparison of adaptive management 

with some other approaches to natural resource management is presented in Section 5.1.

Adaptive management requires stated management 

objectives to guide decisions about what actions 

to take, and explicit assumptions about expected 

outcomes to compare against actual outcomes.







1.2 Key Points

Adaptive management acknowledges uncertainty 

about how natural resource systems function and how 

they respond to management actions.

Adaptive management is designed to improve understanding of how a resource system works, so as to 

achieve management objectives.

Adaptive management makes use of management 

interventions and followup monitoring to promote 

understanding and improve subsequent decision 

making.
8
In this chapter we describe the conditions under 

which adaptive management is applicable, and highlight 

some challenges, limitations, and benefits of an adaptive 

approach to resource management.

2.1. Conditions that Warrant an Adaptive 

 Management Approach

Not all decisions can or should be adaptive. In some 

cases there is no opportunity to apply learning; in others, 

there is little uncertainty about what action to choose; 

and in still others, there is disagreement about objectives. 

But the concept of adaptive management is so intuitively 

appealing that the phrase has been applied indiscriminately, with the result that many management applications 

fail to achieve the improvements expected from adaptive 

management. In many instances, that failure may have 

less to do with the approach itself than with the inappropriate contexts within which it is purported to apply (29). 

An important question is which decision problems are 

appropriate for the application of adaptive management.

There is a considerable literature that explores reasons 

why the practice of adaptive management has not lived up 

to its promise, and extensive documentation of some of 

the more prominent failures. But only recently has attention focused proactively on those attributes of resource 

management that make a problem amenable to adaptive 

management. The following discussion draws from 

published sources as well as the experiences of management agencies within the Department of the Interior.

There are two key conditions that are mentioned in 

all thoughtful analyses. First, “there must be a mandate to 

take action in the face of uncertainty” (12,24). That is, the 

problem must be important enough to require action of 

one sort or another. Situations without this imperative can 

result in either delayed action as more information is 

acquired or action foregone altogether. Second, there 

must be the institutional capacity and commitment to 

undertake and sustain an adaptive program. This condition includes an institutional stability for long-term 

measurement and evaluation of outcomes, which should 

allow the early investment in an adaptive approach to 

pay off in long-term management. Together, these two 

conditions imply that decision makers must be motivated 

and patient, that is, they must care about improving 

management over extended time frames (12).

In addition to these two overarching conditions, 

six more conditions can be identified directly from 

the meaning and context of adaptive management, as 

described in the previous chapter. Adaptive management 

is warranted when there are consequential decisions to 

be made, when there is an opportunity to apply learning, 

when the objectives of management are clear, when the 

value of reducing uncertainty is high, when uncertainty 

can be expressed as a set of competing, testable models, 

and when a monitoring system can be put in place with a 

reasonable expectation of reducing uncertainty.

A real management choice is to be made

As described in Chapter 1, adaptive management 

is first and foremost an approach to the management 

of natural resources and not simply an opportunity to 

learn. Thus, an application of adaptive management must 

involve a real choice among management alternatives that 

affect resource systems. The variability among alternatives must be consequential (i.e., different alternatives 

produce substantively different management impacts), 

and the alternatives must be ecologically, economically, 

politically, and legally feasible.

Chapter 2: When Should Adaptive Management be Used?

9

2
The genesis of alternatives should be multidisciplinary and participatory. They can arise from within the 

management agency, from scientists or engineers working 

for, with, or in opposition to the management agency, 

from the regulated community, or from other stakeholders. Some decisions are particularly difficult because 

a suitable range of alternatives cannot be easily identified. 

In such cases, a collaborative approach in identifying 

alternative actions is especially useful.

Because natural resource systems operate at multiple 

spatial and temporal scales and involve interactions 

among many component systems, the development 

of alternative actions should account for multiscale 

responses. One consequence of this complexity is that 

several pathways may exist to achieve similar outcomes, 

with alternative pathways differing enough in some 

relevant aspects (feasibility, cost, public acceptance) to be 

considered as bona fide alternatives.

The alternatives considered in adaptive management are constrained by existing laws, regulations, and 

policies, both substantive and procedural. A number 

of substantive laws govern natural resource decision 

making (for example, Clean Water Act, Clean Air Act, 

Endangered Species Act, etc.). Of the procedural laws, 

the National Environmental Policy Act (NEPA) and its 

implementing regulations provide considerable guidance 

about developing and considering alternative management 

actions. An emerging view discussed in Section 3.2 sees 

the NEPA process as a powerful and potentially effective 

way to embody adaptive management (30).

There is an opportunity to apply learning

A condition of adaptive management is that resource 

management decisions can be revisited and modified 

over time or that multiple decisions of a similar nature 

can be made over time. That is, decision making needs 

to be iterative over time and possibly space; otherwise, 

learning cannot be applied. Many examples of adaptive 

management treat a single management unit (for example, 

a single river or a continental population of ducks) over 

time, applying the learning derived from earlier actions 

to decisions made at later times. But equally appropriate 

are situations where similar management units are each 

treated only once, and the learning accrued from treatments of some units is used in decisions about how to 

treat other units at a later time (31). 

Besides iterative decision making, several other 

considerations affect the opportunity to apply learning. 

First, perhaps obviously, the adaptation of actions must 

be possible. That is, there must be flexibility in the 

decision making process to adjust management actions 

in response to measured outcomes (32). This requires 

both flexibility in the actions themselves as well as 

flexibility within the management institutions to adopt 

the change. Second, management institutions must have 

the stability to measure outcomes and use the results at 

later times. Adaptive management sometimes has failed 

because institutions managing the process dissolved 

before the learning could be applied (33). Third, it must 

be possible to acquire understanding quickly enough 

to apply it to subsequent management decisions. Some 

ecological processes respond very slowly to management 

(for example, forest systems). If learning can occur only 

after observing slow response variables, many iterations 

of decision making may have passed before the new 

knowledge can be applied. 

Ideally the response to previous management 

actions can be assessed before a decision about the next 

management action is made. For example, the response of 

waterfowl populations to hunting regulations in one year 

can be assessed in time to inform the setting of hunting 

regulations in the following year (34). On the other hand, 

Ideally the response to previous management actions 

can be assessed before a decision about the next 

management action is made. For example, the response 

of waterfowl populations to hunting regulations in one 

year can be assessed in time to inform the setting of 

hunting regulations in the following year. 

10
11

applications of adaptive management in forestry can be 

limited by the fact that the relevant response variables 

may not be measurable until decades after a management 

action is taken (35). 

Clear and measurable management objectives 

 can be identified

An adaptive approach requires explicit and measurable objectives. As described in the next three conditions, 

uncertainty about how to achieve objectives is what 

motivates adaptive management and drives the design 

of the monitoring system. To address this uncertainty 

stakeholders must agree on the objectives. Although an 

adaptive management framework can serve to structure 

dialogue among stakeholders, adaptive management itself 

is not designed to resolve conflicts about management 

objectives. If the objectives are not clear and measurable, 

the adaptive framework is undermined.

Objectives need to be measurable for two purposes: 

first, so progress toward their achievement can be 

assessed; second, so performance that deviates from 

objectives may trigger a change in management direction. Explicit articulation of measurable objectives helps 

to separate adaptive management from trial and error, 

because the exploration of management options over time 

is directed and justified by the use of objectives.

Objectives must be relevant to the project or program 

to which they apply. An example of a project objective 

might be to increase biodiversity of amphibians by 25 

percent in a local watershed. An example of a program 

objective is that used by the U.S. Fish and Wildlife 

Service for adaptive harvest management, namely the 

maximum long-term harvest of waterfowl consistent 

with population goals in the North American Waterfowl 

Management Plan (36, 37). In both cases, the objectives 

are measurable, relevant to the management problem, and 

useful for decision making, evaluation, and learning. The 

nature and use of objectives are discussed in more detail 

in Section 3.1.

The value of information for decision 

 making is high

The fundamental motivation for adaptive management is that the impact of management actions on 

resources is uncertain, and the reduction of that uncertainty will accelerate progress in meeting management 

objectives over time (34). Although uncertainty can be 

identified in almost any resource management problem, 

its reduction does not automatically lead to better decision 

making. An adaptive management application should 

target learning that will change management actions and 

improve the ability to achieve management objectives.

The “value of information” refers to how much better 

the expected performance of a managed system would be 

if uncertainty were reduced. A high value of information 

means that the decision maker will potentially choose 

different alternatives if the system is better understood. 

With improved understanding comes better decisions, so 

that success in achieving objectives becomes more likely. 

The prospect of substantially improved decision making 

justifies the cost of monitoring and assessment (24) in 

adaptive management. Conversely, an adaptive approach 

is not warranted if the value of information is low, 

essentially because the potential improvement in management does not justify its costs. Sometimes the tradeoffs 

between costs and benefits can be made explicitly, 

particularly in applications in which an economic value 

can be ascribed to learning. 

Provided careful thinking, analysis, and modeling 

are undertaken prior to implementation, one of the 

advantages of an adaptive approach is that surprises can 

be anticipated (29). Preparing for the unexpected means 

fully acknowledging uncertainty, articulating the ways in 

which assumptions might be wrong, exploring the consequences to management of uncertainty, and having the 

appropriate monitoring in place to recognize and benefit 

from unexpected outcomes.
Uncertainty can be expressed as a set of 

 testable models

A formal approach to adaptive management uses 

the tools of structured decision analysis to inform and 

analyze the problem. A key step is to predict the effects 

of management actions that are relevant to the objectives. 

But predictions require models, whether conceptual or 

quantitative. Adaptive management utilizes multiple 

models, each imbedding a particular hypothesis about 

how the natural resource system responds to management. These models are tested with monitoring data to 

determine which model best represents system responses. 

In this way the hypotheses underlying management 

decisions can be expressed and tested.

Models are critical in an adaptive management 

process, if only as a means to encourage managers, 

scientists, and other stakeholders to think carefully 

about the structure and dynamics of the systems they are 

managing. When there is contention among stakeholders 

about how the system will respond to management, 

modeling forces stakeholders to express these differences 

as alternative hypotheses, which then can be tested. The 

models embodying the hypotheses in question also can 

be used to identify critical monitoring variables to use for 

comparing hypotheses, and they provide a framework for 

interpreting monitoring results and evaluating alternative 

actions to best achieve management objectives.

Models can be qualitative and conceptual, quantitative and highly detailed, or anywhere in between. In all 

cases, their function in an adaptive management context 

is to make predictions about how a natural system will 

respond to management actions and to evaluate the 

consequences of uncertainty. A common complaint used 

to justify not undertaking an adaptive program is that the 

data are sparse and there is too much uncertainty to build 

models. But this is precisely where adaptive management 

is most valuable—in expressing and reducing uncertainty. 

The alternative to building models of system dynamics is 

to allow the assumptions of decision makers and stakeholders—essentially, the models that exist in the minds of 

a few individuals—to remain unexpressed and untested.

A monitoring system can be established 

 to reduce uncertainty

Monitoring is fundamental for adaptive management, 

as a source of data with which to test alternative models 

and measure progress toward accomplishing management 

objectives. Simply put, adaptive management is not 

possible without effective monitoring (see Section 3.1 for 

a more detailed discussion of monitoring). 

There are important details, however, that influence 

whether a monitoring system will help reduce uncertainty 

to any useful degree, and these should be considered 

when evaluating whether to undertake an adaptive 

program. For example, anticipated effects of alternative 

actions need to be substantial, because field monitoring 

can seldom detect subtle differences. Thus, management 

experiments must be dramatic enough to produce an 

observable response from the ecosystem, or they will 

not facilitate learning (32). It is useful here to recall that 

the statistical power to distinguish among hypotheses is 

influenced by sample size and the magnitude of treatment 

effects, and these factors apply as well to an adaptive 

monitoring system. Poor monitoring precision does more 

than simply slow the rate of learning; imprecise monitoring can produce misleading evidence that supports 

inappropriate management. Inaccurate or imprecise 

monitoring can actually be counterproductive to the goals 

of management (38).

Learning is accelerated when the principles of 

experimental design—replication, randomization, and 

control—are used. Attention to these principles, and 

their incorporation where possible, will lead to more 

rapid improvements in management. The amount of 

temporal and/or spatial replication is an especially 

important design feature because it determines the 

12
13

necessary sampling intensity. All other things being 

equal, management actions that can be replicated many 

times at different locations will reduce uncertainty more 

quickly. Replication over time is also valuable (and more 

common), but typically the sample size is necessarily 

lower, and information accrues more slowly. 

A realistic assessment of the potential for monitoring 

is a critical condition for adaptive management. This 

assessment should include not only the power of the 

monitoring system and the efficiency of its design, but 

also the institutional resources needed to sustain the 

monitoring (and analysis of the resulting data) over the 

time frame required to inform management.

2.2. Institutional Context for 

 Adaptive Management

There are a number of factors associated with 

management problems that can encourage the use of 

adaptive management. These include not only certain 

characteristics of the management situation itself, but 

also the nature and commitments of implementing 

organizations.

Using pre-existing institutional structures

Certain characteristics of the record of management 

may help to determine whether adaptive management is 

appropriate for a particular situation. One is a history of 

decision making that indicates a willingness to address 

the risk of unintended and/or undesirable natural resource 

impacts. Others include previous stakeholder involvement 

in a collaborative group environment, cost sharing of 

collaborative efforts, and a demonstrated commitment 

to evaluation and scientific rigor. The existence of these 

characteristics prior to the creation of a formal program 

is a strong indication that adaptive management is potentially useful. 

An example of designing around pre-existing 

conditions is the U.S. Fish and Wildlife Service adaptive harvest management (AHM) program, which was 

built upon a series of features that were already in place 

when it was first initiated. Thus, stakeholders were 

already involved in harvest management, well developed 

models were available, a decision making process was 

in place that involved federal, state, and public interests, 

and extensive, long-term monitoring programs were 

ongoing (39). AHM was designed from the outset to 

take advantage of these preadaptations, recognizing that 

considerable uncertainty still remained about the impacts 

of harvest regulations. 

Commitment of executive leadership

Adaptive management involves an ongoing commitment of leadership and support. Soon after the initiation 

of an adaptive management project, executive leadership 

may anticipate a reduction or elimination of stakeholder 

conflict, a rapid reduction in the amount of scientific 

investigation that is needed, and early declines in funding 

needs. But adaptive management activities require 

management involvement and funding throughout the life 

of the project, not just at its inception. 

From a financial perspective, long-term funding 

highlights the commitment of implementing organizations 

to adaptive decision making, and it promotes the planning 

and implementation of the monitoring and evaluation 

needed for adaptive management. Conversely, a lack of 

long-term support limits progress in reducing uncertainty. 

The support required for an adaptive approach may 

include not only funding for monitoring and evaluation, 

but also an investment in more inclusive and robust 

decision making processes. It is essential that executive leadership be aware of uncertain outcomes and be 

prepared to make the necessary changes as adaptive 

management progresses through implementation. 

Finally, executive leadership is needed to support an 

institutional culture and the organizational arrangements 

that will acknowledge uncertainty and promote learning. 

Adaptive management flourishes in a learning organization that encourages experimentation, rewards risk taking, 

and embraces the lessons learned from experimentation. 

