United States

Department of 

Agriculture

Forest Service

Northern 

Research Station

General Technical

Report NRS-P-107

Environmental Futures 

Research: Experiences, 

Approaches, and 

Opportunities
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Abstract

These papers, presented in a special session at the International Symposium on Society 

and Resource Management in June 2011, explore the transdisciplinary fi eld of futures 

research and its application to long-range environmental analysis, planning, and policy. 

Futures research began in the post-World War II era and has emerged as a mature 

research fi eld. Although the future of complex social-ecological systems cannot be 

predicted, these papers show how futures research can offer perspectives and methods 

that help researchers, decisionmakers, and other stakeholders explore alternative futures 

and gain environmental foresight—insight that can inform decisionmaking on environmental 

challenges. One author points out that the study of the future can be thought of as the study 

of change. He discusses three types of futures: the expected future, a range of plausible 

alternatives, and the preferred future, which decisionmakers can shape depending on their 

choice of action. An example of the methodology of futures research is provided in another 

chapter, which illustrates the use of scenario development. Another chapter identifi es global 

trends that could dramatically change social-ecological systems.

The second half of the collection applies the methods and approaches of futures research 

to natural resource management. A global and a regional scenario illustrate scenario 

planning, a methodology that produces sets of plausible futures that could develop from 

current conditions depending on alternative human choices and drivers of change. Another 

example demonstrates how analysts can incorporate global scenarios and modeling, and 

scoping of trends and issues, into forest inventory data to gain insight into the regional 

forests of tomorrow. A chapter on linking global scenarios with assessments of U.S. natural 

resources as required under the Resources Planning Act considers both opportunities and 

challenges. Lessons learned from an analysis of futures research conducted since the 

1970s at the U.S. Environmental Protection Agency are also offered. These papers suggest 

that the perspectives and methods of futures research hold great potential for developing 

the foresight needed to meet environmental challenges of the 21st century.

The fi ndings and conclusions of each article in this publication are those of the individual 

author(s) and do not necessarily represent the views of the U.S. Department of Agriculture, 

Forest Service. All articles were received in digital format and were edited for uniform type 

and style; each author is responsible for the accuracy and content of his or her own paper.

Manuscript received for publication 1 June 2012
The Authors

David N. Bengston, Peter C. Bishop, Stephen R. Carpenter, Peter J. Ince, 

George H. Kubik, Linda L. Langner, W. Keith Moser, Robert L. Olson, 

Adena R. Rissman, Stephen R. Shifley, and Kay E. Strong

Environmental Futures Research: 

Experiences, Approaches, and Opportunities

Compiled by

David N. Bengston

General Technical Report NRS-P-107
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CONTENTS

Foreword .................................................................................................................................1

David N. Bengston

Futures Research:

A Neglected Dimension in Environmental Policy and Planning ...............................4

David N. Bengston

An Approach to the Future ...............................................................................................13

Peter C. Bishop

A Framework for Developing Foresight in Natural Resource Management .........18

Kay E. Strong

Global Mega Forces: Implications for the Future of Natural Resources ...............25

George H. Kubik

Scenarios and Decisionmaking for Complex Environmental Systems .................37

Stephen R. Carpenter and Adena R. Rissman

The Northern Forest Futures Project: 

A Forward Look at Forest Conditions in the Northern United States ....................44

W. Keith Moser and Stephen R. Shifl ey

Linking Global Scenarios to National Assessments: 

Experiences from the Resources Planning Act (RPA) Assessment.......................... 55

Linda L. Langner and Peter J. Ince

Environmental Futures Research at the U.S. Environmental 

Protection Agency ..............................................................................................................66

Robert L. Olson

About the Authors ..............................................................................................................78
Page intentionally left blank
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 1

FOREWORD

David N. Bengston

in Madison, WI, on June 6, 2011. Speakers in these 

sessions included academic and professional futurists, 

as well as environmental researchers who have applied 

futures methods in their work.

Th e fi rst four papers introduce futures research as a 

broad approach to developing environmental foresight 

and highlight some fundamental principles of futures 

thinking. In the opening paper I provide an overview 

of futures research. Th e goal of futures research is to 

explore possible, plausible, and preferable futures in 

order to anticipate and prepare for those futures. I 

briefl y trace the development of futures research from 

its beginnings in the post-World War II era, to a 

mature transdisciplinary fi eld with a considerable body 

of literature, many specialized journals, professional 

organizations, and distinct methods. Th e paper concludes 

with a call for environmental futures research to help 

develop the foresight needed for a sustainable future.

In an insightful paper, Peter Bishop, professor and 

director of the graduate program in Futures Studies at 

the University of Houston, identifi es some fundamental 

perspectives for thinking about and approaching the 

study of the future. He begins with a consideration of 

change because, as he states, “the study of the future is 

the study of change.” After describing the four main 

attributes of change, Professor Bishop addresses an 

approach to forecasting that takes uncertainty seriously. 

He concludes by identifying three broad drivers of the 

future and how each driver can be thought of as creating 

a diff erent type of future: the baseline future, a range of 

alternative futures, and the preferred future.

Futurist and economist Kay Strong of Baldwin-Wallace 

College—and a graduate of and former instructor in the 

Futures Studies program at the University of Houston—

describes a framework for developing foresight that 

has been used to prepare professional futurists at the 

University of Houston. Framework forecasting is 

an organizing technique for gathering and sorting 

information about the topic of interest when conducting 

futures research. Professor Strong also briefl y describes 

Environmental foresight is insight into future 

environmental challenges and opportunities, and the 

ability to apply that insight to prepare wisely for a 

sustainable future. Successful environmental planning, 

management, and policy require the development and 

continual updating of foresight. U.S. Environmental 

Protection Agency (EPA) Administrator Stephen 

Johnson has stated: “Failure to look beyond present 

conditions only ensures that emerging problems will be 

more diffi cult to address and that opportunities may be 

missed” (U.S. EPA 2005: 1). Th e soundness and acuity 

of our environmental foresight are key determinants of 

success in addressing critical environmental issues.

Rapid technological, socio-cultural, and economic 

changes with the potential for sweeping environmental 

eff ects have greatly increased the need for environmental 

foresight. In addition to the increasing pace of change, 

some who study social-ecological systems believe that 

“surprise” is pervasive and increasing along with the 

expanding scale of human impacts (Gunderson and 

Folke 2008, Kates and Clark 1996). Examples of 

environmental surprise range from sudden disasters like 

the collapse of fi sheries to more gradual events such as 

unexpected eff ects of climate change. Surprise greatly 

complicates the challenge of developing environmental 

foresight. Th e prevalence of surprise in social-ecological 

systems implies that some important uncertainties are 

irreducible and that traditional scientifi c tools are blunt 

instruments for developing environmental foresight. 

New approaches are needed.

Although no one can predict the future of complex 

social-ecological systems, the authors of the papers in this 

compilation believe that it is both possible and urgent 

to develop useful insights into emerging environmental 

problems and needs, and to apply these insights to help 

achieve a sustainable future. Th e authors explore the 

potential of futures research, a transdisciplinary fi eld 

of inquiry that has been developing for more than 50 

years, to address this important challenge. Th e papers 

were presented in two sessions at the International 

Symposium on Society and Resource Management, held 
2 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

the process of scenario development, a core method 

of futures research that can use the information from 

framework forecasting.

George Kubik of the Anticipatory Futures Group, 

LLC and the University of Minnesota discusses “global 

mega forces,” defi ned as major emerging trends with 

the potential for high-impact outcomes in the future. 

He fi rst identifi es seven broad categories of global mega 

forces and briefl y discusses their implications for natural 

resource futures. Kubik then examines two technological 

mega forces in detail: networked sensor-actuator 

technologies and electronic performanceware systems. 

Th ese two developments are highlighted because of their 

potential to signifi cantly aff ect the future of society and 

natural resources.

Th e next four papers provide examples of futures research 

methods and approaches applied to natural resource 

issues. Stephen Carpenter and Adena Rissman of the 

University of Wisconsin discuss scenario planning, 

which they describe as a method for thinking creatively 

and systematically about plausible futures. Th e sets of 

plausible stories produced by scenario planning explore 

how the future might develop from current conditions 

under a range of alternative human choices and the 

eff ects of uncontrollable drivers. Carpenter and Rissman 

describe examples of global (Millennium Ecosystem 

Assessment) and regional (Yahara Watershed, Madison, 

WI) scenario planning. Th ey conclude that scenarios 

can help address some fundamental challenges in 

sustainability science.

Th e Northern Forest Futures Program (NFFP) is 

described by Keith Moser and Stephen Shifl ey, scientists 

with the U.S. Forest Service, Northern Research Station. 

Th e NFFP is a cooperative eff ort involving the Northern 

Research Station, the Northeastern Area Association of 

State Foresters, and academic scientists. Using data from 

existing assessments and inventories, a scoping of trends 

and issues, and scenarios from the Intergovernmental 

Panel on Climate Change (IPCC) linked with selected 

global circulation models, the NFFP is a “window on 

tomorrow’s forests” for the Northeast and Midwest.

A long-standing and prominent futures assessment 

of renewable natural resources is discussed by Linda 

Langner, National Program Leader for the Resources 

Planning Act Assessment, U.S. Forest Service Research 

and Development, and Peter Ince, a research forester 

with the U.S. Forest Service, Forest Products Laboratory. 

As required by the Forest and Rangeland Renewable 

Resources Planning Act (RPA) of 1974, the periodic 

RPA Assessments project resource conditions and trends 

50 years into the future. Th e 2010 RPA Assessment 

included scenarios linked to global scenarios developed 

by the IPCC. Ince and Langner discuss the development 

of quantitative linkages with the IPCC scenarios 

and methodological challenges that were faced in 

disaggregating the IPCC data.

Finally, Robert Olson, Senior Fellow at the Institute 

for Alternative Futures, describes the futures research 

carried out by the U.S. EPA dating back to the 1970s. 

More than any other environmental or natural resource 

agency in the United States, the EPA has pursued futures 

research, albeit with varying levels of commitment over 

time, in an eff ort to anticipate emerging environmental 

issues, threats, and opportunities rather than simply react 

to them after the fact. Olson was involved in much of 

this work fi rst-hand as a consultant to the agency. He 

reviews past and current eff orts to develop a capacity for 

environmental foresight within the EPA, and discusses 

important lessons for other agencies and institutions 

concerned with our environmental future.

Given the pace and complexity of change today, the need 

to anticipate emerging environmental issues, threats, and 

opportunities is great. Attempting to “look beyond the 

headlights,” anticipate change, and prepare for a range of 

alternative futures is vital in environmental aff airs. Th e 

problem is that we are often ineff ective, not systematic, 

or just plain naïve in our attempts to anticipate change. 

Th is collection of papers suggests that the methods 

and perspectives of futures research off er a promising 

set of approaches to develop the foresight needed to 

successfully address the environmental challenges of 

tomorrow.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 3

LITERATURE CITED

Gunderson, L.; Folke, C. 2008. A diff erent future 

(editorial). Ecology and Society. 13(2): 57. Available 

at http://www.ecologyandsociety.org/vol13/iss2/

art57/. (Accessed 27 June 2012).

Kates, R.W.; Clark, W.C. 1996. Environmental 

surprise: expecting the unexpected. Environment. 

38(2): 6-11, 28-34.

U.S. Environmental Protection Agency (EPA). 2005. 

Shaping our environmental future: f oresight in the 

Offi ce of Research and Development. Washington, 

DC: U.S. Environmental Protection Agency, Offi ce of 

Science Policy, Offi ce of Research and Development. 

20 p.
4 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

FUTURES RESEARCH:

A NEGLECTED DIMENSION IN ENVIRONMENTAL POLICY AND PLANNING

David N. Bengston

centuries. Th e welfare of future generations was the root 

concern of George Perkins Marsh’s monumental 1864 

book “Man and Nature” (Lowenthal 2001), which 

has been called “the fountainhead of the conservation 

movement” in the United States (Mumford 1931: 35). 

In the 1960s, the modern environmental movement 

was spurred by an urgent desire to avoid the dystopian 

ecological future refl ected in the title of Rachel Carson’s 

“Silent Spring” (1962). Th e seminal Brundtland 

Commission report, “Our Common Future,” sparked 

a worldwide and ongoing discussion about sustainable 

development, defi ned as “. . . development that meets the 

needs of the present without compromising the ability 

of future generations to meet their own needs” (World 

Commission on Economic Development 1987: 43). 

Visions of environmental futures that have motivated 

generations of environmental stakeholders have often been 

dominated by neo-Malthusian warnings of environmental 

degradation, natural resource scarcity, food shortages, 

and overpopulation (e.g., Brown 1954, Meadows et al. 

1972, Sears 1935), although other visions have portrayed 

a much brighter view of environmental futures (e.g., 

Glesinger 1949, Lomborg 2001, Simon 1981).

Th e pervasive orientation toward the future in 

conservation thinking has been institutionalized 

in environmental protection and natural resource 

management agencies over the past century, beginning 

with the founding legislation and mission statements 

of these agencies. For example, the “Organic Act” that 

created the U.S. National Park Service in 1916 states that 

the purpose of the National Parks is to “ . . . conserve 

the scenery and the natural and historic objects and 

the wild life therein and to provide for the enjoyment 

of the same in such manner and by such means as will 

leave them unimpaired for the enjoyment of future 

generations” (National Park Service Organic Act, 16 

U.S.C.1., 1916). Th e mission of the U.S. Forest Service 

is to “ . . . sustain the health, diversity, and productivity 

of the Nation’s forests and grasslands to meet the needs 

of present and future generations” (U.S. Department of 

Agriculture, Forest Service 2008). Numerous additional 

Abstract. Th e need for strategic foresight in an 

increasingly complex and rapidly changing world poses 

a formidable challenge to environmental planners and 

policy makers. Th is paper introduces futures research as 

an under used but fruitful set of approaches to addressing 

this challenge. Futures research is a transdisciplinary 

social science that uses a wide range of methods to 

explore possible, plausible, and preferable futures with 

the goal of anticipating and preparing for those futures. 

Th e historical context for environmental futures is briefl y 

reviewed, an overview of futures research as a distinct 

fi eld of study is presented, and several of the main 

methods of futures studies are described.

INTRODUCTION

Futures research is a transdisciplinary fi eld of inquiry 

that uses a variety of distinctive methods to explore 

alternative futures. Th is paper introduces futures 

research as an underused but fruitful set of approaches 

to the formidable challenge of anticipating change in 

a complex and rapidly changing world. Futurists have 

developed important insights into the nature of change, 

perspectives for thinking creatively and deeply about the 

future, and an array of methods for exploring alternative 

futures. Futures research has the potential to enrich 

environmental and natural resource planning and policy 

with a cross-fertilization of new ideas and approaches. 

Th e next section describes the historical context for 

environmental futures. An overview of futures research as 

a distinct fi eld of study follows. A fi nal section describes 

several of the main methods developed and employed by 

futurists.

The Historical Context for Environmental 

Futures

Conservationists, environmentalists, and environmental 

professionals have always been motivated by a strong 

concern for future generations and by visions of 

sustainable—or more often unsustainable—ecological 

and social futures. Th is orientation toward the future 

dates back to the beginnings of the Progressive Era 

conservation movement of the late 19th and early 20th 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 5

examples of future-oriented missions could be given for 

national, state, and local environmental agencies around 

the world, as well as for nongovernmental environmental 

organizations and environmental policy think tanks.

Environmental agencies and organizations have often 

struggled to fulfi ll these future-oriented missions, 

however. Environmental agencies and scientists have 

devoted substantial eff ort to forecasting, but this work 

has been plagued by a host of shortcomings and the track 

record has been poor at best (Pilkey and Pilkey-Jarvis 

2007, Sarewitz et al. 2000, Sherden 1998). Ecological 

forecasts are fi lled with irreducible uncertainties due to 

drivers beyond the scope of ecology (e.g., climate change, 

demographic change, and management interventions), 

unknown feedbacks in coupled social-ecological systems, 

and unpredictable human actions (Carpenter 2002). Th e 

complex interactions of people and ecosystems ensure 

that ecological forecasts are highly uncertain. Experience 

in the social sciences confi rms that predictions of social 

phenomena are also notably inaccurate. Sociologist 

Seymour Martin Lipset reviewed the accuracy of forecasts 

in economics, demography, sociology, and political 

science, and concluded, “Social scientists are good 

historians. Th ey are able to understand the processes 

in what has already happened. But they have not been 

good forecasters” (Lipset 1983: 157). Even the latest 

generation of economic forecasting models (Dynamic 

Stochastic General Equilibrium models), the product of 

a decade of intense research, fail dismally at forecasting 

basic economic variables, although they perform no 

worse than other economic forecasting methods (Edge 

and Gurkaynak 2010).

Despite the shortcomings of traditional approaches 

to social and ecological forecasting, the need for 

environmental foresight has increased in recent decades 

as the pace of change has accelerated and the frequency 

of surprise has increased. Th e Millennium Ecosystem 

Assessment (2005: 1) concluded that “over the past 50 

years, humans have changed ecosystems more rapidly 

and extensively than in any comparable period of time in 

human history, largely to meet rapidly growing demands 

for food, fresh water, timber, fi ber, and fuel.” Surprises 

are increasing along with the expanding scale of human 

impacts (Gunderson and Folke 2008). Hibbard et al. 

(2007) refer to the period following World War II as 

the “Great Acceleration,” a time of signifi cant increase 

in the scope, scale, and intensity of impacts on the 

social-ecological system. Global indicators of the Great 

Acceleration discussed by Hibbard and colleagues include 

rapid growth in human populations, atmospheric carbon 

dioxide concentrations, average global temperatures, use 

of nitrogenous fertilizers, percentage of marine fi sheries 

fully exploited, and species extinctions. Add to these 

changes the rapid pace of technological change with the 

potential for sweeping environmental eff ects—such as 

genetic engineering and nanotechnologies—and it is 

clear that the need for environmental foresight has never 

been greater (Olson and Rejeski 2005).

AN OVERVIEW OF FUTURES RESEARCH1

Futures research, also called futures studies, futures, 

and strategic foresight, has been defi ned as a 

“methodological-based form of inquiry into alternative 

futures in terms of what is possible, probable, and/or 

preferable with the goal of anticipating and possibly 

infl uencing those futures” (Kubik 2009: x). Bell 

(1997) further characterizes futures research as a 

transdisciplinary social science and an “action science” 

with an orientation to informing decisionmaking 

and action. Futures research is distinct from strategic 

planning, although there is a symbiosis and a widely 

recognized link between these two fi elds (Cole 2001). 

Both futures research and planning may identify 

preferable futures in terms of vision and goals. But where 

planning involves the development of a specifi c course of 

action to achieve stated goals, futures research provides 

a broader and longer-term perspective, explores a range 

of alternative futures, and provides essential context for 

planners’ and policy makers’ more specifi c concerns.

A central principle of futures research is the importance 

of exploring and preparing for multiple plausible futures, 

not just the one considered most likely, because the 

future is fundamentally uncertain (Bishop et al. 2007). 

As futurist Herman Kahn stated, “Th e most likely 

future isn’t” (1982: 82). In other words, even what is 

considered the most likely future is a low-probability 

1

Th is section draws from Bengston et al. (2012).
6 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

event given the complex nature of social-ecological 

systems and the frequency of discontinuous change and 

surprise. Th e most disruptive type of discontinuous 

change involves events of low probability but high 

impact, which futurists often refer to as “wild cards” 

(Cornish 2004, Petersen 1997). Rather than attempting 

to predict the most likely future—the goal of traditional 

scientifi c forecasting—the goal of futures research is 

to explore a range of possible and plausible alternative 

futures, in addition to the most probable future or 

baseline forecast (Bishop 1998, Cornish 2004). Th e 

frequency of discontinuous change makes it vitally 

important that we think broadly about the future, to 

minimize the risk of being surprised and unprepared.

Th e origins of futures research are sometimes traced 

back to a long tradition of utopian writings exploring 

preferred futures, beginning with the publication of 

Th omas More’s “Utopia” in 1516. Bell (1997), Strathern 

(2007), and others have examined the early roots 

and many diverse strands of futures research, which 

reveal the deep human need—rooted in survival—to 

anticipate and infl uence the future course of events. In 

the modern era, futures research is sometimes traced to 

the 1901 publication of H.G. Wells’ “Anticipations of 

the Reaction of Mechanical and Scientifi c Progress upon 

Human Life and Th ought,” which proposed a science 

of the future (Wager 1991). In 1932, Wells discussed 

the need for “professors of foresight” and university 

departments of foresight to anticipate and prepare for 

the future (Wells 1987). Not until the post-World 

War II era, however, did futures research begin to take 

shape as a distinct fi eld of study. Work on the future 

of military technology was carried out in the 1950s by 

RAND Corporation, a think tank that grew out of early 

operations research and systems analysis. RAND served 

as a training ground for many early futurists, including 

Herman Kahn, one of the pioneers of scenario analysis, 

and Olaf Helmer, who helped develop the Delphi 

method. Th e Defense Advanced Research Projects 

Agency—one of many U.S. Department of Defense units 

that include futures research—was established in 1958 

as a response to a “wild card” event: the Soviet Union’s 

launching of Sputnik.

Th e development of futures research accelerated 

during the turbulent 1960s and 1970s. Many futures 

organizations were founded at this time, including the 

U.S.-based World Future Society in 1966 and the more 

international World Futures Studies Federation in 

1967. Best-selling futures books such as “Future Shock” 

(Toffl er 1970), “Limits to Growth” (Meadows et al. 

1972), and “Megatrends” (Naisbitt 1982) captured the 

public’s imagination and elevated popular awareness of 

futures research.

In recent decades, futures research has developed into 

a well-established transdisciplinary fi eld. Numerous 

academic and popular futures journals have appeared, 

including Foresight, Futures, Futures Research 

Quarterly, Futuribles (in French), Futurics, Journal 

of Futures Studies, On the Horizon, Th e Futurist, 

Technological Forecasting and Social Change, and 

World Future Review. Many business journals regularly 

publish futures research, such as International Journal 

of Forecasting, Long Range Planning, and Strategic 

Management Journal. Academic futures programs 

have also developed around the world, and the World 

Futures Studies Federation has compiled a list of the 

various tertiary futures educational programs, including 

graduate programs in futures studies and programs 

that incorporate futures studies, as well as single units, 

short courses, and online futures studies courses (World 

Futures Studies Federation 2012). Th e World Future 

Society’s annual conference currently attracts about 

1,000 attendees, and its “Futurist Directory” lists nearly 

1,400 people professionally involved in the study of 

the future (World Future Society 2000). A major 

global futures research eff ort, the Millennium Project 

(Millennium Project 2012), was initiated in 1992 

by the Smithsonian Institution, Th e Futures Group 

International, and the United Nations University. Th e 

Millennium Project is now an independent, non-profi t 

futures research think tank with nodes in 40 countries 

around the world, and it produces an annual “State of 

the Future” report as well as many special studies.

Within futures research, a variety of distinct traditions 

have developed since the 1960s. Futurists hold many 

diff erent views of what futures research is and how the 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 7

study of the future should be approached (Inayatullah 

1996). Gidley et al. (2009) identify fi ve traditions, which 

they label predictive-empirical, critical-postmodern, 

cultural-interpretive, prospective-action (or participatory 

futures), and integrative-holistic. A detailed discussion 

of these traditions or other proposed typologies of 

futures research is beyond the scope of this paper, but 

each can generate useful insights depending on the 

decision context. Multiple traditions are often employed 

in futures research as a strategy for dealing with 

fundamental uncertainties.

In sum, futures research is now a mature fi eld of study 

with a considerable body of literature, many specialized 

journals, professional organizations, and distinct methods 

and perspectives for studying possible, plausible, and 

preferable futures. Th e majority of futures research 

nonetheless remains invisible to the scholarly community 

and the public because it takes place in military units, 

intelligence agencies, and corporations around the 

world and is hence proprietary or confi dential. In 

nearly all major corporations, applied futures research 

is quietly carried out either by a dedicated futures 

group or, more often, under rubrics such as strategic 

and long-range planning, technological forecasting, 

strategy development, and horizon scanning. Limited 

versions of this research are sometimes published (e.g., 

Chief of Force Development 2010, Central Intelligence 

Agency 2000, Royal Dutch/Shell Group 2005), but 

most is closely guarded and unpublished. Th us, due to 

the proprietary or confi dential nature of most futures 

research, the published literature is the tip of a much 

larger iceberg (Bell 1997).

FUTURES RESEARCH METHODS

As a transdisciplinary fi eld of inquiry, futures research 

embraces methodological pluralism, the philosophy of 

science that claims multiple disciplinary approaches, 

frameworks of analysis, and ways of knowing are required 

to understand complex systems or phenomena (Norgaard 

1989). Consequently, futurists have developed a wide 

range of methods and borrowed or adapted methods 

from many fi elds. A comprehensive futures project 

usually involves multiple methods to address diff erent 

dimensions of the problem. Several leading futurists 

have provided comprehensive reviews of futures research 

methods (e.g., Bell 1997, Fowles 1978, Glenn and 

Gordon 2009, Helmer 1983). Th is section briefl y reviews 

several of the main methods used in futures research: 

scanning, visioning, the Delphi method, and scenarios.

Scanning, also called horizon scanning or environmental 

scanning, refers to a wide range of processes for 

identifying and understanding signifi cant emerging 

trends in the external environment of an organization 

(e.g., a government agency, corporation, or nongovernmental organization) or an area of interest (e.g., 

biological diversity, wildfi re, or ecosystem services). 

Ideally, scanning serves as an early warning system to 

identify potential threats and opportunities. Th e goal 

is to fi nd early indications of future developments 

that may be important. Gordon and Glenn (2009: 4) 

characterize scanning as “the central input to futures 

research” because the emerging trends identifi ed through 

scanning are often used in other futures research 

methods. Scanning was fi rst used extensively during 

World War II and has long been standard practice in 

business as well as many government agencies (Cornish 

2004). Th e digital age has transformed scanning and 

there are now hundreds of approaches tailored to specifi c 

decisionmaking contexts, all of which involve identifying 

and classifying trends or potential trends into categories. 

A key element of eff ective scanning systems is feedback 

from management to the scanning team, so the system 

can “learn” to produce the most germane information 

and improve performance (Gordon and Glenn 2009).

Visioning or preferred futures methods involve 

identifying and choosing a preferred image of the 

future, a vital step in most comprehensive futures 

research projects (Hines and Bishop 2007). A vision 

is a compelling statement of the future that a group 

or organization wants to create based on shared deep 

values and purpose (Bezold 2009), or an idealized state 

that conveys the possibility of future attainment (Huber 

1978). Images of the future are important because 

they enhance options and possibilities in the present 

(Slaughter 1995). “Future workshops” to create visions 

of preferred futures were organized and conducted in 

Europe by writer and futurist Robert Jungk beginning in 
8 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

1962 (Jungk and Mullert 1987). While Jungk and others 

were conducting future workshops in Europe, Americans 

Edward Lindaman and Ronald Lippitt created a similar 

method called Preferred Futuring. Various forms of 

Preferred Futuring have been used by tens of thousands 

of organizations (Lippitt 1998).

Th e Delphi method, named after the Greek oracle at 

Delphi, is a futures research technique that solicits 

and structures the opinions of a panel of experts over 

multiple rounds to develop assessments of alternative 

futures (Kubik 2009). Th is method was developed 

at the RAND Corporation in the early 1950s in a 

study of the likely eff ects of nuclear war (Linstone and 

Turoff 1975). Early applications of this method were 

dominated by forecasting advancements in science and 

technology, following the lead of the classic Delphi study 

by Gordon and Helmer (1964). Th e Delphi method, in 

its many forms, has been applied in thousands of studies 

internationally for a wide range of purposes (Gordon 

2007).

Scenario development and analysis is the most widely 

used futures research tool for helping decisionmakers 

think creatively about possible and plausible futures 

in the context of a world of great uncertainties. Glenn 

and Th e Futures Group International (2009: 2) defi ne 

a scenario as “... a story with plausible cause and 

eff ect links that connects a future condition with the 

present, while illustrating key decisions, events, and 

consequences throughout the narrative.” Th e output of 

scenario analysis is a set of stories or narratives about 

plausible futures. Th e stories are not predictions, but 

represent a range of plausible futures intended to help 

decisionmakers and other stakeholders build adaptive 

capacity to make their systems more resilient. Th e 

scenario method was developed by Herman Kahn and 

others at RAND Corporation and was fi rst brought 

to public attention by the publication of Kahn’s 

infl uential books (e.g., Kahn 1962, Kahn and Weiner 

1967). Scenario analysis has been widely used for many 

decades in military and business planning (Bradfi eld et 

al. 2005). More than two dozen specifi c techniques for 

developing scenarios have been identifi ed, and Bishop 

et al. (2007) discuss eight broad types of scenario 

development methods. Unlike other futures research 

methods, scenario analysis has increasingly been applied 

to environmental issues. A growing number of large-scale 

environmental studies include or are based on scenario 

methods, such as the Intergovernmental Panel on 

Climate Change (IPCC) reports (Solomon et al. 2007), 

and the Millennium Ecosystem Assessment (Carpenter et 

al. 2005, Raskin 2005).

Many other futures research methods have been 

developed by futurists or adapted from other fi elds, each 

with unique advantages and disadvantages depending 

on the context. For example, the Millennium Project’s 

“Futures Research Methodology—v.3.0” describes more 

than 30 individual methods, including the futures wheel, 

cross-impact analysis, technology sequence analysis, and 

relevance trees. Together, these methods constitute a 

diverse and powerful tool kit for examining alternative 

futures.

CONCLUDING COMMENT

Th is paper has briefl y introduced futures research as a 

vital but often overlooked dimension in environmental 

science and policy. Futures research explores a range of 

possible, plausible, and preferred futures, and examines 

their implications for planning, management, and 

policy. Th e methods of futures research have been 

widely and productively applied in business and military 

spheres over the past 50 years, yet are mostly unknown 

in environmental aff airs, with the exception of the 

recent surge in the use of scenario analysis in global 

environmental assessments. Th ese relatively recent 

applications of a core futures method are encouraging 

and have demonstrated the usefulness of futures 

research as an alternative to traditional forecasting 

methods in dealing with irreducible uncertainties and 

exploring alternative futures. Application of the full 

range of methods and perspectives of futures research to 

environmental policy, however, has been scattered and 

minimal. Consequently, futures research has contributed 

relatively little to environmental issues to date, despite 

the need to eff ectively explore alternative futures for 

sound policy and planning in a rapidly changing world. 

Futures research off ers a valuable set of tools and 

perspectives, and has an important role in sustainability 

science and policy.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 9

LITERATURE CITED

Bell, W. 1997. Foundations of futures studies, 

volume 1: History, purposes, and knowledge. New 

Brunswick, NJ: Transaction Publishers. 365 p.

Bengston, D.N.; Kubik, G.H.; Bishop, P.C. 2012. 

Strengthening environmental foresight: 

potential contributions of futures research. 

Ecology and Society. 17(2): 10. Available at 

www:ecologyandsociety.org/vol17/iss2/art10. 

(Accessed 22 June 2012).

Bezold, C. 2009. Using vision in futures planning. 

In: Glenn, J.C.; Gordon, T.J., eds. Futures research 

methodology—version 3.0 (CD-ROM). Washington, 

DC: Th e Millennium Project.

Bishop, P. 1998. Th inking like a futurist. Th e Futurist. 

32(5): 39-42.

Bishop, P.; Hines, A.; Collins, T. 2007. Th e current 

state of scenario development: an overview of 

techniques. Foresight. 9(1): 5-25.

Bradfi eld, R.; Wright, G.; Burt, G.; Cairns, G.; Van 

Der Heijden, K. 2005. Th e origins and evolution 

of scenario techniques in long range business 

planning. Futures. 37(8): 795-812.

Brown, H. 1954. Th e challenge of man’s future. New 

York, NY: Viking Press. 290 p.

Carpenter, S.R. 2002. Ecological futures: building an 

ecology of the long now. Ecology. 83(8): 2069-2083.

Carpenter, S.R.; Pingali, P.L.; Bennett, E.M.; Zurek, 

M.B., eds. 2005. Ecosystems and human well-being: 

scenarios - fi ndings of the Scenarios Working 

Group. Millennium Ecosystem Assessment Series. 

