Decision Making in Natural Resource Management

A Structured, Adaptive Approach

Michael J. Conroy, James T. Peterson

• Publisher: Wiley-Blackwell
• Year: 2013
• Print ISBN:
  9780470671740
  9780470671757
• Edition: 1
• eBook ISBN:
  9781118506233
• Topic: Biological Sciences
• Subtopic: Biology
• Index: Biological Sciences

This book is intended for use by natural resource managers and scientists, and students in the fields of natural resource management, ecology, and conservation biology, who are confronted with complex and difficult decision making problems. The book takes readers through the process of developing a structured approach to decision making, by firstly deconstructing decisions into component parts, which are each fully analyzed and then reassembled to form a working decision model.  The book integrates common-sense ideas about problem definitions, such as the need for decisions to be driven by explicit objectives, with sophisticated approaches for modeling decision influence and incorporating feedback from monitoring programs into decision making via adaptive management. Numerous worked examples are provided for illustration, along with detailed case studies illustrating the authors' experience in applying structured approaches. There is also a series of detailed technical appendices.  An accompanying website provides computer code and data used in the worked examples.

Additional resources for this book can be found at: www.wiley.com/go/conroy/naturalresourcemanagement.

PART I. INTRODUCTION TO DECISION MAKING

1

Introduction: Why a Structured Approach in Natural Resources?

In this chapter, we provide a general motivation for a structured approach to decision making in natural resource management. We discuss the role of decision making in natural resource management, common problems made when framing natural resource decisions, and the advantages and limitations of a structured approach to decision making. We will also define terms such as objective, management, decision, model, and adaptive management, each of which will be a key element in the development of a structured decision approach.

The first and obvious question is: why do we need a structured approach to decision making in natural resource management? We have thought a lot about this question, and realize that while the answer may not be obvious, it really comes down to some basic premises. For us, natural resource management is a developing field, and many aspects of it are not “mature.” In many respects we think that conservation and natural resource management suffer from the perception that many have that it is an ad hoc and not particularly scientific field. In our view, we have a choice: we can either use ad hoc and arguably non-scientific means to arrive at decisions; or we can use methods that are more formal and repeatable. In our view, the latter will better serve the field in the long run.

We also want to emphasize that when we refer to “management” we are speaking very broadly. That is, “management” includes virtually every type of decision we could make about a natural resource system, which would include traditional game management tools (e.g., harvest and habitat management), but also reserve design, legal protection and enforcement, translocation, captive propagation, and any other action intended to effect a conservation objective. This means that we consider conservation and management as one and the same and believe that artificial distinctions only serve to confuse students and practitioners.

The Role of Decision Making in Natural Resource Management

Virtually all problems in natural resource management involve decisions: choices that must be made among alternative actions to achieve an objective. We will define “decisions” and “objectives” more formally in the coming chapters, but can illustrate each with some simple examples. Examples of decisions include:

• Location on the landscape for a new biological reserve.
• Allowable season lengths and bag limits for a harvested population.
• Whether to capture a remnant population in danger of extinction and conduct captive breeding.
• Whether to use lethal control for an exotic invasive limiting an endemic population, and if so, which type of control.
• Whether and how to mitigate the impact of wind turbines on bird mortality.

Note that in each case, there is a choice of an action, and that some choices preclude others. So for example, if we choose location A for our reserve, given finite resources and other limitations, we have likely precluded locations B–D. Similarly, if we close the hunting season we cannot at the same time allow liberal bag limits. If we capture the remnant population we have (at least immediately) foregone natural reproduction, and so on.

Also, each of the above decisions is presumably connected to one or more objectives. We will develop objectives more fully in Chapter 3, but broadly stated, the objectives associated with the above decisions might be, respectively:

• Provide the greatest biodiversity benefit for the available funds and personnel.
• Provide maximum sustainable harvest opportunity.
• Avoid species extinction and foster species recovery.
• Restore an endemic population.
• Minimize bird mortality while fostering “green” energy.

So, at a very basic level, decision making is about connecting decisions to objectives, and structured decision making (SDM; Hammond et al. 1999, Clemen and Reilly 2001) is just a formalized way of accomplishing that connection. For some of us this connection (and way of thinking) is so obvious that it hardly needs stating, and certainly doesn’t require a book-length coverage. However, we have in our careers in academia and government, and working with natural resource management agencies, NGOs, and business, encountered numerous examples in which we believed that problems in the management of resources were exacerbated, and in some cases directly caused, by poor framing of the decision problem.

We also want to emphasize the important role of science in decision making. Science should inform decision making, but we must always recognize that science is a process and not an end. Thus, we can use science to inform decision making, but we must always be seeking to improve our scientific understanding as we make decisions. We sometimes use the analogy of a 3-legged stool of management, research, and monitoring to make this point (Conroy and Peterson 2009).