To successfully employ an adaptive approach in management, a philosophical shift from “expert” to collaborative 
2.2 Key Points

For adaptive management to be successful, executive 

leadership must support needed changes to existing 

institutional culture and structures.

Stakeholders must be willing to work collaboratively 

in a group environment to plan specific courses of 

action.

In order for a specific adaptive management strategy 

to work on the ground, stakeholders must support the 

strategy goals and objectives.

Implementation of adaptive management can be 

facilitated by using pre-existing structures and 

processes.

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Glen Canyon Dam

14

learning will likely be necessary. Executive leadership 

must play a critical role in the transition to a learning 

organization and in sustaining it thereafter. These issues 

are discussed in more detail in section 5.4.

Consensus on management objectives

Although technical information and scientific 

understanding are required to assess tradeoffs and levels 

of risk associated with different actions, the selection of 

an appropriate management strategy is in essence a social 

decision that requires consensus building. In order for a 

management strategy to work on the ground, stakeholders 

must support the project goals and its objectives. 

Consensus on goals and objectives at the beginning 

of an adaptive management project sets the stage for an 

iterative, adaptive management cycle (40). However, 

consensus must continue through the life of the project. 

Consensus is sustained by ongoing collaboration, through 

which the potential conflicts arising in experiential 

learning can be resolved (41,42). 

Consensus is promoted by collaborative frameworks 

that foster mutual learning, relationship building, and the 

creation of a shared understanding as the basis for agreement. Collaborative structures are in essence negotiated 

agreements among stakeholders, which are embraced and 

sustained because the stakeholders accept the outcome 

of a process they perceive to be participatory and fair 

(43,44).
2.3. Limitations of 

 Adaptive Management

Although adaptive management often can enhance an 

agency’s ability to achieve resource objectives, there are 

situations where its application may not be appropriate. 

An agency considering the employment of adaptive 

management should ensure that its use is suitable for the 

particular situation. Adaptive management should not 

be employed if one or more of the following limitations 

apply.

Decision making occurs only once

If resource management decisions cannot be revisited 

and modified over time, then adaptive management 

cannot be meaningfully employed. Many decisions are 

essentially irreversible in that follow-up adaptation is 

either infeasible or impossible. An example is the removal 

of a dam on a large river where the decision can be 

made only once. Of course, such a decision may be part 

of a larger decision making program, for example the 

management of a watershed that includes many dams, 

where learning that follows from the removal of one dam 

informs subsequent decisions about other dams.

Monitoring cannot provide useful information 

 for decision making

A suitable monitoring strategy is a key requirement 

for any adaptive management approach. Data collected 

from monitoring are used to test alternative models and 

measure progress toward management objectives. There 

are several situations in which an effective monitoring 

program cannot be established:

• The frequency of monitoring cannot keep pace 

with changes in the natural system. If monitoring is too 

infrequent or the system changes at too rapid a pace, 

monitoring data may be unrepresentative of the resource 

system by the time a decision is to be made.

• A design for experimental management and 

monitoring cannot be developed to test hypotheses. 

If understanding of the resource system is so limited 

(or management is so constrained) that designing a 

meaningful experiment becomes problematic, adaptive 

management may not be appropriate. This problem is 

most likely to occur when the geographic scale of the 

problem is extensive, replication is difficult or impossible, 

or there are many potentially confounding environmental 

factors that combine to influence outcomes.

• A firm commitment to funding and institutional 

support for monitoring is lacking. Adaptive management 

should not be employed without a clear commitment to 

monitoring over the life of the project. If a commitment 

for monitoring is in question, it may be necessary to take 

another approach to decision making that does not rely 

on monitoring, such as expert systems, management 

intuition, or non-technical understanding of the system.

There are irresolvable conflicts in defining 

 explicit and measurable management

objectives or alternatives

If explicit and measurable management objectives 

cannot be identified or alternatives cannot be determined, 

then adaptive management is not feasible. Conflicts may 

arise in a collaborative process in which stakeholders with 

different interests fail to agree upon these components. 

One alternative in this situation is conflict resolution.

Collaborative management is never easy, and agencies 

and stakeholder groups should not abandon the approach 

until the possibility of agreement on the key components 

of adaptive management is exhausted.

Decisions that affect resource systems and 

 outcomes cannot be made

Adaptive management should only be considered in 

situations where management actions substantially influence the outcome. In certain situations, a management 

agency can only partially influence the resource system. 

For example, if an agency manages a relatively small area 

surrounded by private land, and the adaptive management 

project applies only to the agency-managed land, management activities on the private lands may well dominate 

the effect of agency actions. In such a situation, adaptive 

management is unlikely to be useful.

Some resource decisions are essentially irreversible 

in that follow-up adaptation is either infeasible or 

impossible. An example is the removal of a dam on a 

large river where the decision can be made only once. 

15
Risks associated with learning-based decision 

 making are too high.

It is sometimes considered inadvisable to use adaptive 

management when the “worst case scenario” resulting 

from a management action would be unacceptable to 

stakeholders. An example of such a situation might arise 

when management actions can lead to the extinction of 

extremely rare, threatened, or endangered resources. In 

this particular situation one approach might be to include 

management thresholds that prevent the worst-case 

scenario from occurring. 

The limits of acceptable risk can vary substantially 

among applications, so adaptive management should not 

automatically be discounted even when dealing with rare 

or fragile resources. The relevant issue here is the value 

of information (see Section 2.1), taking into account the 

risks associated with learning-based decision making. In 

assessing risks, it is important to analyze the risk of the 

“do nothing” alternative, because the risk associated with 

maintaining the status quo may well be as high or higher 

than that of the alternatives. 

In fact, an adaptive management approach often can 

alleviate the level of risk through a careful articulation of 

objectives, management alternatives, and other elements 

of the resource problem. If the levels of uncertainty and 

risk are high, an adaptive approach that includes pessimistic alternatives and very high penalties for negative 

outcomes may well be the preferred approach to management.

Each of the limitations listed above is often encountered in natural resource management. In addition, other 

conditions can undermine adaptive management, for 

example an inability to reach agreement about the key 

elements of structured decision making, or a mismatch 

between the rate of change in system process and the 

frequency of management interventions. When such limitations are encountered, decision makers should question 

whether the use of adaptive management is appropriate, 

and perhaps consider other approaches to manage public 

lands and resources. 

2.3 Key Points

Adaptive management is not appropriate for singletime decision making.

It is not appropriate if monitoring information is 

unavailable to decision makers.

It is not appropriate if there are irresolvable conflicts 

about objectives or decision alternatives.

It is not appropriate if management interventions 

cannot influence system behaviors in ways that affect 

management returns.

It is not appropriate if there is not a commitment to 

sustained funding for monitoring and assessment. 











An example of high-risk management involves 

management actions that can lead to the 

extinction of extremely rare, threatened, 

or endangered resources.

16
2.4. Benefits and Challenges in 

 using Adaptive Management

Benefits

An adaptive approach provides flexibility 

 to act in the face of uncertainty

Adaptive management helps managers address 

resource issues by providing the flexibility to adjust 

management actions as additional understanding is 

gained. It can help determine whether management 

actions are having desired effects and whether mitigation 

measures are cost effective. The flexibility of adaptive 

management to respond to changing environmental conditions and improved understanding can result in better 

decision making.

An adaptive management 

approach is learning based

The concept of learning is central to adaptive 

management (8), with learning seen as a means to good 

management. Learning within the context of adaptive 

management derives from evaluation of previous 

management actions, the results of which are used to 

inform subsequent actions (8). The premise of an adaptive 

management approach is that the behavior of resource 

systems is uncertain but management is required anyway, 

and the reduction of uncertainty over time can lead to 

better management. 

Adaptive management specifies what 

 actions are to be taken and when

Adaptive management produces management strategies that specify what management actions are to be 

taken and how and when they should be adjusted. These 

strategies are based in turn on an explicit articulation of 

the management problem, what is known (and not known) 

about the resource system being managed, and the 

objectives of management (8). This explicitness makes 

it possible for stakeholders to focus on the key attributes 

involved in learning-based resource management, while 

avoiding the confusion and controversy that typically 

results when key management elements are not open to 

discussion and negotiation.

Adaptive management encourages long-term 

 collaboration among stakeholders

Adaptive management brings resource managers, 

researchers, and other stakeholders together and encourages long-term collaboration through the development 

and strengthening of institutional ties (45). These ties are 

important in maintaining the level of support needed to

successfully implement adaptive management. Through 

strengthened collaboration, stakeholders can be encouraged to remain involved over the life of an adaptive management project.

Adaptive management promotes 

 optimal decision making with the 

 information available

Adaptive management fosters the acquisition of new 

knowledge and understanding by specifying hypotheses 

and designing management alternatives to test them 

against field data (8, 46). The information accumulated 

through this process is used to adjust strategy periodically 

on the basis of what has been learned. In this sense, adaptive management allows decision makers at each juncture 

to make the best decisions they can with the information 

available at that time (41).

17
Challenges

Institutional reluctance to change

For adaptive management to be embraced on an 

institutional level, refinements in existing approaches 

to natural resource management are needed (8,47). An 

example might involve new ways of dealing with overlapping responsibilities and authorities among agencies, 

so as to reduce or eliminate resistance to one agency’s 

adaptive management project by another agency that has 

regulatory oversight. 

Some barriers to implementation go beyond the 

operational level. One such barrier is an inadequate 

recognition that the targets of resource management 

are rapidly becoming more inclusive. For example, 

ecosystem management traditionally is approached by 

targeting only one or a few system attributes, failing 

to account for the broader resource context and its 

implications for resource management. A framework for 

adaptive management allows the resource problem to be 

identified in a more inclusive context that includes issues 

like system viability and sustainability. 

Another institutional barrier is a lack of the resource 

planning and design capacity that are required for adaptive management (see Section 3.1). For example, agency 

programs often have an inadequate capacity for the 

outcome-based monitoring needed for adaptive management. The problem here is not so much an inability 

to understand the process and procedures of adaptive 

management, as it is that program operations focus on 

tracking and assessment of activities and outputs rather 

than resource outcomes.

Implementation of adaptive management will require 

a shift in focus toward resource sustainability as a strategic target, with resource planning and design, decisionbased monitoring, and assumption-driven research as 

central activities. In essence, adaptive management will 

require refinements to the resource management business 

model and adjustments in the organizational and institutional arrangements that support it. See Section 5.4 for 

further discussion on organizational roles 

 and implications.

Commitment to monitoring and evaluation 

 over the life of the project

In times of shrinking funding, managers must carefully assess the cost of the monitoring and assessment 

that inform decision making in an adaptive approach. 

The costs of timely monitoring and assessment over 

extended time scales are substantial, and often appear 

to be especially high at the outset of a project when 

compared with the costs of trial and error with only 

incidental monitoring (8). Agencies must be willing to 

make a commitment to cover the costs of monitoring 

and evaluation over the life of an adaptive management 

project; otherwise, discontinuing the monitoring effort 

will lead quickly to the cessation of adaptive decision 

making. Agencies also need to commit to a schedule for 

monitoring, analysis, and re-examination of decisions as 

understanding accumulates. In the absence of a commitment of resources for timely monitoring and evaluation 

over the life of the project, the use of adaptive management becomes problematic.

Significant time lags between management 

 actions and their impacts

Time itself is a challenge in implementing adaptive 

management (48). In many cases, the overall costs 

associated with adaptive management are tied as much to 

the timeframe of the project as they are to its complexity. 

Some adaptive management plans require years of 

monitoring in order to be able to ascertain the results of 

an initial action. Of course, models that forecast some 

future endpoint as a consequence of a decision or series of 

decisions should also be able to predict resource status at 

various intervals prior to that endpoint, allowing management assessments to be performed on the predicted status 

over an abbreviated interval. The problem of time lags 

is further complicated by the fact that individual decision makers and/or managers rarely remain in the same 

position over the needed timeframes (8). 

Implementing adaptive management in a 

 complex legal environment

Legal issues must be weighed when deciding whether 

to implement an adaptive management strategy. In many 

cases, a NEPA decision process is required of federal 

agencies. 

18
2.4 Key Points

Adaptive management promotes cooperative decision 

making in the face of uncertainty about the impacts of 

management interventions.

Adaptive management produces management strategies consisting of actions that are tied to resource 

status and current understanding.

Adaptive management brings resource managers, 

researchers, and other stakeholders together and 

encourages long term collaboration.

Resistance to institutional change and a complex legal 

environment can be impediments to adaptive 

management.

Agencies must be willing to commit to monitoring 

and evaluation over the life of an adaptive management project.

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







Projects should be tailored to the resource being 

managed, the environmental conditions of the project 

area, the project objectives, and the capabilities of the 

manager to implement decisions and carry out the 

subsequent monitoring and assessment.

Depending on the resource problem and the scope of 

the project, requirements under other federal laws may 

also be triggered. Some laws may constrain or even 

preclude the use of adaptive management (see Section 

3.2); on the other hand, legal considerations sometimes 

can be successfully integrated with it. Indeed, the case 

studies included on the enclosed CD suggest that adaptive management might make NEPA compliance more 

effective and efficient in some instances.

Collecting enough information 

to evaluate progress

The amount of data required for adaptive management depends on the system being managed, the actions 

being implemented, the objectives of management, and 

the amount of uncertainty (49,50). Project costs obviously 

increase for applications that require more frequent 

monitoring and the collection of larger amounts of data 

during each monitoring event. 

Projects should be assessed individually, with each 

project tailored to the resource being managed, the 

environmental conditions of the project area, the project 

objectives, and the capabilities of the manager to implement decisions and carry out the subsequent monitoring 

and assessment. A considerable amount of up-front planning may be required; however, an initial investment of 

time and effort increases the likelihood of better decision 

making and resource stewardship in the future.

19
20
From an operational point of view, adaptive management simply means learning by doing (i.e., learning 

through management) and adapting what one does 

based on what is learned (i.e., adjusting management 

as understanding improves). Learning contributes to 

management by providing information on which to base 

management strategies, and management reinforces 

learning by implementing actions that are useful in 

investigating the resource system. A sequential application of these component activities should produce both 

improved understanding of resource dynamics and 

improved resource management (51). 

As noted earlier, the emphasis in an adaptive 

approach is first and foremost on resource management. 

The value of understanding, and the monitoring and 

analysis that produce understanding, is inherited from 

their contributions to the objectives of resource management. Although the focus is on learning, the ultimate goal 

of the effort is smart management.

This chapter focuses on the implementation of 

adaptive management. The actual process of using 

adaptive management is discussed in terms of its key 

structural elements and the integration of these elements 

into an iterative cycle of management, monitoring, and 

assessment. Also highlighted are some legal issues that 

focus on compliance with the relevant environmental and 

administrative laws. 

3.1. Operational Sequence for 

 Adaptive Management

Implementation of adaptive management can be 

described in terms of two phases: a set-up phase in 

which its key components are developed, and an iterative 

phase in which the components are linked together in a 

sequential decision process. The set-up phase has five 

structural elements, namely stakeholder involvement, 

management objectives, potential management actions, 

predictive models, and monitoring plans. The iterative 

phase uses these elements in an ongoing cycle of learning 

about system structure and function, and managing based 

on what is learned.