Washington, DC: Island Press. 560 p.

Carson, R. 1962. Silent spring. Boston, MA: Houghton 

Miffl in. 368 p.

Central Intelligence Agency. 2000. Global trends 2015: 

a dialogue about the future with nongovernmental 

experts. Available at http://www.dni.gov/nic/PDF_

GIF_global/globaltrend2015.pdf (Accessed 22 June 

2012).

Chief of Force Development. 2010. Th e future of the 

security environment, 2008-2030. Part 1: Current 

and emerging trends. Ottawa, ON: Chief of Force 

Development, National Defense Headquarters. 

Available at http://www.cfd-cdf.forces.gc.ca/sites/

page-eng.asp?page=7241. (Accessed 22 June 2012).

Cole, S. 2001. Dare to dream: bringing futures 

into planning. Journal of the American Planning 

Association. 67(4): 372-383.

Cornish, E. 2004. Futuring: the exploration of the 

future. Bethesda, MD: World Future Society. 313 p.

Edge, R.; Gurkaynak, R.S. 2010. How useful are 

estimated DSGE model forecasts for central 

bankers? Brookings Papers on Economic Activity 

(BPEA), Fall 2010. Washington, DC: Brookings 

Institution. Available at http://www.brookings.edu/~/

media/projects/bpea/fall 2010/2010b_bpea_edge.pdf. 

(Accessed 22 June 2012).

Fowles, J., ed. 1978. Handbook of futures research. 

Westport, CT: Greenwood Press. 822 p.

Gidley, J.M.; Fien, J.; Smith, J.A.; Th omsen, D.C.; 

Smith, T.F. 2009. Participatory futures methods: 

towards adaptability and resilience in climatevulnerable communities. Environmental Policy and 

Governance. 19(6): 427-440.

Glenn, J.C.; Th e Futures Group International. 2009. 

Scenarios. In: Glenn, J.C.; Gordon, T.J., eds. Futures 

research methodology—version 3.0 (CD-ROM). 

Washington, DC: Th e Millennium Project.

Glenn, J.C.; Gordon, T.J., eds. 2009. Futures 

research methodology—version 3.0 (CD-ROM).

Washington, DC: Th e Millennium Project. Available 
10 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

at http://www.millennium-project.org/millennium/

FRM-V3.html#toc. (Accessed 22 June 2012).

Glesinger, E. 1949. Th e coming age of wood. New 

York, NY: Simon and Schuster. 279 p.

Gordon, T.J. 2007. Energy forecasts using a 

“roundless” approach to running a Delphi study. 

Foresight. 9(2): 27-35.

Gordon, T.J.; Glenn, J.C. 2009. Environmental 

scanning. In: Glenn, J.C.; Gordon, T.J., eds. Futures 

research methodology—version 3.0 (CD-ROM). 

Washington, DC: Th e Millennium Project.

Gordon, T.J.; Helmer, O. 1964. Report on a longrange forecasting study. RAND Paper P-2982. Santa 

Monica, CA: RAND Corporation.

Gunderson, L.; Folke, C. 2008. A diff erent future 

(editorial). Ecology and Society. 13(2): 57. Available 

at http://www.ecologyandsociety.org/vol13/iss2/

art57/. (Accessed 22 June 2012).

Helmer, O. 1983. Looking forward: a guide to futures 

research. Beverly Hills, CA: Sage Publications. 376 p.

Hibbard, K.A.; Crutzen, P.J.; Lambin, E.F.; Liverman, 

D.M.; Mantua, N.J; McNeil, J.R.; Messerli, B.; 

Steff en, W. 2007. Group report: decadal-scale 

interactions of humans and the environment. 

In: Costanza, R.; Graumlich, L.J.; Steff en, W., eds. 

Sustainability or collapse? An integrated history and 

future of people on earth. Cambridge, MA: Th e MIT 

Press: 341-375.

Hines, A.; Bishop, P., eds. 2007. Th inking about 

the future: guidelines for strategic foresight. 

Washington, DC: Social Technologies. 242 p.

Huber, B.J. 1978. Images of the future. In: Fowles, 

J., ed. Handbook of futures research. Westport, CT: 

Greenwood Press: 179-224.

Inayatullah, S. 1996. What futurists think. Futures. 

28(6/7): 509-692.

Jungk, R.; Müllert, N. 1987. Future workshops: how to 

create desirable futures. London, UK: Institute for 

Social Inventions. 126 p.

Kahn, H. 1962. Th inking about the unthinkable. New 

York, NY: Horizon Press. 254 p.

Kahn, H. 1982. Th e coming boom: economic, political 

and social. New York, NY: Simon and Schuster. 

237 p.

Kahn, H.; Weiner, A.J. 1967. Th e year 2000: a 

framework for speculation on the next thirty-three 

years. New York, NY: MacMillan. 431 p.

Kubik, G.H. 2009. Projected futures in competency 

development and applications: a Delphi study 

of the future of the wildlife biology profession. 

Minneapolis, MN: University of Minnesota. Ph.D. 

dissertation. 519 p.

Linstone, H.A.; Turoff , M. 1975. Introduction. In: 

H.A. Linstone; Turoff , M., eds. Th e Delphi method: 

techniques and applications. Reading, MA: Addison 

Wesley Publishing: 3-12.

Lippitt, L.L. 1998. Preferred futuring: envision the 

future you want and unleash the energy to get 

there. San Francisco, CA: Berrett-Koehler. 230 p.

Lipset, S.M. 1983. On the limits of social science. In: 

Smith, R.B., ed. An introduction to social research: 

Volume I of handbook of social science methods. 

Cambridge, MA: Ballinger: 149-168.

Lomborg, B. 2001. Th e skeptical environmentalist: 

measuring the real state of the world. Cambridge, 

UK: Cambridge University Press. 515 p.

Lowenthal, D. 2001. Marsh’s Man and Nature in the 

21st century. Forest History Today. (Spring/Fall): 

57-63. Available at http://www.foresthistory.org/

publications/FHT/FHTSpringFall2001/lowenthal.

pdf. (Accessed 22 June 2012).
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 11

Meadows, D.H.; Meadows, D.L.; Randers, J.; Behrens, 

W.W., III. 1972. Limits to growth: a report for 

Th e Club of Rome’s Project on the Predicament of 

Mankind. New York, NY: Universe Books. 205 p.

Millennium Ecosystem Assessment. 2005. Ecosystems 

and human well-being: synthesis. Washington, DC: 

Island Press. 137 p.

Millennium Project. 2012. Th e Millennium Project.

On-going programs. Available at www.millenniumproject.org. (Accessed 26 June 2012).

Mumford, L. 1931. Th e brown decades: a study of 

the arts in America, 1865-1895. New York, NY: 

Harcourt, Brace and Co. 266 p.

Naisbitt, J. 1982. Megatrends: ten new directions 

transforming our lives. New York, NY: Warner 

Books. 290 p.

National Park Service Organic Act. 1916. Available at 

www.cr.nps.gov/local-law/FHPL_NPSOrganic1.pdf. 

(Accessed 26 June 2012).

Norgaard, R.B. 1989. Th e case for methodological 

pluralism. Ecological Economics. 1(1): 37-57.

Olson, R.; Rejeski, D., eds. 2005. Environmentalism 

and the technologies of tomorrow: shaping the next 

industrial revolution. Washington, DC: Island Press. 

195 p.

Petersen, J.L. 1997. Out of the blue: wild cards and 

other big future surprises—how to anticipate 

and respond to profound change. Arlington, VA: 

Arlington Institute. 189 p.

Pilkey, O.H.; Pilkey-Jarvis, L. 2007. Useless arithmetic: 

why environmental scientists can’t predict the 

future. New York, NY: Columbia University Press. 

230 p.

Raskin, P.D. 2005. Global scenarios: background 

review for the Millennium Ecosystem Assessment. 

Ecosystems. 8(2): 133-142.

Royal Dutch/Shell Group. 2005. Shell global scenarios 

to 2025. London, UK: Shell International Limited. 

220 p.

Sarewitz, D.; Pielke Jr., R.A.; Byerly Jr., R., eds. 2000. 

Prediction: science, decision making, and the 

future of nature. Washington, DC: Island Press. 405 

p.

Sears, P. 1935. Deserts on the march. 1988 

Conservation Classics edition. Washington, DC: 

Island Press. 256 p.

Sherden, W.A. 1998. Th e fortune sellers: the big 

business of buying and selling predictions. New 

York, NY: John Wiley. 308 p.

Simon, J. 1981. Th e ultimate resource. Princeton, NJ: 

Princeton University Press. 415 p.

Slaughter, R.A. 1995. Th e foresight principle: cultural 

recovery in the 21st century. Westport, CT: Praeger. 

232 p.

Solomon, S.; Qin, D.; Manning, M.; [et al.], eds. 2007. 

Summary for policymakers. In: IPCC, Climate 

change 2007: the physical science basis. Contribution 

of Working Group I to the Fourth Assessment 

Report of the Intergovernmental Panel on Climate 

Change. Cambridge, UK: Cambridge University 

Press. Available at http://www.ipcc.ch/pdf/assessmentreport/ar4/wg1/ar4-wg1-spm.pdf . (Accessed 28 July 

2010).

Strathern, O. 2007. A brief history of the future. 

London, UK: Robinson. 322 p.

Toffl er, A. 1970. Future shock. New York, NY: 

Random House. 505 p.

U.S. Department of Agriculture, Forest Service 2008. 

U.S. Forest Service—caring for the land and 

serving people. Washington, DC: U.S. Department 

of Agriculture, Forest Service. Available at http://

www.fs.fed.us/aboutus/mission.shtml. (Accessed 23 

March 2012).
12 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Wager, W.W. 1991. Th e next three futures: paradigms 

of things to come. New York, NY: Praeger. 165 p.

Wells, J.G. 1987 (1932). Wanted—professors of 

foresight! Futures Research Quarterly. 3(1): 89-91.

World Commission on Environment and Development. 

1987. Our common future. Oxford, UK: Oxford 

University Press. 347 p.

World Future Society. 2000. Th e futurist directory: a 

guide to individuals who write, speak, or consult 

about the future. Bethesda, MD: World Future 

Society. 436 p.

World Futures Studies Federation. 2012. World Futures 

Studies Federation. Available at http://wfsf.org. 

(Accessed 26 June 2012).
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 13

AN APPROACH TO THE FUTURE

Peter C. Bishop

knowing a set of possibilities is not as satisfying as really 

knowing what will happen. But when really knowing is 

impossible, is it not better to know something about the 

future (its possibilities) than to ignore it and know little 

or nothing?

CHANGE

Th e study of the future is the study of change. But 

everything does not change at the same time or at 

the same rate, so every future is some combination of 

constants and changes. Constants and changes form 

strata, where the top levels are changing faster compared 

to the constant or slower-changing lower levels. Th e 

ocean serves as an analogy: the waves are driven by the 

winds, but currents are driven by the moon and the 

rotation of the Earth.

Our personal and organizational futures are shaped 

by two sets of forces: change that happens to us (from 

the external world beyond our control, which we call 

“inbound” change) and change that we create ourselves 

(based on our decisions and actions, which we call 

“outbound” change). Th erefore, the future is partially 

constrained by the forces of the world (i.e., we cannot 

get the exact future we want), but we are not totally 

constrained because we still have some discretion. People 

and groups have diff erent proportions of constraint and 

discretion in diff erent situations, and those proportions 

themselves can change over time. But some measure of 

both inbound and outbound change shapes the future all 

the time.

Change also occurs at two rates: continuous, incremental 

change, versus discontinuous, disruptive change. 

Discontinuous change reaches further down into the 

strata, and results in more fundamental changes. It may 

change so much that the world becomes unrecognizable.

Continuous and discontinuous change alternate to 

form a pattern of punctuated equilibrium as in the 

theory of biological evolution (Gould and Ethredge 

1972). Punctuated equilibrium consists of eras, which 

Abstract. Th is paper describes the rudiments of an 

approach to the future that we should teach and practice 

in our personal and professional lives. It begins with a 

consideration of change. Th e future is about change. If 

there were no change, we would have no reason to pay 

attention to the future. Th e paper concludes with an 

approach to long-term forecasting that takes uncertainty 

seriously. Th e result is a set of plausible futures for which 

we must be ready; otherwise, we run the risk of being 

surprised—or worse.

INTRODUCTION

My colleague, Draper Kauff man, created a set of 

aphorisms about systems thinking (Kauff man 1980: 39), 

one of which is “High morality depends on accurate 

prophecy.” If we desire to do good and we defi ne a good 

action as one that has good outcomes, then we must be 

able to tell what the outcome of an action is before we 

can judge whether it is good or not. So forecasting is not 

just a nice description of the future; it is knowledge that 

is essential to knowing what to do.

It is disappointing, therefore, that so few people teach 

about the future when, in fact, we will live the rest of 

our lives there. Almost everything we do is intended to 

understand or to infl uence the future. But where is the 

future in our educational systems? We study the past, 

which we should, but why not study an equal amount 

about the future?

Th ere are two answers to that question – one professional 

and the other epistemological. Th e professional answer 

is that teachers do not teach what they do not know. 

Since they were never taught about the future, how can 

we expect them to teach their students about the future? 

Th e more important and deeper answer is that most 

people believe that the future is unknowable. You cannot 

teach things you cannot know. But that is a fallacy. Th e 

future is knowable in exactly the same way that next 

week’s weather is knowable or next week’s stock market 

or next week’s ball scores. We can know them as a set 

of possibilities, as plausible alternative futures, any one 

of which has a signifi cant chance of occurring. Granted, 
14 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

are relatively long periods of stability and continuous 

change separated by shorter periods of instability and 

disruptive change. Th e change from one era to another is 

characterized by an S-curve with three periods: a run-up 

period in which change is slow and incremental, a period 

of explosive growth in which change is unexpected and 

chaotic, and a maturation period in which change slows 

and the characteristics of the new era emerge.

Every system matures over time—from individuals to 

the planet as a whole. In the process, systems get good 

at what they do—actions become more routine and 

more effi cient; fewer mistakes are made. And the system 

will remain in that state as long as its environment lets 

it. Th e environment is usually changing, however, and 

sooner or later it puts new demands on the system that 

it is unable to meet or even recognize. A mature system 

reaches the law of diminishing returns because it is 

approaching its inherent capacity for performance. It 

cannot get much better short of radically changing how 

it does things. According to the old sayings, “If you keep 

doin’ what you been doin’, you’ll keep gettin’ what you 

been gettin’,” or “Th e defi nition of insanity is doing the 

same thing over and over again and expecting diff erent 

results.” Th e law of diminishing returns means that 

simply adding more inputs (people, money, time, eff ort) 

will not improve performance much more. To create real 

change, one has to dismantle the current system (era), 

partially at least, and build a new one.

Understandably, most people do not want to usher in 

a new era because they are familiar with and good at 

what the old era requires. What is more, the transition 

between eras is always diffi cult. Would that it were 

not so, but transformational change always involves 

taking some steps backwards, in terms of reduced 

performance, heightened risk, more mistakes, and 

extra cost compared to remaining in the existing era. 

We pay that price and take those risks, however, in 

order to achieve breakthrough results. Th e costs and 

diffi culties are actually investments that pay off when a 

successful transformation creates an increased capacity 

for performance of which the old system (era) was simply 

incapable.

Human systems also change at four levels simultaneously: 

individuals, groups or organizations, the group’s 

immediate environment, and the global environment. 

Physicians and psychologists manage change at the 

individual level; managers, at the group level; and 

traditional forecasters and planners, at the level of the 

immediate environment. Once in a while, however, it is 

necessary to take a look at the global environment, the 

macro world out there, because many changes in the 

immediate environment come from there. Th ose changes 

in turn aff ect the organization and the individuals in that 

environment.

Th e global environment consists of domains—large 

domains of action and change. Diff erent people use 

diff erent categories to characterize these domains, 

but they are all based on a simple fi ve-segment model 

called STEEP, the acronym of the segments: social, 

technological, economic, environmental, and political 

(Morrison 1992). Each of these domains is changing all 

the time and aff ecting the immediate environment of 

groups and individuals as it does so. And each domain 

aff ects every other domain. No matter what causal chain 

is considered—social structure aff ects the technologies 

that get invented and produced (technology), which 

aff ects how much money people make and the standard 

of living they enjoy (economy), which in turn impacts 

the biophysical world (environment), some of which is 

regulated by government (political). Any other sequences 

would also work.

Th e fi nal attribute of change is the time horizon, how 

long it takes for some changes to have an eff ect. Most of 

what we do deals with the near-term, measured in hours 

or days. We also deal with the medium-term, measured 

in weeks or months. Rarely do we consider the longterm, sometimes called the strategic horizon, measured in 

years or even decades. And that oversight is unfortunate 

because some changes will have eff ects for decades or 

perhaps even centuries. Most of our time cannot be spent 

on the strategic horizon. Our enterprises would collapse 

and we would fail in the near- and medium-term. But 

spending no time on strategic matters is just as risky. If 

we do not invest our time (and our money) for some 

long-term return, the long-term future will be just what 

it is today or more likely worse.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 15

So the four main attributes of change are:

• Source—Inbound and Outbound

• Rate—Continuous and Discontinuous

• Level—Individual, Group, Immediate 

environment, Global environment

• Time—Near-term, Medium-term, and Longterm (Strategic)

Would that we had learned even this little bit in school 

so we could understand and manage change with more 

intelligence and forethought.

FORECASTING

Given these attributes of change, how can we know 

anything about changes and the eff ects that are yet 

to come? Th e answer is simple: exactly the way we 

know about anything that we cannot directly observe. 

We make inferences (call them judgments, estimates, 

interpretations, or conclusions) based on two types of 

information—evidence and assumptions (Toulmin 

1958). We all know about evidence. Th ose are the facts 

that support the inference. Assumptions, however, are 

the shadowy partners of the evidence. We have been 

taught to “state your assumptions,” but we do it poorly, 

casually, even haphazardly, more to just fi ll in that box 

and move on.

But assumptions are the key to the whole ballgame, 

even though they have gotten a bad rap in our scientifi c, 

fact-oriented culture. Everyone makes assumptions all 

the time. Th e light will come on when I fl ick the switch; 

the car will start when I turn the key. Professionals also 

make assumptions in science (the instrument is properly 

calibrated), in law enforcement (the fi ngerprint was 

left yesterday, not last year), in fi nance (gold will be a 

good hedge against infl ation). Most importantly for our 

argument here, historians also make assumptions. Th e 

document or the photograph was not altered; the date on 

the building is accurate; people believed what they wrote 

in their diaries. Th ose are all excellent assumptions, by 

the way, and they are hard to challenge.

Forecasters use evidence and assumptions in exactly the 

same way. Evidence can be time series data, people’s 

hopes and fears, an organization’s statement about 

executing a new strategy. Th e diff erence, however, 

is that assumptions about the future are much easier 

to challenge. A trend that has gone on for 20 years 

might not go on for another 20, people may not get 

what they hope for, or organizations may not execute 

their strategy successfully. Th ese are quite reasonable 

alternative assumptions, to be sure. Does that make the 

original assumption wrong? No, it’s just not as solid as 

the historian’s. Does it make the conclusion wrong? No, 

it just introduces a fair amount of uncertainty into the 

conclusion. Does it mean that we know nothing about 

the future when we make such assumptions? Finally and 

defi nitely, no! We know the expected future if we accept 

the original assumptions, and we know one or more 

alternative futures if we consider one or more of the 

alternative assumptions.

But do we not have to choose which assumptions we will 

use in making our forecast? Absolutely not! And that is 

the fallacy of traditional forecasting. Making assumptions 

resolves uncertainty. It literally makes it go away. As 

a result, I can state my conclusion with much more 

certainty than I should because, of course, I have stated 

my assumptions, haven’t I? But stating assumptions 

does not resolve the uncertainties in the world—only 

in our heads and in our forecasts and in our plans. Th e 

big problem with traditional forecasting is not that 

people do not state their assumptions. Good forecasters 

do. It is that they do not challenge those assumptions 

with alternatives. Challenging an assumption does not 

mean that the original assumption is wrong or even less 

probable than an alternative assumption. We are not 

trying to disprove anything. We are merely raising the 

possibility that the original assumption might be wrong 

because there is an alternative assumption that might be 

true instead. Notice the emphasis on “might.” We are 

not saying it is; we are just saying that it might be. In 

that statement, then, is the power of knowing the future 

as it really exists.

Th e presence of plausible alternative assumptions 

measures the amount of uncertainty in an argument. If 

there are none, the forecast is strong; if there are some 

or many, then the forecast is accordingly weaker. Th is 

distinction appears in courtrooms, in the United States 
16 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

at least, every day. Lawyers call it the diff erence between 

doubt and reasonable doubt (Diamond 1990). Anyone 

can doubt any conclusion. No conclusion about the 

world is true beyond doubt. Descartes taught us that. 

But reasonable doubt requires a reason. We must have 

some basis for doubting—not just the possibility that 

the conclusion is false, but some reason that it might 

be. In American jurisprudence, a jury that has reasons 

for its doubt about the guilt of the accused, not just 

the possibility that the defendant is innocent, must 

return a verdict of “not guilty.” Notice that the verdict 

is not “innocent.” Jurors do not know with certainty 

that the defendant did not commit the crime. Th ey 

just know that the case against the defendant is weaker 

than it should be. Usually, that weakness comes from 

assumptions that the prosecution had to make that have 

reasonable and plausible alternatives.

Futurists take uncertainty seriously, perhaps because 

statements about the long-term future are less certain 

than statements about the near-term future. For the 

same reason, other forecasters often make no statements 

about the long-term future at all. Th ey know that they 

cannot discount the presence of signifi cant amounts of 

uncertainty. And that is why most people do not think 

about the long-term future either—because they cannot 

be sure.

Futurists take a diff erent tack. Realizing that we ignore 

the long-term future at our peril, they fi nd a way to talk 

about it in a rigorous yet meaningful way. Identifying 

plausible alternative assumptions suggests plausible 

alternative futures. It is actually that simple. Th e result 

is a future that is not a single state the way most people 

talk about it, but rather a set of alternative futures 

(“scenarios”).

Th at is the way we should talk about the long-term 

future in all professional work—what might occur, 

not just what we think will occur. And that is what we 

should be teaching our students in general education, 

from high school on, and in all our professional schools. 

If the mission of a profession is to do good for some 

group of people in the future, then rigorous forecasting 

of that future should be an essential skill of every 

professional.

CONCLUSION

A useful scheme for forecasting based on these premises 

(though one that is much simpler than what is actually 

used) identifi es three types of drivers of the future.

Trend—continuous, inbound change of 

some variable over time, often described by a 

mathematical function. Examples include the 

aging of society, economic growth, and increasing 

planetary temperature. Constants, trends, and 

plans lead to the expected or baseline future. 

Th e expected future is more probable than any 

of the other futures in the set, provided that the 

individual or group accepts the assumptions it 

requires, i.e., assuming nothing really surprising 

happens.

Event—a sudden, inbound change in some 

condition, usually closing one era and opening 

a new one. Events are the surprises that the 

assumptions of the expected future assume will 

not occur. But they might. And if they do, they 

can create a future signifi cantly diff erent from 

what was expected. Examples would be the 

collapse of the Soviet Union, the introduction of 

Hyper Text Markup Language and creation of 

the World Wide Web, and the terrorist attacks 

on 9/11.

Choice—outbound decisions and actions taken 

by ourselves and others for a particular purpose. 

Choice comprises the decisions and actions 

taken to infl uence the future. Examples would 

be President Franklin D. Roosevelt’s decision to 

create Social Security and set 65 as the retirement 

age, IBM’s decision to use Bill Gates’ MS-DOS 

operating system for the personal computer, and 

the decision to ban chlorofl uorocarbons in an 

eff ort to preserve the ozone layer.

Each of the three drivers creates a diff erent type of future 

with its own characteristics and sets of futures research 

tools to deal with them:
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 17

Trends lead to an expected or baseline future, the 

future that would occur if all or most plausible 

assumptions turn out to be true.

Events lead to plausible futures, alternatives to 

the expected future. Scenarios based on plausible 

alternative assumptions are a common tool to 

explore plausible futures.

Choices lead to the preferred future, the result of 

visioning, planning, and action to move in the 

direction of the preferred future.

Th e three drivers combine to create the cone of 

plausibility (Taylor 1990), an image of the future 

consisting of a cone expanding through time. Th e 

baseline future is the center-line of the cone, the 

plausible futures are all the other regions of the cone, and 

the preferred future is one area of the cone selected as the 

vision or goal for an individual or a group. Th e purpose 

of traditional predictive forecasting is to establish the 

center of the cone, the purpose of scenario forecasting 

is to explore the other major regions of the cone (i.e., 

other plausible futures), and the purpose of visioning and 

goal-setting is to select a region to use as the guide for 

decision and action.

People can move toward their preferred future in two 

ways: outside-in, i.e., scanning and understanding their 

future and then deciding how to proceed through it, 

or inside-out, i.e., establishing a vision or a goal and 

taking the best path to it. Each approach uses the same 

sets of tools, but in diff erent orders. Th e outside-in 

approach begins with research and forecasting, then 

goes to visioning and goal-setting, and fi nally ends with 

planning and action. Th e inside-out approach begins 

with visioning and goal-setting, then assesses the future 

environment through research and scanning, and fi nally 

ends with planning and action.

So can we know the future? No; as a singular condition, 

the future cannot be known. But can we know the 

futures? Absolutely, or we can know at least most of 

them. And that is how we should approach the future.

LITERATURE CITED

Diamond, H.A. 1990. Reasonable doubt: to defi ne, or 

not to defi ne. Columbia Law Review. 90(6): 1716-

1736.

Gould, S.J.; Eldredge, N. 1977. Punctuated equilibria: 

the tempo and mode of evolution reconsidered. 

Paleobiology. 3(2): 115-151.

Kauff man, D.L. 1980. Systems One: an introduction 

to systems thinking. Second edition. St. Paul, MN: 

Future Systems. 44 p.

Morrison, J.L. 1992. Environmental scanning. In: 

Whitely, M.A.; Porter, J.D.; Fenske, R.H., eds. A 

Primer for New Institutional Researchers. Tallahassee, 

FL: Th e Association for Institutional Research: 86-99.

Taylor, C.W. 1990. Creating strategic visions. Carlisle 

Barracks, PA: Strategic Studies Institute, U.S. Army 

War College. 21 p.

Toulmin, S.E. 1958. Th e uses of argu ment. Cambridge, 

UK: Cambridge University Press. 251 p.
18 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

A FRAMEWORK FOR DEVELOPING FORESIGHT IN 

NATURAL RESOURCE MANAGEMENT

Kay E. Strong

and to envision what is desired. Th ree principles 

diff erentiate futures research from traditional forecasting 

methodologies. Taking the long view means looking 

a decade or more into the future, thinking from the 

“outside-in” by placing emphasis on the uncontrollable 

external environment, and actively seeking a diversity 

of perspectives. Opening doors to new insights is a key 

objective of futures research.

Framework forecasting is a methodology taught at the 

University of Houston (Houston, TX) for conducting 

futures research. Th e framework itself is an organizing 

technique which directs the gathering and sorting of 

information on the topic of interest. Once completed, 

the information framework serves as the foundation 

for generating foresight about the long-term future. 

Th is paper provides a brief overview of the University 

of Houston’s fundamental framework for anticipating 

the future. Th e framework diff erentiates among three 

futures: the probable, plausible alternatives, and the 

preferred. Finally, the process and purpose for scenario 

development are highlighted.

FRAMEWORK OVERVIEW

Gaining access to knowledge about a future that is 

already here but not evenly distributed requires spending 

time trying to understand and give context to the 

changes occurring in today’s world. Th e intelligence 

we gather is sorted into one of the following sections 

of the forecasting framework: (1) time horizon and 

domain defi nition, (2) current assessment, (3) drivers of 

future change, (4) uncertainties, (5) summary, and (6) 

information sources.

Time Horizon and Domain Defi nition

Good futures research is most eff ective when used to 

make better decisions in the present about the future we 

are trying to pursue. It can help ensure that the strategies 

and goals for 2020, 2025, or 2030 are informed by 

insights into the world we are likely to inhabit. Th e 

time horizon establishes the depth of the forecast, that 

Abstract. Th is paper describes a fundamental framework 

for anticipating and infl uencing the future that has been 

used to prepare professional futurists at the University 

of Houston for more than 35 years. Th e overview of the 

framework addresses how futures researchers organize 

information about changes in the world (e.g., by defi ning 

the domain, or scope, of the forecasting topic and 

identifying drivers of future change). Specifi c techniques 

to develop foresight, including environmental scanning 

and trend analysis, are discussed. Th e paper summarizes 

the three kinds of futures typically explored: the probable 

future, plausible alternatives, and preferable futures, 

whether centered on individuals, organizations, or 

society at large. Plausible futures are among many aspects 

of futures forecasting where scenarios can be used. 

Defi nitions and descriptions of scenarios are provided. 

Th e process of developing scenarios is illustrated, and 

their purpose in the forecasting framework is presented.

INTRODUCTION

Writer William Gibson reportedly quipped, “Th e 

future is already here—it’s just not evenly distributed.”1

Assuming Gibson is correct, how does one gain access 

to the knowledge about the future that is already here? 

Some disciplines rely on quantitative modeling to project 

the current and past state of the world environment 

forward in time. Because these models are driven by 

known data, their predictions about the future meet 

the standards of reliability and internal consistency, 

hallmarks of sound scientifi c research. Unfortunately, 

most of these predictions fall short of realization beyond 

a window of 2 or 3 years due to unanticipated factors. 

To better anticipate the future and manage its inevitable 

uncertainty, some have turned to the forecasting 

methodologies employed by futures research. Th e 

U.S. Environmental Protection Agency (EPA) defi nes 

futures research as “a platform to engage in strategic 

conversations to better understand uncertainty and 

shape a sustainable future” (U.S. EPA 2005: 1). Futures 

research relies more heavily on qualitative modeling 

to forecast what is probable, to anticipate possibilities, 

1

William Gibson, writer, National Public Radio, August 31, 

1993.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 19

is, how far into the future the forecast will illuminate. 

Th e domain defi nition defi nes the scope of the forecast 

topic: what will be included in the forecast, and what 

will not be included. To be clear on the purpose from 

the outset, it is important to identify the focal issue(s) 

and the key question(s) to be addressed given the selected 

time horizon. Th e more precise the defi nition, the more 

focused the information search. For example, what is the 

future of “symviability” (ecological-cultural symbioses 

and intercultural symbioses) in the United States (Boyd 

and Zeman 2010)? Speculative statements about what 

might or could happen in the future for the topic of 

interest should be avoided.

Current Assessment

Th e current assessment is characterized as a snapshot 

highlighting essential facts, quantities, and structures 

about the domain, listing key players (stakeholders) 

who will be aff ected and have an interest in the possible 

outcomes, identifying their current interests and 

announced goals and plans for the future, and identifying 

the historical events that brought about the domain’s 

current state. Th ese events most likely occurred abruptly, 

disturbing life as we had known it. Th e emergence of the 

World Wide Web, the fall of the Berlin Wall, and the 

recent global recession are examples of game-changing, 

discontinuous events.

Drivers of Future Change

Identifying “what is driving future change” (events, 

trends, issues, ideas, images, and actions) is central 

to understanding where the future of the domain is 

heading. Environmental scanning is a systematic and 

ongoing process for detecting early signs of “what is 

happening and what is likely to happen” in the external 

environment of the domain by reviewing and analyzing 

current literature, Web sites, and other sources to 

identify and monitor change. Long-time futurists 

Gordon and Glenn (1994: 1) remind us that “[n]o 

system will be able to eliminate all uncertainty; the 

objective of a scanning system is simply to fi nd early 

indications of possibly important future developments 

to gain as much lead time as possible.” Th e intelligence 

gathered by scanning can be used to generate new 

perspectives regarding future opportunities and risks as 

well as to challenge established assumptions and current 

wisdom about the domain.

