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Advanced Review
Developing qualitative scenario
storylines for environmental
change assessment
Mark D. A. Rounsevell∗and Marc J. Metzger
This article reviews the historic evolution of qualitative scenario storylines and
the various methods used in their development and application in environmental
change assessment. The scenario method largely emerged from military strategy
and war planning, with the techniques being adopted and advanced further by
the business sector. Scenario storylines became widely applied to environmental
problems from the 1970s and since then a number of new studies have been
developed at both global and regional scales. Many different methods are used in
scenario storyline development although most examples applied to environmental
change assessment are exploratory and defined through a matrix logic that reflects
different dimensions of environmental change drivers. This article discusses
several development techniques for scenario storylines, provides examples of
existing scenario storylines, discusses the differences between them, and highlights
anumberoflimitationsinthecurrentscenariostorylinedevelopmentmethods.The
credibility, legitimacy, and saliency of future scenario storylines are discussed with
respect to personal beliefs, the equifinality of alternative development pathways,
the validation and uncertainty of assumptions, stakeholder engagement in visions
development, and participatory methods. 2010 John Wiley & Sons, Ltd. WIREs Clim Change
2010 1 606–619
Herbert Kahn’s phrase ‘The most likely future
isn’t’ succinctly lays out the motivation and
imperative for methods that allow us to explore
the future. The phrase embodies the notion that
what we think will happen in the future probably
will not because the basis of our thought process
is itself flawed: our thinking being limited by
personal experience, prejudice, and other forms of
bias. Scenario analysis has emerged as a means of
characterizing the future and its uncertainties through
structured, but imaginative thinking as a process that
pushes us beyond the axioms and norms that are the
constraints of conventional wisdom. Scenarios have
been defined as1:‘... plausible and often simplified
descriptions of how the future may develop based on
a coherent and internally consistent set of assumptions
about key driving forces and relationships’. Scenarios
can be qualitative or quantitative or a mix of
∗Correspondence to: mark.rounsevell@ed.ac.uk
School of Geosciences, University of Edinburgh, Edinburgh EH8
9XP, UK
DOI: 10.1002/wcc.63
these. Storylines are the qualitative and descriptive
component of a scenario, which create images of
future worlds. They can reflect the assumptions
within scenarios about the drivers of change, or
they can describe the consequences or outcomes of
a scenario. Although most storylines are based on
written narratives, other forms of communicating
images of the future are possible. This includes telling
stories through imagery and animation,2filmmaking
(e.g., The Age of Stupida), and model simulations
or conceptual trend mapping.3In the subsequent
discussion we use the term ‘scenario storyline’ to refer
to the qualitative component of scenarios. Scenario
storylines have an important role to play when we
have limited understanding of the causal relationships
within a system that prevents quantification of these
relationships in models. Although scenario storylines
attempt to open our eyes to different ways of
perceiving our world, they are not predictions and
they do not seek truth. What they do try to achieve
is to stimulate, provoke, and communicate visions
of what the future could hold for us. They aim for
creativity, rigor, internal coherence, and plausibility.
606 2010 John Wiley & Sons, Ltd. Volume 1, July/August 2010
WIREs Climate Change Developing qualitative scenario storylines
As a tool, scenario storylines are more useful the
further into the future we explore as uncertainties also
increase and predictions become unsound.
Scenario storylines are used increasingly in envi-
ronmental change assessment as a means of exploring
uncertainties about the consequence of human actions
on the environment and the response of society to envi-
ronmental change. Much of this effort has been driven
by concern about climate change, as an exemplar of
human–environment interactions with the work of the
Intergovernmental Panel on Climate Change (IPCC)4
notable in refining the role of scenario storylines
in environmental change assessment. In this article,
we explore a wide range of methods for the devel-
opment of qualitative, scenario storylines and their
application in environmental impact, adaptation, and
vulnerability assessments. In particular, we discuss
how scenario storylines are used to make regional
interpretations of global drivers, how they assist in
highlighting uncertainties and in communicating com-
plex transitions in future worlds. We focus on the three
main challenges for the development of scenario story-
lines in environmental studies, notably their saliency
(are the scenarios relevant to information needs?),
credibility (are the scenarios scientifically sound?),
and legitimacy (who developed the scenarios and
how?).5
HISTORIC CONTEXT OF SCENARIOS
TO EXPLORE GLOBAL CHANGE
Human interest in the future has a long history that
can be traced back to the writings of early philoso-
phers, such as Plato’s description of his ideal Repub-
lic and visionaries from Thomas More to George
Orwell.6However, formal scenario techniques were
first developed by military strategists and the first
documented outlines of what we now regard as sce-
narios can be found in the 19th century writing of the
Prussians Von Clausewitz and Von Moltke.7
Modern day scenario techniques emerged in the
post-war period. In order to guide the development of