Although adaptive management is described here 

by a series of steps in the set-up and iterative phases, 

it is important to recognize that adaptive management 

is a complex endeavor that includes much more than 

simply following a sequence of steps. Properly executed, 

the process involves ongoing, real-time learning, both 

in a technical sense and in terms of process itself. 

Stakeholders need to be engaged at the stage of initial 

problem formulation and remain engaged throughout 

implementation. By implication, an adaptive approach to 

management improves on the traditional communications 

approach in which scientists create knowledge and then 

pass it on to practitioners, with other stakeholders acting 

as passive observers (51). Instead, an adaptive approach 

actively engages parties in all phases of the project, 

facilitating mutual learning and reinforcing the commitment to learning-based management. 

Set-up phase

Adaptive management prescribes the integration 

of decision making, monitoring, and assessment into 

an iterative process of learning-based management. To 

implement the process, certain elements must be put 

in place, and then used in a cycle of iterative decision 

making. 

Chapter 3: How Should Adaptive Management be Implemented? 3

21
Step 1- Stakeholder involvement

Ensure stakeholder commitment to adaptively 

manage the enterprise for its duration

Of particular importance in adaptive management is 

that stakeholders assess the resource problem (see Fig. 

1.1) and reach agreement about its scope, objectives, 

and potential management actions, recognizing that 

differences of opinion about system responses may exist 

even when there is consensus on these issues. Clearly, 

agreement about scope, objectives, and interventions is 

not possible in the absence of stakeholder involvement in 

establishing them. Thus, a first step in adaptive management is to engage the appropriate stakeholders (See Case 

Study 1 and BLM Collaboration Desk Guide on CD for a 

discussion of stakeholder involvement). 

Several activities are involved. First, stakeholders 

must be identified and encouraged to participate. This 

might involve personal contacts, public announcements, 

formal consultations, or other means. Second, a process 

must be implemented that solicits stakeholder input in 

the design of the adaptive management project and, in 

particular, the identification of management objectives 

and potential management actions. Depending on the 

project, this may require formal or informal consultations, 

legally mandated and administered procedures, or other 

approaches. In any case, stakeholder involvement in 

identifying key components of the project should be open 

and transparent. Third, stakeholders must commit to an 

agreed-upon process of reducing uncertainties and/or 

disagreements about the effects of management. That is, 

having reached agreement on the scope of the management problem and its objectives and potential interventions, stakeholders must then commit to an iterative 

process of objective-driven decision making.

In general, the group of stakeholders should be broad 

enough to express the uncertainty (perhaps through 

disagreement) that is the focus of adaptive management. 

However, adaptive management is not prescriptive about 

who the stakeholders are, how many there are, or what 

their perspectives or values are. The scale and complexity 

of stakeholder involvement can vary greatly among 

projects and is influenced by the scale and complexity 

of the application itself. Many adaptive management 

projects involve only one or a few stakeholders, as with 

a refuge manager who is unsure how to manage water 

control structures on the refuge, or a farmer who is unsure 

how to seed and cultivate some of his farmland, or a fish 

hatchery manager who is uncertain about how long to 

age fish stocks before releasing them in a reservoir. Other 

projects may involve a large number of disparate stakeholders, as with the seasonal release of water from a dam 

on a large river, or the production of timber on a large 

regional forest, or the management of a coastal fishery. 

As a general rule, the number of stakeholders, and the 

breadth of their perspectives and values, will vary with 

the geographic, ecological, administrative, and political 

scale of the adaptive management project.

Stakeholders should play a role in identifying 

the scope of the project as well as the objectives and 

potential management actions. Within a context of legal 

and institutional boundaries, stakeholders help to define 

the operating environment of an adaptive management 

project, and they influence both decision making and 

the opportunity to learn. All too frequently, a decision 

making process is undertaken without agreement about 

scope, objectives, and management alternatives. Without 

this agreement, any management strategy likely will 

be viewed as reflecting unshared objectives and inappropriate or unnecessary limitations on management. 

The prospects for conflict increase dramatically in such a 

situation.

Case Study 1: For decades, there has been concern about the 

ecological impacts of the operation of Glen Canyon Dam on 

downstream resources, particularly the riparian areas along the 

Colorado River in the Grand Canyon, Arizona. In recent years 

efforts have been made to evaluate and adapt management 

actions for resource protection through experiments that are 

monitored for their effects in the Grand Canyon. (See included 

CD for additional information on this project).

22
The success of an adaptive management project 

requires an adequate understanding of the resource issues 

and the dedication to stay abreast of new information. The 

interface between scientific investigation and stakeholder 

understanding becomes increasingly difficult as proposed 

actions become more technical, and it is not uncommon 

for both scientists and stakeholders to become impatient 

and frustrated. Engagement and communication among 

stakeholders is critically important if arguments on the 

meaning of science are to be minimized.

Of particular concern in adaptive management is the 

asymmetry between management interventions, which 

often must be implemented in a relatively short amount of 

time, and their impacts, which sometimes require years or 

even decades to be recognized. This asymmetry imposes 

special demands on stakeholders to remain engaged over 

an adequate timeframe for learning to occur. Among other 

things, it may be useful, and even necessary, to design 

monitoring and assessment programs at different scales, 

so as to build understanding incrementally while anticipating unexpected results that may require adaptations in 

the project. Otherwise, premature interruption of monitoring efforts, or stakeholder pressure to terminate the 

application of adaptive management, could short-circuit 

the expected benefits of improved decision making.

Recognizing stakeholder interests and ensuring 

their involvement for the duration of the management 

enterprise are requirements for learning–based management in general. But involvement is more than passive 

participation in information sharing and other stakeholder 

prerogatives. Adaptive management involves the 

commitment of time, resources, and active engagement 

of stakeholders. These requirements often are underestimated. If stakeholders are unwilling to dedicate sufficient 

time and effort, group deliberations have the potential 

to devolve into value-based arguments, minimizing the 

positive impacts of monitoring and evaluation. Program 

documents should explicitly state the responsibilities of 

the stakeholders, and every effort must be made to ensure 

that stakeholders will meet those responsibilities over the 

life of the project.

Step1- Key Points

A strong effort must be made to identify and engage 

the appropriate stakeholders.

All phases of the adaptive management process must 

be open, transparent, and accessible to stakeholders.

Stakeholders must strive for agreement on scope, 

objectives, and management alternatives for the adaptive management application.

Stakeholders must commit to a process for adjusting 

management strategy over time, based on resource 

status and learning.

Stakeholder organizations must be encouraged to 

commit time and energy to adaptively manage the 

resource over the agreed-upon timeframe.

Stakeholders must commit resources for monitoring 

and assessment, in addition to decision making.













Bemidji Crude-Oil Research Project; measuring crude-oil 

thicknesses during the aquifer test. 

23
Step 2- Objectives

Identify clear, measurable, and agreed-upon 

 management objectives to guide decision 

 making and evaluate management 

 effectiveness over time

Objectives, resource status, and learning all influence 

the choice of management interventions in adaptive 

management. But objectives also play a crucial role 

in evaluating performance, reducing uncertainty, and 

improving management through time. It therefore is 

important to have clear, measurable, and agreed-upon 

objectives at the outset, to guide decision making and 

assess progress in achieving management success (See 

Case Study 2 for a discussion of setting objectives).

The term “objective” is used here to mean some 

desired outcome or performance measure that can be used 

to guide decision making and measure success. Objectives 

typically are expressed in terms of management performance over the timeframe of a project. For example, 

measures might be harvest yield, population size, water 

flows, or the probability of a negative impact on resource 

status, with an objective of maximizing accumulated 

harvest, achieving a desired population size, maintaining 

water flow, or minimizing a probability of extinction.

Because management objectives are used to guide 

decisions in managing (and often changing) certain 

aspects of a target resource through time, they should be 

more specific than common, “broad-brush” statements 

or overall program purposes that appear in many project 

documents. For example, generic statements such as 

“provide public access and recreational opportunities” or 

“improve water quality to enhance and restore commercial fishing” are purpose statements indicating why 

management is to be undertaken, rather than objectives 

that can help to guide decision making. 

Objectives should address the resource issue or 

problem that initially motivated management, and reflect 

the social, economic, and/or ecological values of stakeholders. Underlying an adaptive approach is the recognition that stakeholders influence what is to be managed 

and under what circumstances. Finding common ground 

among disparate and often contentious parties is not an 

easy task when there are differences in understanding 

about the resource system and differences in ideas about 

the desired focus and direction of management. For objectives to be realistic and mutually acceptable, parties must 

work toward an agreement on the purpose and approach 

to resource management and seek a common basis for 

recognizing management success. In particular, objectives should be defined cooperatively through a dialogue 

among managers, scientists, and other stakeholders. 

In the context of adaptive management, objectives 

must be relevant to the decision making process and 

possess a number of attributes that render them useful 

as guides to management (52). To be useful for decision 

making and evaluation, objectives need to exhibit the 

following technical features: 

• Specific: 

Objectives should be unambiguous, with specific 

metrics and specific target conditions. Specificity can 

be encouraged by articulating objectives with Who, 

What, Why, and/or Where phrases.

• Measurable:

Objectives should contain elements that can be 

 readily measured, so as to promote the evaluation of 

 management actions and recognize their contributions 

 to successful management.

• Achievable:

Objectives should be based on the capacities of 

 the natural resource system being managed and 

 the political or social system within which manage-

 ment occurs.

• Results-oriented:

Objectives should contain for resource endpoints 

 and/or conditions representing their achievement. 

 For example, a results-oriented habitat objective 

 might describe the habitat conditions expected when 

 the objective is achieved.

• Time-fixed:

Objectives should indicate the timeframe for achievement, consistent with the duration of the project. 

Project implementation may be in stages, but the 

overall timeframe should be clear.

24
Case Study 2: The Trout Creek Mountain Restoration focuses 

on compatibility between livestock grazing and critical habitat 

for listed Lahontan cutthroat trout within the Trout Creek and 

Oregon Canyon Mountains, Oregon. This time sequence shows 

the dramatic changes along Cottonwood Creek, V Pasture, 

looking downstream starting in 1988. Until 1989 this pasture 

was grazed during the summer every year. Despite changes in 

the timing and intensity of grazing, chronic trespass prevented 

acceptable levels of riparian improvement. Enforcement, 

changes in permittees, and fence repairs since then have 

allowed 2 years of actual rest. Note the increased reproduction 

in aspen by 2002. (See included CD for additional information 

on this project).

Step 2- Key Points

Objectives substantively influence decisions and 

management strategies. 

Objectives should incorporate the social, economic 

and/or ecological values of stakeholders, and reflect 

the value of learning over time.

To be useful as guides for decision making and evaluation, objectives should be specific and unambiguous, 

measurable with the appropriate field data, achievable 

but challenging, results-oriented, and applicable over 

the timeframe of the enterprise. 







It is often the case in adaptive management that 

there are multiple objectives for resource management. 

For example, one might seek to sustain species richness 

in a refuge, while attempting to maximize visitor use, 

maintain a harvest program for one or more species of 

wildlife, and allocate resources to these activities so as 

to minimize costs. In such a situation it is important to 

be able to weigh different objectives in terms of their 

perceived importance, so as to facilitate the comparison 

and prioritization of management alternatives.

25
Step 3- Management actions

 Identify a set of potential management actions 

 for decision making

Like any iterative decision process, decision making 

in adaptive management involves the selection of an 

appropriate management action at each point in time, 

given the status of the resources being managed at that 

time. Resource managers and stakeholders, typically 

working with scientists, have the responsibility of identifying the set of potential actions from which this selection 

is made (See Case Study 3 for a discussion about identifying management actions).

The management alternatives in an adaptive management project constitute a key element in its operating 

environment, and they can strongly influence the selection 

of a management strategy (see Section 5.1). Just as the 

choices made in daily life depend on one’s available 

options, so too are strategy choices in an adaptive 

management project constrained by the set of available 

options. If these options fail to span a reasonable range of 

management activities or fail to produce recognizable and 

distinct patterns in system responses, adaptive management will be unable to produce effective and informative 

management strategies. This argues for careful thinking 

about the potential actions to be included in a project. 

Case Study 3: The Sonoita Valley Planning Partnership is an 

ad hoc, volunteer association of Federal, State, and local agencies, user groups, organizations, and individuals with a common 

interest in the upper Cienega watershed, which includes the 

42,000 acres of public lands within the Las Cienegas National 

Conservation Area, Arizona. The goal of the partnership is to 

perpetuate naturally functioning ecosystems while preserving 

rural grasslands for future generations. (See CD for additional 

information on this project).

26
Management alternatives in adaptive management 

often focus on a potential change in resource status or 

the alteration of process rates. Examples of the former 

include culling a livestock herd to maintain a population 

at carrying capacity, stocking a lake to sustain a fishery, 

or withdrawing water from a reservoir to maintain an 

appropriate volume of water in it. Examples of the latter 

include harvest regulations that target an acceptable 

mortality rate, alteration of nesting habitat to enhance 

population reproductive rate, or control of the amount 

and timing of visitor disturbance so as to influence avian 

migration patterns positively. 

In designing an adaptive management project, 

management alternatives should be included that will 

produce different responses and thereby promote learning. 

One way to structure alternatives for this purpose 

is to limit their number, and maximize differences 

among them. An example is the Five Rivers Landscape 

Management Project (See Case study 4), which used three 

Case Study 4: The Five Rivers Landscape Management Project began in 1998 as an attempt to apply adaptive management at 

large scales. The project was designed for 32,000 acres of productive Siuslaw National Forest land in coastal Oregon. (See CD for 

additional information on this project).

different management alternatives: (1) passive management in which plantations are allowed to develop into old 

growth with no intervention other than road closures; (2) 

frequent light-touch thinning and road maintenance; and 

(3) heavy thinning followed by 30-year road closures. 

Another example involves the impact of harvest, which 

is likely to be easier (and less costly) to recognize with 

a few widely spaced harvest rates rather than many that 

are closely spaced. In both examples a smaller number 

of alternatives helps to reduce implementation costs, 

minimize problems that otherwise can arise with partial 

controllability (see Section 5.2), and highlight differential 

responses of the resource. 

Because of natural variation, resource systems often 

are extraordinarily difficult to control with management 

actions, and “cause and effect” relations are usually 

unclear and difficult to recognize. It is important to 

include options that can help to reduce these difficulties, though this sometimes leads to a broader range of 

27
Step 3- Key Points

Potential actions consist of activities under management control (for example, harvest, stocking, restoration).

Alternatives typically focus on alterations of resource 

status or process rates.

The suite of available actions should be designed to 

promote learning.

The alternatives should be explicit and documented.

Stakeholders should participate in the identification of 

alternatives.











potential actions than otherwise would be desireable. In 

any case, the options under consideration should always 

be designed to achieve specific objectives.

To ensure clarity and transparency it is important to 

make the management options explicit. Too often the set 

of options is unstated, and simply assumed to be recognized and understood by managers and other stakeholders. 

Ambiguity as to the alternatives under consideration can 

lead to conflict among stakeholders and the possibility of 

legal challenges to the decision making process.