An eff ective environmental scanning process has the 

potential to generate an overwhelming amount of 

information. Th erefore, classifi cation and analysis of 

this information are essential. Common mnemonic 

classifi cation methods include STEEP (society, 

technology, economics, environment, politics), 

DEGEST (demography, economics, government, 

environment, society, technology), and EPISTLE 

(economic, political, informational, social, technological, 

legal, environmental). A well-rounded scanning process 

will endeavor to explore across all relevant macro-level 

categories as they pertain to the domain of interest, 

including:

• Cultural factors such as behavior, values, and 

institutions that enable a society or group to 

develop and maintain identity; language; ethics; 

religion; arts; aesthetics; and recreation;

• Demographic dynamics such as population 

size, rates of change, gender distribution, age 

structure, ethnicity, family composition, and 

migration;

• Economic assumptions (global-regional-local) 

such as growth rates, production, fi nance, 

distribution of resources (e.g., food, water, and 

energy) and products between regions and across 

sectors of society, and consumer behavior;

• Ecological factors as a source of inputs (i.e., air, 

water, land, energy, resources) and outputs (i.e., 

waste, pollution, climate change), ecosystems, 

and land-use planning;

• Institutional assumptions such as actions, 

processes, traditions, and institutions through 

which authority is exercised; confl ict and 

governance; role of non-governmental 

organizations; and public policy;

• Science and technology assumptions such 

as rate of development; accessibility; role in 

transforming structure of production; nature 

of work; use of leisure time; advances in cyber-, 

nano-, bio-, and information/communication 

technologies; and transportation;
20 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

• Social factors such as human development (i.e., 

such basic needs as health, education, security, 

identity, and freedom), lifestyles, and beliefs.

Following discovery and classifi cation, scanning hits 

(information that indicates a possible or plausible change 

in the future) are graded or ranked according to their 

perceived importance and relevance. Th e highest ranking 

hits are coded into the framework; others are dismissed. 

Table 1 shows the ranking scheme devised by the EPA to 

grade a scanning hit across seven criteria of importance to 

this agency (U.S. EPA 2005).

Over time, drivers of future change may evolve or multiple 

drivers interact. When they do, trends take shape. A trend 

is a statement about the direction of change (i.e., more, 

less) in those forces shaping the future, usually gradual, 

long-term, or cumulative. A trend does not have to 

be dynamic, however; it can be stable and continuous 

through time (i.e., a constant) or it may oscillate in 

recognizable patterns (i.e., a cycle). Demographic and 

economic trends are particularly good candidates for 

extrapolation using basic mathematical projection 

techniques. EPA’s futures handbook (U.S. EPA 2005: 

12) off ers the following advice for analyzing trends: 

• Identify and state the trend. Give the trend a 

name and a verb. State the direction of change. 

For example, “Th e U.S. population grew by at 

least 10 percent during the 1990s.”

• Document for credibility. Researchers must 

validate trends just as they must validate data in 

their scientifi c research, using numbers, graphs, 

and verifi able documentation.

• Explore potential countertrends. Identify 

countertrends that may reduce, reverse, or alter 

the course of the original trend. For example, 

if one trend states that the U.S. population is 

aging steadily, whereas another trend states that 

hundreds of thousands of young immigrants are 

moving to the United States each year, the fi rst 

trend is weakened by the second.

• Generate implications. Identify the implications 

of the trend for the future of the environment. 

Will this trend aff ect the research being done 

now, or the research planned for later? To 

avoid bias, explore implications and actions in 

a group setting. Consider implications that are 

(a) obvious, (b) possible, and (c) speculative. 

Explore how diff erent parts of an organization 

might be aff ected and how they could better 

prepare for potential implications.

• Determine options. Identify the research 

needs or how to develop more knowledge 

in a particular area. Once the researcher has 

adequate knowledge, identify what individuals 

or organizations can do now to avoid a bigger 

problem later. Describe the appropriate actions, 

the obstacles to achieving these actions, and the 

risks associated with inaction.

Uncertainties

Uncertainties arise from non-trend drivers of future 

change such as potential events and actions, emerging 

issues, and new ideas and images. Uncertainties have 

the potential to hijack the expected future and are, 

therefore, the core around which alternative futures 

Ranking Criteria for Scans

Minimum Allowable

Ranking Value

Maximum Allowable

Ranking Value

Novelty 1 = old hat 5 = never been seen before

Scope 1 = affects almost nobody 5 = affects everybody

Severity 1 = slight effect 5 = human fatality, ecological disaster

Visibility 1 = of little interest 5 = of great interest

Timing 1 = 20+ years into the future 5 = imminent

Probability 1 = little chance of happening 5 = already an issue or certain to happen

Organizational Relevance 1 = no authority to act 5 = full authority to act

Table 1.—U.S. Environmental Protection Agency’s system for ranking the importance of environmental scanning hits
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 21

scenarios are woven. For example, the World Economic 

Forum’s Global Risks Report 2011 identifi ed six global 

uncertainties as high in both likelihood and potential 

impact: climate change, extreme energy price volatility, 

economic disparity, fi scal crises, geopolitical confl ict, and 

global governance failure. Th ese uncertainties are likely 

to be connected to and impact most domains.

Information Sources

Th is section of the framework is a record of resources 

important to the researcher’s domain, such as written 

and electronic publications, Internet sites, domainspecifi c organizations, and experts in that domain. To 

keep the forecasting framework up-to-date, the analyst 

will periodically return to these resources.

WHAT FUTURE?

In futures research, a wide range of methods may be 

used to generate the probable future. Th is baseline 

forecast is primarily data-driven, describing the diff erence 

between the present and the expected or most likely 

future for the domain of interest. Th e baseline forecast 

is built upon a coherent and internally consistent set 

of assumptions about key driving forces and their 

relationships. It extrapolates current conditions, known 

trends, stakeholders’ announced plans and goals, and 

experts’ projections in the fi eld forward to the selected 

time horizon. As an extension of the present, the baseline 

assumes no disruptions. Nevertheless, plausible alternative 

futures which are data-driven with a touch of imagination, 

embrace the reality of disruptions and uncertainties. 

Alternative futures scenarios are generated with at least one 

plausible uncertainty at their core. Preferred futures, the 

third kind of futures, are value-driven and used in action 

planning by individuals or organizations to bring about 

a desired future. Visioning and strategic planning are the 

tools used to infl uence the course of the future.

Even with the most rigorous approach, the forecast may 

miss the target. Why? Erica Orange, vice president of the 

futures consulting group Weiner, Edrich, Brown, says, 

“In order to learn new things and become truly objective 

about the future, you fi rst have to begin forgetting—by 

discarding no longer useful information. Change gives 

information, knowledge, expertise a short shelf life” 

(quoted in Weeks 2010). Forecasts are improved by 

challenging underlying assumptions and by continuously 

updating the information framework through 

environment scanning.

SCENARIO DEVELOPMENT

What are scenarios? Th e United Nations Environment 

Programme (2002: 320) defi nition states, “Scenarios 

are descriptions of journeys to possible futures. Th ey 

refl ect diff erent assumptions about how current trends 

will unfold, how critical uncertainties will play out 

and what new factors will come into play in alternative 

environments.” According to Zurek and Henrichs 

(2007), scenarios are not facts, predictions, forecasts, 

or speculation, but a means to create projections and to 

explore environments characterized by uncertainty and 

complexity. In “Environmental Futures,” Alcamo (2008) 

lists six types of environmental scenarios, each with a 

distinct purpose:

• Exploratory scenarios start in the present, have a 

set of assumptions on policies, and identify key 

driving forces;

• Anticipatory scenarios start in the future with 

a prescribed vision (optimistic, pessimistic, or 

neutral) and work backward in time to visualize 

how that future could emerge;

• Reference scenarios describe the (default) future 

state in the absence of additional, new, and 

focused environmental policies;

• Policy scenarios describe a future state in 

the presence of additional, new, and focused 

environmental policies;

• Qualitative scenarios describe possible futures in 

primarily non-numeric formats; and

• Quantitative scenarios describe possible futures 

in primarily numeric formats (models).

Another distinction is between inquiry-driven and 

strategy-driven scenarios. In essence, inquiry-driven 

scenarios estimate and assess alternative future states of 

the environment, while strategy-driven scenarios focus 

on strategy development, evaluation, and planning to 

improve environmental quality and achieve a triple 

bottom line: ecological-social-economic sustainability.
22 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Several international organizations have been active in 

developing global environmental futures scenarios. Th e 

Millennium Ecosystem Assessment, an interdisciplinary 

framework involving more than 1,360 experts 

worldwide, analyzed the conditions, trends, and services 

provided by the world’s ecosystems as well as envisioning 

possible solutions to restore, conserve, or enhance the 

sustainable use of the ecosystems (Millennium Ecosystem 

Assessment 2005). Th e Intergovernmental Panel on 

Climate Change has used scenarios to illustrate how 

alternative policy pathways may or may not achieve 

an environmental target (Carter et al. 2007). Th e 

World Water Council, sponsor of the World Water 

Vision (Cosgrove and Rijsberman 2000), advocates 

development of a common strategic vision on water 

resources and management among all stakeholders with 

the support of strategic initiatives and activities.

Th e development of a scenario is a synthesis activity 

focused on conceiving, formulating, and elaborating 

a set of scenarios. Th e futures forecasting framework 

discussed earlier is an excellent approach to gathering and 

organizing information that can be used for generating 

scenarios. One popular approach to building scenarios 

was developed by Peter Schwartz (1991) and is used by 

the strategy consulting fi rm Global Business Network 

(GBN). Th e GBN scenario planning process begins by 

brainstorming a list of driving forces of future change 

(e.g., trends, uncertainties, surprises) which are both 

highly unpredictable and highly relevant to the focal 

issues and the key questions identifi ed at the onset of 

the foresight project. Pre-determined forces, those easily 

extrapolated by standard forecasting techniques, are 

separated from the fundamental uncertainties. Linkages 

between the driving forces are identifi ed. Th e remaining 

uncertainties are prioritized to facilitate identifi cation of 

the two most critical. At least two extreme but plausible 

outcomes for each of the critical uncertainties are 

described. Finally, the scenario logic that integrates the 

two (or more) most important drivers into one future is 

constructed.

A GBN 2-by-2 scenario matrix subsequently can be 

created. One driver is mapped onto the horizontal 

axis with the extreme outcomes located at either end. 

Likewise, the second driver is mapped along the vertical 

axis. Each quadrant is a scenario logic representing 

a provocative yet plausible outcome of the two 

uncertainties. Th e scenario matrix off ers four distinct 

future trajectories for the domain over the time horizon, 

which are given titles that capture the essence of the 

scenario logics. Figure 1 illustrates a typical 2-by-2 

scenario matrix.

Figure 1.—2-by-2 scenario matrix.

Global 

Integration 

Regional 

Integration 

Reactive 

Decisionmaking 

Good 

Neighbors 

A Step 

Behind 

Slippery 

Slope 

One 

Earth 

Proactive 

Decisionmaking 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 23

Believable plot lines for the scenario logics are written 

as if the observer is living at the selected time horizon, 

say 2030. Th e information gathered into the framework 

should be fi ltered back into the scenario where most 

appropriate. In a paragraph or two, how and why that 

“world” came into being are described. Embellishing the 

scenario script with interesting characters, specifi c facts, 

dates, events that occurred, and confl ict or surprising 

developments deepens the reality. Scenarios should be 

written in a format that is convincing and suffi ciently 

absorbing to draw the reader in. To give the scenario a 

deeper sense of future reality, scenarios are sometimes cast 

into an artifact of the times dated at the time horizon, such 

as an editorial blog, a letter addressed to a special-interest 

group, a news podcast, or a day-in-the-life video.

Recall that good futures research is most eff ective when 

used to make better decisions in the present about the 

future we are trying to pursue (or avoid). Forecasts of 

long-term futures are generated based on the information 

gathered into the framework. Scenarios are a means to 

summarize the main drivers, external conditions, and 

key uncertainties at play and to describe a set of plausible 

futures for a domain of interest. Scenarios are platforms 

for rehearsal. If decisionmakers assess the implications of 

each scenario based on the original focal issue and key 

questions, then the robustness of goals and strategies can 

be tested against the range of future possibilities. As a 

fi nal step, decisionmakers need to develop a monitoring 

plan to identify specifi c leading (early warning) indicators 

that the future is, in fact, resolving itself toward one 

or another of the alternative futures. With suffi cient 

advance warning, users of forecasts are well-positioned to 

side-step the obstacles and seize the opportunities that lie 

in the future.

CONCLUDING COMMENT

A fundamental question for environmental planners, 

managers, and policy-makers is how they might benefi t 

from futures research. Futures research off ers a variety of 

techniques and tools for identifying and exploiting the 

uncertainties that underlie unpredictability in traditional 

forecasting. Since the objective is not to improve 

predictive power but rather to open doors to new 

insights, the methodologies long employed by futurists 

should be welcome additions to the toolkit of scientists 

concerned with environmental management and policy.

LITERATURE CITED

Alcamo, J., ed. 2008. Environmental futures: the 

practice of environmental scenario analysis.

Amsterdam, Th e Netherlands: Elsevier. 197 p.

Boyd, G.; Zeman, V. 2010. Towards a global-systems 

steering vision that is simple enough, but not too 

simple: symviability. Proceedings of the 54th Annual 

Meeting of the International Society for the System 

Sciences (ISSS). Available at http://journals.isss.org/

index.php/proceedings54th/issue/view/10. (Accessed 

6 July 2012).

Carter, T.R.; Jones, R.N.; Lu, X.; [et al.] 2007. New 

assessment methods and the characterisation of 

future conditions. In: Climate change 2007: impacts 

adaptation and vulnerability. Working Group II 

contribution to the Fourth Assessment Report of 

the Intergovernmental Panel on Climate Change. 

Cambridge, UK: Cambridge University Press: 133-171.

Cosgrove, W.J.; Rijsberman, F.R. 2000. World Water 

Vision: making water everybody’s business. World 

Water Council. London, UK: Earthscan. 108 p.

Gordon, T.J.; Glenn, J.C. 1994. Environmental 

scanning. Available at http://crrm.u-3mrs.fr/web/

IMG/pdf/environment_scan-2.pdf. (Accessed 6 July 

2012).

Millennium Ecosystem Assessment. 2005. Scenarios: 

fi ndings of the Scenarios Working Group.

Washington, DC: Island Press. 560 p.

Schwartz, P. 1991. Th e art of the long view: planning 

for the future in an uncertain world. New York: 

Doubleday. 272 p.

United Nations Environment Programme. 2002. 

GEO-3: Global environmental outlook. Available 

at http://www.unep.org/geo/geo3/english/515.htm. 

(Accessed 6 July 2012).
24 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

U.S. Environmental Protection Agency. 2005. Shaping 

our environmental future: foresight in the Offi ce of 

Research and Development. Washington, DC: U.S. 

Environmental Protection Agency.

Weeks, L. 2010. 2010 isn’t what many futurists of 

the past imagined. GPB News, Georgia Public 

Broadcasting, Mon., October 18, 2010. Available at 

http://www.gpb.org/news/2010/10/18/2010-isntwhat-many-futuristsof-the-pastimagined. (Accessed 6 

July 2012).

World Economic Forum. 2011. Global Risks 2011. 

Sixth edition. An initiative of the Risk Response 

Network. Available at http://riskreport.weforum.

org/#/1/8. (Accessed 6 July 2012).

Zurek, M.B.; Henrichs, T. 2007. Linking scenarios 

across scales in international environmental 

scenarios. Technological Forecasting and Social 

Change. 74: 1282-1295.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 25

GLOBAL MEGA FORCES: 

IMPLICATIONS FOR THE FUTURE OF NATURAL RESOURCES

George H. Kubik

complexity are anticipated to dominate the global scene 

in future decades (Enriquez 2001, Micklethwait and 

Wooldridge 1996), placing escalating pressures on how 

social-ecological systems will operate and what they will 

become. In the midst of these interacting forces the role 

of anticipatory, future-savvy leaders and decisionmakers 

will be crucial to outcomes for society and natural 

resources. An understanding of futures thinking and 

global forces enhances organizations’ and individuals’ 

ability to think strategically and proactively about the 

future. Such strategic thinking is especially important in 

natural resource management. In addition, this approach 

helps to prepare organizations and individuals to respond 

more eff ectively to future alternatives—both foreseen and 

unforeseen. Th us, decisionmakers, policy formulators, 

and practitioners can all be expected to benefi t from an 

increased understanding of global forces coupled with 

knowledge of futures studies.

In futures research, it is important to understand that the 

future is not predictable in detail. Th roughout history 

there have been many attempts to predict the future, 

from the prophecies of ancient Egyptian priests and 

the Greek Oracles at the Temple of Delphi, to those of 

American economist Ben Bernanke, current chairman 

of the Federal Reserve. However, attempts at prediction 

have proven to be largely unsuccessful in the long term 

as science increasingly recognizes the limits to prediction 

and modeling in complex systems (Batty and Torrens 

2001). According to Batty and Torrens, current scientifi c 

prediction is characteristically embedded in qualifi cation. 

At the same time, science is becoming less oriented to 

prediction and more directed toward the development of 

understanding as a framework for structuring debate.

While some scientists assert that the future is rendered 

more predictable with the generation of greater 

information, other scientists are beginning to challenge 

this traditional assumption (Cunningham et al. 2002, 

Gell-Mann 1994). For example, recent studies in 

complexity theory have argued that the generation of 

additional data does not ensure improved outcomes, 

Abstract. Th e purpose of this paper is to provide 

an overview of leading global mega forces and 

their importance to the future of natural resource 

decisionmaking, policy development, and operation. 

Global mega forces are defi ned as a combination of 

major trends, preferences, and probabilities that come 

together to produce the potential for future high-impact 

outcomes. Th ese forces are examined in terms of their 

possible, probable, and preferable future impacts on 

natural resources. Th e paper is presented in two stages. 

First, it identifi es seven commonly cited categories of 

existing, emerging, and projected global mega forces for 

direction and implications. Next, two technological mega 

forces with potential for high impact—networked sensoractuator technologies and electronic performanceware 

systems—are identifi ed and examined in detail.

INTRODUCTION

Th e intent of this paper is two-fold: First, to stimulate 

strategic thinking about the future of natural resources 

based on emerging mega forces, and second, to identify 

exemplars of the implications of these mega forces for 

the future of natural resources. Th ese objectives are 

accomplished by identifying a series of major global 

forces, the factors that drive them, and their implications 

for natural resource futures. Global mega forces are 

defi ned as a combination of major trends, preferences, 

and probabilities that come together to produce the 

potential for high-impact outcomes in the future. Th e 

forces are outlined in terms of the emerging challenges 

and opportunities they present for policy makers, 

decisionmakers, and practitioners who will determine the 

future of natural resources.

Th e approach involves a description of the major forces 

likely to shape future events. It is not a prediction or 

prescription of which specifi c futures will actually occur. 

Rather, a limited number of forces are presented that can 

be anticipated to produce disproportionate infl uences on 

the future.

Why is the study of global mega forces important to 

the future of natural resources? Accelerating change and 
26 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

greater predictability, or risk reduction when dealing 

with chaotic or complex adaptive systems (Briggs 

and Peat 1999, Holling 1978). In these frameworks, 

bifurcations, emergent processes, and discontinuous 

events confound predictive eff orts—despite information.

So what does this mean to the future of natural 

resources? With so many forces and variables at work, 

is it hopeless to try to anticipate the future? Proponents 

of futures research would typically respond to these 

questions by stating that, while we cannot predict the 

future, we can anticipate a range of possible, probable, 

and preferable future outcomes, and use that information 

to infl uence the future.

Let’s examine this rationale. Futures research is 

premised on the basic principle of unpredictability: 

that is, the future is inherently unpredictable in detail, 

many alternative futures are possible, and specifi c 

future outcomes cannot be known with certainty. 

However, while futures research is not focused on 

predicting the future, it does assume that a disciplined 

futures research approach aids in shaping preferred 

future outcomes. Future outcomes can be positively 

infl uenced by improving forecasting and futures-oriented 

decisionmaking in the present. Further, knowledge of 

global forces and pertinent variables contributes to the 

robustness of the futuring process and its outcomes. Th e 

incorporation of a futures approach and a knowledge of 

global forces provides four distinct advantages to policy 

makers, decisionmakers, and practitioners: it increases 

the robustness of our forecasting ability in the natural 

sciences, amplifi es our understanding of emerging 

phenomena in this area, better prepares us for working 

with uncertainty, and enhances our ability to create and 

communicate our visions of preferred futures.

Understanding the importance of global mega forces 

in terms of emerging natural resource futures requires 

an awareness of the changing nature of change. Th e 

accelerating generation of data, information, knowledge, 

and ideas is bringing about profound global changes 

in almost every area of life. Bits are replacing atoms, 

telecommunication is instantaneous, and digital 

technologies are everywhere. Information fl ows freely 

around the world 24 hours a day, every day—and the 

Internet forms a global communications network that 

is always on, off ering electronic services on demand. 

No society, enterprise, or individual is immune to 

the cascading changes that are being produced by this 

development. It is in this milieu that societies and natural 

resource managers everywhere are being challenged to 

develop robust frameworks that will successfully guide 

them into the future.

Why are some forces and their impacts more important 

than others—and often, more diffi cult to identify? 

Th e culprit here is the increased dimensionality 

of the changes. Change is occurring along three 

dimensions—speed, complexity, and magnitude of 

impacts. Historically, we have experienced rapid change 

primarily across one dimension, or sometimes two. But 

rarely has rapid change occurred across all three of these 

dimensions at the same time.

Making this process more diffi cult is the nature of 

the interactions taking place among global forces 

and pertinent variables. Scientists are increasingly 

discovering that the relationships among these forces are 

characteristically non-linear and complex in nature; that 

is, they do not operate in direct proportion to each other 

(Briggs and Peat 1999). Similar to Newton’s famous 

three-body problem in physics, the outcomes of these 

interacting forces are, in large part, not subject to easy 

projection or modeling using the conventional tools of 

science. Futures research aids us in: (1) understanding 

the non-linear relationships existing among global 

forces, (2) more eff ectively addressing global forces and 

uncertainties across all three dimensions of change, and 

(3) coping with increasing uncertainty in the future(s) of 

natural sciences.

SEVEN GLOBAL MEGA FORCES

Many global forces are at work shaping the future. Some 

of these forces have been long recognized and typically 

include political, demographic, economic, sociocultural, and technological dimensions. More recently, 

the list of categories of global forces has been expanded 

to include environmental, scientifi c, and information 

dimensions. Many other global mega forces are less 

widely recognized. Often, these forces are outside our 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 27

traditional scanning focus, believed to exceed the scope 

of our mission, or considered to be beyond our ability 

to address in a scientifi c manner. Other forces and 

variables may be considered to be outside our ability to 

eff ectively intervene. In contravention to this theme, I 

assert that it is important to recognize that we infl uence, 

and are infl uenced by, the full spectrum of global factors. 

Without an awareness of the major forces at work, 

deciphering the future can seem like embarking on a 

road trip without a roadmap or a destination.

While many global mega forces and trends are present, 

we focus on seven easily recognizable mega forces: 

demographics, globalization, economics, work, digital 

networks, information, and digital technologies. For 

the most part these forces are already well known, but 

that knowledge may not be evenly distributed and the 

implications for natural resources not examined. In 

the following subsections, each mega force is briefl y 

described and then possible implications for natural 

resources are outlined.

1. Demographics

Demographic mega forces typically encompass major 

changes in characteristics occurring among populations. 

Examples include age, gender, race, employment, and 

location. Demographic change is always a fundamental 

driver of long-term social change (Schwartz 2003). Two 

examples of mega forces in demographic change are 

presented here: population growth and urbanization.

A. Population growth.

Population growth is a commonly cited demographic 

mega force. Th e current world population is 

approximately 7 billion people and increasing. However, 

population growth rates are unevenly distributed among 

nations and peoples. For example, Beazley (2009) has 

projected that China, Russia, and Japan will exhibit 

relatively low changes in population size during the 

period 2009 to 2050. During that same interval, Beazley 

has projected that the population of India will increase 

dramatically from 1.135 billion to 1.592 billion, Nigeria 

from 137 million to 258 million, Bangladesh from 147 

million to 243 million, and Pakistan from 164 million 

to 305 million. In general, the population of Europe is 

expected to decline during that same period from 729 

million to 517 million, while less developed countries are 

expected to account for 70 percent of global population 

growth by 2030 (Beazley 2009, McKinsey and Company 

2010).

Continued world population growth will place growing 

pressures on the global land base and water resources. 

Diff erences in population growth rates among nations 

will result in accelerating confl icts over natural resources, 

and will be a major factor in infl uencing natural resource 

decisions and policies around the globe. Population 

growth and increasing affl uence will amplify the need 

to conserve natural resources in the face of escalating 

demands for their consumptive use, such as agriculture 

and resource extraction (Hall et al. 2000, Organ and 

Fritzell 2000).

B. Urbanization.

Th ere is a continuous and substantive transition in 

populations from rural to urban among most nations 

around the globe (Beazley 2009). For the fi rst time in 

history, more people are living in cities than in rural 

areas and their work and social preferences are changing. 

Rising urban populations are creating major changes 

in expectations regarding the sharing of global wealth, 

the right to meaningful work, and access to educational 

resources.

An increasing percentage of the world’s population 

will be located in urban areas and demand new forms 

of access to natural resources. Urbanization will result 

in accelerated trends toward consumptive practices 

and increases in waste disposal, pollution, and toxic 

discharges. Urban populations will tend to be more 

highly educated and expect greater participation in 

natural resource decisionmaking and policy formulation 

around the globe.

2. Globalization

Globalization refers to the ongoing process by which 

regional economies, societies, and cultures are becoming 

increasingly integrated through a globe-spanning 

network of communication and trade (Friedman 2007).
28 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Increased globalization will require adoption of a 

broader, more international view of natural resources 

by countries, enterprises, and individuals everywhere. 

Adoption of a global agenda for natural resources will 

be demanded as historical and locality-based natural 

resource agendas become increasingly irrelevant. 

Furthermore, an increasing percentage of the world’s 

population will demand direct involvement in natural 

resource decisions and planning.

3. Economics

Major shifts are occurring in the economic leadership 

of the global economy. Maddison (2007) documented 

the peaking of the United States’ share of world Gross 

Domestic Product (GDP) during the 1950s and 

contrasted it to Asia’s rising share of GDP. According 

to the International Monetary Fund, GDP is the most 

commonly used single measure of a country’s overall 

economic activity. It is especially notable that China and 

India have dominated world GDP during 14 of the last 

16 centuries, while North America and Western Europe 

have enjoyed less than 200 years at the top of the world 

GDP list. At the same time, historical and geographical 

divisions of individual economies are becoming less 

relevant in the context of the rising and interconnected 

global market. As Friedman (2007) has noted, the world 

is fl at—or at least becoming fl atter.

Funding priorities for natural resources will begin to 

shift in unforeseen directions as a result of globalized 

economic interests in the environment and changes in 

the relative GDP standings of nations. Economic actions 

taken in one part of the world will no longer be viewed 

as localized or separate from the rest of the world.

4. Work

New generations of workers are increasingly mobile and 

educated, and always plugged-in. Work environments 

are characterized by accelerating change, anytimeanywhere connectedness, rapidly redefi ned roles 

and competencies, an explosion in open source 

innovation, greater involvement and collaboration, and 

unprecedented increases in complexity and uncertainty. 

Emerging work challenges are demanding new forms 

of enterprises that are capable of greater and faster 

organizational agility, resiliency, and fl uidity, and better 

and faster decisionmaking (Hamel 2007, Rubinstein and 

Firstenberg 1999, Ulrich 2000).

As the nature of work quickly evolves and more 

workers are drawn into the global workforce, workers’ 

expectations and priorities for leisure and recreation 

are also changing. Greater affl uence for segments of 

the world’s population is being accompanied by shifts 

in lifestyle preferences and leisure activities. In “Th e 

Rise of the Creative Class”, Florida (2002) has argued 

that high-income individuals place an elevated value 

on active outdoor recreational activities exemplifi ed by 

mountain biking, kayaking, trail running, snowboarding, 

and rock face climbing. Increases in these activities, 

and similar leisure vectors, can be expected to produce 

future shifts in environmental and natural resource 

orientations. Growing rejection of resource-consumptive 

and polluting industries will further impact the future of 

natural resource management decisions and planning.

5. Digital Networks

An explosion is occurring in the development, 

availability, and widespread use of digital networks in all 

areas of human activities (Tapscott 1996, Tapscott and 

Williams 2010). Digital networks are stimulating major 

transformations in the nature of work, learning, society, 

and leisure. Th e global Internet is exerting unforeseen 

impacts on every aspect of living and working around the 

globe.

Th e business world commonly uses three types of digital 

networks: the Global Area Network, which we identify 

as the Internet; Wide Area Networks; and Local Area 

Networks. Other types of networks are quickly emerging. 

Rapidly evolving personal networks include Personal 

Area Networks and Body Area Networks (Dertouzos 

1997, Heinrich 2005). Th ese networks provide personal 

connectivity for individuals and are projected to use 

fabric for circuitry and body movement for power 

generation (Starner 1996). Other developing network 

confi gurations involve System Area Networks, Home 

Area Networks, and Car Area Networks.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 29

Vastly improved access to people, devices, and information 

is redefi ning work, leisure, learning, and social activities 

around the globe. Natural resource landscapes that were 

formerly remote from most of the world’s population will 

come under increased scrutiny, monitoring, and review by 

globally networked individuals with access to vast arrays 

of natural resource information and networked sensors. 

Social media such as Facebook, Twitter, and YouTube will 

enhance the ability to disseminate opinions, videos, and 

information about natural resource activities everywhere. 

Internet forums, weblogs, social blogs, microblogging, 

wikis, and podcasts will increasingly impact natural 

resource decisionmakers, policy makers, and practitioners 

everywhere as greater percentages of the world’s population 

become connected, networked, aware of natural resource 

issues, and demand to have their voices heard.

6. Information

In 1996 former President William J. Clinton stated, 

“When I took offi ce, only high energy physicists had ever 

heard of what is called the World Wide Web . . . Now 

even my cat has its own page” (Ingenito 2010: 9). Th e 

number of Internet users is growing exponentially. Th e 

total number of Internet users worldwide has increased 

from 16 million Internet users (0.4 percent of the world’s 

population) in 1995 to over 2.1 billion users (30.4 

percent of the world’s population) today (Internet World 

Stats 2011a). Asia currently accounts for 44.0 percent 

of the world’s Internet users, while Europe accounts for 

22.7 percent, and North American usage accounts for 

13.0 percent (Internet World Stats 2011b). According to 

Internet World Stats (2011b), the Internet penetration 

rate is currently 78.3 percent for North America, 58.3 

percent for Europe, and 23.8 percent for Asia.

Nearly every individual around the globe will have 

access to the Internet in the future. Th e Internet will be 

a ready source of information to increase awareness and 

understanding about natural resources and the decisions 

that aff ect them. Natural resource decisionmakers, policy 

planners, and practitioners will become increasingly 

accountable in ways and to degrees that are currently 

unforeseen. Th e result will be greater scrutiny of natural 

resource activities and increased demands for meaningful 

participation—from everywhere.

7. Digital Technologies

Digital technologies in the form of computers, 

telecommunications, sensors, and actuators are 

becoming ubiquitous and increasingly transparent in 

operation. As a result, an explosion of collected data, 

the generation of new information and knowledge, and 

unforeseen developments in scientifi c visualization, 

intelligent devices, and performance amplifi cation and 

augmentation systems are occurring. Digital technologies 

are becoming faster, cheaper, smaller, networked, and 

capable of operating at all scales. Th ey are increasingly 

blending into the backgrounds of built and natural 

environments. Emerging digital technologies are rapidly 

transforming every aspect of human life (Martin 1996, 

Tapscott 1996, Tapscott and Williams 2010).

Digital technologies increase our ability to monitor 

and learn about natural resources, communicate our 

opinions and priorities to others, and act on our 

decisions. One important outcome of this development 

is how we consider and interact with natural versus 

built environments. Th e growing presence of digital 

technologies can be expected to radically alter traditional 

defi nitions and distinctions between natural and built 

environments. It can be anticipated that future debates 

and exchanges concerning natural versus built or 

engineered environments will radically infl uence how 

we defi ne and experience natural resources in the future 

(Kahn 2011).