Common Mistakes in Framing Decisions

Poorly Stated Objectives

It is apparent to us that, in many cases, the objectives of management are poorly stated, if they are stated at all. This can lead to decisions that lead nowhere – that is, they are not connected to any apparent objectives. This in turn means that the decisions do not address the management problem, waste resources, and potentially create unnecessary conflict among the stakeholders. The reverse also can occur when objectives are stated, but management decisions are apparently arrived at by an independent process. As a result, the objectives cannot be achieved because they are not connected to management actions. Again, the management problem is not addressed, resources are wasted, and unnecessary conflict created; additionally, stakeholders (parties who have an interest in the outcome of decision making, and who may or may not be decision makers) may feel disenfranchised, since apparently their input in forming objectives has been ignored.

Prescriptive Decisions

A related situation arises in cases where “decisions” are formulated in a rule-based, prescriptive manner that presumes that certain sets of conditions (perhaps attributes measured via monitoring) necessarily trigger particular actions. Such formulaic approaches (common in many species recovery plans) may be useful tools in a decision-making process, but do not constitute decision making (except in the trivial sense of having decided to follow the formula).

Confusion of Values and Science

When attempts are made to define objectives, a very common problem that we see is the confusion of values (or objectives) with science (or data/ information). That is, conflating what we know (or think we know) about a problem, with what we are trying to achieve. Most natural resource professionals come from a background in the biological or earth sciences, and are more comfortable discussing “facts” and data than they are discussing values. As we will see, “facts” come into play when we try to connect candidate decisions to the objectives we are trying to achieve. Objectives, on the other hand, reflect our values (or the values of those with a stake in the decision whose proxies we hold). If we do not get the values (objectives) right, the “facts” will be useless for arriving at a decision. More insidiously, disagreements about “facts” or “science” are frequently a smokescreen or proxy for disagreement about values. One needs to look no further than the cases of the Northern Spotted Owl (Strix occidentalis caurina) or anthropogenic climate change. In each case, scientific belief (and supporting “facts”) coincides remarkably with the values of the respective stakeholder communities, with for example timber industry advocates tending to be skeptical of the obligate nature of ancient forests for owls, and many political or social conservatives questioning the science of climate change (Lange 1993, McCright and Dunlap 2011, Martin et al. 2011, Russill 2011).

Poor Use of Information

Another very common disconnect we see is the poor use of information from monitoring programs. While some general-purpose monitoring can perhaps be justified (e.g., the Long Term Ecological Research Network [LTER; http://www.lternet.edu/] programs that provide baseline monitoring in relatively undisturbed areas), omnibus monitoring programs that are not connected to and do not support decision making are often unproductive (see also Nichols and Williams 2006). Rather, we agree with Nichols and Williams (2006) that changing the focus and design of monitoring programs as part of an overarching program of conservation-oriented science or management.

This is not to say that monitoring (of any kind) is an absolute requirement of decision making. In some cases, there are few data to support quantitative statements about a decision’s impact, and little prospect that sufficient data will be acquired in the near term to allow unequivocal statements about management; many problems involving imperiled species and their habitats fall into this category. Nonetheless, it is incumbent on managers to make decisions given whatever data or other knowledge is available. Putting off a decision until more information is available is, of course, itself a decision, with potentially disastrous consequences (“paralysis by analysis” is another variant). The reality is that we can always learn more about a system; the trick is to use what we know now to make a good decision, while always striving to do better with future decisions.

What Is Structured Decision Making (SDM)?

SDM consists of three basic components. The first is explicit, quantifiable objectives, such as maximizing bear population size or minimizing human–bear conflicts. The second is explicit management alternatives (actions) (e.g., harvest regulations or habitat management) that can be taken to meet the objectives. The third component is models that are used to predict the effect of management actions on resource objectives (e.g., models predicting population size after various harvest regulations). Because knowledge about large-scale ecological processes and responses of resources to management are always imperfect, uncertainty is incorporated in SDM through alternative models representing hypotheses of ecological dynamics and statistical distributions representing error in model parameters and environmental variability.

Why Should We Use a Structured Approach to Decision Making?

Some decision problems have an obvious solution and need no further analysis. In such cases, two or more decision makers with the same objective would probably arrive at the same decision, perhaps without even consciously making a choice. Such decision problems probably do not require a structured approach.

However, we suggest that these types of problems are not typical of natural resource management. In our experience, natural resource decision problems are typically complex, and multiple decision makers can easily disagree on the best decision. Furthermore, the process by which natural resource decision makers arrive at decisions tends to be difficult to explain, which in turn makes it difficult to communicate. For example, a supervisor, who has much knowledge and experience to draw on, trying to explain decisions to a new employee, who has only a rudimentary understanding of issues. Inevitably, this results in miscommunication due to the ad hoc way d...

Table of contents

• Cover
• Title page
• Copyright page
• List of boxes
• Preface
• Acknowledgements
• Guide to using this book
• Companion website
• PART I. INTRODUCTION TO DECISION MAKING
• PART II. TOOLS FOR DECISION MAKING AND ANALYSIS
• PART III. APPLICATIONS
• PART IV. APPENDICES
• Glossary
• Index