The identification of management options is often a 

greater challenge than some anticipate. Just as different 

stakeholders see the resource system differently and 

identify different objectives for its management, so will 

they recognize differences in the feasibility and acceptability of management options. Even when there is rough 

agreement on their nature and extent, there still may be 

different perspectives about the appropriate number and 

composition of management alternatives. It is important 

to take the necessary time and effort to think carefully 

about these issues, so as to reach agreement on a realistic 

and politically acceptable set of alternatives.

Because of natural variation, resource 

systems often are extraordinarily difficult to 

control with management actions, and “cause 

and effect” relations are usually unclear and 

difficult to recognize.

28
Step 4- Models

Identify models that characterize different 

 ideas (hypotheses) about how the 

 system works

Models play an important role in virtually all applications of structured decision making, whether adaptive or 

otherwise. In order to make smart decisions, it always is 

important to compare and contrast management alternatives in terms of their costs, benefits, and resource consequences. Models typically express benefits and costs as 

outputs of management through time. More importantly, 

they allow one to forecast the impacts of management.

The term “model” is used here to mean a plausible 

representation of a dynamic natural resource system (See 

Case Study 5 for a discussion of model development). 

Models can be as informal as a verbal description of 

system dynamics (for example, a simple description of 

reservoir size that is positively influenced by runoff and 

negatively influenced by water release), or as formal 

as a detailed mathematical expression of change (for 

example, an age-structured multi-species model with 

density-dependent vital rates that are affected by random 

environmental changes). The models used in an adaptive 

management project are not restricted to a particular 

kind. In many instances only a few models are required 

to capture contrasting views about the system, and these 

often can be described with limited technical detail.

Case Study 5: In 1995, the U.S. Fish and Wildlife Service 

implemented an approach known as adaptive harvest management, in which managers seek to maximize sustainable harvests 

against a background of various sources and degrees of 

uncertainty. (See CD for additional information on this project).

29
Although model complexity can vary widely 

depending on the ecological and management scale of 

the application, the models used in adaptive management 

generally share certain attributes (53):

• Resources are described as changing though time, so as 

 to allow learning to occur and management to adapt to 

 learning (Fig. 3.1).

• The resource system is characterized by key components 

 of interest (for example, population size, resource 

 biomass or volume, biodiversity) that are the focus of 

 management and the targets of monitoring.

• Resource changes often are described in terms of 

 processes (for example, reproduction, mortality, spatial 

 movement) that are thought to be directly influenced by 

 management.

• Fluctuating environmental conditions are incorporated 

 as needed to characterize resource dynamics.

• Management impacts are described in terms of costs, 

 benefits, and influences on resource components or 

 processes that are highlighted in the model.

• Models are calibrated with available data and knowl-

 edge, to ensure compatibility with current understanding 

 about resource structures and functions.

Models play a key role in representing uncertainty. In 

adaptive management, structural or process uncertainty is 

captured in contrasting hypotheses about system structure 

and function, and the hypotheses are imbedded in the 

suite of models used to forecast resource changes through 

time. At any point, the available evidence will suggest 

differences in the adequacy of each of these models to 

represent resource dynamics. As evidence accumulates 

over time, the confidence placed in each model (and its 

associated hypothesis) evolves, through a comparison of 

model predictions against monitoring data. 

To be useful, the models in a particular project must 

meet certain conditions, including a requirement that 

different models predict different outcomes in response 

to management. However much two models may differ 

in the way they describe system dynamics, if both predict 

the same responses to management, then recognizing 

which is more scientifically credible will be of little use in 

improving management.

An example that highlights many of these 

points is the modeling framework used for adaptive 

harvest management of waterfowl. Adaptive Harvest 

Management (AHM) was initiated in 1995 as a process 

for setting annual regulations for the sport hunting of 

waterfowl in North America (37). For AHM, a simple 

model was used to account for associations among fall 

harvest, seasonal survivorship, and spring reproduction 

(Fig. 3.2). Contrasting hypotheses about the impact of 

harvest on annual survivorship were easily incorporated 

into different versions of the model, by describing 

different functional relations between harvest rates and 

post-harvest survival. In addition, contrasting hypotheses 

about the importance of density dependence in recruitment were incorporated by describing recruitment in 

terms of spring population size. In combination, these 

hypotheses define four models, each with its own 

predictions about harvest impacts and each with its own 

measure of confidence that evolves over time (54). The 

models and their measures of confidence characterize 

structural or process uncertainty, which is reduced over 

time as harvest actions are taken and post-harvest monitoring data are used to update the confidence measures.

resource

system

management

action

environmental

conditions

resource

system

management

action

resource

system

management

action

environmental

conditions

environmental

conditions

time

t-1 t t+1

Figure 3.1. Change in resource system as influenced by 

fluctuating environmental conditions and management actions. 

Management produces immediate returns (costs and/or 

benefits) and longer-term changes in resource status.

30
Like the management options in an adaptive 

management application, models can strongly influence 

the identification (and acceptability) of management 

strategies. If the models fail to incorporate meaningful 

hypotheses, or fail to produce recognizable differences 

in population dynamics, an adaptive approach may be 

unable to produce useful and informative strategies. This 

argues for engaging managers, resource scientists, and 

other stakeholders in a thoughtful and deliberate process 

of selecting the models to be used in an application. 

Step 5- Monitoring plans

Design and implement a monitoring plan to 

 track resource status and other key 

 resource attributes 

The learning that is at the heart of adaptive management occurs through a comparison of model-based 

predictions against estimated responses based on 

monitoring data. It is by means of these comparisons that 

monitoring is used to understand resource dynamics, and 

thus to confirm the most appropriate hypotheses about 

resource processes and their responses to management. 

By tracking useful measures of system response, well 

designed monitoring programs facilitate evaluation and 

learning in adaptive management.

In general, monitoring provides data in adaptive 

management for four key purposes:

(i) to evaluate progress toward achieving objectives;

(ii) to determine resource status, in order to identify 

 appropriate management actions; 

(iii) to increase understanding of resource dynamics 

 via the comparison of predictions against survey 

 data; and

(iv) to enhance and develop models of resource dynamics 

 as needed and appropriate.

Monitoring programs should be designed from 

the outset to inform decision making with data that 

are relevant to the management issues in the adaptive 

management project (55,56). For example, variables such 

as survival, harvest, stocking, and reproduction rates can 

be estimated with properly designed monitoring efforts 

and used to adaptively manage a biological population. 

Surveys producing such information can be invaluable 

as sources of longterm data with which to develop the 

adaptive management project (See Case Study 6 for a 

discussion about developing a monitoring plan).

fall

adults

breeding

population 

fall

young 

winter 

population

Ss

Sw

1-ha

1-hy

A

Figure 3.2. Conceptual model of the annual cycle of mallard 

population dynamics. Model includes survival rates for springsummer (Ss

) and fall-winter (Sw), along with harvest rates for 

young (hy) and adults (ha) and age ratio (A) for reproduction/

recruitment.

Step 4- Key Points

Models in adaptive management should characterize system behaviors and responses to management 

actions.

Models should incorporate different ideas (hypotheses) about how the resource system works and how 

it responds to management.

The suite of models should capture key uncertainties 

(or disagreements) about resource processes and 

management effects.

Models must be compatible with, and calibrated to, 

available data and knowledge.









31
Case Study 6: The Bully Creek Landscape Area Management 

Project of the Bureau of Land Management is within the Mal-

heur Resource Area, Vale District, Oregon. The project repre-

sents ground-level resource planning for public lands. On the 

top are views of Allotment #3 on a tributary of Cottonwood Creek 

in 2001 (first year after change in riparian management) and 

2005 (after 5 seasons of riparian management). On the bottom 

are views of the Muir Spring aspen stand (with protective fenc-

ing) in 2003 (first year after treatment), and 2006, which shows 

a close-up of the same site with continued aspen regeneration. 

(See CD for additional information on this project). 

Monitoring in adaptive management inherits its 

focus and design from the larger management context of 

which it is a part. Thus, field surveys are not motivated by 

scientific curiosity, nor are survey data gathered with only 

a vague hope that somehow they will prove useful for 

management. Instead, monitoring programs are designed 

to focus on the information needed to make manage-

ment decisions and evaluate their impacts. There may 

be scientific or other values in broad-scale surveillance 

monitoring, and data collected in this way can sometimes 

prove useful for resource conservation. But monitoring 

in the context of adaptive management is much more 

efficient and effective if it targets specific attributes for 

the specific purposes listed above. Simply put, the value 

of monitoring in adaptive management is derived from its 

contribution to adaptive decision making, and monitoring 

efforts should be designed with that goal in mind (57).

Step 5- Key Points

A monitoring plan should be designed to estimate 

system state and other attributes needed for decision 

making and evaluation.

The plan should promote learning through a compari-

son of estimates against model-based predictions.

The plan should be efficient, in that it produces esti-

mates that have maximum precision for a given cost, 

or minimum cost for a given level of precision.



32
Iterative phase

At this point in the operational sequence of adaptive management it is assumed that the key elements 

are in place. Thus, the appropriate stakeholders have 

been engaged in articulating the scope and nature of the 

resource issue. The objectives and management alternatives of the project have been identified. Forecasting 

models that capture uncertainty (or disagreement) about 

the impacts of management have been identified. And 

a monitoring effort has been designed that targets the 

resource attributes needed for learning, evaluation, and 

decision making. The stage is now set to incorporate these 

elements into an iterative decision process that will lead to 

improved understanding and management.

Step 6- Decision making

Select management actions based on 

 management objectives, resource conditions, 

 and understanding

At each decision point in the timeframe of an adaptive management project, an action is chosen from the set 

of available management alternatives. The management 

objective identified in Step 2 is used to guide this selection, given the state of the system and the level of understanding when the selection is made. The appropriate 

action is likely to change through time, as understanding 

evolves and the resource system responds to environmental conditions and management actions. That is, 

management is adjusted both to changing resource status 

and to learning. It is the influence of reduced uncertainty 

(or learning) on decision making that makes the decision 

process adaptive.

There are many ways to design the actual process of 

selecting an alternative. For example, formal optimization 

methods can be used to select from the available management alternatives an option that best accounts for current 

and future consequences (53,58,59). Alternatively, less 

computation-intensive search procedures can be used to 

produce suboptimal (but in many cases quite acceptable) 

management strategies. Finally, one sometimes can rely 

on less structured approaches or common sense to identify acceptable strategies. Irrespective of the approach, 

decision making should be driven by the management 

objectives and informed by resource status and process 

uncertainties.

Step 7- Followup monitoring

Use monitoring to track system responses to 

 management actions

Monitoring is used in adaptive management to track 

system behavior, and in particular to track the responses 

to management through time. In the context of adaptive 

management, monitoring is seen as an ongoing activity, 

producing data after each management intervention to 

evaluate the intervention, update the measures of model 

confidence, and prioritize management options in the next 

time period (See Case Study 7 for a discussion of followup monitoring).

Field surveys, banding programs, remote sensing, and 

other monitoring approaches can generate the data needed 

to estimate key indicators of resource dynamics (20). The 

information thus produced is used to compare data-based 

estimates of system components against expectations, and 

thus to measure performance in achieving management 

objectives. Monitoring information also factors directly 

into the learning process, through the comparison of 

estimates against model predictions. Subsequent decision 

making reflects the increasing degree of credibility earned 

by the most appropriate model(s), and management 

performance is adaptively improved.

Monitoring data play into these assessments in 

multiple ways. For example, estimates of system state 

typically are used in the process of identifying stateStep 6- Key Points

At each point in time, selection of a management 

action is made from the set of possible alternatives.

The selection of a management action is guided by 

objectives, which are used to evaluate alternatives 

and identify an action that contributes to meeting the 

objectives.

The appropriate action depends on resource status 

and the current level of understanding about resource 

dynamics.

Management is adjusted over time as resource conditions change and understanding evolves.









33
specific decisions. In some cases, estimates of resource 

status are directly included in the objectives, and thus are 

needed to assess the expected benefits, costs, and consequences of particular decisions. Of particular importance 

in adaptive management is the use of estimates of status 

and perhaps other attributes for comparison against model 

predictions so as to improve understanding of resource 

dynamics.

In many but not all instances, it is useful to collect 

data prior to initiating management. For example, if the 

management objective is to increase the size of a previously unperturbed population over some time period, 

a “baseline” population size prior to any management 

Case Study 7: The National Park Service (NPS), State of 

Montana, USDA Forest Service, and the USDA Animal and 

Plant Health Inspection Service developed an adaptive management strategy in 2000 that allows Montana to maintain its 

brucellosis-free status and NPS to maintain a bison population 

that fluctuates in response to ecosystem processes. (See CD for 

additional information on this project).

Step 7- Key Points

Monitoring typically occurs after management interventions.

Resource status and other key indicators of impacts are 

estimated with monitoring data.

Estimates based on monitoring data are used to evaluate management impacts and inform decision making 

at the next decision point.

Because the amount of monitoring data increases over 

the course of an application, the amount of information 

about system processes also increases.









intervention can be used to compare population size 

before and after the initial intervention. On the other 

hand, an objective of maximizing harvest may not require 

baseline conditions prior to the start of management. In 

the latter case, decision making pursuant to the objective 

is not informed by a comparison of resource status against 

a starting value. The point here is that the design of a 

monitoring effort, and in particular the need for initial 

“baseline” information, is determined by the nature of the 

project and its objectives. Even when baseline information is needed, its comparative value declines rapidly as 

the project proceeds through time, essentially because 

monitoring after each intervention establishes new 

“baselines” throughout the life of the project. 

34
Step 8- Assessment

Improve understanding of resource dynamics 

 by comparing predicted and observed changes 

 in resource status

The information produced by monitoring folds into 

assessments of decision making, performance evaluation, 

and learning. For example, the comparison of model 

predictions against estimates of actual responses is a 

key element of learning, with the degree of coincidence 

between predicted and observed changes used as an 

indicator of model adequacy. Confidence is increased in 

models that accurately predict change, and confidence 

decreases for models that are poor predictors of change. 

In this way evidence accumulates over time for the most 

appropriate hypothesis about resource dynamics, and 

understanding of the resource system is thereby advanced.

As important as it is, learning is not the only role 

played by analysis and assessment in adaptive management. Thus, an assessment of desired against actual 

outcomes can be used to evaluate the effectiveness of 

management and measure its success in attaining management objectives. In addition, an assessment of management alternatives as to their projected costs, benefits, 

and resource impacts contributes to the selection of a 

management option in the next time period.

Step 8- Key Points

Assessment/analysis includes parameter estimation, 

comparative assessments, and prioritization of management alternatives.

Comparison of predicted and actual responses is used 

to update understanding of management impacts.

Comparison and ranking of projected outcomes 

for management alternatives is used in selection of 

management actions.

Comparison of desired and actual outcomes is used to 

evaluate management effectiveness.









35
As shown in Fig. 3.3, the iterative cycle can begin 

with any of the Steps 6 to 8. However, it is useful to think 

of it as starting with a management decision, which is 

followed by post-decision monitoring and the subsequent 

assessment of monitoring data. This sequence of activities 

is repeated over the course of the application, during 

which learning occurs continuously and the management 

strategy is continuously adjusted based on what is learned.