OTHER GLOBAL FORCES OF SPECIAL 

SIGNIFICANCE

Th ere are obviously many other signifi cant global 

forces at work that off er the potential to impact 

natural resources in the future. However, they are too 

numerous to list and individually address in this paper. 

A few illustrative global forces include emerging “new 

economics,” changing societal values, political power 

shifts, biotechnology, greening movements, transgenic 

organisms,1

 alternative energy sources, and technologies 

for sustainability. Instead of expanding on these forces, 

1

Transgenic organisms are genetically modifi ed or engineered 

organisms whose genetic material has been altered through the 

use of one or more technologies.
30 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

the remainder of this paper will address two specifi c 

mega forces that exhibit high potential to impact the 

future of societies and natural resources: networked 

sensor-actuator systems and Electronic Performance 

Enhancement Systems (EPES). Together, these mega 

forces are already beginning to demonstrate their ability 

to transform natural resources everywhere.

Networked sensor-actuator systems

Sensors are devices designed to perceive environmental 

states, monitor changes in environmental conditions, 

and communicate the resulting data to interrogators 

or other nodes (Culler et al. 2004, Heinrich 2005). 

Sensors are built or grown to detect wide ranges 

of variables including temperature, altitude, light, 

chemical composition, weight, pressure, proximity, 

and acceleration. Specifi c functions include pattern 

recognition, environmental analysis, and monitoring. 

Th e development of sensor webs is of special importance 

to natural resources. Sensor webs were fi rst described 

by NASA in 1997 in reference to networks of sensors 

that communicate wirelessly and self-organize in ways 

that permit individual sensor components to act and 

coordinate as a unit.

Actuators are the counterpart to sensors. Th ey are 

cybernetic devices designed to control or regulate some 

aspect of the environment by physically acting on the 

environment to bring about a change in a predetermined 

condition or status. Actuators are important because 

they permit matter to become an active agent rather 

than an inert substance (Glenn 1989). Actuators can 

be used for a variety of purposes over a wide range of 

environments. Applications include fl y-by-wire control 

of aircraft, regulation of automated machining tools 

on factory fl oors, remote release of chemicals to reduce 

insect populations, triggering of stomata to control 

transpiration rates in leaves, or the activation of fi re 

suppression systems in response to signifi cant increases in 

ambient temperature.

Networked sensors and actuators are already present 

in large numbers in our homes and businesses—and 

the natural environment. Th ey are primarily used 

for monitoring, tracking, and controlling functions. 

Networked sensor-actuator systems are present in 

factory assembly lines, aircraft and vehicles, home 

thermostats, medical dosage regulators, agricultural 

fertilizer applicators, weather monitors, tracking collars 

for endangered species, and indicators for diseased trees 

in forests.

Th e rapid expansion of research, development, and 

application of networked sensors and actuators has been 

well documented over the last several decades. Th ese 

eff orts have resulted in an explosion in the number of 

networked instrumentation and activation systems that 

are embedded in natural and built environments around 

the planet. Illustrating this point, Kelly (1998) observed 

that the number of computer chips embedded in objects 

is increasing at a much faster rate than the number of 

computer chips located in computers.

It is notable that networked sensors and actuators are 

being generated at ever-decreasing scales. For example, 

the Defense Advanced Research Projects Agency is 

designing networked sensor-actuator systems (also 

known as “smart dust” or “smart mote” technologies) 

to be produced in extremely large numbers at the 

nanometer level. Th is scale is representative of a new class 

of nanotechnology machines operating at the molecular 

and sub-molecular levels, where one nanometer equals 

one billionth of a meter (Kurzweil 2005). Drexler 

(1986), Drexler and Peterson (1991), and Regis (1995) 

have forecast that these micro and nano-scale artifacts 

will become cheap enough, and small enough, to drift 

in the air, be embedded in buildings and appliances, 

become part of organisms, be plowed into the soil, and 

become infused in the water.

Advancements in the development of smart dust 

technologies represent a signifi cant factor in the 

expanding fi eld of networked sensor-actuator technology 

(Heinrich 2005, Kahn et al. 2000). Self-organizing 

networked sensor-actuator systems operating at this 

level are frequently termed swarm technologies. Swarm 

technologies require that each distinct component 

sensor and/or actuator in the network be mobile, selfpowered, and able to dynamically re-confi gure its role 

and relationships to conform to changes in environment, 

group objectives, network relationships, and relative and 

absolute position (Kurzweil 2005).
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 31

Th e following paragraphs summarize some trends in the 

development of networked sensor-actuator systems.

Connecting people, objects, and environments. Th e 

emerging ability to connect people, objects, and 

environments requires ongoing developments in the 

density, scale, and intelligence of connectivity. A recent 

example is development of the 2011 Internet Protocol 

version 6 (IPv6) addressing standard. Th is standard was 

designed to replace the prior Internet Protocol version 

4 (IPv4) that was fi rst implemented in 1981. Adoption 

of the new IPv6 standard provides the ability to address 

many more devices in the present, and more importantly, 

in the future. How many devices could be connected? 

Davies (2012) has stated that the IPv6 Internet Protocol, 

also known as the Next Generation Internet Protocol 

or IPng, is capable of connecting approximately 3.402 x 

1038 addresses. Th is very large address space is capable of 

connecting 6.65 x 1023 devices for every square meter of 

the earth’s surface, or over a thousand devices for every 

atom on the surface of the earth (Davies 2012).

Building networked sensors and actuators at nano-levels.

Another requirement for developing future sensoractuator networks is the ability to design and build these 

devices at ever-decreasing scales—eventually approaching 

the nanometer level. Current developments in this area 

include devices being built at the scale of approximately 

1 to 100 nanometers (1-100 x 10-9 meters). Kaku (2011) 

and in a seminal work Drexler (1986) have asserted that 

projections of nanotechnology futures suggest these 

machines will be suffi ciently large in number and small 

in size as to eventually vanish from human awareness and 

perception.

Nanometer devices are initially expensive to design and 

prototype. However, the primary cost of these systems 

is incurred in the design and testing stages rather than 

production. Once designed and tested, sensor-actuator 

networks could be assembled (or grown) using highly 

automated reprogrammable assembly lines, or be 

designed for self-replication. Scientists such as Drexler 

(1986), Drexler and Peterson (1991), and von Neumann 

(Brown 2000) developed the concept of self-replicating 

automata as a means of future fabrication of devices 

such as networked sensors and actuators. Th eir approach 

suggests that future self-replicating devices of this nature 

would possess the capability of mass reproduction and 

be able to generate copies of themselves at geometrically 

increasing rates.

Everyone and everything becoming plugged-in. It is 

projected that sensor-actuator networks will become 

ubiquitous in future built and natural environments. 

Th is projection anticipates a world where individuals 

and environments are increasingly “plugged-in” to each 

other. In this future world everyone would have the 

capability to connect to everything else—in homes, 

businesses, and natural resources. Realization of this 

outcome will require the expanding development and 

application of smart networks operating at a variety 

of scales including Global Area Networks, Wide 

Area Networks, Local Area Networks, Personal Area 

Networks, and Body Area Networks. Future applications 

in the natural resource area could include smart Forest 

Area Networks, Ecosystem Area Networks, Tree Area 

Networks, Microagronomy Area Networks, or individual 

Critter Area Networks.

Th is view of the future holds the promise that everyone 

will have the option of being connected to everyone else, 

and to everything else, on the planet. As future smart 

sensor and actuator networks become ubiquitously 

embedded throughout the globe, these devices will hold 

the potential to connect to every blade of grass, every 

leaf, and every organism on the planet. Indeed, this will 

be the dawn of a connected planet.

Why is this connectedness important? As objects 

become smarter, networked, and capable of both 

sensing and acting on their environments, they radically 

expand and redefi ne the options available for natural 

resource managers. Networked ecologies of things that 

continuously monitor and act on their environments, 

and update data in real time, also provide alternatives to 

traditional concepts of labor-intensive data collection, 

static information systems, and legacy approaches to 

planning and decisionmaking.

Environmental processes infused with multitudes 

of networked sensors and actuators will increasingly 

enable natural resource environments to be monitored 
32 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

continuously, controlled more precisely, and acted 

on more quickly. Natural resource agencies that 

take advantage of these capabilities stand to be more 

proactive, anticipatory, and agile, rather than reactive 

or slow responding. An example of a next step in this 

projected evolution is the development of a smarter 

planet.

A smarter planet. IBM recently introduced a marketing 

campaign premised on building a smarter planet 

(Palmisano 2008). Th e company’s assertion is that 

the planet is rapidly becoming more instrumented, 

interconnected, and intelligent. It has projected this 

concept across a wide spectrum of applications that 

thematically include buildings, businesses, cities, energy, 

education, healthcare, security, transportation, and 

water.

IBM’s view of the future provides an interesting 

perspective. Its premise is that the world is becoming 

smaller, fl atter, and smarter and the application of 

technology will facilitate this process through increased 

digital instrumentation, interconnection, and embedded 

intelligence. It proposes to accomplish this goal by 

embedding large numbers of networked sensors and 

actuators in our built and natural environments, and by 

creating increasingly smarter digital systems to coordinate 

their functions.

Some have taken this view of the future even further. 

American author, inventor, and futurist Raymond 

Kurzweil (2005) has forecast that humanity will 

eventually impart intelligence to every atom in the 

universe using smarter digital technologies. Perhaps 

Kurzweil’s forecast will be realized someday. In the 

interim, this view suggests a greatly expanded role for 

smart, networked sensors and eff ectors in the future(s) of 

natural resources.

Electronic Performance Enhancement Systems

Th e world is entering a new age characterized by 

demands for accelerating human performance. Th is 

new age demands faster work outputs that are of higher 

quality than their predecessors. Signifi cantly, it also 

requires leading-edge knowledge, innovation, and 

idea workers at a time when these resources are only 

beginning to be understood as capital assets (Dickelman 

1999, Stewart 1997).

It can be anticipated that the future of natural resources 

work will closely parallel demands for work performance 

made elsewhere in the economy. Th is view of the future 

suggests that decisionmaking, policy development, 

and associated natural resources work will continue 

to become more complex and demanding. It is also 

indicative of the need for future natural resource workers 

who will be capable of providing world-class performance 

on demand, anytime and anywhere.

To respond to this challenge, it is probable that future 

natural resources work will increasingly involve the 

application of networked smart technologies, tools, 

and environments. Projections of future smart tool 

technologies suggest that these devices will exhibit two 

notable characteristics: they will actively learn as they 

are used and continuously reprogram themselves in 

response to changing needs. Smart tools will also exist in 

the form of smart environments that contain embedded 

intelligence. Autonomous and semi-autonomous robots 

will be another example. Future projections suggest 

that these mind-tools will be capable of evolving 

independently of their initial design parameters and will 

demonstrate greater intelligence over time (Kaku 2011, 

Kurzweil 2005). Th ey will also operate transparently in 

the background. Th e purpose of these smart tools and 

environments will be specifi c: to augment and amplify 

human ability to conduct work.

Electronic Performance Enhancement Systems constitute 

a major response to future performance challenges. EPES 

are a class of rapidly emerging technology-based systems 

designed to enhance human ability to learn and perform 

cognitive-based work. Th ese performanceware systems 

are composed of hardware and software components that 

work together to fuse the processes of learning and doing 

among users, and provide this capability on demand 

(Rosenberg 2001).

EPES will enable future decisionmakers, policy 

formulators, and practitioners to immediately engage in 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 33

leading-edge performance situations. Performanceware 

systems will also eliminate extensive periods of pretraining and education as prerequisites for performance. 

Th e overall intent is to amplify and augment both 

professionals and novices in any environments—physical 

or virtual—and to enable peak performance under 

any conditions. It can be projected that EPES will be 

a leading factor in 21st-century work and learning 

(Winslow and Bramer 1994).

EPES are an outgrowth of earlier computer-enhanced 

learning systems exemplifi ed by Computer-Based 

Training, Intelligent Computer-Assisted Instruction, and 

Intelligent Tutoring Systems (Gery et al. 1999, Mandl 

and Lesgold 1988). Th ese systems were based primarily 

on the application of expert systems and advances in 

Human-Computer Interface technologies. Th e business 

world in particular has developed and applied variants 

identifi ed as Decision Support Systems, Executive 

Information Systems, Executive Support Systems, and 

Electronic Performance Support Systems.

Th ese precursors to EPES were developed mainly by 

business, education, and military interests, and have 

been widely applied throughout these enterprises. Future 

development and application of EPES will continue to 

depend on the fusion of a variety of separately evolving 

technologies. Th ese technologies include artifi cial 

intelligence, computers, expert systems, neural networks, 

and telecommunications.

Current design strategies for EPES outline several 

commonly shared building blocks. EPES, intelligent 

software agents, and smart systems (which include 

emerging classes of smart robots) are frequently 

characterized as anticipatory, interconnected, 

knowledgeable, trustworthy, networked, convenient, 

reliable, and helpful (Aarts et al. 2002, Kaku 2011). 

Th ey provide assistance in response to user inquiries 

such as “help me,” “explain to me,” “orient me,” “show 

me,” and “do for me.” Th ey help close the otherwise 

widening gap between relatively slowly developing 

human competencies, abilities, and knowledge, and the 

exponential increases that characterize digitally based 

machine capabilities and information resources.

Expertise on a chip. Why is the escalating development 

and application of electronic performanceware systems 

important to the future of natural resources? Today, we 

observe the presence of performanceware systems largely 

in the form of expert systems made up of embedded 

subroutines. Th e purpose of these systems is largely to 

automate routine and repetitious tasks and off -load 

the functions into silicon. Th ese systems reduce the 

cognitive workload of natural resource workers by 

handling recurring work. Examples include the Apple 

iPhone and similar devices that are revolutionizing how 

we communicate, learn, and conduct work (Kelly 2010, 

Tapscott and Williams 2010). Th ese and similar devices 

are already impacting natural resource work by providing 

expertise-on-a-chip.

Projections indicate an escalating demand for improved 

work performance. Th is mega force will continue 

well into the future as we face the full impacts of the 

emerging 7 billion mind economy. One strategy is to 

embed smarter devices in our environments, tools, and 

bodies. Evolving performanceware systems in the form 

of EPES represent a major opportunity to augment and 

amplify our ability to continuously deliver world-class 

performance on behalf of natural resources. Earlier in 

this paper we noted that future generations of natural 

resource workers will be highly mobile, educated, and 

always plugged-in. Th e question is, “What will they be 

plugged into—and why?”

CONCLUDING THOUGHTS

Th e purpose of this paper has been to address the 

subject of mega forces of change. Seven broad mega 

forces were identifi ed and their implications for natural 

resources briefl y touched upon. Limitations in the 

length of this paper precluded further description and 

detail. Th e paper also explored two leading mega forces 

in greater detail. Th ese mega forces were identifi ed as 

developments in networked sensor-actuator technologies 

and Electronic Performance Enhancement Systems. It 

was asserted that the future impact of these mega forces 

on natural resources would prove to be nothing less 

than revolutionary. Th eir potential impacts may even 

be compared to the combined historical impacts of the 

printing press and electricity.
34 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

We conclude with a key question: What diff erence 

might we be able to make by adding formalized futures 

thinking to our conceptual resources? We live in an 

increasingly interconnected world. It is a world where the 

distinctions between the built and natural environments 

are blurring. In this milieu, we generate ever more 

knowledge and information about our past, present, and 

possible futures. Our challenge is to use this knowledge 

and creativity in extraordinary ways. An understanding 

of futures thinking and global forces enhances the ability 

of organizations and individuals to think strategically and 

proactively about the future.

LITERATURE CITED

Aarts, E.; Harwig, R.; Schuurmans, M. 2002. Ambient 

intelligence. In: Denning, P.J., ed. Th e invisible 

future: the seamless integration of technology into 

everyday life. New York, NY: McGraw-Hill: 235-250.

Batty, M.; Torrens, P.M. 2001. Modeling complexity: 

the limits to prediction. CASA Working Paper 36. 

London, UK: Centre for Advanced Spatial Analysis, 

University College London. Available at http://

discovery.ucl.ac.uk/260/1/paper36.pdf. (Accessed 26 

June 2012). 37 p.

Beazley, M. 2009. Snapshot: the visual almanac for our 

world today. New York, NY: Octopus Books. 224 p.

Briggs, J.; Peat, F.D. 1999. Seven life lessons of chaos: 

timeless wisdom from the science of change. New 

York, NY: HarperCollins Publishers. 207 p.

Brown, J. 2000. Minds, machines, and the multiverse. 

New York, NY: Simon & Schuster. 396 p.

Culler, D.; Estrin, D.; Srivastava, M. 2004. Overview of 

sensor networks. Computer. 37(8): 41-49.

Cunningham, J. B.; Gerrard, P.; Schoch, H.; Hong, 

C. L. 2002. An entrepreneurial logic for the new 

economy. Management Decision. 40(8): 734-744.

Davies, J. 2012. Understanding IPv6: your essential 

guide to implementing IPv6 on Windows. 

Redmond, WA: Microsoft Press. 716 p.

Dertouzos, M.L. 1997. What will be: how the new 

world of information will change our lives. New 

York, NY: HarperEdge. 336 p.

Dickelman, G.J. 1999. Performance support: crossing 

the chasm from ideas to practice. Performance 

Improvement. 38(7): 5.

Drexler, K.E. 1986. Engines of creation. Garden City, 

NY: Anchor Press/Doubleday. 298 p.

Drexler, K.E.; Peterson, C. 1991. Unbounding the 

future: the nanotechnology revolution. New York, 

NY: Quill William Morrow. 304 p.

Enriquez, J. 2001. As the future catches you: how 

genomics & other forces are changing your life, 

work, health & wealth. New York, NY: Crown 

Business. 259 p.

Florida, R. 2002. Th e rise of the creative class: and how 

it’s transforming work, leisure, community and 

everyday life. New York, NY: Basic Books. 404 p.

Friedman, T.L. 2007. Th e world is fl at: a brief history 

of the twenty-fi rst century. New York, NY: Picador/

Farrar, Straus and Giroux. 672 p.

Gell-Mann, M. 1994. Th e quark and the jaguar: 

adventures in the simple and the complex. New 

York, NY: W.H. Freeman and Company. 392 p.

Gery, G.; Malcolm, S.; Cichelli, J.; et al. 1999. 

Performance support in internet time: the state of 

the practice. Performance Improvement. 39(6): 7-17.

Glenn, J.C. 1989. Future mind: artifi cial intelligence. 

Washington, DC: Acropolis Books, Ltd. 307 p.

Hall, C.A.; Jones, P.W.; Donovan, T.M.; Gibbs, J.P. 

2000. Th e implications of mainstream economics 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 35

for wildlife conservation. Wildlife Society Bulletin. 

28(1): 16-25.

Hamel, G.; Breen, B. 2007. Th e future of management. 

Boston: Harvard Business School Press. 272 p.

Heinrich, C. 2005. RFID and beyond: growing 

your business through real world awareness. 

Indianapolis, IN: Wiley Publishing, Inc. 267 p.

Holling, C.S. 1978. Adaptive environmental 

assessment and management. New York: John Wiley 

& Sons. 377 p.

Ingenito, D. 2010. Democracy in the 21st century: 

social media and politics—global village or cyberBalkans? Los Angeles: University of Southern 

California. 71 p. M.A. thesis.

Internet World Stats. 2011a. Internet growth statistics. 

Available at http://www.internetworldstats.com/

emarketing.htm. (Accessed 6 August 2011).

Internet World Stats. 2011b. Internet usage statistics. 

Available at http://www.internetworldstats.com/stats.

htm. (Accessed 6 August 2011).

Kahn, J.M.; Katz, R.H.; Pister, K.S. 2000. Emerging 

challenges: mobile networking for ‘smart dust.’

Journal of Communication and Networks. 2(3): 188-

196.

Kahn, P.H. 2011. Technological nature: adaptation 

and the future of human life. Cambridge, MA: Th e 

MIT Press. 248 p.

Kaku, M. 2011. Physics of the future: how science will 

shape human destiny and our daily lives by the year 

2100. New York, NY: Doubleday. 389 p.

Kelly, K. 1998. New rules for the new economy: 10 

radical strategies for a connected world. New York, 

NY: Viking. 179 p.

Kelly, K. 2010. What technology wants. New York, 

NY: Viking. 406 p.

Kurzweil, R. 2005. Th e singularity is near: when 

humans transcend biology. New York, NY: Viking 

Penguin. 652 p.

Maddison, A. 2007. Contours of the world economy 

1-2030 AD: essays in macro-economic history. 

Oxford, UK: Oxford University Press. 448 p.

Mandl, H.; Lesgold, A. 1988. Learning issues for 

intelligent tutoring systems. New York, NY: 

Springer-Verlag. 326 p.

Martin, J. 1996. Cybercorp: the new business 

revolution. New York, NY: AMACOM American 

Management Association. 326 p.

McKinsey and Company. 2010. Global forces: how 

strategic trends aff ect your business. Available at 

http://ww1.mckinsey.com/clientservice/strategy/pdf/

Strategic_Trends.pdf. (Accessed 5 August 2011).

Micklethwait, J.; Wooldridge, A. 1996. Th e witch 

doctors: making sense of the management gurus. 

New York, NY: Times Books. 369 p.

Organ, J. F.; Fritzell, E.K. 2000. Trends in 

consumptive recreation and the wildlife profession. 

Wildlife Society Bulletin. 28(4): 780-787.

Palmisano, S. 2008. A smarter planet: instrumented, 

interconnected, intelligent. Available at 

http://www.ibm.com/ibm/ideasfromibm/us/

smartplanet/20081117/sjp_speech.shtml. (Accessed 

18 July 2012).

Regis, E. 1995. Nano: Th e emerging science of 

nanotechnology: remaking the world—molecule by 

molecule. Boston, MA: Little, Brown and Company. 

325 p.

Rosenberg, M.J. 2001. E-learning: strategies for 

delivering knowledge in the digital age. New York, 

NY: McGraw-Hill. 343 p.

Rubinstein, M.F.; Firstenberg, I.R. 1999. Th e minding 

organization: Bring the future to the present and 
36 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

turn creative ideas into business solutions. New 

York, NY: John Wiley & Sons, Inc. 206 p.

Schwartz, P. 2003. Inevitable surprises: thinking ahead 

in a time of turbulence. New York, NY: Gotham 

Books. 247 p.

Starner, T. 1996. Human-powered wearable 

computing. IBM Systems Journal. 35(3&4): 1-12.

Stewart, T. A. 1997. Intellectual capital: the new 

wealth of organizations. New York, NY: Doubleday/

Currency. 278 p.

Tapscott, D. 1996. Th e digital economy: promise and 

peril in the age of networked intelligence. New 

York, NY: McGraw-Hill. 342 p.

Tapscott, D.; Williams, A.D. 2010. Macrowikinomics: 

rebooting business and the world. New York, NY: 

Portfolio/Penguin. 424 p.

Ulrich, D. 2000. Context, capability, and response. 

In: Chowdhury, S., ed. Management 21C: Someday 

we’ll all manage this way. Harlow, UK: Prentice HallPearson Education Limited: 235-249.

Winslow, C.D.; Bramer, W.L. 1994. Future work: 

putting knowledge to work in the knowledge 

economy. New York, NY: Th e Free Press. 384 p. 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 37

SCENARIOS AND DECISIONMAKING FOR COMPLEX 

ENVIRONMENTAL SYSTEMS

Stephen R. Carpenter and Adena R. Rissman

social-ecological systems, or even compute probability 

distributions for social-ecological futures.

Despite these diffi culties, the need to think about the 

future of social-ecological systems cannot be avoided. 

Th e defi nition of sustainability includes the notion 

of non-decreasing wealth: sustainable policies meet 

the needs of the present without undermining future 

generations’ ability to meet their needs (Arrow et al. 

2004). Inevitably, environmental actions aff ect future 

generations as well as the present. Th erefore, presentday decisionmakers must think about long-term 

consequences of environmental actions.

In view of profound uncertainty, how can environmental 

decisions best be guided to meet current and future 

human needs? Tools are needed to organize vast amounts 

of information, and portray uncertainties that cannot 

be computed using the usual tools of decision theory. 

Decisions can at least use all of the information available 

when the decision is made, even if that information 

is incomplete. Scenarios are one of the tools for 

supporting decisions in this setting. Here we provide a 

brief summary of scenarios for complex environmental 

decisions.

WHEN ARE SCENARIOS USEFUL?

Th e set of plausible and possible future trajectories for 

a social-ecological system occupies a vast and mostly 

unknown space (Fig. 1). Most of the space is in the realm 

of unasked questions—outcomes that are not imagined 

and therefore not subject to inquiry. Imaginable but 

non-computable outcomes occupy a smaller part of 

the total space. Th ese are outcomes that are plausible, 

are potentially important, and should be considered in 

decisionmaking even though they are diffi cult to analyze. 

A still smaller space is occupied by the recognized 

uncertainties, unknowns which are subject to formal 

analysis with computable probabilities. What we know 

for certain occupies the smallest region of all.

Abstract. Scenarios are used for expanding the scope 

of imaginable outcomes considered by assessments, 

planning exercises, or research projects on socialecological systems. We discuss a global case study, the 

Millennium Ecosystem Assessment, and a regional 

project for an urbanizing agricultural watershed. 

Qualitative and quantitative aspects of scenarios are 

complementary. Scenarios can help address several of the 

currently recognized challenges of sustainability science.

INTRODUCTION

Society faces unprecedented challenges due to the pace 

and magnitude of environmental change (Millennium 

Ecosystem Assessment 2005). Human actions are 

important drivers of environmental changes through 

eff ects on land use, biogeochemical cycles, species 

invasions, disease emergence, and climate. Th ese actions 

have large and long-lasting consequences for provision 

of food and fresh water; regulation of fl oods, pests and 

diseases; and the other benefi ts that people receive from 

nature, which collectively are called ecosystem services. 

Changes in ecosystem services aff ect human food 

security, health, and access to resources for both current 

and future generations.

Future changes in systems of people and nature (socialecological systems) are deeply uncertain. Th e high 

velocity and vast extent of current changes in Earth’s 

systems have not occurred before in the history of 

our species. We cannot rely on historical analogs for 

guidance. Social-ecological dynamics are unpredictable 

for many reasons, including nonlinear processes, the 

propagation of shocks in an increasingly connected 

world, and the role of human volition. Controllability 

of social-ecological systems is equally uncertain. Our 

ability to predict the consequences of policy instruments 

and management interventions is limited. Actions 

intended to mitigate environmental problems often have 

unintended consequences, including the emergence 

of new and unexpected problems. Collectively, these 

uncertainties make it impossible to predict futures of 
38 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Decisionmaking under uncertainty is a lively discipline 

with many tools that are useful for environmental 

decisions (Polasky et al. 2011). Some established and 

eff ective tools, such as optimization of expected utility 

or related alternatives, are designed for the realm of 

recognized uncertainties (Polasky et al. 2011). In 

this realm, scenarios are not as eff ective as the more 

established tools. Scenarios are not especially useful if 

the set of potential outcomes is known, probabilities 

are computable for the outcomes, desirability (utility) 

of the outcomes is computable (or at least rankable), 

and the controllability of the social-ecological system is 

understood.

Scenarios are uniquely valuable for expanding the space 

of imaginable outcomes by prompting questions that 

have not yet been asked. Scenarios also organize and 

condense complex information in ways that improve 

communication and understanding. Th us, scenarios 

evoke broad conversations about the future while 

providing a framework to integrate diverse points of 

view about the future. Simulation modeling is not 

essential for scenarios, but in many cases scenarios and 

simulation models have been used in complementary 

ways within a single project. Examples of scenario 

projects are presented in the next two sections of the 

paper. 

MILLENNIUM ECOSYSTEM ASSESSMENT

Th e Millennium Ecosystem Assessment (MA) was 

conducted from 2000 to 2005 to assess the status 

and future of the world’s ecosystem services and the 

implications for human well-being. Scenarios for global 

ecosystem services from 2000 to 2050 were developed 

as a part of the MA. Th e creators of the MA scenarios 

were able to learn from earlier eff orts to build global 

environmental scenarios, notably the Global Scenarios 

Group of the Stockholm Environment Institute (Raskin 

2005) and the Special Report on Emissions Scenarios 

of the Intergovernmental Panel on Climate Change 

(Nakicenovic and Swart 2000). Yet ecosystem services 

and their links to human well-being had never before 

been addressed by a global scenarios program (Bennett 

et al. 2003). Th e MA scenarios team had to consider 

nonlinear ecological feedbacks (Cumming et al. 2005) as 

well as relationships of ecosystem conditions to diverse 

aspects of human well-being (Butler et al. 2005). Th e 

challenges of addressing ecosystem services in the context 

of global change were reviewed in depth by the MA 

scenarios team in the early stages of the project (Chapters 

2, 3, and 4 of Millennium Ecosystem Assessment 2005).

Th e overarching question for the MA Scenarios Working 

Group was: What will be the condition of the world’s 

Figure 1.—The space of all possible future trajectories for a social-ecological 

system. Modifi ed from Carpenter et al. (2006).
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 39

ecosystem services in 2050, and what changes will 

occur along the way? Th e process of building the MA 

scenarios began with a workshop to review the status of 

global scenarios and the particular challenges posed by 

ecosystem services. Shortly after this workshop, MA staff 

conducted a telephone survey of about 60 global thinkers 

to gather ideas about the vulnerability and resilience of 

the Earth’s systems (Bennett et al. 2005). At about the 

same time, pilot projects were launched to “learn by 

doing” scenarios for several regions around the world.

Four storylines emerged from broad discussions 

following the synthesis of previous global scenarios and 

the interviews of global thinkers (Carpenter et al. 2006). 

In Global Orchestration, economic development and 

globalization accelerate. Environmental management 

is reactive, responding to crises as they arise. In Order 

From Strength, nations emphasize their own security, 

leading to a divided world with slower economic growth. 

Environmental management is reactive. Adapting 

Mosaic also envisions a less globalized world, in response 

to movement toward local and regional management 

of ecosystem services. Environmental management is 

proactive, emphasizing local knowledge, engagement 

of local people, and property rights to create incentives 

for more resilient stewardship of natural resources. 

In TechnoGarden, economies are globalized and 

technological innovation is booming. Environmental 

management is proactive due to implementation of largescale innovative technological approaches for maintaining 

fl ows of ecosystem services. Th e four scenarios portray 

very diff erent combinations of opportunities, risks, 

benefi ts, and costs. Outcomes are quite diff erent across 

regions. Daily life for people would be very diff erent in 

the four worlds of the scenarios.

Logical consequences of the four storylines were 

developed in both qualitative and quantitative form. 

Narratives emphasized the coherent and logical features 

of the storylines while attempting to explain what it 

would be like to live in each of the four worlds, in 

rich countries as well as poor ones (Cork et al. 2006). 

Quantitative analyses grounded in the logical structures 

of the storylines generated computable outcomes. Th is 

process required an analysis of drivers of change and 

their implications for ecosystem services (Nelson et al. 

2006). Global models for macroeconomics, human 

demography, demand for food and fresh water, nitrogen 

emissions, climate, and biodiversity were run in parallel 

to compute changes in global land cover and land use, 

freshwater fl ows, freshwater quality, species diversity, 

and other outputs (Alcamo et al. 2005, van Vuuren et 

al. 2006). Harmonizing the qualitative and quantitative 

analyses, as well as the linkages among the various global 

models, was a major task for the Scenarios Working 

Group (Carpenter et al. 2006).

Th e MA exposed, and in some cases illuminated, several 

challenges of global scenarios for ecosystem services. 

Th ese challenges include the problems of dealing with 

many diff erent response variables (in contrast to climatechange scenarios that focus on only one response, 

greenhouse gas emission to the atmosphere), the 

challenges of harmonizing qualitative and quantitative 

scenarios, and the diffi culty of integrating multiple global 

models. Th e MA also focused attention on the diffi culty 

of analyzing and understanding the interactions of localand global-scale processes (Biggs et al. 2007). Research 

on the integration of global and local scenarios has 

become an important frontier of scenarios research. We 

address one recently initiated case in the next section of 

this paper.