The cycle typically terminates at the end of the timeframe with a final management action that is informed by 

assessment of the data collected just prior to the terminal 

time. It is also possible, if unlikely, that all uncertainty 

about ecological structure and function can be eliminated

at some point, whereupon the learning-based adaptive 

approach can give way to non-adaptive resource management for the remaining time.

Figure 3.3. Iterative cycle of adaptive management. Management actions are based on objectives, resource status, and learning. 

Data from followup monitoring are used to assess impacts and update understanding. Results from assessment guide decision 

making in the next time period.

... management 

action

monitoring

assessment management 

action

assessment ...

time

monitoring

Step 9- Iteration

Cycle back to Step 6

The gain in understanding from monitoring and 

assessment in Steps 7 and 8 is used to inform the selection 

of a management action at the next decision point. As 

understanding evolves, so too does the decision making 

that is influenced by improved understanding. In this way, 

the iterative cycle of decision making, monitoring, and 

assessment leads gradually to improved understanding 

of resource dynamics, and improved management as a 

consequence of improved understanding.

36
Step 9- Key Points

The cycle of Steps 6 through 9 is iterated until the end 

of the timeframe.

Iterations can begin at any point in the cycle; however 

a natural entry point is with decision making.

The direct linkage from assessment to management 

action in Fig. 3.3 expresses the contribution of learning to decision making, by providing information on 

which to base smart decisions.

The two-step linkage from management action to 

assessment in Fig. 3.3 expresses the contribution of 

management to learning, through interventions that 

are useful in investigating the resource system.









Technical and process learning 

in adaptive management

The operational sequence described above provides 

a framework for implementing adaptive management, 

with a focus on reducing structural or process uncertainty 

and thereby improving management. However, adaptive 

management involves much more than simply following 

the sequence of steps outlined here.

Just as adaptive management can be described in 

terms of two phases, learning with adaptive management can be seen to occur at two levels. Thus, adaptive 

management provides an opportunity to learn not only 

about ecological processes, but also about the adaptive 

process itself. In Chapter 1, adaptive management was 

described in terms of a cycle that included not only 

monitoring, evaluation, and adjustment of management 

actions, but also problem assessment and design (Fig. 

1.1). The latter elements focus on problem formulation, 

stakeholder involvement, identification of objectives, and 

the other elements included in the setup phase of adaptive 

management. In fact, it is useful to think of adaptive 

management not only in terms of an ongoing sequence of 

decision making, post-decision monitoring, and assessment as described here, but also in terms of periodic 

but less frequent recycling through the elements in the 

setup phase and adjustment of these elements as needed 

to account for evolving stakeholder perspectives and 

institutional arrangements (Fig. 3.4). The broader context 

of learning that focuses on the components of adaptive 

management as well as technical uncertainty is sometimes 

called “double-loop” learning (12). 

In many applications of adaptive management, both 

kinds of learning are of key importance. For example, it 

can be as important to understand and track the social and

institutional relations that influence adaptive management 

elements and stakeholder perspectives, as it is to resolve 

technical issues about system structure and process (54). 

Although the motivation of an adaptive approach is to 

improve resource management by reducing structural

uncertainty, its success can be impeded by a failure to 

adapt to social and institutional changes that inevitably 

occur over time. Because these changes can themselves 

be a result of early successes in reaching objectives, it is 

important to recognize and if possible account for them as 

decision making moves forward.

The need to better understand and characterize the 

elements of adaptive management often becomes more 

pressing as the iterative process of adaptive management 

rolls forward. Thus, stakeholder perspectives and values 

can shift as the adaptive process unfolds, and previously 

unanticipated patterns in resource dynamics can arise 

that require an adjustment of objectives, alternatives, and 

other elements of the process. In this sense, learning about 

the adaptive management process extends the context 

of adaptive learning to include changes in institutional 

arrangements and stakeholder values as well as changes 

in the resource system.

37
An emphasis on both technical and process learning 

has important implications for the institutional framework 

for resource management. Many managers contend 

that adaptive management is simply common business 

practice in their organizations and that they have been 

using adaptive management all along (51). In fact, the use 

of adaptive management in resource management almost 

always requires a fundamental shift from the status quo. 

For example, it typically is necessary to rethink the nature 

of risk aversion that characterizes decision making in 

most Federal agencies, and to explicitly recognize uncertainty as a key attribute of natural resource management. 

Without a willingness to embrace uncertainty, adaptive 

management is unlikely to succeed (47).

In addition, adaptive management requires a 

much more open process of decision making, in which 

stakeholders are directly engaged and decision making 

authority is shared among them. It also requires that 

objectives, assumptions, and the other elements of 

the decision making process be explicit, and therefore 

amenable to analysis and debate. Finally, it requires a 

strong commitment by managers to the necessary monitoring and assessment that underlie adaptive management, 

not as marginal activities but as essential elements of the 

process. It is undoubtedly true that many, perhaps most, 

projects in DOI involve monitoring, and in some cases 

management actually considers the results of monitoring. 

But that by itself is a long way from structured, adaptive 

decision making in a learning-based environment.

3.2. Legal Considerations when Applying 

 Adaptive Management

In addition to ecological and societal factors, a 

number of legal considerations influence adaptive 

management and potentially constrain its success. The 

Federal government is often criticized for the length of 

time it takes to plan and implement a particular action, 

and public concerns increase when an agency reconsiders 

its action and begins planning and compliance activities 

all over again. Well-designed and executed adaptive 

management strategies can help to alleviate this concern. 

Agency officials should invest significant effort on 

legal issues at two critical stages of adaptive management: (1) at the time a decision is made to utilize adaptive 

management for a particular project and (2) at the time 

the agency seeks to adjust management decisions based 

on the information derived from monitoring and assessment. Knowing what federal laws and regulations require, 

and what limitations apply prior to agency decisions, 

allows stakeholders to anticipate the legal requirements 

and integrate them into the adaptive management process. 

However, agency officials should recognize that some 

laws and implementing regulations prescribe specific 

activities and assessments in ways that could limit or even 

preclude the use of adaptive management.

Figure 3.4. Two-phase learning in adaptive management. 

Technical learning involves an iterative sequence of decision 

making, monitoring, and assessment. Process and institutional 

learning involves periodic reconsideration of the adaptive 

management set-up elements.

Set-up phase

stakeholders

objectives

alternatives

models

monitoring

Iterative phase

decision making

monitoring

assessment

38
Application of adaptive management will vary 

depending on geographic setting, ecological complexity 

and participating stakeholders, as well as the specific 

statutory provisions authorizing and sometimes 

constraining actions. Some examples include:

• National Park Service Organic Act of 1916 

 (applicable to the National Park Service).

• Reclamation Act of 1902 

 (applicable to the Bureau of Reclamation).

• Surface Mining Control and Reclamation Act of 1977 

 (applicable to the Office of Surface Mining).

• Federal Land Policy Management Act of 1976 

 (applicable to the Bureau of Land Management).

As a general matter, statutes of this type impose 

obligations on a particular agency. In addition, a number 

of statutes apply to all Federal agencies and serve to 

either limit agency actions or require certain tasks before 

an agency takes action. Regulations issued by other 

Executive Branch agencies can also limit agency actions. 

The use of adaptive management within the 

Department of the Interior does not alter the legal context 

that applies to Federal agency actions. Simply put, all of 

the applicable laws, regulations, and polices continue to 

apply to agency actions whether or not adaptive management principles are used in a particular context.

Statutory and other authorities that 

apply to Interior agencies

The first place to look for the authorized boundaries 

of agency activity is in the statutory foundation or appropriations authority that supports the activity. Although 

few useful generalizations can be made about statutory 

requirements, the importance of identifying underlying 

authorities cannot be overstated. Employees working on 

an adaptive management project should understand the 

authority under which they are entering into the project 

and be sure to embark on it only when there is clear 

statutory authorization. 

The statutes discussed here are not intended to 

provide an exhaustive accounting of applicable law. 

However, they are some key authorities that agency 

personnel should consider regarding adaptive management. Many other statutes such as the Clean Air Act, the 

Clean Water Act, and the National Historic Preservation 

Act may be involved in particular applications of adaptive 

management.

Native American wickiup structures were listed in 2003, 

on Colorado’s Most Endangered Places List by Colorado 

Preservation, Inc. The Wickiup Project is supported by the 

Bureau of Land Management, Dominquez Archaeological 

Research Group and the Colorado State Historic fund.

One of the benefits of clean water in the Cold River, 

a salmon stream in Massachusetts

39
In the examples below, Departmental employees 

are assumed to be actively working with non-Federal 

stakeholders on an adaptive management project. Most 

projects of adaptive management involve such interactions at some level of the application.

Statutory authorities that apply 

directly to adaptive management

National Environmental Policy Act. One of the 

most important statutes for an agency to consider as 

it implements adaptive management is the National 

Environmental Policy Act (NEPA). The primary goal of 

this statute is to ensure that agency decision makers and 

the public recognize and account for environmental and 

other related impacts of proposed agency actions.

Compliance with NEPA generally requires a series 

of procedural steps, and certain NEPA processes involve 

public participation and public review and comment. In 

complex or controversial situations, NEPA potentially 

involves the preparation of a Notice of Intent to prepare 

an Environmental Impact Statement (EIS), as well as 

a Draft EIS, a Final EIS, and a Record of Decision 

assessing environmental impacts of major Federal actions. 

In less complex or controversial actions, environmental 

compliance often can be accomplished with a simpler 

Environmental Assessment (EA) that culminates in a 

Finding of No Significant Impact. In some cases, an 

action can be categorically excluded from the requirement 

for NEPA compliance.

The NEPA requires an EIS of proposed “major 

Federal actions significantly affecting the quality of the 

human environment.” An EIS must include an analysis of 

alternatives to a proposed action. The activities resulting 

from a particular adaptive management process may rise 

to the level of a major Federal action requiring an EIS, 

and in any event they likely will need to be analyzed 

for NEPA compliance. Less complex or controversional 

actions may be addressed by a less comprehensive EA. 

Under NEPA, following the completion of an EA the 

agency will either identify significant impacts (and 

prepare an EIS), or prepare a Finding of No Significant 

Impact. Of course, some actions can be categorically 

excluded from NEPA’s documentation requirement.

As an example, a proposal resulting from collaboration between a DOI agency and an environmental 

nonprofit organization might call for the nonprofit to 

conduct habitat improvement for a protected species. It is 

possible that this undertaking could be considered a major 

Federal action. In such a circumstance, the collaborative 

activities resulting in a Federal action covered by NEPA 

must comply with NEPA’s documentation and procedural 

requirements. Given that many Federal actions may be 

challenged in Federal court, non-Federal stakeholders 

should be made aware of the possibility of litigation 

inherent in Federal actions.

An EIS incorporating adaptive management, whether 

as a “stand-alone” alternative or part of another alternative, needs to clearly describe how the approach would 

be implemented. This not only includes what types of 

actions are proposed initially, but also the results that are 

expected from monitoring and assessment, and future 

actions that may be implemented based on those results. 

Decision makers and the public must be able to see how 

the adaptive management approach would be implemented, including potential future actions and anticipated 

impacts on the environment. 

One common challenge to making adaptive management work in natural resource decision making is that 

ongoing monitoring may reveal “new, significant information” that requires an agency to prepare a Supplemental 

Environmental Impact Statement. This requirement 

is triggered when “[t]he agency makes changes in the 

proposed action that are relevant to environmental 

concerns; or [t]here are significant new circumstances 

or information relevant to environmental concerns and 

bearing on the proposed action or its impacts” (40 CFR § 

1502.9 (c)). If management adaptations that could occur 

in light of new information are fully documented and 

analyzed at the beginning of a NEPA process, the need to 

supplement NEPA documents may be reduced. Put differently, if an EIS anticipates significant information that can 

arise from monitoring and assessment, the agency may 

not need to supplement the EIS when invoking management changes based on the newly acquired information.

40
An important statute for an agency to consider as it 

implements adaptive management is the National 

Environmental Policy Act . The primary goal of 

this statute is to ensure that agency decision makers 

and the public recognize and account for 

environmental and other related impacts of 

proposed agency actions.

41
Of particular relevance to Federal agencies engaged 

in activities that may affect listed species is Section 7 of 

the ESA. Section 7 enlists agencies of the Federal government to support species conservation and avoid actions 

that would contribute to species extinction. 

Given the importance of conserving endangered and 

listed species, the complexity associated with protecting 

these imperiled species, and the impacts the ESA may 

have on society and agency decision making, any adaptive management program that may affect listed species or 

critical habitat is more likely to be successful if it involves 

FWS and/or NOAA early in the process. Key to efficient 

Endangered Species Act. The Endangered Species 

Act of 1973 (ESA) provides a broad, comprehensive 

approach to the conservation of threatened and endangered species. By Congressional direction, the ESA is 

administered by the U.S. Fish and Wildlife Service (FWS) 

and the NOAA-Fisheries (National Marine Fisheries 

Service). In general, the FWS deals with terrestrial and 

fresh water species, while NOAA-Fisheries deals with 

anadromous fish and marine species. As part of their 

administration of the ESA, these agencies:

• “List” endangered and threatened species

• Designate critical habitat for listed species

• Publish plans to identify actions needed to assist in the 

 recovery of listed species

• Consult with other federal agencies whose actions may 

 affect listed species

• Work with non-federal entities to develop and approve 

 habitat conservation plans

• Work cooperatively with other nations to conserve 

 listed species

• Administer international agreements to limit trade in 

 endangered and listed species

and effective consultation is an initial description of the 

range of potential adaptations and effects of those actions 

on listed species and their designated critical habitats. 

Re-initiation of consultation is far less likely to be needed 

if the initial consultation clearly considers the action to be 

adaptive and addresses the full range of possible adaptations and their associated potential effects. 

In some cases involving large-scale Federal programs, 

consultation is appropriate at both a broad programmatic 

level as well as the level of individual projects or actions 

that may affect listed species. Careful consideration of 

effects and alternatives can set the stage (for example, 

through adoption of best management practices or design 

standards) for expedited consultation on later individual 

actions. 

Agencies whose actions may affect listed species 

should design monitoring programs with input from FWS 

and/or NOAA-Fisheries. Learning by doing - the critical 

centerpiece of adaptive management - is particularly 

important in ESA situations, where cause and effect can 

be particularly difficult to ascertain. New information on 

listed species, or the effects of actions on listed species, 

may require re-initiation of Section 7 consultation by a 

Federal agency, or may trigger changes in habitat protection pursuant to approved Habitat Conservation Plans 

(HCP). Knowing and understanding the ESA and its 

requirements will be essential to successfully integrating 

the elements of an adaptive management program with 

efficient ESA procedural compliance.

Integration of adaptive management principles has 

been utilized by the FWS in the context of HCPs under 

Section 10 of the ESA. The FWS has developed guidelines regarding this aspect of HCP planning (included in 

the reference CD). Particular attention should be given 

to the issue of which party is to be responsible for any 

required changes in mitigation and/or minimization 

of “take” to listed species as a result of monitoring 

programs. Any effort in this regard must take into consideration the No Surprises assurances that a permittee can 

receive pursuant to the regulations that implement Section 

10(a)(1)(B).