WATER SUSTAINABILITY AND CLIMATE IN 

THE YAHARA WATERSHED, WISCONSIN

Th e Yahara Watershed includes the fi ve lakes of 

Madison, WI. It drains 996 km2

 and is home to about 

400,000 people. Th e watershed has been substantially 

altered by agricultural land use, urbanization, and climate 

change (Carpenter et al. 2007, Kucharik et al. 2010). 

Climate change, population growth, land-use change, 

and competing goals for the region place growing 

pressure on freshwater resources. Groups with competing 

water management goals include farmers, urban and 

suburban residents, developers, realtors, recreational 

lake users, neighborhood associations, environmental 

organizations, business organizations, and policy makers.

Water management in the region confronts many 

changes. Groundwater levels are declining in the deep 
40 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

aquifer that supplies drinking water, while runoff from 

road salt is increasing the salinity of surface water 

and shallow groundwater. Lake levels are becoming 

more variable over time, due to the increasing area of 

impermeable surface and more variable precipitation. 

Fluctuating lake levels trigger confl ict over management 

of the locks that regulate discharge from the lakes. Some 

of the changes have come as surprises. In the late 1960s, 

Eurasian watermilfoil invaded the lakes and severely 

disrupted boating until the weed densities declined 

by about 1990. Diversion of sewage by 1971 did not 

cause the expected improvements in lake water quality. 

Instead, poor water quality and algae blooms were 

maintained by heavy runoff of nutrients from agricultural 

lands and construction sites (Carpenter et al. 2007). Th e 

recent invasion of spiny water fl ea is harming the native 

grazers in the lakes, and is likely to lead to more severe 

algae blooms. Th e lakes are vulnerable to invasion by 

zebra mussels in the future, which will litter beaches with 

sharp shells while promoting thick mats of decomposing 

algae along shorelines. Meanwhile climate change, 

urbanization, and intensive agriculture are likely to drive 

further changes in the hydrology and biogeochemistry of 

the lakes.

Scenarios of social-ecological change in the watershed 

from 2010 to 2060 will be developed as part of a 

new project that the authors have initiated with coinvestigators Chris Kucharik, Steve Loheide, and Monica 

Turner. Th e overarching questions for the scenarios 

exercise are: (1) What will be the future condition 

of the natural capital and ecosystem services of the 

region between the present and 2060? and (2) What 

human actions will make the region more resilient (or 

vulnerable) to climate change? 

Th e principal goal of the scenarios is to expand basic 

knowledge about sustainability and change in socialecological systems (Table 1). Scenarios can be used to 

address many of the pressing questions of sustainability 

science (Kates et al. 2001, Swart et al. 2004). Qualitative 

narratives will be developed, based on in-person 

interviews and participatory workshops. Quantitative 

implications for land use, land cover, hydrology, and 

water quality will be modeled. Th e primary goal of 

this National Science Foundation-funded project is 

research, but outreach and public education are also 

important objectives. Th e scenarios will provide an 

arena for conversation about the future. Because the 

time horizon is signifi cantly longer than the time frame 

of local politics, discussions can encourage a context 

of collaborative learning rather than confl ict. Broad 

collaborative thinking may reveal new ways of improving 

the resilience of the region that are not known at present. 

In the long run, collaborative learning may help change 

the ways that people think about the region.

EVALUATING SCENARIO PLANNING

Scenarios have been widely used by businesses, nonprofi t 

organizations, researchers, and policy-makers, but 

relatively few evaluations of scenario planning have 

been conducted (Chermack et al. 2001). Improved 

understanding of the value of scenario planning could 

enhance its application in diverse contexts. Scenario 

planning engages groups to imagine plausible future 

alternatives, articulate previously unasked questions, 

and consider trajectories of change with unknowable 

outcomes. Evaluations may examine whether the 

theoretical advantages of scenario planning were realized, 

such as creating plausible alternative futures, encouraging 

creativity and collaboration, enhancing causal and 

story-based thinking, and changing mental models 

(Harries 2003). In addition, evaluations could address 

outcomes in terms of improved decisionmaking, changed 

behavior, or enhanced performance (Bartholomew and 

Ewing 2009). Since scenarios are not forecasts, it would 

be unreasonable to evaluate scenarios on the basis of 

whether they accurately predict future conditions. Yet 

some organizations highlight the success of scenarios 

in helping decisionmakers anticipate future changes in 

an increasingly interlinked world, although these selfreported success stories are not representative (Harries 

2003).

Scenario planning for social-ecological change in the 

Yahara Watershed in Wisconsin will incorporate an 

evaluative component. Th e evaluation process will 

examine the role of scenario planning in enhancing 

participants’ understanding of complex and dynamic 

social-ecological relationships, perceptions of utopian 

and dystopian futures, and perceived mechanisms and 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 41

pathways of change. It will also examine the role of 

scenarios in changing the discourse in regional media 

and policy-making contexts on adaptive strategies for 

increasing resilience and decreasing vulnerability in the 

face of climatic, water resource, and human population 

change.

CONCLUSIONS

Scenarios can increase the scope of environmental 

assessments by asking new questions and expanding 

the domain of uncertainties to be considered. Both 

qualitative and quantitative scenarios are useful. 

Qualitative narratives can be accessible to non-technical 

participants and thereby expand the diversity of people 

who participate in the scenario process (Carpenter et al. 

2009). Qualitative scenarios are also useful for thinking 

about rare unpredictable events that are diffi cult to 

compute. Qualitative scenarios can help frame the socialecological context for quantitative scenarios. Quantitative 

analyses enrich scenarios by providing details about 

computable aspects of environmental change, including 

important ecosystem services such as provision of food 

and fresh water. In addition, quantitative analyses 

provide a useful check on the plausibility of assumptions 

that are made when constructing qualitative scenarios.

Beyond playing a role in assessment, scenarios can help 

address basic research challenges in sustainability science 

(Table 1). Scenarios have also been used as a teaching 

device in university courses dealing with social-ecological 

systems (Biggs et al. 2010).

Use of scenarios in environmental assessment, 

management, and research seems to be expanding 

rapidly, based on the number of citations apparent 

in Google Scholar and Web of Knowledge. Th is brief 

article has only scratched the surface of an extensive and 

growing literature. We hope, at least, to have exposed 

some of the opportunities and challenges of scenarios for 

addressing change in social-ecological systems.

Table 1.—Research challenges to be addressed using scenarios in the Yahara Watershed project. 

Research challenges of sustainability science are based on Kates et al. (2001) and Swart et al. (2004).

Research Challenge Key Aspects of the Challenge Contribution of Scenarios

Spanning spatial scales Local, regional, and global processes interact. Identifying cross-scale feedbacks and their 

potential consequences

Spanning response 

times

Societal decisions about long-term change must be 

made in the short term.

Linking long-term goals to short-term 

decisions

Recognizing wide range 

of outlooks

Values and preferences for the future differ among 

people.

Accounting for perspectives that are 

recognized through outreach activities, 

surveys, etc.

Refl ecting critical 

thresholds, surprise, 

and uncertainties

Unprecedented changes cannot be calibrated 

in models, and nonlinear thresholds are hard to 

measure.

 Creative “what if” scenarios suggesting 

novel analyses and model simulations

Accounting for human 

volition

Human behaviors have strong effects yet are hard to 

forecast.

Normatively distinct viewpoints of desired or 

undesired futures being cast as scenarios 

for analysis and model simulation

Combining qualitative 

and quantitative thinking

Values, culture, and institutions have as much 

impact on sustainability as do quantifi able aspects 

of social, economic, and biophysical change.

Combining narrative scenarios with 

quantitative model simulations

Engaging stakeholders Stakeholders have deep local knowledge of the 

system. Engaging them widens the knowledge base, 

helps address normative aspects of sustainability, 

and increases learning by all participants.

Providing a framework for synthesis and 

communication among researchers and 

stakeholders
42 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

LITERATURE CITED

 Alcamo, J. D.; van Vuuren, D. P.; Ringler, C.; Cramer, 

W.; Masui, T.; Alder, J.; Schulze, K. 2005. Changes 

in nature’s balance sheet: model-based estimates 

of future worldwide ecosystem services. Ecology 

and Society. 10(2): 19. Available at http://www.

ecologyandsociety.org/vol10/iss2/art19/. (Accessed 6 

July 2012).

 Arrow, K.; Dasgupta, P.; Goulder, L.; Daily, G.; 

Ehrlich, P.; Heal, G.; Simon, L.; Mäler, K.-G.; 

Schneider, S.; Starrett, D.; Walker, B. 2004. Are we 

consuming too much? Th e Journal of Economic 

Perspectives. 18: 147-172.

 Bartholomew, K.; Ewing, R. 2009. Land use—

transportation scenarios and future vehicle travel 

and land consumption: a meta-analysis. Journal of 

the American Planning Association. 75: 13-27.

 Bennett, E.; Carpenter, S.; Peterson, G.; Cumming, 

G.; Zurek, M.; Pingali, P. 2003. Why global 

scenarios need ecology. Frontiers in Ecology and the 

Environment. 1: 322-329.

 Bennett, E. M.; Peterson,G.D.; Levitt, E. A. 2005. 

Looking to the future of ecosystem services. 

Ecosystems. 8: 125-132.

 Biggs, R.; Diebel, M.W.; Gilroy, D.; Kamarainen, A.M.; 

Kornis, M.S.; Preston, N.D.; Schmitz, J.E.; Uejio, 

C.K.; Van De Bogert, M.C.; Weidel, B.C.; West, 

P.C.; Zaks, D.P.; Carpenter, S.R. 2010. Preparing 

for the future: teaching scenario planning at 

the graduate level. Frontiers in Ecology and the 

Environment. 8: 267-273.

 Biggs, R.; Raudsepp-Hearne, C.; Atkinson-Palombo, 

C.; Bohensky, E.; Boyd, E.; Cundill, G.; Fox, H.; 

Ingram, S.; Kok, K.; Spehar, S.; Tengo, M.; Timmer, 

D.; Zurek, M. 2007. Linking futures across scales: a 

dialog on multiscale scenarios. Ecology and Society. 

12(1): 17. Available at http://www.ecologyandsociety.

org/vol12/iss1/art17/ (Accessed 6 July 2012).

 Butler, C.D.; Corvalan, C.F.; Koren, H.S. 2005. 

Human health, well-being, and global ecological 

scenarios. Ecosystems. 8: 153-162.

 Carpenter, S.R.; Bennett, E.M.; Peterson, G.D. 2006. 

Scenarios for ecosystem services: an overview. 

Ecology and Society. 11(1):29. Available at http://

www.ecologyandsociety.org/vol11/iss1/art29/. 

(Accessed 6 July 2012).

 Carpenter, S.R.; Benson, B.J.; Biggs, R.; Chipman, J.W.; 

Foley, J.A.; Golding, S.A.; Hammer, R.B.; Hanson, 

P.C.; Johnson, P.T.J.; Kamarainen, A.M.; Kratz, T. 

K.; Lathrop, R.C.; McMahon, K.D.; Provencher, 

B.; Rusak, J.A.; Solomon, C.T.; Stanley, E.H.; 

Turner, M.G.; Vander Zanden, M.J.; Wu, C.-H.; 

Yuan, H. 2007. Understanding regional change: 

a comparison of two lake districts. Bioscience. 57: 

323-335.

 Carpenter, S. R.; Folke, C.; Scheff er, M.; Westley, 

F. 2009. Resilience: accounting for the 

noncomputable. Ecology and Society. 14(1):13. 

Available at http://www.ecologyandsociety.org/vol14/

iss1/art13/ (Accessed 6 July 2012).

 Chermack, T. J.; Lynham, S.A.; Ruona, W.E. A. 2001. 

A review of scenario planning literature. Futures 

Research Quarterly. 17: 7-32.

 Cork, S. J.; Peterson, G.D.; Bennett, E.M.; PetschelHeld, G.; Zurek, M. 2006. Synthesis of the 

storylines. Ecology and Society. 11(2): 11. Available 

at http://www.ecologyandsociety.org/vol11/iss2/

art11/. (Accessed 6 July 2012). 

 Cumming, G. S.; Alcamo, J.; Sala, O.; Swart, R.; 

Bennett, E.M.; Zurek, M. 2005. Are existing global 

scenarios consistent with ecological feedbacks?

Ecosystems. 8: 143-152.

 Harries, C. 2003. Correspondence to what? Coherence 

to what? What is good scenario-based decision 

making? Technological Forecasting and Social 

Change. 70: 797-817.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 43

 Kates, R.W.; Clark, W.C.; Corell, R.; Hall, J.M. Hall; 

Jaeger, C.C.; Lowe, I.; McCarthy, J.J.; Schellnhuber, 

H.J.; Bolin, B.; Dickson, N.M.; Faucheux, S.; 

Gallopin, G.C.; Grübler, A.; Huntley, B; Jäger, 

J.; Jodha, N.S.; Kasperson, R.E.; Mabogunje, A.; 

Matson, P.; Mooney, H.; Moore, B.; O’Riordan, 

T.Svedin, U. 2001. Sustainability science. Science. 

292: 641-642.

 Kucharik, C.; Serbin, S; Vavrus, S.; Hopkins, E.; 

Motew, M. 2010. Patterns of climate change across 

Wisconsin from 1950 to 2006. Physical Geography. 

31: 1-28.

 Millennium Ecosystem Assessment. 2005. Ecosystems 

and human well-being: scenarios. Washington, DC: 

Millennium Ecosystem Assessment. Available at www.

maweb.org/en/SYNTHESIS.aspx. (Accessed 7 July 

2012).

 Nakicenovic, N.; Swart, R.J., eds. 2000. Special report 

on emissions scenarios. Cambridge, UK: Cambridge 

University Press.

 Nelson, G.C.; Bennett, E.M.; Berhe, A.A.; Cassman, 

K.; DeFries, R.; Dietz, T.; Dobermann, A.; Dobson, 

A. Dobson, Janetos, A.; Levy, M.; Marco, D.; 

Nakicenovic, N.; O’Neill, B.; Norgaard, R.; PetschelHeld, G.; Ojima, D.; Pingali, P.; Watson, R.; Zurek, 

M. 2006. Anthropogenic drivers of ecosystem 

change: an overview. Ecology and Society. 11(2): 29. 

Available at http://www.ecologyandsociety.org/vol11/

iss2/art29/. (Accessed 7 July 2012).

 Polasky, S.; Carpenter, S.R.; Folke, C.; Keeler, B. 

2011. Decision-making under great uncertainty: 

environmental management in an era of global 

change. Trends in Ecology & Evolution. 26(8): 398-

404.

 Raskin, P.D. 2005. Global scenarios: background 

review for the Millennium Ecosystem Assessment. 

Ecosystems. 8: 133-142.

 Swart, R.J.; Raskin, P.; Robinson, J. 2004. Th e problem 

of the future: sustainability science and scenario 

analysis. Global Environmental Change Part A. 14: 

137-146.

 van Vuuren, D.P.; Sala, O.E.; Pereira, H.M. 2006. Th e 

future of vascular plant diversity under four global 

scenarios. Ecology and Society. 11(2): 25. Available 

at http://www.ecologyandsociety.org/vol11/iss2/

art25/. (Accessed 7 July 2012).
44 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

THE NORTHERN FOREST FUTURES PROJECT: 

A FORWARD LOOK AT FOREST CONDITIONS IN THE NORTHERN 

UNITED STATES

W. Keith Moser and Stephen R. Shifl ey

INTRODUCTION

Th e 20-state region from Maine to Maryland to Missouri 

to Minnesota, referred to as the North, has a higher 

proportion of forest cover (42 percent) and a greater 

share of the U.S. population (41 percent) than the other 

three quadrants of the United States (Fig. 1).

Today, forest conditions in the North refl ect the human 

activities of many decades or centuries ago. Th e largescale harvesting of old-growth timber that was common 

in the 19th and early 20th centuries was followed by forest 

fi res, forest species succession, and most destructively 

by agricultural and urban land clearing. Forest-based 

cultures were replaced by farming, land development, 

or open-range grazing as settlers followed the loggers 

across the landscape (Williams 1989). Over time, 

however, marginal farm and pasture lands were gradually 

abandoned in many areas, allowing millions of acres 

of former agricultural land to revert naturally to forest 

cover. As a consequence, forest land in the North 

increased from 134 to 172 million acres (28 percent) 

from 1907 to 2007, while total U.S. forest land area 

showed little change (Smith et al. 2009). Th is increase 

in forest area in the North is remarkable because over 

that same period population in the quadrant increased 

from 52 to 124 million people (138 percent) and total 

U.S. population increased from 87 to 300 million (245 

percent) (Shifl ey et al. 2012, U.S. Census Bureau 2012).

Future forest conditions in the North will be infl uenced 

by contemporary land use decisions and forest 

management activity, as well as population change 

and many other factors. For example, the increase in 

forest area appears to have nearly peaked as expanding 

urban areas in the North now subsume 4 million acres 

per decade, of which 1.5 million acres was formerly 

forest land (Nowak and Walton 2005, Shifl ey et al. 

2012, Smith et al. 2009). How will forest resources and 

ecosystem services change in proximity to expanding 

Abstract. Forests and forest ecosystems provide a 

critical array of benefi ts, from clean air and water to 

commercial products to open space. Th e forests and their 

ability to provide desired benefi ts constantly change in 

response to natural forces, human decisions, and human 

needs. Th e complexity and rate of change demand a 

rigorous evaluation of existing and emerging natural 

and anthropogenic forces, analysis of potential impacts 

of those forces, and consideration of how our response 

to them aff ects future forest sustainability. Nowhere 

is the apparent need for analysis of these challenges 

more critical than in the Upper Midwest and Northeast 

because this quadrant of the United States has both the 

greatest population density and the greatest percentage of 

forest cover.

Th e Northern Forest Futures Project is intended to 

be a window on tomorrow’s forests, revealing how 

trends evident today and choices today and tomorrow 

can change the future landscape of the Northeast and 

Midwest. Th e project is a cooperative eff ort of the U.S. 

Forest Service, the Northeastern Area Association of 

State Foresters, and the academic community. Th is 

eff ort began with existing assessments and inventories 

and identifi cation of trends and public issues. Current 

research is evaluating alternative future forest conditions 

based on scenarios from the Intergovernmental Panel 

on Climate Change, coupled with selected global 

circulation models and interpreted in the context of 

the latest ecological and social science. Th e results will 

provide a better understanding of the range of outcomes 

that may aff ect the North’s 172 million acres of forest 

and the lives of the 124 million people who live near 

them. Th is information will be the basis for educational 

outreach that allows individuals, organizations, and 

resource managers to directly assess how diff erences that 

result from alternative social and economic choices about 

resource use, development, policy, and management 

aff ect the well-being of their communities and forests. 

Ultimately, the Northern Forest Futures Project provides 

the information needed for making wise decisions about 

the sustainable management of public and private forests 

in the northern United States.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 45

urban areas that house 80 percent of the North’s 

population? Th e age distribution of the North’s forest 

stands is concentrated in the 40- to 80-year-old age 

classes, rather than evenly balanced across a broader 

range of age classes. How is this age-class imbalance 

likely to aff ect forest biodiversity in coming decades, 

and how are management activities likely to aff ect future 

forest age-class distributions? Th e North’s forests are 

being affl icted by new or expanding invasive insects 

and diseases. How are invasive species likely to aff ect 

the future condition of northern forests? How will the 

overarching eff ects of climate change over the next 50 

years aff ect these patterns and trends? Th ese and related 

questions have spurred research under the Northern 

Forest Futures Project.

Although the tradition of reporting forest statistics dates 

back to the 19th century, information on today’s forests 

is more detailed and more complete than ever before. 

National assessments such as the Resources Planning 

Act (RPA) (USDA Forest Service 2012b), the 2010 

National Report on Sustainable Forests (USDA Forest 

Service 2011a), and the billion-ton biomass report (Oak 

Ridge National Laboratory 2011, Perlack et al. 2005) 

highlight national trends and forecast national changes. 

Recently completed forest action plans for each state 

examine forest resource issues and proposed activities to 

address the most pressing of them (USDA Forest Service 

and Northeastern Area Association of State Foresters 

2011). Th e Northern Forest Futures Project operates at 

a scale between states and the nation to examine issues, 

current conditions, trends, and projections of forest 

conditions, applying a consistent methodology to the 

20 states within the North, individually and collectively. 

Th e methodology is linked to the Forest Inventory and 

Analysis (FIA) forest resource inventories and is intended 

to bring new forest resource projection capabilities 

to state and regional inventory data. Key projection 

methodologies and assumptions were developed from the 

methods applied for national RPA projections (USDA 

Forest Service 2012b) as well as the Southern Forest 

Futures Project (USDA Forest Service 2012c).

Th e Northern Forest Futures Project includes three 

components: (1) scoping contemporary issues and 

problems facing northern forests, (2) an assessment of 

current forest conditions and recent trends for a wide 

range of forest attributes, and (3) projections of future 

forest conditions for a range of alternative harvest, 

climate, and socioeconomic scenarios. Th e fi rst and 

Figure 1.—Distribution of forests and people in the United States (Homer et al. 2004, Shifl ey et al. 2012, 

Smith et al. 2009, U.S. Census Bureau 2012). Shading shows forest land.
46 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

second components have been completed. Dietzman 

et al. (2011) analyzed hundreds of sources to produce 

a prioritized summary of issues and concerns recently 

expressed about the current condition of northern 

forests, which is supplemented by a summary of the 

issues raised in the forest action plans recently developed 

by each of the 20 states in the North (USDA Forest 

Service and Northeastern Area Association of State 

Foresters 2011). Th ese products identify issues that can 

benefi t from (or in some cases require) collaboration 

among states to address eff ectively. Examples include 

controlling invasive species, sustaining forest biodiversity, 

protecting water quality through watershed-scale 

management, and sustaining a viable wood products 

industry. Th e second component assessment is addressed 

by the recent publication of an assessment of 36 

indicators of forest conditions in the North (Shifl ey 

et al. 2012). It provides a collective analysis of forest 

conditions and trends with comparative data at state and 

regional scales for many indicators of forest condition. 

In the remainder of this paper, we concentrate on the 

third component—development of forest projection 

capabilities.

METHODS FOR FORECASTING CHANGE 

IN THE NORTHERN FOREST

Overview

Th e projection component of the Northern Forest 

Futures Project seeks to estimate forest area, size, 

structure, and species composition under alternative 

scenarios for 2010 to 2060 across the 20-state North. In 

most cases these projections will be made for individual 

states and aggregated for regionwide estimates of change 

over time. Infl uencing these projections will be largescale estimates of land use change, forest harvesting, 

and climate change over the time period. Fortunately, 

the Northern Forest Futures Project is able to utilize 

regional land use change and forest harvesting estimates 

developed as part of the 2010 Resources Planning Act 

assessment that includes national projections of forest 

change (USDA Forest Service 2012b, 2012c; Wear 

2011). Climate change scenarios examined under the 

Northern Forest Futures Project are tied to climate 

projection models from the Intergovernmental Panel 

on Climate Change (IPCC) (Nakicenovic et al. 2000). 

State-scale forest resource projection methods follow 

those developed for the Southern Forest Futures Project 

(Wear and Greis in press), except the projected harvest 

levels were adjusted to match as closely as possible the 

RPA timber market scenarios and the forecasts of forest 

conditions (pers. comm., David Wear, USFS, May 

2012). To maximize compatibility among projections 

for the North and the South, projection models for the 

North were implemented by the Southern Forest Futures 

Project team (Huggett et al., in press) and converted 

by Pat Miles into a Microsoft Access database that 

can be readily summarized and analyzed using his FIA 

EVALIDATOR program (Miles 2012).

Th e Northern Forest Futures Project projections will 

focus on a core subset of future scenarios that refl ect 

high, medium, and low levels of climate change. Th e 

projection system accesses inputs of other models, 

quantifi es scenario assumptions, and applies them to 

current forest inventory data (i.e., FIA plots), transforms 

these inventory data using calculated relationships, 

outputs the projected forest inventory data, and 

summarizes the projected data into a cohesive assessment 

of conditions under each scenario (Wear et al., in press).

Th ere are two major benefi ts of this design. First, it 

largely mirrors the structure of the information fl ows 

of the RPA and the Southern Forest Futures Project, so 

the Northern Forest Futures Project can take advantage 

of existing algorithms, software, and expertise. Because 

those methods have already undergone peer review 

(Polyakov and Wear 2010, Wear et al., in press), so 

we can concentrate on understanding the implications 

of expected changes in northern forests rather than on 

developing projection methodology. Second, the future 

(projected) forest inventory database possesses the same 

data elements and structure as the current FIA inventory 

database. Within the constraints of usable data in this 

future dataset, the same analyses applicable to current 

FIA data will work for the future data. Th is provides 

substantial effi ciencies in summarizing projection results 

and making direct comparisons to past and current forest 

conditions.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 47

Estimating Future Climate Change

Th e IPCC has evaluated alternative future climate 

scenarios based on selected atmospheric, economic, 

technological, and population variables (IPCC 2007). 

Future increases in greenhouse gas emissions are 

estimated based on four IPPC storylines. Th ese storylines 

have diff ering assumptions about future economic, 

social, and technology changes that will infl uence future 

greenhouse gas emissions. Th e three IPCC storylines 

used in the Northern Forest Futures Project projections 

are summarized in Table 1. Th ese storylines, which 

are also used in the RPA and Southern Forest Futures 

Project, can be summarized as follows:

• A1B—a future where the rest of the world 

approaches the United States in terms of per 

capita wealth, technology use, and population 

growth

• A2—a future where the world is not converging 

on the U.S. experience, but rather is much more 

regionally focused

• B2—a future of global sustainable development, 

with some regional economic convergence

Th e scenarios are categorized as very high, high, and 

medium global energy use for storylines A1B, A2, and 

B2, respectively (Table 1). Each storyline incorporates 

corresponding estimates of land use change and 

future greenhouse gas emissions. At least seven global 

circulation models (competing hypotheses) predict and 

map future temperature and precipitation based on 

estimates of future greenhouse gas emissions. To limit 

the total number of alternatives examined, we paired 

each of the three selected IPPC storylines (Table 1) with 

one of the midrange coupled global circulation models 

(CGCM) published by the Canadian Centre for Climate 

Modeling and Analysis (2012a, b). To defi ne three 

Northern Forest Futures scenarios that represent high, 

medium, and low relative levels of future climate change, 

we modeled climate change using CGCM3.1 for IPCC 

storylines A1B and A2, and we used CGCM2 with 

IPCC storyline B2. Th e CGCM models chosen for the 

Northern Forest Futures Project analyses are intended to 

be consistent with the climate models used by the RPA 

and the Southern Forest Futures Project.

Table 1.—Overview of IPCC storylines used in the 4th RPA asessment; 

Source: Nakicenovic et al. (2000) and Ince et al. (2011a)

Storyline Characteristics Storyline A1B Storyline A2 Storyline B2

General Description Globalization, Economic 

Convergence

Heterogenic Regionalism, 

Less Trade

Localized Solutions, 

Slow Change

Global Real GDP Growth Very High (6.2x) Medium (3.2x) Medium (3.5x)

U.S. GDP Growth Medium (3.3x) Low (2.6x) Low (2.2x)

Global Energy Use Very High High Medium

Oil & Gas Availability High Low Medium

Technological Pace & 

Direction

Rapid; Gas,

Biomass & Other Renewables

Slow; Coal & Gas Medium; Gas, Oil & 

Biomass

Global Population Growth Medium (1.3x) High (1.7x) Medium (1.4x)

U.S. Population Growth Medium (1.5x) High (1.7x) Medium (1.3x)

General Development 

Themes

Economic growth; Introduction 

of New & More Efficient 

Technologies; Capacity Building

Self-reliance, 

Preservation of Local 

Identities

Sustainable 

Development, 

Diversifi ed Technology

Global Expansion of 

Primary Biomass Energy 

Production (2010-2060)

High (Highest for USA) Medium Medium (lowest for 

USA)
48 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Modeling Forest Change Under a 

Changing Climate

A version of the forest dynamics model (Wear et al. 

in press) is used to estimate change in northern forest 

conditions in response to projected land use change and 

the projected change in climate conditions outlined 

above. Th e model starts with a set of current FIA 

inventory plots that represent initial forest conditions 

for a given state and then operates on that inventory 

list to estimate change in FIA plot characteristics over a 

50-year scenario. By summarizing the estimated future 

conditions of plots for the entire state (or any subset), 

it is possible to estimate the cumulative change in forest 

conditions over time.

In practice, the modeling process is complex and 

incorporates data from numerous sources. However, 

the core modeling technique is based on an imputation 

process that in its simplest form is intuitive. For example, 

begin with a list of all FIA plots for a given state. Th en, 

for the next 5-year interval, stochastically estimate which 

plots will be harvested and replace each of those with a 

duplicate copy of a recently harvested FIA plot drawn 

from a pool of plots with matching ecological conditions. 

Harvest probability estimates are based on empirical 

models of historical harvest choices for each forest-type 

group; these probabilities are adjusted by a common 

scalar to simulate the level of harvest used for the RPA 

Scenario’s harvest projection alternatives (pers. comm., 

David Wear, May 2012). Th en, estimate which plots will 

be largely undisturbed and stochastically replace each 

of those with a copy of a plot that is 5 years older but 

otherwise of the same forest type and found on similar 

site conditions.

Th e next step is to use results from an external model 

of land use change (Wear 2011) to estimate increases or 

decreases in forest area for the projection period; model 

the change in forest area by proportionally increasing 

or decreasing the area that each FIA plot represents on 

the forest landscape (i.e., adjust the plot area expansion 

factor). Forest changes resulting from climate change 

are modeled by modifying the general methodology 

to replace plots representing forest growing under one 

historical climate regime with corresponding plots 

representing forest growing under a diff erent historical 

climate regime (e.g., slightly warmer and wetter) that 

refl ects the mapped changes in climate for future decades 

from a specifi c Coupled Global Climate Model.

Th e forest dynamics model has three submodels: 

partitioning, transition, and imputation. Th ese 

submodels facilitate estimation of transition probabilities 

used to classify FIA plots, summarize detailed 

inventory data, and estimate change over time. Th e 

partitioning submodel groups similar FIA plots by 

identifying attributes such as age, density, precipitation, 

temperature, and live timber volume to develop groups 

(buckets) of similar plots. Th e transition submodel 

estimates the probabilities that a given plot will transition 

from one status (bucket) to another based on historical 

transition rates observed from re-measured FIA plots. 

Two separate versions of the transition submodel 

have been developed for (1) unharvested and partially 

harvested plots and (2) harvested plots that will be 

replaced by a plot representing new forest regeneration. 

Th ese transition probabilities are used by the imputation 

submodel to predict a future condition for each 

inventory plot for the next time interval by stochastically 

drawing a replacement plot from the most appropriate 

partition group (bucket) as developed in the partition 

process. For example, if the transition probabilities state 

that a 40-year-old oak-pine plot will become a 45-yearold oak-pine plot (instead of an oak-hickory plot or 

some other forest-type group), then the model imputes 

what this 40-year-old plot will look like in 5 years by 

randomly picking an oak-pine plot from the bucket of 

existing 45-year-old plots that have similar ecological 

characteristics. Th is plot then becomes the new base plot 

for the next 5-year time step.

Th e completed simulation summarizes the results of 

these transitions for future decades by summarizing plot 

conditions for a projected future date in the same way 

that one would summarize forest conditions for any 

current or past forest inventory (Miles 2012). Th e forest 

condition forecasts are modifi ed to account for projected 

land use change from an external land use model. 

Removals of wood products from timberland are derived 

from a separate model and summarized by hardwoods 

and softwoods.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 49

DISCUSSION

Limitations of the Modeling Framework

Model resolution

Th e partition submodel used to defi ne groups of similar 

plots for the imputation process operates at the foresttype group level of aggregation, which is necessary 

to ensure suffi cient sample sizes for imputation. For 

example, the oak-hickory forest-type group is an 

aggregation that includes 17 distinct forest types (e.g., 

white oak, red oak, bur oak, yellow-poplar/white oak/

red oak, sweetgum/yellow-poplar, red maple/oak, 

southern scrub oak) and dozens of oak species. During 

the projection, the partition submodel aggregates more 

than 100 forest types into 10 or fewer forest-type groups 

that are carried forward in the projection. Projections of 

future forest species composition can be reported only 

by forest-type group, not by forest type or individual 

species. Th us, even though the projection system carries 

complete individual FIA plots forward in time, there are 

limits on the suite of variables that can be realistically 

summarized for future decades. Th e primary variables 

available for characterizing future forest inventories 

include forest-type group, area, age, site quality, size 

class, number of trees, volume, and biomass. Likewise, 

the methodology limits the spatial scale of results 

reporting to inventory units, entire states, or groups of 

states.

Verifi cation and validation

Th e forest dynamics model has been verifi ed for U.S. 

forests by determining that the model is working 

as expected: the computer algorithms are correctly 

implementing the statistical models and the external 

assumptions about land use change and harvest are 

correctly applied to the projected forest conditions. Th e 

model projections have been validated in two ways. 

First, before the model was applied for the 2010 RPA 

projections, past FIA inventories for selected states were 

projected forward in time with the calibrated model 

and compared to observed present-day FIA inventories. 

Results were judged satisfactory by the model developers 

(pers. comm., David Wear, USFS, May 2012), and the 

subsequent RPA regional and national projections of 

forest change for 2010 to 2060 based on the model have 

undergone internal and external review. Second, the 

initial round of state-scale projections of forest change 

from 2020 to 2060 for the Northern Forest Futures 

Project were reviewed by the Forest Service FIA analysts 

working in the North and by state foresters and planners 

from northern states. Th ose evaluations, based on expert 

knowledge of forest conditions and past trends at the 

state scale, resulted in some modifi cations to model 

calibration for individual states, particularly with respect 

to estimated changes in forest area. More rigorous 

statistical validation of model projection accuracy and 

bias for individual northern states will occur over time 

with ongoing FIA state inventories. Present-day model 

projections from 2010 to 2060 serve as provisional 

hypotheses of forest change, and FIA statewide forest 

inventories completed in the coming decades will 

determine the accuracy of those projections in a de facto 

validation process.

In general, we anticipate that the longer the projection 

periods are, the lower the accuracy of the projection will 

be. For this application the imputation model uses the 

trends observed in the 2003 to 2008 forest inventories 

and other inputs, such as climate models, to build 

transition matrices. Consequently, trends occurring in 

that time span determine the future rates and patterns 

of forest change for the entire projection period. Th is 

may downplay the infl uence of some longer term trends, 

especially if those trends vary greatly from year to year. 

For example, mortality rates inherent in the model 

structure are based on those observed from 2003 through 

2008 and may not refl ect longer term or episodic cycles 

of forest pest attacks.

Complexity

Th e imputation model is a custom product developed 

by the U.S. Forest Service, Southern Research Station’s 

Forest Economics and Policy project (Wear et al., in 

press). Calibration and application require specialized 

knowledge and programming skills, which limits model 

implementation to a group of specialists. However, after 

a scenario is modeled the results will be readily accessible 

using a simple Web-based interface (Miles 2012).
50 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Strengths of the Modeling Framework

Linkage to FIA data

Th ere are many practical advantages to this modeling 

framework. Foremost, it can be calibrated and applied 

using existing FIA data that systematically sample all 

forest conditions in the United States. Consequently, 

it can be applied to all states in the North. Moreover, 

the same methodology has been applied to forecast 

nationwide changes in forest conditions as part of the 

RPA Assessment (USDA 2012b). Projections for the 

20-state North use the same methods to provide state 

forecasts. Because the projection model input and output 

are databases of standard FIA plots, data summaries over 

time can be created using standard Web-based tools used 

to summarize current and historical FIA fi eld inventory 

data (Miles 2012). Th is provides an effi cient mechanism 

for summarizing projected changes over time in forest 

area, number of trees, age, size class, volume, and 

biomass in the same manner that present and past FIA 

data can be summarized.

Linkages to other forest characteristics 

Use of the FIA forest inventory plots as the basis for 

projecting forest conditions in future decades provides 

opportunities to link projected changes in forest 

conditions to estimates of other ecosystem services. 

Many forest attributes that can be estimated using a 

contemporary FIA inventory also can be estimated using 

projected inventory conditions (Table 2). Four principal 

investigative themes are outlined below.

1. Invasive species

Th e Northern Forest Futures baseline assessment (Shifl ey 

et al. 2012) summarizes invasive insects and diseases that 

are likely to negatively impact northern forests in coming 

decades. Th ese include (but are not limited to) emerald 

ash borer (Agrilus planipennis), gypsy moth (Lymantria 

dispar), Asian long-horned beetle (Anoplophora 

glabripennis), sirex wood wasp (Sirex noctilio), hemlock 

wooly adelgid (Adelges tsugae), and thousand cankers 

disease of black walnut.

Potential impacts of the emerald ash borer are well 

suited to examination with the Northern Forest Futures 

modeling framework. As it spreads, the emerald ash borer 

exclusively attacks ash trees (Fraxinus spp.) and kills 

virtually all of them. Consequently, it is relatively easy 

to model emerald ash borer impact on forest structure 

and composition by systematically removing ash trees 

from the imputed plots as the borer moves across the 

region. Other invasive species present greater modeling 

challenges within this projection system. Th e impact of 

the gypsy moth, which infests multiple species and kills 

only a portion of all infested trees, is much more diffi cult 

to model within the projection system and must be 

analyzed externally (e.g., USDA Forest Service 2012d).

2. Forest biodiversity

Projections of forest age class through time can be used 

to examine broad change in forest age-class diversity. Age 

class is one of the simplest indicators of forest structural 

diversity (e.g., seedling, sapling, poletimber, saw log, and 

Table 2.—Northern Forest Futures Project research topics aligned under natural 

resource, human, or interaction categories (USDA, Forest Service 2011b).

Natural Resources Human Systems

Natural Resource—

Human Interactions

Wildlife habitat and biodiversity Wood products Insects and diseases

Forest area, species 

composition, and size structure

Environmental literacy Stewardship and forest 

management

Water Urban forest dynamics 

and management

Invasive plant species

Recreation Forest fragmentation 

and parcelization

Biomass and bioenergy
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 51

old-growth forest conditions) and associated wildlife 

habitat diversity (Tirpak et al. 2009). Th e current ageclass distribution in the North is clustered in the 40- to 

80-year-old range (Shifl ey et al. 2012). Th is has strong 

implications for current habitat diversity (Greenberg 

et al. 2011). Th e projection system allows exploration 

of anticipated changes in forest age class and structural 

diversity both spatially and temporally.

Gross changes in forest species composition can also 

be explored through the scenario projections of the 

Northern Forest Futures Project. As noted above, the 

assumptions underlying the projection process limit 

analyses of species composition to the aggregated 

forest-type group. Nevertheless, change in the relative 

proportion of oak-hickory vs. maple-beech-birch 

forest-type groups is suffi cient to examine issues such 

as the rate of mesifi cation of northern hardwood forests 

(Nowacki and Abrams 2008) and the associated loss of 

oak forest cover.

3. Wood volume and biomass

Because the modeling system operates on FIA plots as 

the basic unit indicating forest conditions, it is possible 

to summarize estimates of future wood volume and 

biomass over time for individual states or groups of 

states in exactly the same way as for current volume and 

biomass. Volume and biomass typically increase with 

increasing stand age. Consequently, the imbalanced 

age-class distribution of existing northern forests will 

be refl ected in changes in wood volume and biomass 

under alternative future scenarios. Under most IPCC 

storylines, woody biomass is projected to supply an 

increasing proportion of the nation’s energy needs (Ince 

et al. 2011b). Th is will aff ect energy portfolios, forest 

management opportunities, income opportunities for 

landowners, future forest age-class distribution, and 

associated forest biodiversity.

4. Ownership and urban-rural forest distribution

Th e FIA defi nition of forest is based on composition, 

structure, and function. Yet forest land is owned and 

managed for a variety of reasons. Five acres of suburban 

forest in New Canaan, Connecticut, may well be owned 

for diff erent reasons than 5 acres of forest in Aroostook 

County, Maine. One consideration infl uencing diff erent 

attitudes and management practices on forest land can 

be the proximity to the cultural and economic infl uences 

of major metropolitan areas. In the North, 80 percent of 

the population lives in urban areas that cover 6 percent 

of the land area. Consequently, forests near urban areas 

have the potential to provide ecosystem services such 

as aesthetics, recreation, water quality, air quality, and 

wildlife benefi ts to a large number of people. Anticipated 

demographic changes over the next 50 years are 

expected to exert a strong infl uence on forest conditions 

in proximity to urban areas. Specifi c research on the 

expected human infl uences on forest management and 

valuation in urban as well as rural environments helps us 

understand the special values of forests near urban areas 

(Butler et al. 2010, Nowak et al. 2010). 

SUMMARY

Th e Northern Forest Futures Project is intended to 

provide a view of what the region’s forests are today 

and what they might become over the next 50 years. 

Comprising three components—scoping, assessment, 

and projection—the project uses projections of future 

economic, demographic, technological, and climate 

scenarios to produce future scenarios of forest land 

cover, composition, and structure. Th ese future scenarios 

provide a quantitative basis from which to examine 

future forest threats, biodiversity characteristics, biomass 

production and utilization, ecosystem services, and 

landowner attitudes and infl uences. Th e project has 

already completed the issue identifi cation or scoping 

phase (Dietzman et al. 2011) and the initial assessment 

(Shifl ey et al. 2012). Collaborating scientists are now 

completing the projection phase and expect to produce 

an assessment of alternative future northern forest 

conditions within the next year. Th e Northern Forest 

Futures Project can help refi ne expectations about future 

forest conditions and assist policy makers and forest 

managers in defi ning future priorities.
52 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

ACKNOWLEDGMENTS

Th e authors thank Dave Wear, Bobby Huggett, and 

Ruhong Li, Southern Research Station, for their work in 

developing the USFAS model and projecting Northern 

Forest Futures Project data; Pat Miles of Northern 

Research Station FIA for translating the results of the 

USFAS model into FIA database format; the Forest 

Service’s Region 9, the Northern Research Station, and 

Northeastern Area State and Private Forestry for fi nancial 

and other support; and the many collaborators who 

made this project possible. Th e authors especially thank 

Dave Bengston for inviting us to present our paper at the 

ISSRM meeting in Madison, Wisconsin, in 2011.

LITERATURE CITED

Butler, B.J.; Miles, P.D.; Hansen, M.H. 2010. National 

Woodland Owner Survey table maker [Web 

application]. Version 1.0. Newtown Square, PA: U.S. 

Department of Agriculture, Forest Service, Northern 

Research Station. http://fi atools.fs.fed.us/NWOS/

tablemaker.jsp. (27 July 2011).

Canadian Centre for Climate Modelling and Analysis. 

2012a. CGCM3.1 - Coupled Global Climate Model 

(CGCM3), Medium Resolution (T47). http://www.

cccma.bc.ec.gc.ca/models/cgcm3.shtml

Canadian Centre for Climate Modelling and Analysis. 

2012b. CGCM2 - Coupled Global Climate Model, 

Medium Resolution (T47). http://www.cccma.bc.ec.

gc.ca/models/cgcm2.shtml

Dietzman, D.; LaJeunesse, K.; Wormstead, S. 2011. 

Northern Forest Futures Project: scoping of issues 

in the forests of the Northeast and Midwest of 

the United States. Version 3.0. Newtown Square, 

PA: U.S. Department of Agriculture, Forest Service, 

Northern Research Station. 42 p.

Greenberg, C.H.; Collins, B.S.; Th ompson, F.R. III. 

2011. Sustaining young forest communities: 

ecology and management of early successional 

habitats in the Central Hardwood region, USA.

New York: Springer 318 p.

Homer, C.; Huang, C.; Yang, L.; Wylie, B.; Coan, M. 

2004. Development of a 2001 national land-cover 

database for the United States. Photogrammetric 

Engineering and Remote Sensing. 70(7): 829-840. 

Data from Multi-resolution Land Characteristics 

Consortium. www.mrlc.gov. (14 August 2008).

Huggett, R.; Wear, D.N., et al. In press. Forest 

forecasts. In: Wear, D.N.; Greis, J.G., eds. Th e 

Southern Forest Futures Project: technical report. 

Gen. Tech. Rep. SRS-XXX. Asheville, NC: U.S. 

Department of Agriculture, Forest Service, Southern 

Research Station. xxx p.

Ince, P.J.; Kramp, A.D.; Skog, K.E.; Spelter, H.N.; 

Wear, D.N. 2011a. U.S. forest products module : a 

technical document supporting the Forest Service 

2010 RPA Assessment. Res. Pap. FPL-RP-662. 

Madison, WI : U.S. Department of Agriculture, 

Forest Service, Forest Products Laboratory. 61 p.

Ince, P.J.; Kramp, A.D.; Skog, K.E.; Yoo, D.; Sample, 

V.A. 2011b. Modeling future U.S. forest sector 

market and trade impacts of expansion in wood 

energy consumption. Journal of Forest Economics. 

17(2): 142-156.

IPCC Intergovernmental Panel on Climate Change. 

2007. Climate Change 2007: synthesis report. 

Contribution of Working Groups I, II, and III to the 

Fourth Assessment Report of the Intergovernmental 

Panel on Climate Change [Core Writing Team, 

Pachauri, R.K and Reisinger, A. (eds.)]. IPCC, 

Geneva, Switzerland, 104 p.

Miles, P.D. 2012. Forest Inventory EVALIDator 

web-application version 1.5.00. St. Paul, MN: U.S. 

Department of Agriculture, Forest Service, Northern 

Research Station. [Available only on internet: http://

apps.fs.fed.us/Evalidator/tmattribute.jsp]. (12 March 

2012).

Nakicenovic, N. et al. 2000. Special report on 

emissions scenarios: a special report of Working 

Group III of the Intergovernmental Panel on 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 53

Climate Change.Cambridge, UK: Cambridge 

University Press. 599 p. Available online at: http://

www.grida.no/climate/ipcc/emission/index.htm.

Nowacki, G.J.; Abrams M.D. 2008. Demise of fi re and 

mesophication of eastern U.S. forests. BioScience. 

58: 123-138.

Nowak, D.J.; Walton, J.T. 2005. Projected urban 

growth (2000-2050) and its estimated impact 

on the U.S. forest resource. Journal of Forestry. 

103(08): 383-389.

Nowak, D.J.; Walton, J.T.; Dwyer, J.F.; Kaya, L.G.; 

Myeong, S. 2005. Th e increasing infl uence of urban 

environments on U.S. forest management. Journal 

of Forestry. 103(8): 377-382.

Nowak, D.J.; Stein, S.M.; Randler, P.B.; Greenfi eld, 

E.J.; Comas, S.J.; Carr, M.A.; Alig, R.J. 2010. 

Sustaining America’s urban trees and forests: 

a Forests on the Edge report. Gen. Tech. Rep. 

NRS-62. Newtown Square, PA: U.S. Department 

of Agriculture, Forest Service, Northern Research 

Station. 27 p.

Oak Ridge National Laboratory. 2011. U.S. billionton update: biomass supply for a bioenergy and 

bioproducts industry. Oak Ridge, TN. 194 p.

Perlack, R.D.; Wright, L.L.; Turhollow, A.; Graham, 

R.L.; Stokes, B.; Erbach, D.C. 2005.Biomass 

as feedstock for a bioenergy and bioproducts 

industry: the technical feasibility of a billion-ton 

annual supply. DOE/GO-102995-2135 or ORNL/

TM- 2005/66. Oak Ridge, TN: Oak Ridge National 

Laboratory. 60 p.

Polyakov, M.; Wear, D.N. 2010. Harvest choice and 

timber supply models for forest forecasting. Forest 

Science. 56(4):344-355.

Shifl ey, S.R.; Aguilar, F.X.; Song, N.; Stewart, S.I.; 

Nowak, D.J.; Gormanson, D.D.; Moser, W.K.; 

Wormstead, S.; Greenfi eld, E.J. 2012. Forests 

of the northern United States. Gen. Tech. Rep. 

NRS-90. Newtown Square, PA: U.S. Department 

of Agriculture, Forest Service, Northern Research 

Station. 202 p.

Smith, W.B.; Miles, P.D.; Perry, C.H.; Pugh, S.A. 

2009. Forest resources of the United States, 2007.

Gen. Tech. Rep. WO-78. Washington, DC: U.S. 

Department of Agriculture, Forest Service. 336 p.

Tirpak, J.M.; Jones-Farrand, D.T.; Th ompson, F.R., III; 

Twedt D.J. 2009. Multi-scale habitat suitability 

index models for priority landbirds in the Central 

Hardwoods and West Gulf Coastal Plain/Ouachitas 

bird conservation regions. Gen. Tech. Rep. NRS49. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northern Research 

Station. 195 p.

U.S. Census Bureau. 2012. Population estimates.

Washington, DC: U.S. Department of Commerce. 

http://www.census.gov/popest/estimates.html. (23 

May 2012).

U.S. Department of Agriculture, Forest Service. 2011a. 

National report on sustainable forests – 2010.

FS-979. Washington, DC: U.S. Department of 

Agriculture, Forest Service. 212 p. http://www.fs.fed.

us/research/sustain/2010SustainabilityReport/. (11 

June 2011).

U.S. Department of Agriculture, Forest Service. 2011b. 

Northern Forest Futures Project - Issues and 

Infl uences. Newtown Square, PA: Northern Research 

Station. http://nrs.fs.fed.us/futures/issues_infl uences/ 

(20 March 2012).

U.S. Department of Agriculture, Forest Service. 2012a. 

Future scenarios: a technical document supporting 

the Forest Service 2010 RPA Assessment.   Gen. 

Tech. Rep. RMRS-GTR-272. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station. 34 p.

U.S. Department of Agriculture, Forest Service. 2012b. 

Research & Development - RPA Assessment.

Washington, DC: U.S. Department of Agriculture, 
54 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Forest Service. http://www.fs.fed.us/research/rpa/ (13 

March 2012).

U.S. Department of Agriculture, Forest Service. 2012c. 

Southern Forest Futures Project. Washington, 

DC: U.S. Department of Agriculture, Forest Service. 

http://www.srs.fs.usda.gov/futures/ (13 March 2012).

U.S. Department of Agriculture, Forest Service. 2012d. 

Gypsy moth digest—maps and charts. Washington, 

DC: U.S. Department of Agriculture, Forest Service. 

http://www.na.fs.fed.us/fhp/gm/maps_charts/index.

shtml (22 May 2012).

U.S. Department of Agriculture, Forest Service; 

Northeastern Area Association of State Foresters. 

2011. 2010 Statewide forest resource assessments 

and strategies in the Northeast and Midwest: 

a regional summary. Newtown Square, PA: 

U.S. Department of Agriculture, Forest Service, 

Northeastern Area State and Private Forestry. 

51 p. http://www.forestactionplans.org/regions/

northeastern-region (12 August 2011).

Wear, D.N. 2011. Forecasts of county-level land 

uses under three future scenarios: a technical 

document supporting the Forest Service 2010 RPA 

Assessment. Gen. Tech. Rep. SRS-141. Asheville, 

NC: U.S. Department of Agriculture, Forest Service, 

Southern Research Station. 41 p.

Wear, D.N.; Greis, J.G. eds. In press. Th e Southern 

Forest Futures Project: technical report. Gen. Tech. 

Rep. SRS-XXX. Asheville, NC: U.S. Department 

of Agriculture, Forest Service, Southern Research 

Station. xxx p.

Wear, D.N.; Huggett, R.; Li, R.; Perryman, B.; Liu, S. 

In press. Forecasts of forest conditions in regions 

of the United States under future scenarios: a 

technical document supporting the Forest Service 

2010 RPA Assessment. Gen. Tech. Rep. SRS-xxx. 

Asheville, NC: U.S. Department of Agriculture Forest 

Service, Southern Research Station. xx p.

Williams, M. 1989. Americans and their forests.

Cambridge, UK: Cambridge University Press. 599 p.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 55

LINKING GLOBAL SCENARIOS TO NATIONAL ASSESSMENTS: 

EXPERIENCES FROM THE RESOURCES PLANNING ACT (RPA) ASSESSMENT

Linda L. Langner and Peter J. Ince 

Th e 2010 RPA Assessment framework was designed to:

• incorporate global interactions that aff ect 

domestic resource conditions and trends;

• improve analyses of interactions among resources;

• extend our analytical capability to evaluate the 

potential eff ects of climate change across the 

resources; and 

• describe more clearly the complexity and 

uncertainty associated with projecting future 

conditions and trends.

Global conditions and trends increasingly aff ect the 

conditions and trends in domestic natural resources. Th e 

2010 RPA Assessment is framed around a set of future 

scenarios tied to a global set of scenarios that provide a 

coherent interdependent future for global population 

dynamics, socioeconomic factors, and climate change 

for more than 50 years into the future. Th ese scenarios 

provided both quantitative and qualitative connections 

for the domestic resource analyses that project resource 

conditions and trends.

Using global scenarios to frame the 2010 analyses 

provided a coherent framework for evaluating outcomes 

across resource analyses. Socioeconomic and climate 

variables were all linked through these global scenarios. 

Scenarios were not assigned likelihoods, nor were 

any scenarios intended to be “most accurate” per se. 

Rather, these constructed scenarios provide a means 

of qualitatively and quantitatively understanding how 

diff erent socioeconomic processes interacted to create 

diff erent possible greenhouse gas (GHG) emissions 

pathways, how these emissions pathways drove global 

climate models to project diff erent potential future 

climates, and how natural resources would respond to 

alternative futures. Each link in this chain of models is 

subject to uncertainty from a number of sources ranging 

from deliberate modeling assumptions (e.g., the global 

population growth rate selected for a given scenario), to 

stochastic processes in the global climate, economic, and 

Abstract. Th e Resources Planning Act (RPA) Assessment 

provides a nationally consistent analysis of the status 

and trends of the Nation’s renewable forest resources. A 

global scenario approach was taken for the 2010 RPA 

Assessment to provide a shared world view of potential 

futures. Th e RPA Assessment scenarios were linked to the 

global scenarios and climate projections used in the Th ird 

and Fourth Intergovernmental Panel on Climate Change 

Assessments to recognize the infl uence of global forces 

on domestic resource conditions and trends. Th is paper 

reviews the challenges encountered, approaches taken to 

address these challenges, and the lessons learned.

INTRODUCTION

Th e Forest and Rangeland Renewable Resources 

Planning Act of 1974 (RPA) (P.L. 93-378, 88 Stat. 

475, as amended) mandates a periodic assessment of 

the condition and trends of the Nation’s renewable 

resources on forests and rangelands. Known as the 

RPA Assessment, it provides a snapshot of current 

U.S. forest and rangeland conditions and trends on all 

ownerships, identifi es drivers of change, and projects 

50 years into the future. A team of U.S. Forest Service 

(USFS) scientists and their cooperators analyzes trends in 

outdoor recreation, fi sh and wildlife, biological diversity, 

wilderness, forests, range, water, urban forests, landscape 

patterns, and the potential eff ects of climate change on 

these resources.

FRAMEWORK FOR THE 2010 RPA 

ASSESSMENT

Th e framing of the RPA Assessment has evolved over 

time to respond to changes in natural resource issues and 

management. Th e original legislation focused primarily 

on an economic evaluation of whether resource supplies 

could meet consumer demand. As public expectations 

about the role of natural resources broadened to include 

both ecological and socioeconomic values, the RPA 

Assessment analyses also broadened in recognition of the 

interrelationships between ecological and socioeconomic 

conditions in meeting the needs of the American public.
56 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

biological systems themselves. Th e scenarios help explore 

a consistent range of possible futures across resource 

analyses rather than intending to predict future resource 

conditions. Figure 1 presents a schematic that illustrates 

how global scenarios were linked to U.S. data that feed 

the various resource analyses.

SCENARIO APPROACH IN THE 2010 RPA 

ASSESSMENT

Scenarios are used to explore alternative futures and 

are intended to serve as a counterfactual framework for 

objectively evaluating a plausible range of future resource 

outcomes. Th is approach is particularly useful when 

there is considerable uncertainty about the trajectory 

of the driving forces behind political, economic, 

social, and ecological changes (Alcamo et al. 2003, 

Intergovernmental Panel on Climate Change [IPCC] 

2007). Scenario methods can use both qualitative 

and quantitative approaches in visualizing alternative 

futures using diff erent socioeconomic or institutional 

assumptions for the United States. Carpenter et al. 

(2005) and Nakicenovic et al. (2000) reviewed examples 

and uses of scenarios in other applications.

Th e challenge of incorporating global interactions into 

the 2010 RPA Assessment led to the search for a set of 

comprehensive global scenarios to serve as anchors for 

the RPA Assessment analyses. Th ese scenarios would 

provide the global context and quantitative linkages 

between national and global trends. We identifi ed several 

criteria for evaluating and selecting global scenarios:

• Scenarios must be globally consistent in their 

underlying assumptions.

• Scenarios must be from a source that is 

scientifi cally credible and well-documented.

• Scenarios must include assumptions about key 

driving forces of resource change:

 Population and economic growth

 Land use change

 Climate change

 Energy use

• Globally consistent data must be available to 

link to U.S.-scale analyses.

A number of scenario-based approaches were reviewed 

as potential anchors for the 2010 RPA Assessment, 

including the Millennium Ecosystem Assessment 

Examples of Projected Ecosystem Services/Responses

Global IPCC Scenarios

Socioeconomic

Bioenergy

Climate

US Scenarios

Basic Assumptions

Updated & 

Downscaled

Forest

ͻtŽŽĚMarkets

ͻĂƌďŽŶ

Sequestration

Range

ͻForage Supply

ͻŽŶĚŝƚŝŽŶ

Urban Forests

ͻTree Cover

ͻĂƌďŽŶ

ͻĂŶŽƉLJŚĂŶŐĞ

Water

ͻhƐĞƐ

 Supply

ͻsƵůŶĞƌĂďŝůŝƚLJ

Wildlife

ͻůŝŵĂƚĞ^ƚƌĞƐƐ

ͻŝƌĚŝǀĞƌƐŝƚLJ

Recreation

ͻWĂƌƚŝĐŝƉĂƚŝŽŶ

ͻAmenity

Migration

Landscape 

Pattern

ͻ&ƌĂŐŵĞŶƚĂƚŝŽŶ

ͻMosaics 

Data

Resource Modeling Systems

Forest Assessment

Range Assessment

tĂƚĞƌƐƐĞƐƐŵĞŶƚ

tŝůĚůŝĨĞƐƐĞƐƐŵĞŶƚ

Recreation Assessment

Landscape Pattern

Urban Forest 

Assessment

Macroeconomic

ĞŵŽŐƌĂƉŚŝĐ

Climate

Land Use

Figure 1.— RPA Assessment scenario analysis and modeling systems.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 57

(Alcamo et al. 2003, Carpenter et al. 2005), the IPCC 

(Nakicenovic et al. 2000), the “Mapping the Global 

Future” project (National Intelligence Council 2004), 

and the United Nations Environmental Program’s Global 

Environmental Outlook (United Nations Environmental 

Program 2002, 2007). Although these studies exhibited 

wide variations in approach and objectives, all focused on 

a similar set of driving forces that shape the global future.

Scenarios used in both the IPCC third and fourth 

Assessment Reports (known as TAR and AR4, 

respectively) were selected to provide the global scenarios 

for the 2010 RPA Assessment. Th e Special Report on 

Emissions Scenarios from the TAR (Nakicenovic et 

al. 2000) provides detailed documentation of these 

scenarios that were used in both the TAR and AR4. 

Th e advantage of using IPCC scenarios as the basis for 

the 2010 RPA Assessment was the level of scientifi c 

rigor and acceptance surrounding their development, 

the degree of documentation, and the facilitated access 

to the data. Th e availability of both socioeconomic and 

climate data at global, regional, and country scales was 

also a critical decision factor. Th e range of scenarios 

considered in the IPCC Assessments provided a broad 

spectrum of potential futures from which a subset of the 

most relevant to evaluating potential U.S. future resource 

conditions and trends could be selected. In addition to 

their focus on climate change, the IPCC scenarios also 

incorporated detailed analyses of global energy trends, 

featuring alternative levels of growth in renewable 

energy and biomass energy production in the context of 

anticipated peaking of global petroleum production in 

the decades ahead.

None of the IPCC scenarios was considered to be the 

“most likely” or “business as usual” future. Th e IPCC 

deliberately avoided judging the likelihood of future 

scenarios. Although covering a wide range of alternative 

futures, the scenarios also deliberately excluded global 

disaster scenarios. Scenarios simply provide a tool to 

explore a range of future outcomes without judgment 

about the desirability of the outcomes (Nakicenovic et al. 

2000).

Selecting the Scenarios for the 2010 RPA 

Assessment

Th e variation across the IPCC scenarios in projections 

of world population, U.S. population, world and 

U.S. GDP, energy futures, and climate was evaluated. 

Th ere was no pre-determined test of what constitutes 

“suffi cient” variation in any of the variables, so the basic 

test was whether a subset of the IPCC scenarios would 

cover the range of possibilities that were likely to drive 

the greatest variation in resource eff ects in the United 

States. Th ree IPCC scenarios were chosen as the basis 

for the RPA scenarios. We retained the IPCC labels for 

continuity: A1B, A2, and B2. Table 1 lists some of the 

key characteristics of the IPCC scenarios chosen to be the 

basis for developing national scenarios for the 2010 RPA 

Assessment.

Table 1.—Key characteristics of IPCC scenarios used to develop the RPA scenariosa

Characteristics Scenario A1B Scenario A2 Scenario B2

General global description Globalization, 

economic convergence

Regionalism, 

less trade

Slow change, 

localized solutions

Global real GDP growth (2010-

2060) 

High (6.2X) Low (3.2X) Medium (3.5X)

Global population growth 

(2010-2060) 

Medium (1.3X) High (1.7X) Medium (1.4X)

U.S. GDP growth 

(2006-2060) 

High (3.3X) Low (2.6X) Low (2.2X)

U.S. population growth (2006-

2060) 

Medium (1.5X) High (1.7X) Low (1.3X)

Global expansion of primary 

biomass energy production 

High Medium Medium

a Numbers in parentheses (e.g., 6.2X) are the factors of change in the projection period. For example, 

global GDP increases by a factor of 6.2 times between 2010 and 2060 for scenario A1B.
58 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Each IPCC scenario had multiple associated climate 

projections. Th e climate projections vary across scenarios 

in response to the associated levels of energy production 

and GHG emissions, but they also vary within a scenario 

because the general circulation models (GCM) diff er 

in their approaches to modeling climate dynamics. 

Th erefore, we selected three GCMs for each of the three 

scenarios in order to capture a range of future climates.

Scaling and Updating IPCC Data to U.S. 

and Sub-national Scales

Th e IPCC scenarios in combination with the climate 

projections from the GCMs provided the global 

demographic, macroeconomic, and climate assumptions 

for the various component resource analyses in the 2010 

RPA Assessment. Th e next step was to develop national 

and sub-national projections of population, GDP, 

income, bioenergy use, and climate for the United States 

that are linked to the IPCC projections.

Th e IPCC scenario-based projections provided largescale data, primarily at the global and macro-region scale. 

Country-level data for projections of population and 

GDP were also available. Th e IPCC projections of U.S. 

population and GDP were updated with more recent 

U.S. data. In doing so, the trends and cross-scenario 

relationships of IPCC scenarios were maintained. Th e 

updated estimates were then disaggregated to obtain U.S. 

county-level income and population data for the RPA 

scenarios.

Projecting U.S. population and economic information 

at the county level involved a number of simplifying 

assumptions. Accounting for all the various state and 

local events that govern the change and development 

of towns and counties is impossible. As a result, the 

RPA county-level projections should not be taken as 

statistically reliable projections of possible economic or 

demographic futures for specifi c counties. Rather, the 

overall spatial pattern of change in response to alternative 

scenarios is more important in our analyses, displaying 

the heterogeneity that would not be evident if projections 

were made only at the RPA regional or national levels.