42
The Endangered Species Act’s purposes include providing 

a means to conserve the ecosystems upon which endangered 

and threatened species depend, and providing a program 

for the conservation of the species

43
Federal Advisory Committee Act (“FACA”). Under 

FACA, Department officials may not receive advice 

from a group that the Department has established or that 

it uses (i.e., manages or controls) unless the Department 

complies with the provisions of FACA. The FACA 

requires certain actions to set up and operate a committee 

or similar group to provide advice to Federal officials. 

FACA does not require any particular outcome regarding 

the substance of advice on a particular matter. Rather, it 

establishes a number of actions and approaches to ensure 

balanced consideration and input. These actions include 

filing a charter, providing public notice of meetings in 

the Federal Register, and making advisory committee 

information publicly available.

Federal officials who receive advice from non-federal 

stakeholders should be aware of FACA’s potential applicability. However, FACA does not apply to every situation in which a Departmental official receives advice, but 

only to those situations in which the advice comes from 

a group that the Department has established or utilized. 

This means that FACA does not apply to advice received 

from individuals, even in a group setting (such as “town 

hall” meetings). Nor does it apply to advice received from 

preexisting groups, or groups that the Government neither 

manages nor controls. It does not apply to groups that 

simply exchange facts or information; or groups that are 

authorized to carry out operational functions; or groups 

consisting of only Federal, state, local, and tribal government employees exchanging views, information, or advice 

on programs with shared intergovernmental responsibilities. Finally, under some circumstances groups may be 

exempted from the requirements of FACA by another 

statute (such as the ESA for Recovery Implementation 

Teams). For more information on FACA, employees 

should consult FACA regulations in 41 C.F.R. Part 102-3.

Funding authorities

Annual Appropriations Acts and Funding. Agency 

activities cannot be undertaken without available funds 

that are allocated for a particular purpose. Occasionally, 

Congress may insert specific limitations in annual 

appropriations acts that could affect agency activities. 

For example, Congress may enact a provision stating 

that no Federal funds may be spent to map natural gas 

deposits off the coast of California or to study decommissioning of the Glen Canyon Dam. In these situations, any 

Departmental effort to map deposits or undertake such 

a study would be impermissible, even if a non-Federal 

stakeholder thought the activities would assist a particular 

adaptive management process or a non-Federal partner 

donated the necessary resources and/or data for the 

efforts.

44

Antideficiency Act. The Antideficiency Act contains 

a series of controls over the use of Federal appropriated 

funds to ensure that Federal agencies “pay as they go.” 

Government officials are prohibited (without specific 

authority) from making payments, or committing the 

United States to make payments at some future time, 

unless there are available agency funds to cover the cost 

in full. The Antideficiency Act applies to applications of 

adaptive management just as it does to all other Federal 

activities. In essence, no agreement should be entered 

into that commits an agency to the payment of funds in 

the future, in advance of available appropriations to fund 

activities under the agreement. For example, an agreement by an agency that commits $100,000 in grant funds 

to a particular organization for each of the next 5 years 

will likely be improper under the Antideficiency Act, 

unless there are sufficient agency funds that are available 

for the grant for more than one year. 

Other relevant statutes and authorities 

 Administrative Procedure Act (APA). The APA 

provides a procedure by which Federal agency actions 

may be challenged in court. Although there are several 

ways to challenge an agency action under APA, the most 

commonly employed is the claim that an agency action is 

“arbitrary, capricious, an abuse of discretion, or otherwise 

not in accordance with law.” This standard applies equally 

to adaptive management projects as to other activities, 

so agency decisions in a particular adaptive management 

application may ultimately be reviewed by a court. To 

survive a court challenge, agency decisions must therefore 

be rational, reasonable, and carefully articulated.

APA challenges are usually decided on the basis 

of the administrative record (the materials upon which 

the agency officials relied in taking action). Challenges 

to activities in adaptive management applications are 

no different. Departmental employees must therefore 

ensure that their decisions and actions are based on, and 

supported by, a complete and thoroughly documented 

administrative record. Finally, the APA may also provide 

the basis for challenges under NEPA, the ESA, and other 

statutes.

Substantive Statutory Authority. Often a statute that 

authorizes an activity will also contain specific limitations. For example, a statute that authorizes the Secretary 

to establish a wildlife refuge in cooperation with a State 

may also require the Secretary to ensure that State laws 

apply on the refuge. Conversely, Congress may enact 

statutes that forbid a particular activity. For example, 

Congress has forbidden Federal agencies from creating 

business corporations.
Lobbying Activities. Under 18 U.S.C. § 1913 and 

related authorities, most Department employees may not 

expend appropriated funds for “grass roots” lobbying that 

is designed to influence a member of Congress or official 

of any government (Federal, State, local, tribal) regarding 

his or her position on legislation. That is, Federal 

employees may not engage in lobbying. This restriction 

prohibits encouraging a stakeholder to undertake lobbying 

activities in support of the Department.

Freedom of Information Act. The Freedom of 

Information Act (FOIA), codified in 5 U.S.C. § 552, 

provides members of the general public potential access 

to any information created or obtained by the Department 

and under the Department’s control at the time of a FOIA 

request. Department personnel should keep in mind 

that documents generated during adaptive management 

activities will generally be agency records that are subject 

to release under the FOIA. However, the Department may 

withhold documents from the public that fall within one 

of nine specified FOIA exemptions. Agency personnel 

will want to consider how they intend to gather, store and 

publish information developed as part of the adaptive 

management process, and work with their agency’s FOIA 

offices when responding to requests for information. 

Data Quality Act. Although relatively new, the Data 

Quality Act (DQA) is increasingly affecting the work of 

Interior agencies. Passed in 2001 as part of the Treasury 

and General Government Appropriations Act, the DQA 

directs the Office of Management and Budget to publish 

guidelines applicable to Federal agencies, and provide 

policy and procedural guidance to Federal agencies for 

ensuring and maximizing the quality, objectivity, utility, 

and integrity of information (including statistical informa-

tion) disseminated by Federal agencies. Each agency 

should assess the applicability of the DQA to new or 

ongoing adaptive management projects.

Governmental Integrity. Because agency decisions, 

whether products of adaptive management or not, will 

only stand up if they comport with the law and are 

not “arbitrary and capricious,” agency officials must 

constantly work to ensure that the agency’s decisions 

are supportable based on the information that is avail-

able to the agency. In carrying out agency activities, 

Departmental employees should always act in an 

unbiased, fair, and equitable manner, so as to ensure that 

the public will not have cause to question the integrity of 

the Federal government. All Federal employees should 

endeavor to act impartially and to avoid giving preferen-

tial treatment, or the appearance of preferential treatment, 

to any private entity. 

45
Assessments could help to integrate NEPA and adaptive 

management, especially if environmental analyses will be 

needed subsequent to an initial EIS and impacts are not 

expected to be significant. An Environmental Assessment 

is generally much easier to prepare than an EIS. 

If an agency is constantly undergoing NEPA compliance and documentation, it may be because the original 

NEPA process failed to fully consider a broad range of 

potential adaptive management modifications. Frequent 

follow-up NEPA compliance can erode the public’s 

perception of the integrity of the process, and impede the 

ability to react to new, relevant information. NEPA is 

first and foremost a public process, and its credibility and 

successful implementation is predicated on the public’s 

perception that it is transparent and involves full disclosure of the potential environmental effects of Federal 

actions.

Coyote Gulch

Making Adaptive Management Work: 

The Importance of Integrating Adaptive

Management and NEPA

NEPA serves as a pre-decisional requirement and 

analytical process with the goal of ensuring that both the 

public and Federal decision makers are fully aware of 

the potential impacts of a discretionary Federal action. 

Expanding the NEPA framework to accommodate the 

iterative, data-driven process of adaptive management 

requires the integration of learning-based strategies into 

the existing framework of NEPA requirements and the 

implementing regulations. Of course, compliance with 

other environmental statutes, regulations, and Executive 

Orders is also necessary.

Federal agencies are encouraged to use adaptive 

management as part of the NEPA planning process, 

particularly in circumstances where long-term impacts are 

uncertain and informed decisions in the future will depend 

on monitoring and assessment at that time. Any adaptive 

management alternatives in an Environmental Impact 

Statement can be crafted to allow the necessary flexibility 

for strategy adjustment as learning advances through 

monitoring and assessment. Agencies are encouraged to 

build this flexibility into their management alternatives 

and NEPA compliance activities. Training of NEPA 

practitioners in this important environmental concept is 

paramount. 

 Because NEPA analysis and compliance is procedural and predictive, and includes the evaluation of “all 

reasonable alternatives,” it is important to include a 

sufficiently broad range of management options to ensure 

a comprehensive environmental analysis and a “NEPA 

coverage” that is adequate for whatever contingencies are 

anticipated. The idea is to satisfy the NEPA requirements 

for scientific analysis of potential impacts, and provide 

full disclosure of those impacts. Thoughtful and carefully 

structured alternatives should avoid the triggering of 

additional NEPA compliance later. 

Alternatively, another approach to NEPA 

compliance that has proven successful for adaptive 

management programs is to prepare a “programmatic” 

EIS at the start, which broadly covers the likely range of 

actions that may be taken under the particular adaptive 

management program. Later, any NEPA compliance 

needed for subsequent shifts in the management actions 

as a result of the adaptive management process can then 

“tier” off of the initial programmatic EIS, saving considerable time and work.

Where appropriate, greater use of Environmental 

46
3.2 Key Points

Adaptive management must be integrated with all 

existing legal obligations of the agency; it is not a 

replacement for environmental compliance.

Adaptive management must comply with NEPA and 

other environmental laws. Integration of adaptive 

management and other legal obligations requires 

thoughtful “up-front” planning, and involves an 

investment of time and resources by the agency and 

other stakeholders.

Integrating environmental review procedures with 

adaptive management requires consideration of the 

range of adaptive actions and attendant environmental 

effects that can reasonably be anticipated at the time 

of the environmental review.

The management alternatives and effects considered 

in an adaptive management application must be 

reviewed in light of the relevant environmental laws 

and regulations, so that environmental compliance 

applies not only for the initial action, but also for 

adaptive redirections that may be needed in the future.

For some adaptive management applications, it may 

be appropriate to assess environmental effects of 

future adaptive actions on a case-by-case basis using 

streamlined environmental assessments or informal 

consultations. Such an approach may serve to 

strengthen the case for compliance when uncertainty 

exists regarding the environmental effects of future 

adaptive actions.

Key to successful integration of NEPA and adaptive 

management is a well planned and thorough up-front 

consideration of the range of potential actions and 

their effects, so as to ensure that future actions and 

their effects are within the scope of the initial analysis 

and do not require subsequent environmental analysis.



47
48
Chapters 1 and 2 address the context and conditions 

for adaptive management to be applicable to resource 

management, and Chapter 3 describes adaptive management in operational and legal terms. In these chapters 

we referred to the successful implementation of adaptive 

management without ever explicitly defining success. 

Here we offer a definition, criteria, and steps to promote 

successful implementation. 

4.1. Recognizing Success 

 in Adaptive Management

In general, the implementation of adaptive management is defined as successful if progress is made toward 

achieving management goals through a learning-based 

(adaptive) decision process. This definition contains 

two essential elements. First, it requires progress toward 

achieving objectives, a primary indicator of success 

with any management strategy, whether adaptive or 

not. Second, it requires learning-based management, as 

Chapter 4: When is Adaptive Management Successful?

described in the nine-step operational sequence in Chapter 

3. Specifically, stakeholder involvement, an effective 

monitoring program, and agreed-upon objectives, 

management alternatives, and models must be integrated 

into an iterative learning cycle (see Fig. 3.4). Of course, 

the decision making process must be framed in a context 

of applicable laws, authorities, and regulations.

Based on this definition, we suggest the following 

four criteria for recognizing success in adaptive management (Fig. 4.1): 

• Stakeholders are actively involved and committed 

 to the process.

• Progress is made toward achieving management 

 objectives.

• Results from monitoring and assessment are used to 

 adjust and improve management decisions.

• Implementation is consistent with applicable laws.

adaptive management success

progress toward achieving

resource objectives

informative monitoring

and assessment

stakeholder involvement 

and support 

implementation consistent

with applicable laws

success

factors

success

factors

success

factors 

success

factors

Adaptive Management Success Model

Figure 4.1. Adaptive management success model, with four success criteria. Success factors for each criterion are addressed by a 

series of questions that help practitioners increase the likelihood of success.

49

4
These criteria integrate the structural elements and 

processes described in the preceding chapters. They are 

interrelated and interdependent, and should be viewed 

collectively as indicators of success. 

For an adaptive management project to be successful, 

all four criteria must be met over the project timeframe. 

For example, an adaptive management project is not 

considered fully successful if stakeholders do not see the 

resource management process as legitimate. Likewise, 

results from monitoring and assessments must be used to 

inform adjustments in management practices for it to be 

fully successful. 

Stakeholders are actively involved 

and committed to the process 

Broad stakeholder involvement is critical for adaptive management success. Recall from Chapter 3 that 

engaging stakeholders is one of the key steps in adaptive 

management. Ideally, stakeholders are engaged in 

every aspect of adaptive management, from the initial 

problem formulation to the identification of objectives 

and the design of monitoring and assessment. The fact 

that stakeholders play a role in all aspects of the process 

argues for singling out stakeholder involvement as a key 

success criterion.

Including stakeholders in the adaptive management 

process reinforces stakeholder perceptions of adaptive 

management as a legitimate process, which in turn 

encourages cooperation and reduces the likelihood of 

conflict. Stakeholder involvement in problem identification, process design, monitoring and assessment, and 

other elements of the adaptive management process builds 

support for the process and provides a foundation for 

learning-based resource management. It also provides 

opportunities for resource managers to obtain additional 

information about the natural system and priorities for 

its management before decisions are made. Conversely, 

a lack of stakeholder involvement can by itself cause the 

process to fail. 

Progress is made toward achieving 

 management objectives

In structured decision processes, clear and measurable 

objectives guide decision making and serve as metrics for 

assessing management performance. Because adaptive 

management by design pursues management benefits as 

expressed in the management objectives, progress toward 

achieving objectives is a natural criterion of success.

50
Two points about objectives are emphasized here. 

First, the objectives in natural resources management 

often are multidimensional, and thus involve tradeoffs. 

Improving an outcome associated with one objective may 

involve tradeoffs with outcomes associated with other 

objectives. When multiple management objectives are 

identified, it is important to recognize and account for 

the relationships among them, so that potential tradeoffs 

can inform decision making. In this way, consistent and 

achievable resource management goals and thresholds can 

be established.

Second, it is important to recognize that management objectives may change. In many cases, success 

in attaining objectives can be an ongoing process that 

involves refinement of objectives as understanding accumulates and stakeholder perspectives change. That is, the 

adaptive management system is itself dynamic, including 

its objectives. Adaptive management needs to include not 

only the cyclic evaluation of project performance, but also 

a periodic reassessment of the project objectives.