U.S. Population Projections

Th e U.S. population projection for the IPCC A1B 

scenario was based on the 1990 Census. We updated 

the RPA A1B population projections to align with the 

2004 Census population series for 2000-2050 (U.S. 

Department of Commerce, Bureau of the Census 

2004), with an extrapolation to 2060. Th e population 

projections for A2 and B2 were updated to begin at 

the same starting point in year 2000, and then follow a 

projection path that maintained the same proportional 

relationship to A1B as in the IPCC projections. Table 

2 shows the IPCC U.S. population projections and 

the updated U.S. population projections for the 2010 

RPA Assessment. Figure 2 illustrates the population 

projections for the three RPA scenarios relative to 

historical population trends in the United States. 

County-level population projections were developed for 

the three RPA scenarios (Zarnoch et al. 2010).

Table 2.—IPCC U.S. population projections and updated RPA U.S. population projections, 

2000-2060 (millions of people)

2000 2010 2020 2030 2040 2050 2060

IPCC 

A1B 277 300 324 347 367 383 396

A2 278 306 334 363 390 417 447

B2 278 299 322 337 343 348 351

RPA

A1 B 282 309 336 364 392 420 447

A2 282 315 346 380 416 457 505

B2 282 308 334 353 366 381 397
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 59

U.S. Economic Projections

Macroeconomic trends (e.g., trends in GDP, disposable 

personal income, and labor productivity) have a critical 

infl uence on the supply of and demand for renewable 

resources. Th e IPCC data were based on economic data 

from the early 1990s, so the GDP projections were 

updated to start with the offi cial U.S. GDP value for 

2006 for all three RPA scenarios (U.S. Department of 

Commerce, Bureau of Economic Analysis 2008a).

We applied GDP growth rates (U.S. Department 

of Agriculture, Forest Service 2012) to develop an 

adjusted projection of GDP for the A1B scenario. We 

revised the A2 and B2 GDP projections to maintain 

the same proportional relationship between the three 

RPA scenarios as defi ned by the IPCC U.S. GDP 

projections. Table 3 shows the diff erences between the 

IPCC projections for U.S. GDP and the updated RPA 

GDP fi gures. Figure 3 shows the diff erences among the 

three RPA scenario projections for updated GDP in 

comparison to historical U.S. GDP.

Projections of personal income and disposable personal 

income were also developed for RPA scenarios. Th e 

offi cial U.S. 2006 statistics for personal income (PI) 

and disposable personal income (DPI) were used to 

start the updated projection for the A1B scenario (U.S. 

Department of Commerce, Bureau of Economic Analysis 

2008b). We calculated the A2 and B2 projections for PI 

and DPI to maintain the same proportional relationship 

across RPA scenarios that were used in calculating the 

trajectories for U.S. GDP. Th e national DPI and PI 

projections were disaggregated to the county level (U.S. 

Department of Agriculture, Forest Service 2012).

Figure 2.—Historic U.S. population and projected U.S. 

population to 2060 by RPA scenario.

0

100

200

300

400

500

600

196019651970197519801985199019952000200520102015202020252030203520402045205020552060

Historic

RPA A1B

RPA A2

RPA B2

 Million people 

Table 3.—IPCC U.S. GDP projections and updated RPA U.S. GDP projections, 2000-2060 (billion 2006 USD)

2000 2010 2020 2030 2040 2050 2060

IPCC-U.S GDP

A1B 10,654 13,456 16,888 21,093 26,112 31,117 38,524

A2 10,282 12,484 14,986 18,061 21,436 24,825 30,330

B2 11,297 14,586 17,017 18,905 21,193 23,466 25,640

RPA – U.S. GDP

A1B 13,195 14,736 19,029 23,424 28,835 35,496 43,696

A2 13,195 13,679 16,890 20,057 23,683 28,313 34,401

B2 13,195 15,974 19,164 20,990 23,416 26,778 29,084

0

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000

45,000

50,000

196019651970197519801985199019952000200520102015202020252030203520402045205020552060

Historic

RPA A1B

RPA A2

RPA B2

 Billion dollars 

Figure 3.—Historic U.S. GDP and projected U.S. GDP to 2060 

by RPA scenario.
60 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Population, GDP, and income are important variables in 

determining GHG emissions levels. Although the U.S. 

population accounts for a small proportion of the world 

population, the U.S. contribution to emissions is much 

higher than its percentage of world population because of 

relatively high energy consumption. Th erefore, updating 

the U.S. population and GDP projections (raising them 

modestly as we did) could lead to slightly higher global 

emissions than projected in the IPCC scenarios, or 

could lead to higher energy effi ciency that would off set 

emissions. Regardless, we considered re-aligning the 

IPCC U.S.-level economic and population data with 

more recent data to be critical for projecting national 

resource eff ects within the RPA resource modeling 

systems. By not adjusting GHG emissions we have 

implicitly adopted the same variations in climate change 

across scenarios as projected by IPCC.

It can be noted also that the original IPCC emissions 

scenarios and the adjusted U.S. projections for the 2010 

RPA scenarios were completed before the 2008-2009 

global economic downturn. We chose 2006 as the base 

year for the U.S. economic variables because they were 

the most recent data available when the RPA scenarios 

were constructed. Th e U.S. GDP projection trend line 

from 2006 to 2010 does not account for the downturn 

in GDP and other economic variables through 2010, 

creating some discontinuity in the early years of the 

projection period. However, RPA long-term projections 

are not intended to predict temporary ups and downs, 

meaning that recessions are not part of projected 50-year 

trends. Th e recent global recession was quite severe, but 

the scenarios included in this Assessment have varying 

rates of economic growth, both for the United States and 

globally, that provide a robust set of projections across 

the range of potential futures.1

U.S. Bioenergy Projections

Assumptions about the role of biomass in bioenergy 

projections were linked to the IPCC scenarios as was 

done with other RPA Assessment assumptions discussed 

in this document. Th e assumptions for bioenergy 

projections were incorporated into the RPA Forest 

Assessment Modeling System that includes the Global 

Forest Products Model (GFPM) and the U.S. Forest 

Products Module (USFPM). Th e approach accounted for 

relevant regional land use projections as well as regional 

biomass energy projections provided by IPCC scenarios 

and their supporting database (Nakicenovic et al. 2000). 

For a detailed explanation of the RPA Assessment 

bioenergy assumptions, see Ince et al. (2011).

In all three RPA scenarios, expansion of biomass energy 

plantation area projected in the IPCC macro-regions was 

directly correlated with projected regional expansion in 

primary biomass energy production. Comparing across 

scenarios, A1B had the largest regional expansion in 

the area of biomass energy plantations and also biomass 

energy production, while expansions of biomass energy 

plantation area and biomass energy production were 

both smaller in the A2 and B2 scenarios.

Because the United States maintains a large share 

of global GDP in all three scenarios and energy 

consumption is correlated with GDP, and because 

biomass energy replaces the declining output of 

petroleum-based energy, the U.S. projections of 

expansion in wood energy consumption are prodigious 

in all RPA scenarios. Th e expansion is by far the highest 

in the A1B scenario, followed by the A2 scenario, and 

lowest in the B2 scenario (Fig. 4). In the A1B scenario, 

for example, U.S. wood fuel feedstock consumption 

climbs to levels that dwarf U.S. consumption of wood for 

all other end uses (about fi ve times higher by 2060 than 

all other wood uses), while in the B2 scenario U.S. wood 

fuel feedstock consumption climbs to a level just slightly 

higher than all other commercial uses.

U.S. Land-Use Projections

Land-use change analyses provide a critical link to other 

models that analyze resource changes, such as wildlife 

habitat and timber availability. Th e IPCC provided 

1 In fact, two of the scenarios (B2 and A2) have lower U.S. 

GDP growth over the next 50 years than projected by a 

lognormal regression equation based on historical U.S. GDP 

growth data through 2010 (taking into account the eff ects of 

the recent recession), and the GDP growth of the A1B scenario 

closely matches the 50-year projection of the lognormal 

equation, indicating that the RPA GDP growth assumptions 

are at least as low as or lower than would be expected based 

on a time series regression analysis of historical GDP growth 

through 2010.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 61

global land-use projections by macro region that we used 

to deduce global wood energy consumption by region, but 

separate RPA land-use area projections were developed 

that were not tied to the IPCC land-use projections. 

However, the U.S. land-use projections are indirectly 

linked to the IPCC projections because the RPA land-use 

model includes both population and income variables 

that came from the county-level population and income 

projections described earlier. Th e land-use projections are 

documented in more detail in Wear (2011).

U.S. Climate Projections

We selected AR4 climate model projections for 

A1B and A2 from the PCMDI Climate Model 

Intercomparison Project 3 (CMIP3) Web site, and the 

TAR climate model projections for B2 from the IPCC 

Date Distribution Centre (DDC). Th ree GCMs were 

chosen for each scenario based on the availability of the 

projections in the CMIP3 database at the time this study 

started and the variables needed for the RPA Assessment 

and assessments being done in Canada (Price et al. 

2011). For the TAR climate models, a suite of climate 

models projecting the B2 scenario had been downscaled 

using the same procedure used for the 2010 RPA 

Assessment, and had been used to assess the impact of 

climate eff ects on vegetation (Price et al. 2004). Hence, 

these models were selected. Th e projections from this 

suite of GCMs capture a range of future climates.

Th e resolution of GCM projections stored in either the 

IPCC DDC or at the CMIP3 Web site range from 250 

to 600 km on the side of the grid, far coarser than that 

typically used in many impact assessments, including 

the RPA Assessments. Many of the resource analyses in 

the RPA Assessment are conducted at the county level, 

which in turn necessitated climate projection data at 

that spatial scale. Th e IPCC climate projections were 

fi rst downscaled to the approximately 10-km scale, 

and then aggregated to the county scale. More detailed 

documentation of the development of the RPA climate 

scenario-based projections and downscaling process can 

be found in Joyce et al. (in prep).

For the 2010 RPA Assessment projection period, the 

A1B scenario mean represents the warmest and driest 

scenario at the scale of the United States (Fig. 5). Th e A2 

Figure 4.—Projected expansion from 

2006 to 2060 in the volumes of wood 

consumed for energy by RPA scenario, 

including total U.S. wood fuel feedstock 

consumption, U.S. roundwood 

fuelwood consumption, and world 

roundwood fuelwood consumption.

Figure 5.—U.S. temperature and precipitation changes from 

the historical period (1961-1990) to the decade surrounding 

the year 2060 (2055-2064) for scenario means and scenarioGCM combinations.
62 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

scenario becomes the wettest although the precipitation 

changes at the scale of the United States are small at 

2060. Regional diff erences in precipitation projections 

vary greatly (Joyce et al. in prep). Th e B2 scenario 

projects the least warming of these three scenarios. Th e 

individual model projections vary across the individual 

scenario. For example, within the A2 scenario, the 

CGCM model projects the least warming and the 

MIROC model projects the greatest warming within this 

scenario. While the IPCC climate projections extend 

to 2100, the RPA Assessment resource analyses stop at 

2060.

LESSONS LEARNED

Developing a global scenario-based approach for the 

2010 RPA Assessment was a learning process because 

previous RPA assessments had not employed global 

scenarios. Using common scenario assumptions was not 

new for the RPA process, but using assumptions nested 

within global scenarios was a departure from the past. It 

provided a more coherent framework, even though not 

all resource analyses could use all of the variables in the 

common assumptions.

Th e RPA Assessment is not a climate assessment, but 

rather it is a U.S. renewable resource assessment that 

takes global change into account. Th e RPA analyses 

consider climate as one more variable among many 

to consider in evaluating future resource conditions. 

Using the IPCC scenarios as our global anchor raised 

a concern that we would be seen as climate-focused. 

But the rationale for selecting the IPCC scenarios was 

based on the breadth of the variables they used in their 

analyses as well as the availability of the underlying 

data. For example, apart from climate projections, the 

scenarios also incorporate wide variation in wood energy 

projections linked to the IPCC projections of overall 

global energy production by source in the context 

of peaking oil production. As mentioned previously, 

the driving forces of change tend to be very similar in 

large-scale assessments, regardless of the objective of 

the assessment. Other global assessments, for example, 

point similarly toward anticipated large shifts in energy 

production toward expanded renewable energy and 

biomass energy production.

Although the IPCC scenarios provided a good linkage 

for the RPA scenarios, the major downside was the 

“freshness” of the IPCC socioeconomic data. Even 

though considerable work was done to update GCMs 

between the third and fourth IPCC assessments, 

no updates were done to the underlying scenario 

assumptions, so that the population and economic data 

were somewhat dated. As a result, compromises had 

to be made between staying true to the IPCC scenarios 

and updating to more recent data (as we did for U.S. 

GDP and population projections). For the 2010 RPA 

Assessment, updating the U.S. population and economic 

data was considered more important than maintaining 

strict conformity to the IPCC scenarios because 

population growth and economic factors are important 

drivers of resource change.

Developing the data for the United States, especially 

at the sub-national level, was time consuming and 

complex and also required a number of compromises. 

Even at the national level, there are limited sources for 

50-year projections of population and income. At the 

time the projections were developed, the Census Bureau 

population projections stopped at 2050, ten years short 

of the RPA projection period. No comparable offi cial 

U.S. estimate for GDP or other economic variables 

extends 50 years. Disaggregating the data to smaller 

scales is even more fraught with diffi culties, particularly 

with limited resources to undertake complex analyses. 

Climate downscaling also presents myriad challenges—

once an approach is decided upon, it is time consuming 

to conduct the downscaling and subsequently all of the 

associated data quality checks once the downscaling is 

completed. As long-term analyses become more common 

in large-scale assessments, cooperation across agencies 

to develop sets of U.S. scenarios that could be used in a 

variety of analyses would be extremely useful.

Assumptions at the scale of broad global regions (such as 

IPCC “macro” regions) are not always easy to translate 

to corresponding assumptions for a particular country. 

Th e United States is part of an IPCC macro region 

(OECD90) that includes all of the developed countries 

of Europe, plus Japan, Canada, Australia, and New 

Zealand. However, U.S. trends do not always move in 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 63

concert with the OECD90 regional trend. One of the 

most obvious examples is in population—population 

growth is higher in the United States than in most 

developed countries. Another example of the complexity 

of translating IPCC scenarios to the United States was 

the treatment of bioenergy. To be consistent with the 

role of biomass energy in the IPCC scenarios, it was 

necessary to require large increases in U.S. consumption 

of woody biomass that are outside historic patterns of 

wood energy use, but are consistent with the IPCC view 

that petroleum-based energy will peak and be displaced 

in part by renewable energy and biomass energy during 

the projection period.

Regardless of when scenarios are constructed, some 

event is likely to create havoc with the assumptions 

when the project is on a multi-year timeline. Th e global 

recession began in 2007, right after the 2010 RPA 

scenarios and downscaling were completed. By the time 

the seriousness of the downturn was evident in 2009, 

it was not feasible to re-create the scenarios because of 

time and resource constraints. Th e important role of 

the housing sector in the economic downturn was also 

problematic for the RPA Assessment, since dramatic 

impacts on parts of the forest sector (e.g., reduced 

demand for lumber and wood panel products) are 

unlikely to be reversed in the near future.

Communicating the sometimes complex results 

from scenarios is also challenging. Providing a 

range of potential future outcomes is realistic given 

the many uncertainties associated with long-term 

projections. But there is a danger that users will 

conclude the information is of little use because of 

the uncertainty or because the volume of information 

can be overwhelming. Identifying commonalities and 

diff erences across scenario results and the underlying 

causes of variation across results can help users sort 

through these complexities. Presenting the results of the 

2010 RPA Assessment will be another learning process 

as we develop communication strategies for various user 

groups.

SUMMARY

We chose to take a global scenario approach for the 

2010 RPA Assessment to provide a shared world view 

of potential futures. We linked our scenarios to the 

global scenarios A1B, A2, and B2 developed in the 

Th ird and Fourth IPCC Assessments. Th e use of global 

scenarios enriched the RPA analyses, but also created 

many challenges. Large-scale assessments are multi-year 

projects. Th erefore, linking to a set of scenarios for a 

completed assessment tends to create issues about the 

timeliness of the source data, which in turn require 

decisions about updating and otherwise altering the 

source data, and the potential consequences of those 

alterations. Global assumptions and data, even at smaller 

regional scales, are not always easy to translate to national 

assumptions, especially if the regional trend is not 

consistent with the individual country trend.

Large-scale assessments such as the RPA Assessment 

are time- and resource-intensive. Linking to global 

assessments can actually save some time and resources, 

as it is unnecessary to develop those assumptions, and 

provides a starting place for the national assumptions. 

However, cooperation across agencies for development of 

national assumptions would be even more eff ective than 

individual agencies’ developing unique sets of national 

assumptions. As more large-scale, long-term analyses 

are undertaken, this type of cooperation will become 

increasingly important.

LITERATURE CITED

Alcamo, J.; Ash, N.J.; Butler, C.D.; et al. 2003. 

Ecosystems and human well-being: a framework for 

assessment. Washington, DC: Island Press. 245 p.

Carpenter, S.R.; Pingali, P.L.; Bennett, E.M.; Zurek, 

M.B., eds. 2005. Ecosystems and human well-being: 

scenarios, volume 2. Findings of the Scenarios 

Working Group of the Millennium Ecosystem 

Assessment. Washington, DC: Island Press. 560 p.

Ince, P.J.; Kramp, A.D.; Skog, K.E.; Spelter, H.N.; 

Wear, D.N. 2011. U.S. forest products module. 
64 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

A technical document supporting the Forest 

Service 2010 Resources Planning Act Assessment. 

Res. Pap. RP-662. Madison, WI: U.S. Department 

of Agriculture, Forest Service, Forest Products 

Laboratory. 80 p.

Intergovernmental Panel on Climate Change [IPCC]. 

2007. Climate change 2007, the fourth IPCC 

Assessment Report. Available at http://www.ipcc.

ch/publications_and_data/publications_and_data.

shtml#.T_spqZHhdIE. (Accessed 9 July 2012).

Joyce, L.A.; Price, D.T.; Coulson, D.P.; McKenney, 

D.W.; Siltanen, R.M.; Papadopol, P.; Lawrence, K. 

In preparation. Climate change scenarios for the 

United States: a technical document supporting 

the Forest Service 2010 RPA Assessment. Gen. 

Tech. Rep. RMRS--XXX. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station.

Nakicenovic, N.; Alcamo, J; Davis, G. et al. 2000. 

Special report on emissions scenarios: a 

special report of Working Group III of the 

Intergovernmental Panel on Climate Change. 

Cambridge, UK: Cambridge University Press. 599 

p. Available at http://www.grida.no/climate/ipcc/

emission/index.htm (Accessed 9 July 2012).

National Intelligence Council. 2004. Mapping the 

global future: report of the National Intelligence 

Council’s 2020 Project. Available at http://www.dni.

gov/nic/NIC_globaltrend2020.html. (Accessed 9 July 

2012).

Price, D.T.; McKenney, D.W.; Papadopol, P.; Logan, 

T.; Hutchinson, M.F. 2004. High resolution 

future scenario climate data for North America. 

In: Proceedings of the American Meteorological 

Society’s 26th conference on agricultural and forest 

meteorology, 23–26 August 2004, Vancouver, BC. 

Boston, MA: American Meteorological Society: 

7.7.1-7.7.13. Available at https://ams.confex.com/

ams/AFAPURBBIO/techprogram/paper_78202.htm. 

(Accessed 17 July 2012).

Price, D.T.; McKenney, D.W.; Siltanen, R.M.; 

Papadopol, P.; Lawrence, K.; Joyce, L.A.; Coulson, 

D.P. 2011. High resolution interpolation of climate 

scenario change factors for the conterminous USA 

derived from AR4 General Circulation Model 

simulations. Fort Collins, CO: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research 

Station. Available at http://dx.doi.org/10.2737/RDS2011-0023. (Accessed 17 July 2012).

United Nations Environment Program. 2002. Global 

environment outlook 3. London, UK: Earthscan 

Publications Ltd. 460 p.

United Nations Environment Program. 2007. Global 

environment outlook 4. Valletta, Malta: Progress 

Press Ltd. 572 p.

U.S. Department of Agriculture, Forest Service. 2012. 

Future scenarios: a technical document supporting 

the Forest Service 2010 RPA Assessment. Gen. 

Tech. Rep. RMRS-272. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station. 34 p.

U.S. Department of Commerce, Bureau of Economic 

Analysis. 2008a. National and income product 

accounts table 1.15. Gross domestic product. 

Version January 30, 2008.

U.S. Department of Commerce, Bureau of Economic 

Analysis. 2008b. National and income product 

accounts table 2.1. Personal income and its 

disposition. Version January 30, 2008.

U.S. Department of Commerce, Bureau of the Census. 

2004. US interim projections by age, sex, race and 

Hispanic origin. Internet release March 18, 2004. 

Available at http://www.census.gov/population/

www/projections/usinterimproj/natprojtab01a.pdf. 

(Accessed 17 July 2012).

Wear, D.N. 2011. Forecasts of county-level land 

uses under three future scenarios: technical 

document supporting the Forest Service 2010 RPA 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 65

Assessment. Gen. Tech. Rep. SRS-141. Asheville, 

NC: U.S. Department of Agriculture, Forest Service, 

Southern Research Station. 41 p.

Zarnoch, S.J; Cordell, H.K.; Betz, C.J; Langner, L.L. 

2010. Projecting county-level populations under 

three future scenarios: a technical document 

supporting the Forest Service 2010 RPA 

Assessment. e-Gen. Tech. Rep. SRS-128. Asheville, 

NC: U.S. Department of Agriculture, Forest Service, 

Southern Research Station. 8 p. 
66 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

ENVIRONMENTAL FUTURES RESEARCH AT 

THE U.S. ENVIRONMENTAL PROTECTION AGENCY

Robert L. Olson

began to arise. How many of today’s environmental 

problems could have been avoided if environmental 

concerns had been integrated into the decisions of 

business leaders, government offi cials, and citizens from 

that time onward?

Th at opportunity was, of course, missed. Th e 

understanding, political will, and legal mechanisms 

needed for that to happen were not yet in place. Now, 

however, with new technological revolutions beginning 

to unfold, we have another opportunity to properly 

perceive the changes that are underway, integrate 

environmental concerns into our decisionmaking, head 

off potentially serious environmental damages, and 

shape emerging technologies for both economic success 

and the health of the planet. To be successful, one of 

the changes that urgently needs to occur is for the EPA 

to face forward toward the future and devote more 

of its attention to the environmental challenges and 

opportunities posed by emerging technologies.

In a 1995 report, “Beyond the Horizon” (U.S. EPA 

1995), the EPA’s Science Advisory Board issued a call 

for improving the Agency’s capacity for exactly this kind 

of environmental foresight. It challenged the EPA “to 

begin to anticipate future environmental problems, and 

then take steps to avoid them, not just respond to them 

after the fact.” It urged the EPA to change its priorities 

over time so that eventually, “as much attention should 

be given to avoiding future environmental problems as to 

controlling current ones.”

How well has the EPA done in moving in this direction? 

A review of foresight-related eff orts over time in the 

Agency shows that the shift in direction has begun but 

still has a long way to go.

EARLY FORESIGHT EFFORTS

Almost from EPA’s inception, there have been scattered 

and sporadic eff orts within the Agency to explore the use 

of scanning, scenarios, modeling, and visioning exercises 

Abstract. Relatively little research on environmental 

futures has been carried out in the United States. An 

exception is the long-running futures research that 

the U.S. Environmental Protection Agency (EPA) has 

been conducting since the 1970s. Th is paper reviews 

past and current eff orts toward developing a capacity 

for environmental foresight within the EPA, and 

discusses some lessons for other agencies and institutions 

concerned with the future of the environment.

INTRODUCTION

Th e U.S. Environmental Protection Agency (EPA) 

was born in 1970 facing backwards towards the past. 

Its major challenge over the past 40 years has been 

dealing with the damages caused by the revolutions in 

industrial production that occurred earlier in the 19th 

and 20th centuries. Th is job, ranging from the cleanup 

of abandoned waste sites to the regulation of toxic 

chemicals, will still take decades to fi nish.

Today, however, we are at a critical point where 

technical changes even larger than those that produced 

the earlier revolutions in industry are converging. We are 

in the early stages of multiple revolutions in production, 

information and communications, logistics, and the 

interaction of new technologies such as nano- and 

biotechnology. Th ese revolutions could pose a host of new 

environmental problems, but they also off er the possibility 

of creating a more environmentally advanced technological 

infrastructure based on highly effi cient use of energy and 

materials, clean sources of energy, a “greening” of the 

chemical industry, and a new generation of industrial 

technologies in which pollution is viewed as a design 

failure, not an inevitable by-product of production.

Imagine, if you can, what might have happened if a 

powerful and well-organized environmental movement, 

strong environmental legislation, and a well-functioning 

government agency for environmental protection had 

emerged in the period between the 1850s and 1880s 

when science fi rst began to strongly interact with 

technological development and major new industries 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 67

for environmental foresight. Th e best of the early 

initiatives was in 1975 when EPA’s Offi ce of Pesticide 

Programs commissioned the Center for the Study of 

Social Policy at SRI International to prepare a report on 

“Alternative Futures for Environmental Policy Planning: 

1975 - 2000.” In retrospect, this study pioneered 

important new methods and images of the future, but it 

is unclear whether it had any direct impact on policy and 

planning within the pesticides program (U.S. EPA 1975).

Th e largest single foresight initiative was the 

establishment in the early 1990s of a formal Futures 

Studies Unit in the Offi ce of Policy, Planning and 

Evaluation. Innovative EPA programs such as Energy 

Star were born from the groundbreaking work of the 

futures unit. It helped organize greater intergovernmental 

cooperation to promote environmentally advanced 

technologies, and supported the Science Advisory Board’s 

Environmental Futures Committee in producing the 

“Beyond the Horizon” report in 1995. But the futures 

unit was isolated within the Agency, and many of its 

forecasting eff orts produced “bad news” that others inside 

and outside the Agency did not really want to hear. Th e 

Unit’s director, David Rejeski, left EPA for the White 

House Offi ce of Science and Technology Policy, where 

he felt he could have more infl uence, and in 2001, when 

the Bush Administration came in, the entire Offi ce of 

Policy, Planning and Evaluation was eliminated.

Th e “Beyond the Horizon” report gave foresight eff orts 

greater legitimacy within the Agency. During the latter 

part of the 1990s, a variety of foresight projects were 

undertaken by diff erent offi ces within the Agency, 

including the Offi ce of Radiation and Indoor Air, 

the Offi ce of Research and Development, the Offi ce 

of Human Resources, the Offi ce of Emergency and 

Remedial Response, and the Offi ce of International 

Activities (National Advisory Council for Environmental 

Policy and Technology 2002). Although these eff orts 

produced credible results, they were all sharply limited. 

Th ey were “one-shot” activities rather than part of an 

ongoing, systematic foresight process. Th ey occurred in 

isolation from each other, with little sharing of results 

or lessons of experience. Th ey had only minor impacts 

on the senior agency executives’ priorities, and no 

discernable impact on the Agency’s strategic planning.

THE “FUTURES NETWORK” STRATEGY

In September 1999, Anita Street and Michael Brody 

in the Offi ce of the Chief Financial Offi cer (OCFO), 

which coordinates the Agency’s strategic planning 

process, launched an eff ort to create an Agency-wide 

Futures Network. OCFO contacted senior career 

executives in diff erent parts of the Agency and asked 

them to appoint program and regional staff who have 

planning responsibilities or a particular interest in futures 

analysis to work within the Futures Network to promote 

environmental foresight.

Th e success of the eff ort hinged on the Network 

members’ ability to serve as legitimate ambassadors from 

their offi ces to the Network, and from the Network 

back to senior career executives and colleagues within 

their offi ces. Th e hope was that the Network could help 

overcome some of the limits of past eff orts by stimulating 

futures analysis throughout the Agency, promoting 

capacity-building, helping people share information 

across organizational boundaries, and keeping the 

Agency’s senior career executives aware of and involved 

in foresight activities.

After establishing the Futures Network, the OCFO 

team decided that basic training in “building scenarios” 

would be a good way to familiarize Network members 

with futures methods and to lay the foundation for a 

consistent approach to futures analysis. OCFO allied 

with the Offi ce of Research and Development (ORD) 

to sponsor 30 members of the Network for 3 days of 

intensive training provided by the Global Business 

Network, a leader in the fi eld of corporate scenario 

planning. Th e following spring, OCFO organized 

a follow-on 1-day workshop for Network members 

run by the Institute for Alternative Futures (IAF), a 

leader in scenario planning with public and nonprofi t 

organizations.

Th e strategy the OCFO team and IAF developed was 

to use Network members to interview Agency senior 

executives on their assumptions about the future of 

the environment and the Agency’s evolving role in 

environmental protection. Th e goal was to identify topics 

Agency leaders believed worth exploring further through 
68 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

the use of scenarios. Network members used a standard 

form developed by IAF to conduct 34 interviews with 

senior executives representing nine headquarters and 

nine regional offi ces. Th e results of these interviews were 

presented back to senior managers at a Futures session 

preceding the Agency’s Annual Planning Meeting. Many 

participants in this meeting were surprised to fi nd that 

their personal views about the need for extensive change 

in the Agency were more widely shared than they had 

realized.

Following this session, the OCFO, IAF, and a scenario 

team made up of several Futures Network members 

used the views gathered in the interviews to construct 

four scenarios of the period between 2000 and 2020. 

Th e scenarios and the process used to develop them are 

described in detail in Appendix 1. Below is a simplifi ed 

description of the four images of the future.

• Full Speed Ahead

 Global “long boom” – rapid globalization

 Low social cohesion

 Moderate energy prices

 Huge increases in use of energy, materials, 

and water

• A Darker Age

 Stock market crash, lingering recession, 

economic strains worsening as Baby Boomers 

retire

 Sharply rising oil and food prices, poor 

nations hurt worst

 International terrorism

 Polarized politics, growing intolerance, loss 

of community

• Soft Landing

 Economic slowdown in late 2000s, 

continuing into 2020s

 Global oil production reaching peak in 

2010s and slowly declining

 By 2020, growing realization a slowdown is 

inevitable and has a positive side (e.g., forces 

effi ciency and reduces pollution)

 Painful adjustments but growing social 

cohesion and community

• Eco-Effi ciency Revolution

 During 2010s, “mini-crises” and rising 

energy costs changing the character of 

economic growth

 Rapid innovation in effi cient energy, 

resource, and water use

 Rapid development of energy sources such as 

wind, solar, batteries, hydrogen

 “Greening” of the private sector

 Advanced green technology applications of 

bio- and nanotechnology

In conjunction with a meeting of the Agency’s 

Reinvention Action Council, EPA senior career 

executives met to engage in a “strategic conversation” 

based on these scenarios (Olson and Street 2002). Th e 

primary goal of the meeting was to encourage an open, 

honest exchange of ideas and opinions about possible 

future scenarios and to examine the Agency’s current 

directions in the light of these potential futures. No 

budgets were at stake, and no decisions were needed. 

Th e whole point was to set aside pressing business and 

talk together about issues and aspirations that may be 

important over the generation ahead.

To prepare for the meeting, each participant was asked 

to cast a ballot allocating points (totaling 100) to refl ect 

his or her assessment of the desirability, the likelihood 

of occurrence, and the relative severity of environmental 

impacts of each scenario (Table 1). Th e balloting results 

were reported to the group, which then discussed the 

challenges the Agency may face in the future and changes 

in the Agency’s current directions that may be necessary 

to meet those challenges.

Th e Full Speed Ahead scenario was seen as most likely, 

largely because it came closest to refl ecting current trends 

as well as the underlying assumptions and preferences 

of most leaders in business and government. Many in 

the group were surprised to fi nd, however, that their 

collective assessment was that even though this is an 

appealing scenario in the short run, it is a destructive and 
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 69

negative scenario in the long run, with impacts nearly as 

severe as the gloomiest future, A Darker Age. Th e majority 

clearly favored the Eco-Effi ciency Revolution scenario, and 

the Soft Landing scenario was actually viewed as having 

the lowest environmental impacts. Group members were 

therefore confronted with a disturbing conclusion from 

their own assessment of the scenarios: what they believe 

to be the most likely future, and the future that many 

government policies are geared toward promoting, is very 

diff erent from what they believe is the preferred future 

that they would like to help create.