Results from monitoring and assessment 

 are used to adjust and improve 

 management decisions

The accumulation of understanding and subsequent 

adaptation of management strategy depends on feeding 

monitoring and assessment results back into the decision 

making process. Monitoring and assessment efforts 

should be designed to ensure that key resource parameters 

are adequately measured and appropriately focused, so 

as to contribute to achieving success. In Chapter 3 these 

key process elements were seen to factor directly into the 

operational sequence that defines adaptive management. 

Here we emphasize the importance of monitoring 

resource responses and using the resulting information to 

assess system models, update their confidence measures, 

and reduce system uncertainty. Scientists, managers, and 

stakeholders should collaborate in an interdisciplinary 

assessment of what is known and what is learned about 

the system being managed. Success in adaptive management ultimately depends on effectively linking monitoring 

and assessment to objective-driven decision making. 

51
Implementation is consistent 

with applicable laws

It is almost axiomatic that implementation of adaptive 

management must be consistent with applicable laws to 

be considered successful. The use of adaptive management in a manner that is not consistent with applicable 

laws will eventually lead to distractions from the project 

objectives, or to a breakdown in trust among stakeholders, 

or to a litany of official – and unofficial – sanctions. 

Ensuring that an adaptive management application 

complies with applicable laws, regulations, and policies 

can be challenging because of the many legal considerations and complexities that may be involved. Thoughtful, 

detailed planning and constant attentiveness to the 

requirements of laws, regulations, and policies are needed 

to ensure the success of an adaptive management project.

This criterion should not be assessed in isolation. 

In large measure, success with the previous criteria 

will affect stakeholder assessments of whether an adaptive management project remains in compliance with 

applicable legal considerations. For example, if serious 

disagreements persist among stakeholders regarding the 

appropriateness of monitoring protocols and results, one 

or more of the stakeholders may challenge the validity of 

the program’s results. This in turn can lead to withdrawal 

of stakeholder support, loss of continued funding, and 

even litigation. 

Using the success model

A key success metric that adaptive management 

shares with all management strategies is progress toward 

the achievement of management objectives. As an adaptive management project moves forward in time, it should 

be possible to compare management performance against 

expectations, to get some idea of the progress made up to 

that time in achieving objectives. In the absence of at least 

some indication of progress over a reasonable period, 

there is little justification for continuing a project in its 

current form. 

All four success criteria need to be met for successful 

implementation of adaptive management. They should be 

considered when initially developing an adaptive management project, and reviewed periodically over the life of 

the project to evaluate project implementation and assess 

the likelihood of achieving objectives. In fact, the success 

criteria can themselves be used adaptively, to determine 

where changes are needed in order to achieve success.

The success model provides a framework for both 

technical and process learning, as described in Section 

3.1. The focus is on adaptation not only at the technical 

level, through an iterative application of decision making, 

monitoring, and assessment, but also at the institutional

and process level, through periodic assessments of stakeholder perspectives, management objectives, and other 

process elements. The successful application of adaptive 

management potentially involves learning and adaptation 

at both levels. The following section includes questions 

that can be useful in implementing and evaluating the 

success of an adaptive management project.

Avian Influenza Sampling Project 2006

52
4.2. Key Questions for Successful 

 Implementation

The following questions can be used to increase the 

likelihood of successful adaptive management, and to 

evaluate progress in achieving objectives. The questions 

address each of the criteria identified in Section 4.1 and 

are tied to the operational steps discussed in Section 

3.1 and shown in Box 4.1. The questions should be 

considered throughout the timeframe of an adaptive 

management project, to ensure that success is continually 

considered and evaluated as the project progresses. A 

particular adaptive management project may not be able 

to address all of the issues outlined in the following questions. However, the questions encompass an important set 

of issues that should be considered, so as to increase the 

likelihood of success.

Box 4.1 Adaptive Management 

 Operational Steps

Set-up phase

 Step 1 - Stakeholder involvement 

Ensure stakeholder commitment to adaptively manage 

 the enterprise for its duration

 Step 2 - Objectives 

Identify clear, measurable, and agreed-upon 

management objectives to guide decision making

and evaluate management effectiveness over time

 Step 3 - Management actions 

Identify a set of potential management actions for 

 decision making

 Step 4 - Models 

Identify models that characterize different ideas 

(hypotheses) about how the system works

 Step 5 - Monitoring plans 

Design and implement a monitoring plan to track

resource status and other key resource attributes

Iterative phase

 Step 6 - Decision making 

Select management actions based on management 

 objectives, resource conditions, and enhanced 

 understanding

 Step 7 - Follow-up monitoring 

Use monitoring to track system responses to

management actions

 Step 8 - Assessment 

Improve understanding of resource dynamics by 

 comparing predicted vs. observed change in 

 resource status

 Step 9 - Iteration

Cycle back to Step 6 and, less frequently, to Step 1

USGS scientist is measuring various water-quality conditions in 

Holes Creek at Huffman Park in Kettering, Ohio.

53
Step 1- Stakeholder involvement

Two key aspects of stakeholder involvement are 

emphasized here. First, participation by stakeholders 

is essential if only because stakeholder perceptions 

of adaptive management as a legitimate process can 

promote cooperation and reduce the likelihood of conflict. 

Second, including stakeholders in the process provides 

opportunities for resource managers to obtain additional 

information about both the natural system and stakeholder 

values and priorities before decisions are made. Involving 

stakeholders builds support for the process and provides a 

foundation for learning-based resource management. 

Key questions to consider when involving stakeholders in an adaptive management project include:

• Has a systematic process been developed that facilitates 

 effective participation by stakeholders?

• Have key stakeholders been identified?

• Have agreed upon lines of communication been estab-

 lished and is their importance to successful adaptive 

 management processes understood?

• Are stakeholders committed to and involved in the adap-

 tive management process including the monitoring and 

 assessment program?

• Is the adaptive management process able to adapt to 

 changes in stakeholder and public viewpoints?

Step 2- Objectives

Objectives in adaptive management play important 

roles in decision making, evaluation, and learning. These 

roles are enhanced by the articulation of clear, measureable, and agreed-upon objectives. Because they can 

change through time as the resource system changes and 

stakeholder values evolve, it is useful to revisit objectives 

periodically.

Keeping the following questions in mind will increase 

the likelihood that decision making will be guided by 

resource management objectives:

• Have explicit and measurable management objectives 

 been identified and developed?

• Are the management objectives achievable and 

 sustainable?

• Have performance metrics relating to the management 

 objectives been developed?

• Has a system of monitoring and assessment relevant to 

 the management objectives been developed and imple-

 mented so that progress in meeting the objectives can be 

 tracked?

• Have tradeoffs among management objectives been 

 considered and are they understood?

54
Step 3- Management actions

The set of potential management actions determines 

the range of management flexibility for an adaptive 

project, and influences learning rates as well as progress 

in achieving management objectives. Learning is 

promoted by a wide range of management alternatives, 

but hampered by alternatives that differ only marginally. 

As with other components of an adaptive management 

project, the acceptable range of management options can 

change through time, as stakeholder perspectives and 

resource conditions evolve, legal requirements change, 

and new information becomes available.

Key questions about the set of management alternatives in an adaptive management project include the 

following:

• Has a range of potential management actions 

 been developed?

• Have the specific tasks to implement the management 

 alternatives been identified?

• Is the range of potential actions appropriate for the 

 timeframe under which changes are likely to occur?

• Can the set of management alternatives be adjusted

 through time if needed?

Step 4- Models

Models serve as expressions of ecological understanding, as engines for deductive inference, and as 

articulations of resource response to management and 

environmental change. They also help bring together 

scientists, managers, and other stakeholders in a joint 

assessment of what is known about the system being 

managed, and facilitate an interdisciplinary approach to 

understanding through monitoring and assessment. It is 

important to keep the many roles of models in mind as an 

adaptive management project is implemented.

The following questions relate to the models used in 

an adaptive management project:

• Are the hypotheses underlying the strategies for resource 

 management expressed as testable models?

• Have explicit links between management actions and 

 resource dynamics been incorporated into the models?

• Are the ecological/resource processes that drive resource 

 dynamics understood?

• Are the relevant environmental factors incorporated into 

 the models?

• Are the models calibrated with available information?

55
Step 5- Monitoring plans

The use of objectives to guide decision making 

depends on linking monitoring and assessment results 

with the decision making process. Both monitoring and 

assessment should be designed to ensure that resource 

parameters are adequately measured and appropriately 

focused on relevant performance indicators. Effective and 

useful monitoring is required for the hypothesis testing 

that leads to the reduction of uncertainty that is key to 

adaptive management. 

Important questions about the monitoring plan for an 

adaptive management project include the following:

• Will the monitoring plan support the testing of alterna-

 tive models and measurement of progress toward accom-

 plishing management objectives?

• Is it clear what monitoring data need to be collected to 

 estimate the relevant resource attributes?

• Has the level of accuracy that is needed been identified?

• Are commitments among managers, scientists, and other 

 stakeholders in place to sustain an ongoing monitoring 

 and assessment program?

• Will meaningful and useful data and information be 

 available within timeframes that allow for adaptive deci-

 sion making?

Step 6- Decision making

An adaptive management strategy identifies actions 

at each point in time, with strategy implementation at 

a particular time based on resource status and understanding. The strategy typically evolves through time, as 

learning accumulates and the resource system responds to 

management actions.

Key questions about iterative decision making in an 

adaptive management project include the following:

• Is it clear how decisions will be made?

• Are decisions at each point in time based on the current 

 status and understanding of the resource?

• Are decisions being guided by management objectives?

• Are stakeholders informed and consulted before deci-

 sions are made or changed?

Step 7- Follow-up monitoring

The effects of decision making are tracked with 

post-decision monitoring, and the data collected are 

used to gauge progress in meeting objectives and 

improve ecological understanding. Ideally, post-decision 

monitoring data can be folded into analysis/assessment 

before the next decision point, so that decision making at 

that time can take advantage of updated information and 

understanding.

Key questions about follow-up monitoring in an 

adaptive management project include the following:

• Are the analysis needs understood?

• Is monitoring conducted on a timely basis?

• Is monitoring targeted to system attributes that are 

 useful for evaluation and learning?

• Are monitoring data collected and managed so that they 

 are available and easy to access?

• Can the monitoring data be used to update the measures 

 of model confidence?

56
Step 8- Assessment

The information from monitoring is used to evaluate 

management, improve understanding, and guide decision making. As noted in Chapter 3, these functions are 

promoted by the estimation of resource parameters and 

the comparison of these estimates against model-based 

predictions.

Key questions about analysis and assessment in an 

adaptive management project include the following:

• Have the expected impacts of alternative management 

 strategies been evaluated?

• Is it clear how results are to be understood and 

 interpreted?

• Have thresholds that indicate a change in management 

 been recognized?

• Have the action(s) to be taken when a threshold is 

 reached been identified?

Step 9- Iteration

The adaptive cycle of decision making, post-decision 

monitoring, and analysis/assessment (Fig. 3.3) leads to 

improved understanding as well as improved management. Periodic but less frequent cycling through the 

components of an adaptive management application (Fig. 

3.4) allows for adjustments as stakeholder perspectives, 

institutional arrangement, and resource conditions evolve.

Key questions about iterative feedback in an adaptive 

management project include the following:

• Are management actions and decisions reviewed fre-

 quently based on monitoring and assessment?

• Have incentives been developed to encourage experi-

 mentation and learning?

• Have resource management alternatives been revisited 

 and/or modified over time?

• Has uncertainty related to resource dynamics and the 

 impacts of management actions been reduced through 

 learning over time?

• Are the targets identified in the performance metrics 

 likely to be achieved within the specified timeframe?

Legal considerations

Because of its scope and complexity, the legal 

framework for an adaptive management project can be 

confusing, and it is not always obvious to managers 

and practitioners which legal considerations to focus 

on. Among other things, this suggests the usefulness of 

engaging members of the DOI Solicitor’s Office early on 

in an adaptive management project.

Key questions about legal considerations for an 

adaptive management project include the following:

• Are the applicable resource management laws and 

 regulations understood by managers, scientists, and 

 other stakeholders?

• Have steps been taken to comply with applicable laws 

 and regulations?

• Has a process been developed to focus on compliance 

 throughout the project life?

• Is the process in compliance with specific legal 

 mandates?

4.2 Key Points

Adaptive management allows managers to determine 

systematically whether management activities are 

succeeding or failing to achieve objectives.

An adaptive management project is recognized as 

successful if (1) stakeholders are involved and committed to the process; (2) progress is made toward 

achieving management objectives; (3) results from 

monitoring and assessment are used to adjust management decisions; and (4) implementation is consistent 

with applicable laws.

The implementation of adaptive management can be 

facilitated by considering a series of questions related 

to the success criteria and the operational steps.







57
Rather than relying on anecdotal information 

about resource status, managers can use 

monitoring and evaluation adaptively 

to make smart decisions

58
5

In the course of writing this technical guide, contributors and reviewers raised a number of important issues 

that do not fit naturally into other chapters, but nevertheless merit discussion. Because no document can address 

all the issues that might arise in adaptive management, 

DOI bureaus and offices may wish to develop their own 

planning and implementation guidelines, tailored to 

specific legal and institutional contexts and focused more 

directly on relevant authorities.

5.1. Uses of Information in 

 Natural Resource Management

When considering the application of adaptive 

management, it is important to account for both learning 

and progress in achieving management objectives, as 

well as the possible tradeoffs between them. As indicated 

earlier, learning in adaptive management occurs through 

the comparison of model-based predictions against 

information from monitoring. The role played by monitoring, and the information produced from monitoring, is 

essential in adaptive management. 

Several different approaches to resource management can be distinguished, depending on the relative 

emphases on learning and management objectives (38). 

Management approaches can range from an exclusive 

focus on management objectives with no concern for 

information and learning, to an exclusive focus on 

learning with little regard for achieving management 

objectives (60). The most extreme example of the latter is 

the use of management in a rigorously designed experiment, where the goal is to maximize the precision of 

contrasts among management treatments. 

Management in the absence of 

 systematic monitoring

In this situation, decision making is loosely focused 

on management objectives, and is based on prior 

experience, intuition, expert opinion, etc. Monitoring 

and assessment are not used systematically in decision 

making, so there is little or no opportunity for learning. 

This situation occurs more frequently than many believe. 

For example, managers often feel that their understanding 

of a resource system is sufficient for them to make smart 

Chapter 5: Other Operational Issues

decisions, and anecdotal information about resource status 

is all that is needed to inform those decisions.

Management based on resource status

Here the focus of decision making is on achieving 

management objectives, with little or no recognition 

of uncertainty in the decision making framework. 

Monitoring and assessment focus primarily on resource 

status, rather than the understanding of ecological 

processes. This approach is sometimes misidentified as 

adaptive management, presumably because the measures 

of resource status obtained through monitoring are 

considered in management actions. A great many multiyear resource applications are of this kind. However, few 

of these applications specifically focus on learning about 

the processes that control system dynamics.

Passive adaptive management 

In this case uncertainty is recognized in the decision 

making framework, but the focus is on the achievement 

of management objectives, with learning as an untargeted 

byproduct. Ongoing monitoring programs focus on 

resource status as well as other system attributes that are 

useful for improved understanding through time, and 

assessment produces estimates of resource attributes that 

are used for learning. Because decision making is not 

focused specifically on learning, the rate of learning is 

likely to be substantially lower than with a more proactive 

approach.