Th e discussion of how to bridge this gap between the 

scenarios seen as most likely and most preferable revealed 

a wide range of ideas about changes that may be needed 

in EPA’s strategic direction. Some of the potential 

changes discussed by the group are summarized in the 

list below and the associated participant quotations taken 

from the meeting notes.

1) Dispense with day-to-day activities that others 

can do in order to focus EPA attention on 

higher priorities.

“Th e scenarios make you realize that things we do 

today (like permitting) should go to the states, so that 

EPA can elevate its attention to higher priorities.”

2) Take on a stronger role in promoting 

environmental technologies.

“We need to stimulate heavy investment in 

environmental technology now, ‘while things are 

good’.”

3) Increase EPA’s global involvement and 

international leadership.

“We need to achieve greater domestic consensus, 

elevate the Agency’s international leadership . . . and 

help create incentives for the private sector to help 

developing countries adopt environmentally superior 

technologies.”

4) Expand information and outreach activities.

“Connect what we do—EPA’s programs—to people 

. . . Localize global issues for people so they can 

understand and respond.”

5) Emphasize the importance of research for EPA’s 

overall eff ectiveness.

“Th e biggest threat to EPA is our limited ability to 

measure impacts and articulate risks. Unless we can 

do this better, people won’t invest in environmental 

protection.”

6) Coordinate environmental solutions across 

institutions.

“Solutions to environmental problems require more 

coordinated action across government departments. 

EPA should take the lead in defi ning coordination 

needs . . . State and federal roles need to be better 

integrated . . . Make more use of partnerships to 

achieve goals.”

7) Working with Congress, move toward 

multi-media, whole-system approaches to 

environmental protection.

“Establish greater legislative fl exibility for dealing 

with environmental problems.”

At the meeting’s end, one of the participants said, 

“We’ve been meeting for years and this is the fi rst 

time we’ve had a truly strategic conversation.”

LOSS OF MOMENTUM

At this point, with a Futures Network in place and 

senior executives engaged in the process, it looked 

like environmental foresight was on its way to being 

a signifi cantly larger focus of Agency attention. An 

EPA citizen advisory committee reporting to the EPA 

Administrator, the National Advisory Council on 

Environmental Policy and Technology (NACEPT), 

attempted to reinforce this direction of change 

with its 2002 report, “Th e Environmental Future: 

Table 1.—Results of EPA senior executives’ balloting

Scenario Desirability Likelihood Severity

Eco-Efficiency

Revolution

60% 23% 17%

Full Speed

Ahead

6% 45% 32%

Soft Landing 32% 17% 13%

A Darker Age 2% 15% 38%
70 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Emerging Challenges and Opportunities for EPA” 

(NACEPT 2002). Th e report identifi ed a wide range of 

emerging environmental issues and made three major 

recommendations in line with the recommendations the 

Agency’s Science Advisory Board had made 7 years earlier:

1) Create a comprehensive, continuous, and 

institutional futures scanning process to identify 

emerging trends and issues.

2) Support the ongoing work of EPA’s Futures 

Network and provide additional training on 

forecasting methods.

3) Incorporate futures analysis into EPA’s strategic 

planning.

Unfortunately, the Futures Network initiative began 

to lose momentum over the next several years. Several 

factors were at work. Th e largest was the shift from 

the Clinton to the Bush Administration. Th e senior 

executives who worked with the scenarios had rated 

climate change as the top priority issue for EPA, but that 

and several other issues they rated as high priorities were 

not priorities for the new Administration. None of the 

changes they believed would improve the functioning of 

EPA were things the new Administration favored.

In retrospect, it is also clear that the Agency had not set 

itself up well for maintaining the eff ort. No full-time 

staff was responsible for foresight activities. Th e people 

leading the eff ort had other major responsibilities that 

had fi rst call on most of their time. Not enough activity 

was generated for the Futures Network to keep its 

members engaged. And all the normal resistances that 

bureaucracies have to doing foresight came into play.

In 2002, David Rejeski, who had led the EPA Futures 

Studies Unit and was now at the Woodrow Wilson 

International Center for Scholars, and Bob Olson from 

IAF, who was continuing to work with the OCFO group 

in EPA, organized a workshop sponsored by the National 

Aeronautics and Space Administration that brought 

together people from several government agencies who 

had been involved in foresight eff orts to discuss longterm (50-year) goals for society and the challenge of 

stimulating government agencies to think 50 years out 

(Rejeski and Wobig 2002). In a brainstorming and 

electronic voting process, participants highlighted the 

following reasons for resistance to foresight and longterm thinking:

• Lack of political will

• Leadership failure—lack of vision

• Organizational structure

• Fear of controversy or failure

• Annual budget process

• Tyranny of the inbox

• Insuffi cient methodology/training

CONTINUING EFFORTS

Despite the loss of momentum from the peak in 1999-

2000, the Agency, and especially OCFO, has maintained 

a continuous foresight eff ort. OCFO provided contract 

support to help develop a Foresight and Governance 

Project in the Woodrow Wilson International Center 

for Scholars (now called the Science and Technology 

Innovation Program). Th is program went on, with 

major foundation funding, to do some of the best 

work anywhere on environmental and social issues 

around emerging areas like nanotechnology, genomics, 

and systems biology. OCFO supported NACEPT’s 

work in developing its report on “Th e Environmental 

Future: Emerging Challenges and Opportunities for 

EPA.” It also supported a writing project that led to 

a book, “Environmentalism and the Technologies of 

Tomorrow,” that dealt with emerging developments 

in a wide range of areas including energy and resource 

productivity; nanotechnology; genomics; ecological 

sensing and computing; geoengineering; the future 

of manufacturing; and economic, corporate, and 

governance changes for moving toward a sustainable 

society (Olson and Rejeski 2005).

For a time in the mid-2000s, the Agency’s ORD ran a 

regular environmental scan and produced a handbook 

of foresight methods. Although work in OCFO was 

the fi rst to call attention to the importance of emerging 

developments in nanotechnology and genomics, ORD 

coordinated the cross-Agency eff orts involved in creating 

a Nanotechnology White Paper and Genomics White 

Paper that gave those areas much greater visibility.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 71

Toward the end of the decade, the OCFO futures 

team succeeded for the fi rst time in getting a foresight 

component into the revision of the Agency’s strategic 

plan. Th e plan was organized around fi ve long-term 

goals, with a diff erent team of people working on each 

goal. A “futures workshop” was held with each of these 

fi ve goal teams. In the plan revision, each goal section 

had an “Emerging Issues” section that set out the key 

issues that arose in each workshop and in follow-on 

research. Progress in environmental sensor technology 

emerged as an important topic in nearly all these 

workshops, and OCFO and IAF produced a white 

paper on emerging sensor capabilities for widespread 

circulation in the Agency. Publication of the white paper 

led to a fi eld trial with Web-linked real-time nitrate 

sensors and other experiments in the Agency.

Over the past several years, OCFO has sponsored a 

small but ongoing scanning project to identify emerging 

technologies that may pose serious environmental 

problems or could provide new environmental 

solutions. Th e Futures Network (now called the 

Futures Community of Practice) has been called into 

action around a number of topics, such as evaluating 

the importance to the Agency of diff erent emerging 

technologies and issues, and advising the NACEPT 

Council and the Administrator on hiring needs to 

insure that EPA has the competencies it needs to meet 

tomorrow’s challenges. Other initiatives include foresight 

workshops with other agencies, workshops with state 

offi cials, and a foresight competition in which winning 

proposals for foresight projects were off ered small 

amounts of funding or research support.

LESSONS OF EXPERIENCE

Finally, several lessons have emerged from EPA’s 

experience with environmental foresight that may 

be useful for other organizations concerned with 

the environment or with improving their foresight 

capabilities.

 Th e strategy of developing a Futures Network 

that reaches throughout the organization and 

has links to its senior career executives is highly 

worthwhile. It is a strategy that can be pursued in 

other government agencies and institutions.

 Develop some kind of “legitimizing process” 

where high-level people in the organization 

become involved and identifi ed with the eff ort 

without putting many demands on their time. 

Th e Futures Network was one approach, but 

many other approaches are possible.

 Where possible, have a high-level champion or 

champions who will support and protect the 

foresight function over time.

 Avoid becoming an isolated unit; develop ties 

to other parts of the organization; connect to 

decisionmakers as closely as possible and try to 

understand where foresight can meet their needs.

 Frame eff orts around stimulating thoughtful 

conversations and making better decisions today, 

not “knowing the future.”

 Have a dedicated staff and a line-item budget to 

support the foresight function.

 Make an ongoing scanning/early warning system 

an integral activity.

 Utilize at least one formal method that is credible 

and understandable to all involved.

 Whenever possible, present the results of futures 

analysis to relevant decisionmakers in some 

form of interactive session that gives time for 

participants to integrate ideas into their thinking 

in a group setting.

CONCLUSION

Th e record of EPA’s experience with environmental 

foresight shows that real progress has been made toward 

developing a capacity for better environmental foresight. 

However, this progress is still incomplete and fragile 

and could easily be lost. Environmental foresight is 

not yet institutionalized in a way that assures it will 

continue after its strongest current proponents retire. 

Th e Agency is still far from the goal stated in “Beyond 

the Horizon” of giving as much attention to avoiding 

future environmental problems as to controlling current 
72 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

ones. Proponents of environmental foresight in the 

Agency need to work more closely with senior leadership 

to gain their support and appreciation for the value of 

futures thinking, strive to secure suffi cient resources 

for the Agency to seriously engage in futures work, and 

promote the development of a culture of incentives and 

consequences to encourage foresight in planning.

ACKNOWLEDGMENTS

Th e author would like to acknowledge and thank 

Michael Brody (at EPA), Anita Street (formerly at EPA, 

now at the U.S. Department of Energy), and David 

Rejeski (formerly at EPA, now at the Woodrow Wilson 

Center) for their eff orts over many years to help build 

capacity for environmental foresight within EPA. Parts of 

this paper are drawn from an earlier paper written with 

Anita Street and published in 2002 (Olson and Street).

LITERATURE CITED

National Advisory Council for Environmental Policy and 

Technology (NACEPT). 2002. Th e environmental 

future: emerging challenges and opportunities 

for EPA. Washington, DC: U.S. Environmental 

Protection Agency. 71 p.

Olson, B.; Street, A. 2002. Foresight: the U.S. 

Environmental Protection Agency. Scenario & 

Strategy Planning. 3(6): 14-19.

Olson, R.; Rejeski, D., eds. 2005. Environmentalism 

and the technologies of tomorrow: shaping the 

next Industrial Revolution. Washington, DC: Island 

Press. 195 p.

Rejeski, D.;Wobig, C. 2002. Long-term goals for 

governments. Foresight. 4(6): 14-22.

U.S. Environmental Protection Agency. 1975. Alternative 

futures for environmental policy planning: 1975-

2000. Washington, DC: U.S. Environmental 

Protection Agency, Offi ce of Pesticides Programs. 286 p.

U.S. Environmental Protection Agency. 1995. Beyond the 

horizon: using foresight to protect the environmental 

future. Washington, DC: Science Advisory Board. 34 p.

APPENDIX: THE OCFO SCENARIO 

DEVELOPMENT EFFORT

In July 2000, OCFO formed a Scenario Development 

Team, a subgroup of the existing Futures Network. 

OCFO solicited volunteers to conduct research and 

defi ne the axes around which to build the scenarios. 

After carefully considering the issues of concern raised by 

senior managers during interviews, the Team identifi ed 

several topics for further research:

• climate change

• aquifer depletion/water quality 

• urban sprawl (including non-point source 

pollution and biodiversity loss); 

• biotechnology and nanotechnology 

• chemicals in the environment (specifi cally, 

chemicals or sets of chemicals for which 

associations between exposure and eff ects are 

diffi cult to ascertain, and where there may be 

synergistic and cumulative eff ects of low exposures)

• existing persistent environmental problems 

that may surprise EPA as a result of changes in 

societal drivers; for example, an aging population 

may lead to mass migrations, so areas currently 

in compliance might be in violation of national 

air quality standards in the future.

Th e Scenario Development Team thought it important 

to choose a mix of topic areas that included issues that 

are global in scale, issues that were not on EPA’s “radar 

screen,” and some conventional persistent problems that 

are steadily worsening. An issue paper was developed on 

each of these topic areas. Each issue paper included an 

overview describing the general nature of the problem, 

trend data, the range of views on how the problem might 

change between now and 2020, and environmental 

and human health implications. Th e most important 

fi ndings, or “nuggets,” fed into the scenarios.

Th e scenario team then set out to select two axes to serve 

as a framework for building the scenarios. Th e chosen 

axes, economic growth and social cohesion, were selected 

to highlight social dynamics that have a profound eff ect 

on the environment but are often not considered in EPA 

policies and decisionmaking.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 73

To fl esh out the scenarios, the team engaged in 

an exercise using interconnected computers and 

groupware that allowed everyone to brainstorm ideas 

simultaneously and anonymously, and comment on 

each other’s ideas. Th e writers for each of the scenarios 

mined this computer-enhanced brainstorming session 

to add specifi city and realism to the basic scenario plots. 

Each scenario was then written as a three- to fourpage narrative. Th e boxes below capture the scenario 

highlights.

It is important to be clear that these scenarios are 

not predictions. Th ey are simply alternative stories of 

how the future might unfold — stories that compile 

information about divergent trends and potential 

developments into internally consistent images of 

plausible alternative futures. Th e four scenarios are not 

equally likely, although Scenario Development Team 

members believed they are all within the realm of 

plausibility. Th ey were designed to span the full range of 

potential future conditions. Th e actual future is not likely 

to match with any one of these four images, but it will 

probably fall somewhere within the “possibility space” 

that the scenarios explore.

Th e future is inherently uncertain. Scenarios force us to 

face that uncertainty, but they also make the uncertainty 

easier to think about by bounding it within a small 

number of explicit stories. Th is disciplined process 

makes possible a level of strategic thinking, strategic 

conversation, and strategic planning that is more 

sophisticated than activity based only on the momentum 

of business-as-usual or on implicit and unexamined 

assumptions about the future.

Th e economy axis was defi ned in terms of growth or 

decline in the total production and consumption of 

goods and services. Th ese quantities are what Gross 

Domestic Product (GDP) measures in national 

economies and what Gross World Product (GWP) 

measures at the level of the world economy. At one end 

of the economy axis there is high growth in both U.S. 

GDP and GWP. Toward the other end of the axis, 

growth rates slow or even become negative.

Th e social cohesion axis was defi ned in terms of the 

extent of shared values, mutual trust, inclusiveness of 

participation, and willingness to face common challenges 

and cooperate in meeting them. Cohesion also requires 

a shared commitment to fairness, because extreme gaps 

between rich and poor and other forms of social injustice 

undermine mutual trust.

At one end of the social cohesion axis, most individuals, 

communities, and organizations are aligned around 

shared environmental values and committed to the 

importance of environmental protection. Th e diff erent 

actors within society are willing to cooperate with each 

other and support government action to meet widely 

recognized environmental challenges. Toward the other 

end of the axis, society is increasingly fractionalized. 

Many people are indiff erent or hostile to environmental 

values or refuse to recognize the seriousness of 

environmental challenges. Economic inequities, social 

confl icts, and practices that exclude people from 

participation create distrust and limit society’s ability to 

cooperate in meeting challenges.

Th ese two axes intersect to create four quadrants 

representing four possible alternative futures or scenarios 

that were entitled Eco-Effi ciency Revolution, Full Speed 

Ahead, Soft Landing, and A Darker Age.

High Social Cohesion

Soft Landing Eco-Efficiency

 Revolution

Low Growth High Growth

A Darker Age Full Speed Ahead

Low Social Cohesion
74 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Eco-Effi ciency Revolution (High Economic Growth and High Social Cohesion)

 “Remediable crises” become turning points, changing the character but not the pace of growth.

 Energy price increases during the 2000s make energy a major issue.

 Fuel cells proliferate for power generation in the 2000s; fuel cell cars come on the market in the 

later 2000s. In the 2010s, ultra-light “hypercars” fl ourish, running directly on hydrogen. Use of 

energy from wind and photovoltaics grows rapidly.

 In the late 2000s, a water crisis threatens China’s stability. Th e United Nations Asian Water 

Initiative recommends changes related to water effi ciency, water resource development, 

deforestation, desertifi cation, and climate change. China embarks on an all-out eff ort to implement 

these recommendations.

 Th e idea of “Eco-effi ciency” is popularized globally by the rapid spread of more effi cient, cleaner 

energy technologies and China’s successful response to its water crisis.

 In the 2010s, an eco-effi ciency design revolution aff ects energy production and use, the chemical 

industry, manufacturing, construction, and transportation.

 “Greening of the private sector” occurs as eco-effi ciency proves highly profi table. High economic 

growth is focused on investment in a more environmentally advanced technical infrastructure.

 Environmental protection increasingly focuses on a larger strategy of sustainable development, 

including technology research and development, improved science, coordination across agencies 

and levels of government, partnerships with the private sector, open information access, and 

innovative approaches to public dialogue.

 Th e United States plays an international leadership role promoting a shift to eco-effi cient 

technologies.

 WATER – Water-effi ciency technologies are adopted extensively.

 CHEMICALS – Production increases rapidly but with a shift toward “green chemistry.”

 SPRAWL – Hypercars encourage continuation of sprawl, fragmenting ecosystems.

 BIO/NANO TECH – “Biotechnology soft path” emerges, not a rejection of biotech.

 CLIMATE – Emissions are reduced by the shift toward higher energy effi ciency, fuel cells, and 

renewable energy, with positive economic impacts.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 75

Full Speed Ahead (High Economic Growth and Low Social Cohesion)

 Th e global “Long Boom” is still going strong in 2020, with info-tech the critical catalyst.

 Th e information revolution becomes an across-the-board technology revolution as it 

transforms every other area of technology, from genomics to manufacturing.

 A breakthrough to molecular nanotechnology and nanomanufacturing occurs late in the 

2010s.

 Market-oriented policies around the world accelerate economic globalization.

 Integrated transnational corporations emerge and merge on a global scale. By 2020, a handful 

of economic giants dominates the world’s increasingly borderless economy.

 Large transnationals sometimes play countries off against one another with little regard for 

health and environmental impacts on people in weaker countries; but they also serve as 

effi cient conduits for transferring technology, capital, and expertise.

 Not everyone benefi ts from growth. Rich-poor gaps widen sharply within and especially 

between nations. Economic disasters befall nations that resist globalization. Dysfunctional 

nations in Africa, the former Soviet Union, and Asia are left behind. 

 Huge increases in the use of energy, materials, and water have signifi cant environmental 

impacts but receive little attention given the focus on growth and the promise of 

nanotechnology.

 WATER – Decisionmakers take a supply-oriented approach with huge infrastructure costs and 

growing confl icts.

 CHEMICALS – Chemical production increases rapidly, with new chemicals introduced 

too fast for adequate testing. Production increasingly shifts to locations closer to major new 

overseas markets, where there are growing health and environmental impacts, and novel 

problems from chemical interactions.

 SPRAWL – Sprawl continues unabated with loss of wetlands, ecosystem fragmentation, other 

impacts.

 BIO/NANO TECH – Regulatory process fails to keep up with new biotech products; 

signifi cant problems emerge such as gene transfer and phenotypic surprises, loss of biodiversity 

in food crops; nanotechnology off ers high promise but poses novel risks of serious accidents 

and malicious misuse.

 CLIMATE – Rapid growth in energy/fossil fuel use leads to rapid rise in CO2 concentrations; 

measurable impacts occur in areas such as loss of tundra, extreme weather events.
76 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

Soft Landing (Low Economic Growth and High Social Cohesion)

 Growth is rapid through most of the 2000s with global information infrastructure coming into 

place. 

 An economic slowdown occurs at the end of the 2000s, with further slowing in the next 

decade.

 Initially, there is high frustration at our inability to halt or reverse the slowdown. 

 Over time, an understanding grows that the slowdown is caused by unchangeable realities. 

 Aging populations in industrial nations reduce investment as elders spend down savings, as 

younger workers are heavily taxed to support retired elders, and as working-age populations 

shrink.

 Many developing nations struggle to keep up with rapid population growth and the massive 

challenges they face of housing construction, infrastructure development, public health, and 

education.

 Global oil production peaks in the 2010s and begins to decline; there seems no escape from 

higher prices.

 During the 2020s, a realization spreads that this gradual slowdown has a positive side. 

Environmental impacts drop with slowing energy consumption and resource use. Th e slowing 

pace reduces stress, and family and community strengthen. 

 Global growth “rebalances” as many developing nations with lower wages attract investment. 

 Rising energy prices make it practical and necessary to improve energy effi ciency; less money is 

available, but economic pressures to invest in effi ciency are unrelenting. 

 Global “cyberactivism” emerges as a major force in the evolution of global governance. 

Computer language translation dramatically enhances transnational citizen activism. Key 

goals of activists include helping nations most in need, protection of the global environment, 

democratization of emergent global institutions, and monitoring and regulation of 

transnational corporations.

 WATER – Water is used with greater effi ciency; access to freshwater is recognized as a human 

right; and more careful communal decisions are made regarding development of water 

resources.

 CHEMICALS – U.S. chemical production declines; the greening of domestic manufacturers 

serves as a model for the developing world, but decreasing resources are available for research 

and development, cleanup, and scientifi c research on impacts.

 SPRAWL – Sprawl abates; smart growth emerges as the new ideal with more clustering of 

growth and transit-oriented development.

 BIO/NANO TECH – Th e promise of genetically engineered crops remains unfulfi lled; 

agriculture takes more organic and ecological approaches.

 CLIMATE – Rise in greenhouse gases slows with lower growth.
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 77

A Darker Age (Low Economic Growth and Low Social Cohesion)

 Warning signals emerge in the 2000s: lingering recession, incidents of international terrorism, 

instability in the Middle East, soaring oil prices, tightening global grain prices as China 

imports more, evidence that the 1990s Asian fi nancial crisis was never really resolved, turmoil 

in Russia and China, and more.

 Nervousness about all these factors leads some investors to pull out of the market; big 

institutional investors follow suit, and in 2005 global stock markets crash.

 Crashing stocks set off a chain reaction of protectionist actions and negative economic and 

social events, which act to prevent an economic recovery.

 In the United States and other industrial nations, economic strains worsen sharply as Baby 

Boomers retire.

 In developing nations, large numbers of people are thrown back into grinding poverty. 

 Rage grows against the world’s rich, catalyzing a large increase in terrorism, including 

bioterrorism.

 Large numbers of newly desperate people and environmental refugees try to enter the United 

States.

 Many social problems worsen, including a politics of blame, growing intolerance, a narrowing 

sense of community, and an accelerating spread of AIDS and other new plagues.

 Some environmental impacts ease with slowing growth, but others worsen; some hard-won 

improvements in such basic environmental areas as air and water are lost.

 WATER – Water quality worsens, aquifers become contaminated, waterborne diseases are even 

more prevalent, and confl icts over access escalate.

 CHEMICALS – Production of chemicals slows down, but regulation declines.

 SPRAWL – Sprawl slows with the economy, but inner cities suff er from signifi cant 

deterioration.

 BIO/NANOTECH – Progress is derailed by recession, and adverse eff ects receive little 

attention.

 CLIMATE – Greenhouse gas emissions continue to rise but slow with lower growth; no 

transition to superior technologies is fostered; tropical disease vectors advance in latitude.
78 Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107

About the Authors

David N. Bengston is a research social scientist with the U.S. Forest Service, Northern 

Research Station, and works in a Research Unit titled “People and Their Environments: Social 

Science Supporting Natural Resource Management and Policy” (http://www.nrs.fs.fed.us/units/

socialscience/) in St. Paul, MN. He is also an adjunct professor in the Department of Forest 

Resources and the Graduate Program in Conservation Biology at the University of Minnesota. 

In 2004, Dr. Bengston was an Organisation for Economic Cooperation and Development (OECD) 

Research Fellow at Seoul National University, Republic of Korea. His current research focuses on 

environmental futures.

Peter C. Bishop is an associate professor of strategic f oresight and coordinator of the graduate 

program in Futures Studies at the University of Houston (Houston, TX). Dr. Bishop is also a 

founding board member of the Association of Professional Futurists, and is president of his own 

firm, Strategic Foresight and Development, which offers education and training in futures thinking 

and techniques to the corporate market. Dr. Bishop specializes in techniques for long-term 

forecasting and planning. He delivers keynote addresses and conducts seminars on the future 

for business, government, and not-for-profit organizations, and facilitates groups in developing 

scenarios, visions, and strategic plans for the future.

Stephen (Steve) R. Carpenter is an ecosystem ecologist known for his leadership of large-scale 

experiments and adaptive ecosystem management. Dr. Carpenter serves as the director of the 

Center for Limnology at the University of Wisconsin-Madison, where he is the Stephen Alfred 

Forbes Professor of Zoology. He is co-editor in chief of Ecosystems, and a member of governing 

boards for the Beijer Institute of Ecological Economics, Resilience Alliance, and South American 

Institute for Resilience and Sustainability Studies. Carpenter is a member of the U.S. National 

Academy of Sciences, a Fellow of the American Academy of Arts and Sciences, and a foreign 

member of the Royal Swedish Academy of Sciences. Carpenter is a former president of the 

Ecological Society of America. From 2000 to 2005 he served as co-chair of the Scenarios Working 

Group of the Millennium Ecosystem Assessment.

Peter J. Ince is a research forester in the Economics and Statistics research project at the U.S. 

Forest Service, Forest Products Laboratory in Madison, WI. Dr. Ince specializes in analyzing and 

modeling forest product and timber market trends, and has been a contributor since the 1980s 

to the Forest Service’s periodic nationwide long-range resource assessments, mandated by 

the Renewable Resources Planning Act (RPA) of 1974. He led development of the U.S. Forest 

Products Module (USFPM), a detailed regional economic model of U.S. timber markets, forest 

product production, consumption, and trade, which operates within the Global Forest Products 

Model (GFPM), developed at the University of Wisconsin-Madison. The USFPM/GFPM modeling 

system was employed to provide a long-range timber market outlook under various global 

economic scenarios for the most recent 2010 RPA Assessment.

George H. Kubik is president of Anticipatory Futures Group, LLC and an adjunct professor in 

Innovation Studies at the University of Minnesota, Minneapolis. Dr. Kubik is the former longtime 

president of Minnesota Futurists, a chapter of the World Future Society, and was a strategic 

futurist at the U.S. Fish & Wildlife Service (retired). He is the author of “Projected futures in 

competency development and applications: a Delphi study of the future of the wildlife biology 

profession” (2009 Ph.D. dissertation, University of Minnesota), and numerous journal articles on 

futures research.

Continued
Environmental futures research: experiences, approaches, and opportunities GTR-NRS-P-107 79

Linda L. Langner is the National Program Leader for the Resources Planning Act Assessment for 

the U.S. Forest Service Research and Development in Washington, D.C. She is responsible for 

management and oversight of the Forest Service’s national assessment of the status and trends 

of renewable resources on U.S. forest lands and rangelands, which is conducted by scientists 

at Forest Service Research Stations across the United States. In previous assignments with the 

Forest Service, Dr. Langner has been the National Program Leader for economics research, led the 

economic analysis for the 2001 Roadless Rule, and developed benefit estimates for forest outputs 

and amenities.

W. Keith Moser is a research forester with the U.S. Forest Service, Northern Research Station 

Forest Inventory and Analysis Unit in Saint Paul, MN. He is the state analyst for Missouri and 

Kansas; the product line specialist for ground vegetation and invasive plants; Station representative 

for the working group that reviews the Forest Service’s information exchange and management 

actions affecting the Great Lakes Indian Fish and Wildlife Council and constituent tribes; and a 

Core Team member of the Northern Forest Futures Project (NFFP), in which the Forest Service 

and universities collaborate to project forest extent and composition for a 20-state region over the 

next 50 years. Within NFFP Dr. Moser is the Team Leader for Projections, and Sub-team Leader for 

efforts that document and model forest threats.

Robert (Bob) L. Olson is a Senior Fellow at the Institute for Alternative Futures (IAF) in Alexandria, 

VA. He was a founding member of IAF’s Board of Directors and served as its research director for 

a dozen years. Formerly he was a project director and consultant to the director at the Office of 

Technology Assessment of the U.S. Congress and a Fellow at the Center for Cooperative Global 

Development at the American University. Dr. Olson has worked extensively with the U.S. Environmental 

Protection Agency’s environmental futures program and is the author or editor of numerous 

publications on environmental futures, including “Environmentalism and the Technologies of 

Tomorrow: Shaping the Next Industrial Revolution” with co-editor David Rejeski (2005, Island Press).

Adena R. Rissman is an assistant professor in the Department of Forest and Wildlife Ecology at 

the University of Wisconsin-Madison. Dr. Rissman is a faculty affiliate of the Nelson Institute for 

Environmental Studies, the Agroecology Program, and the Land Tenure Center. Her interdisciplinary 

research investigates the relationships between society and the environment in ecosystem 

management, conservation, and sustainable use. She investigates institutional approaches to 

conservation and new models of governance over public and private lands. Dr. Rissman’s research 

employs mixed quantitative and qualitative methods, including spatial analysis, surveys, and 

interviews.

Stephen (Steve) R. Shifl ey has been a research forester with the U.S. Forest Service for 34 years. 

For the past two decades he has been located at the Northern Research Station’s Forest Science 

Lab in Columbia, MO. Throughout his career Dr. Shifley has conducted research on predicting 

forest dynamics at tree, stand, and landscape scales. Recently he has worked with a new cadre 

of associates interested in forecasting and analyzing large-scale, long-term changes expected in 

forests of the 20-state northeastern quadrant of the United States – the Northern Forest Futures 

Project. He has authored or co-authored more than 100 scientific and technical papers, including 

two editions of the book “The Ecology and Silviculture of Oaks.”

Kay E. Strong is an associate professor in economics at Baldwin Wallace University near Cleveland, 

OH. Prof. Strong’s areas of expertise include international economics, contemporary socialeconomic issues, curriculum development and assessment in economics, and futures studies. 

During the 2008-09 academic year, Dr. Strong was instrumental in creating two public-access 

teaching wikis, the Foresight Education Project and the Futures of the U.S. She also developed a 

prototype undergraduate course, Strategic Foresight, with Prof. Peter Bishop, director of the Futures 

Studies program at the University of Houston.
Printed on Recycled Paper

Bengston, David N., comp. 2012. Environmental futures research: experiences, 

approaches, and opportunities. Gen. Tech. Rep. NRS-P-107. Newtown Square, PA: 

U.S. Department of Agriculture, Forest Service, Northern Research Station. 79 p.

These papers, presented in a special session at the International Symposium on Society and 

Resource Management in June 2011, explore the transdisciplinary fi eld of futures research 

and its application to long-range environmental analysis, planning, and policy. Futures 

research began in the post-World War II era and has emerged as a mature research fi eld. 

Although the future of complex social-ecological systems cannot be predicted, these papers 

show how futures research can offer perspectives and methods that help researchers, 

decisionmakers, and other stakeholders explore alternative futures and gain environmental 

foresight—insight that can inform decisionmaking on environmental challenges. One 

author points out that the study of the future can be thought of as the study of change. He 

discusses three types of futures: the expected future, a range of plausible alternatives, and 

the preferred future, which decisionmakers can shape depending on their choice of action. 

An example of the methodology of futures research is provided in another chapter, which 

illustrates the use of scenario development. Another chapter identifi es global trends that 

could dramatically change social-ecological systems.

The second half of the collection applies the methods and approaches of futures research 

to natural resource management. A global and a regional scenario illustrate scenario 

planning, a methodology that produces sets of plausible futures that could develop from 

current conditions depending on alternative human choices and drivers of change. Another 

example demonstrates how analysts can incorporate global scenarios and modeling, and 

scoping of trends and issues, into forest inventory data to gain insight into the regional 

forests of tomorrow. A chapter on linking global scenarios with assessments of U.S. natural 

resources as required under the Resources Planning Act considers both opportunities and 

challenges. Lessons learned from an analysis of futures research conducted since the 1970s 

at the U.S. Environmental Protection Agency are also offered. These papers suggest that 

the perspectives and methods of futures research hold great potential for developing the 

foresight needed to meet environmental challenges of the 21st century.

KEY WORDS: strategic foresight, scenarios, trends, forecasting, change, environmental 

scanning

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