Active adaptive management 

Decision making involves the active pursuit of 

learning, either through experimental management that 

focuses directly on learning, or quasi-experimental 

management that focuses simultaneously on learning 

and achievement of management objectives. Both 

approaches anticipate the effect of management on the 

rate of learning, and both are included under the rubric 

of “management by experiment.” Monitoring focuses on 

resource status as well as other system attributes needed 

to improve understanding through time, and assessment 

produces estimates of resource attributes that can be used 

for learning.

59
Figure 5.1. Priorities in different management approaches. 

Not shown is management in the absence of monitoring, which 

devalues learning and focuses only loosely on management 

objectives.

active adaptive management

passive adaptive management

management based on resource status

low

high

level of uncertainty / emphasis on learnin

g

60

It should be emphasized that both active and passive 

adaptive management utilize management interventions 

in a learning process. The key distinction between the 

two approaches is the degree to which decision makers 

anticipate the influence of management on learning, and 

the degree to which management is used proactively to 

accelerate the rate of learning.

Figure 5.1 orders the management approaches 

described above with respect to their emphases on 

learning. Several points can be made. First, adaptive 

approaches to management place a greater emphasis 

on uncertainty and learning than non-adaptive decision 

making. Second, non-adaptive management is oriented 

solely on management objectives, whereas adaptive 

management considers learning as well. Third, passive 

adaptive management places a stronger emphasis on 

learning than non-adaptive management. As a general 

rule, it makes little sense to manage adaptively to reduce 

uncertainty, if uncertainty is not at issue in the management problem. When uncertainty does limit effective 

management, there often is substantial value in managing 

adaptively (see Section 2.1 for additional discussion on 

this point).

As a general rule, adaptive 

management is most useful when 

the consequences of management are 

uncertain, but objectives are clear 

and the potential for management 

intervention is high.
5.2. Accounting for Uncertainty 

 in Adaptive Management

An important concern is how to represent and account 

for uncertainty in applications of adaptive management 

(61,62). At a minimum, four sources of uncertainty influence the management of natural resource systems.

Environmental variation is the most prevalent source 

of uncertainty, and is largely uncontrollable and possibly 

unrecognized. It often has a strong influence on natural 

resource systems, through such factors as random variability in climate.

Partial observability refers to uncertainty about 

resource status. An obvious expression of partial observability is the sampling variation that arises in resource 

monitoring.

Partial controllability expresses the difference 

between the actions targeted by decision makers and the 

actions that are actually implemented. This uncertainty 

typically arises when indirect means (for example, 

regulations) are used to implement a targeted action (for 

example, setting a harvest or stocking rate), and it leads 

time

t-1 t t+1

resource

system

environmental

variation

partial

control

structural

uncertainty

partial

observability

management

action

environmental

conditions

resource

system

management

action

resource

system

management

action

environmental

conditions

environmental 

conditions

... ...

Figure 5.2. Uncertainty sources in natural resource management. Partial control limits the influence of management actions. 

Environmental variation affects resource system status and dynamics. Partial observability limits the recognition of system status. 

Structural uncertainty limits the ability to characterize system change.

to the possible misrepresentation of management interventions and thus to an inadequate accounting of their 

influence on resource behavior.

Structural or process uncertainty concerns a lack of 

understanding (or lack of agreement) about the structure 

of biological and ecological relations that drive resource 

dynamics. 

Environmental variation, partial observability, partial 

controllability, and structural uncertainty all limit a 

decision maker’s ability to make informed management 

decisions (Fig. 5.2). Special emphasis is given in adaptive management applications to structural or process 

uncertainty. However, the other forms uncertainty 

also can be incorporated in an adaptive management 

project, depending on their importance. For example, a 

typical approach to environmental variation is to include 

environmental conditions in the resource models in an 

adaptive management project (Fig. 5.2), with probabilities 

assigned to different values of the relevant environmental 

variables. In this way model behaviors will reflect 

environmental variation, as will the projected responses 

to management actions. Environmental variation therefore ramifies through the decision making process, as 

projected responses to management guide the selection of 

management actions.

61
5.3. The Measurement of Learning

Much has been said about learning in the preceding 

chapters, but questions remain about how learning 

actually is achieved and recognized. In Chapter 3, 

uncertainty was described in terms of different hypotheses 

about how a resource system responds to management 

actions, along with models imbedding these hypotheses 

and their associated measures of confidence. As evidence 

accumulates through monitoring, confidence grows 

in the models (and their associated hypotheses) that 

accurately predict responses to management, and confidence declines for models that are poor predictors. It is 

through the sequential comparison of predictions against 

monitoring data that the adequacy of a hypothesis about 

biological and ecological processes is gradually revealed. 

A comparison of hypothesis-based predictions against 

evidence is an essential feature of scientific investigation, 

and a key reason why adaptive management is described 

as “science-based.”

Questions remain about possible mechanisms for 

updating the confidence in a particular hypothesis 

Generically, at each point in time one can use a measure 

of the difference between the response predicted by a 

model and the response estimated with monitoring data. 

A small difference indicates a good fit for the model, and 

a large difference indicates a poor fit. These differences 

can be calculated for each model after each post-decision 

monitoring event, and used to update confidence levels of 

the models through time. Depending on the desired rigor, 

an updating protocol can be fairly simple or technically 

complicated (63).

5.4. Learning Organizations

Learning in adaptive management derives from 

management actions, and is used in turn to inform 

subsequent actions. But many important issues about 

how best to facilitate learning are framed in terms of 

adaptive institutional arrangements, structures, and 

processes—features that are often lacking in traditional 

management (64). Despite frequent assertions about the 

use of adaptive management and the depiction of learning 

as a key element in applications, there has been limited 

progress in making adjustments to promote learning 

institutionally (48). 

The notion of technical and process learning bears 

directly on the concept of learning-based organization, 

the institutional framework for adaptive management. At 

the heart of both an adaptive management project and the 

learning-based organization that supports it is the explicit 

recognition of uncertainty as a key attribute of natural 

resource management. Indeed, adaptive management is 

not feasible unless the relevant management institutions 

have the capability and willingness to embrace uncertainty (47). Among other things, embracing uncertainty 

means recognizing different views of a managed system, 

as well as a direct involvement of stakeholders who 

have different perspectives, and a commitment to shared 

decision making that allows uncertainty to be reduced. 

At issue here is an organizational structure and 

context that can promote and facilitate an adaptive 

approach to resource management. Attributes of a 

learning organization include the following:

• acknowledgement that the world is uncertain and that 

 failure to predict outcomes accurately is common. 

• recognition of the importance of training people in 

 group interactions and collaboration. 

• positive reinforcement and rewards for experimentation 

 and learning. 

• recognition that surprises and even crises can be 

 opportunities for learning (65). 

62
In fact, many observers think that the major challenges facing adaptive management are fundamentally 

institutional (8). Institutions are built on major premises 

and long-held beliefs that are deeply imbedded in 

educational systems, policies, and norms of professional 

behavior (66). Yet Senge (4) argues that a learning 

organization is “... where people continually expand their 

capacity to create the results they truly desire, where new 

and expansive patterns of thinking are nurtured, where 

collective aspiration is set free, and where people are 

continually learning to see the whole together.” There 

is a natural tension between the tendency of large, longstanding organizations to maintain a strong institutional 

framework for thinking and decision making, and the 

need in adaptive management for an open, collaborative approach that recognizes alternative perspectives, 

embraces uncertainty, and utilizes participative decision 

making (67).

Structuring a learning-based adaptive organization 

can be handicapped by a pervasive belief that adaptive 

management does not constitute a significant departure 

from the past, but is only a process of adjusting over time 

(51). One consequence is that little attention is given 

to the institutional barriers to its implementation, and 

little effort is expended on the redesign of organizational 

structures and processes to accommodate an adaptive 

style of management. At a minimum, it is necessary 

to rethink the notions of risk and risk aversion, and to 

promote conditions that encourage, reward, and sustain 

learning by individuals.

5.5. Realistic Expectations for 

 Adaptive Management

Adaptive management is designed to produce 

gradual improvements in management through a 

stage-wise process that promotes incremental learning. 

However, there is nothing prescriptive in the notion of 

adaptive management about the length of time required 

to see substantive improvements in understanding 

and management. In some cases it may be possible to 

recognize improvement in only one or a few cycles of 

the adaptive cycle (Fig. 3.3). In others, learning occurs 

much less rapidly. Several conditions can influence the 

rate of learning, including the size and complexity of the 

resource system, the number and extent of management 

alternatives, and the sources and magnitudes of uncertainty. 

Of interest here is the influence of the management 

approach itself on rates of learning. As mentioned above, 

learning can be accelerated by the use of active adaptive 

management, which utilizes management interventions 

proactively for the purpose of learning. Learning rates 

are maximized when interventions are imposed in an 

experimental context that includes randomization, replication and experimental control. Under these circumstances, 

contributions to resource objectives are temporarily 

postponed so that understanding can be attained as 

quickly as possible (68). Even here, however, environmental variation, partial controllability, partial observability, and the magnitude of structural uncertainty can 

slow the accumulation of knowledge, and thus impede the 

improvement of management. 

One caveat about adaptation and the rate of learning 

should be mentioned here. We have described adaptive 

management in terms of a cycle of decision making, 

monitoring, and assessment that aims at reducing 

structural uncertainty (Fig. 3.3). Uncertainty is reduced 

gradually in adaptive management, through the sequential 

evaluation of hypotheses and accretion of knowledge 

about them. However, the accretion of knowledge is 

clearly undermined if the resource system changes more 

rapidly than the rate of learning about it. Even if system 

structure and processes remain relatively stable, the identification of strategies to achieve management objectives 

is undermined if the objectives change more rapidly than 

adaptive management can learn how to achieve them. 

The point here is that for adaptive management to be 

effective, the need to reassess and possibly change set-up 

phase components (stakeholders, objectives, alternatives, 

models, monitoring) should be less frequent than the 

iterative cycle of technical learning (decision making, 

monitoring, and assessment) (Fig. 3.4). Otherwise, 

learning cannot keep pace with changes in the structure of 

the resource system and changing stakeholder values and 

perspectives. 

63

smallmouth bass
Key Points

Active and passive approaches to adaptive management can be distinguished from other management 

approaches based on their treatment of uncertainty 

and emphasis on learning. 

Multiple sources of uncertainty can influence resource 

systems and alter the capacity to manage them.

Learning is advanced by the sequential comparison of 

model predictions against monitoring data, whereby 

confidence in an underlying hypothesis is based on 

the relative accuracy of model predictions. 

The practice of adaptive management flourishes in a 

learning organization that is open to surprise, accommodates risk, and encourages and rewards learning.

Learning in adaptive management proceeds most 

rapidly when pursuit of resource objectives is temporarily postponed so that management interventions are 

implemented according to an experimental design. 











64
65

Concluding Remarks

Adaptive management can be applicable to local resource projects as well as large-scale conservation programs, 

though the legal constraints on an adaptive approach may differ across scales. But the basic framework presented in this 

technical guide, involving an iterative process of management, monitoring, and evaluation, applies in either case. The 

key issues in deciding to use adaptive management are whether there is substantial uncertainty about the impacts on 

management, and whether the reduction of that uncertainty can be expected to improve management. 

For many important problems, adaptive management holds great promise in reducing the uncertainties that limit 

the effective management of natural resource systems. In many cases, utilizing management itself in an experimental 

context may be the only feasible way to gain the system understanding needed to improve management. In concept, 

adaptive management is neither conceptually complex nor operationally intricate. However, it requires refinements of 

the business models of DOI agencies, to more fully reflect system sustainability and resilience, more explicitly account 

for uncertainty, and more fully incorporate conservation planning, decision-based monitoring, and evaluation. 

A realistic assessment of its challenges suggests that adaptive management is likely to be neither short-term nor 

inexpensive, and a considerable amount of up-front planning may be required. Stakeholders and implementing organizations must commit to providing the necessary resources for monitoring and assessment over the time required to make 

progress in achieving project objectives. In particular, an initial investment of time and effort will increase the likelihood of better decision making and resource stewardship in the future. The need for patience and flexibility in adaptive 

management highlights the importance of carefully considering the potential use of an adaptive approach, and careful 

planning and evaluation when adaptive management is used. 
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References

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Estimation

The aggregation of field data into measures of resource attributes. Examples include means, variances, and correlation coefficients computed with sample data. Multiple estimators are always available for any resource attribute, and the 

choice of which particular estimator to use is based on statistical features such as bias and precision.

Experimentation

The imposition of treatments on subjects or experimental units for the explicit purpose of learning about treatment 

effects by observing outcomes. Ideally experimentation involves random allocation of treatments to experimental units, 

replication of treatments, and the use of controls for comparative purposes.

Experimental management

The use of management interventions for the purpose of understanding the effects of management. Interventions 

are used as experimental treatments, ideally (but infrequently) in the context of randomization, replication, and experimental control. 

Hypothesis

A suggested but unconfirmed assertion or explanation of observed patterns. Hypotheses can take many forms, 

for example, a hypothesized magnitude of a resource attribute or a mathematical relationship between attributes. 

Hypotheses are tested by comparison against field data.

Management by experiment

An approach to management that recognizes management interventions as experiments, by means of which understanding can be enhanced as management proceeds through time.

Management action

An action affecting a managed system, taken as a result of a management decision. In the context of natural 

resources, management actions typically influence the status of resources or the processes that control resource 

dynamics.

Management alternative

A potential management action. In sequential management, a management action is selected at each point in time 

from an identified set of management alternatives. The set of management alternatives constrains and influences the 

choice of a management strategy.

Management decision

A decision to take a management action. In adaptive management, decision making typically is driven by management objectives, with active stakeholder involvement. Adaptive decision making takes into account both the current 

status of resources and the level of understanding about them.

Key Terms

71
Management option

Used interchangeably with management alternative.

Management strategy

A prescription of management actions pursuant to management objectives. In the context of adaptive management, 

a management strategy describes time-specific management actions to be taken, conditional on current resource status 

and the level of understanding about resource dynamics. Management strategies often are expressed in terms of resource 

thresholds, on either side of which a different action is to be taken.

Model 

Any representation, whether verbal, diagrammatic, or mathematical, of an object or phenomenon. Natural resource 

models typically characterize resource systems in terms of their status and change through time. Models imbed hypotheses about resource structures and functions, and they generate predictions about the effects of management actions.

Objective

A desired outcome or performance measure that expresses stakeholder values and serves to guide natural resource 

decision making and evaluation of success.

Stakeholders

Individuals and organizations (e.g., managers, scientists, private citizens, nongovernmental organizations) with a 

vested interest in a shared enterprise. Interests can include an expectation of received benefit, a perceived threat, a prior 

investment of time and/or resources, or values shared with others associated with the enterprise. Active engagement of 

stakeholders promotes the successful implementation of adaptive management.

Threshold

The limiting value of a resource attribute that triggers a change in management actions. Management strategies 

often include thresholds, such that one action is specified for resource values less than the threshold and a different 

action is specified for larger resource values.

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Key Terms