new weapons systems in the emerging cold war, Her-
man Kahn and colleagues developed scenarios for the
US Air Defence System Missile Command at the Rand
Corporation in the 1950s.7Their methods, referred to
as Intuitive-Logic Models,6have since dominated sce-
nario development. In the 1960s, Kahn began to apply
his scenario methodology to social forecasting and
public policy, publishing his book The Year 2000: A
Framework for Speculation on the Next Thirty-Three
Years in 1967.8It has become a landmark in the field
of scenario planning9by providing one of the earliest
definitions of scenarios, demonstrating their use as a
tool for exploring complex and uncertain domains,
and generating controversy that spawned numerous
counter studies,6including the Club of Rome Reports
The Limits to Growth10 and Mankind at the Turning
Point.11
Although initially in the domain of public policy
planning, it was not long before the business commu-
nity adopted these techniques, notably Royal Dutch
Shell. Its profitable navigation through the 1970s oil
crisis has become a classic story of the usefulness
of scenario planning.6,12,13 Strategic planners at Shell
used scenarios to integrate disperse investigations of
the global oil markets and concluded that at some
volume of production oil was more valuable kept in
the ground than sold. This led to one scenario in
which a coalition of oil-producing countries was able
to limit production, causing oil prices to rise. This
scenario was considered at the time to be radical, but
plausible. The scenario exercise led Shell to adjust its
business management and hedge against a potential
for high oil prices by increasing the efficiency of its
refining and shipping operations. Consequently, Shell
was able to adapt to expensive oil much faster than its
competitors.12,13 By the 1980s, scenario planning was
awell-establishedplanningtoolinlargecorporations,
with 75% of the Fortune 100 companies reporting
using scenario techniques in 1981.14
Meanwhile, scenarios remained an important
tool in public policy planning. The most profound
example is perhaps the role scenarios played in shap-
ing the debate and influencing the agenda for political
change in South Africa. The 1984 scenarios developed
for the Anglo American Corporation, a global mining
company, explored future uncertainties that would
affect its South African operations. Its domestic sce-
narios illustrated how a bleak ‘low-road’ scenario of
escalating violence could propel South Africa into an
economic wasteland, while appropriate action could
result in a ‘high-road’ scenario with democratic wel-
fare and economic growth.15,16 Consequently, Anglo
executives decided to share their views and insights
via ‘road show’ lectures reaching ‘25,000 to 30,000
people from all walks of life’, as well as a book17
that became a national best seller. Two further sce-
nario studies for South Africa followed in the 1990s:
the business-led Old Mutual/Nedcors scenarios and
the much discussed Mont Fleur scenarios. The latter
were based on a series of joint workshops with a
diverse group of leaders from South Africa’s business,
political, and civil society coordinated by the Univer-
sity of Cape Town and facilitators from Shell.15,16
Although it is difficult to assess the real contribution
of these scenario studies to socioeconomic reform in
South Africa, they have helped in breaking prevailing
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paradigms and in stimulating discussion about change,
in both government and society.16
Emerging concerns about the earth’s long-term
carrying capacity led to the first wave of global envi-
ronmental scenarios, including the first mathematical
models developed by the Club of Rome10,11 as well
as speculative narratives.18 After a brief lull, a sec-
ond wave of integrated global analyses followed the
Brundtland Report19 and the 1992 Rio World Confer-
ence on Environment and Development. The Limits to
Growth was updated20 and the first integrated mod-
els of climate change impacts were developed.21,22
Although there were advances in these new models, the
credibility of numerical models remains limited to sim-
ulating well-understood systems over sufficiently short
times. Conversely, new narrative scans of alternative
futures23,24 provide saliency, but lacked the structure
and rigor of the quantitative approaches. The Global
Scenario Group (GSG), convened in 1995, realized
that complementing quantitative modeling techniques
with qualitative scenario exploration would provide
a broader perspective than is possible from math-
ematical modeling alone.25–27 The GSG scenarios
have since been adopted for a range of global envi-
ronmental assessments including the UNEP Global
Environmental Outlook.28 Furthermore, combining
rich qualitative storylines with quantitative modeling
techniques, known as the storyline and simulation
approach,29,30 has become the accepted method for
integrated environmental assessment and has been
used in all major assessments including those by the
IPCC,4Millennium Ecosystem Assessment,1,31 and
many regional and national studies.29,32
All the scenarios discussed above followed the
Intuitive-Logic model, initially developed by Kahn.8
Although this forms the most widely used method,
even referred to as the ‘gold standard of scenario
development’,33 there are many other techniques.34–36
An early contrasting school of scenario development
formed the La Prospective model, stemming from
the French philosopher Gaston Berger’s work in the
1950s. It focused on developing positive (or nor-
mative) images of the future that would provide a
guiding vision for policy makers. While the intuitive-
logic model aims to provide understanding of broad
trends and processes, La Prospective focuses on spe-
cific strategic decisions and tactical plans.6However,
the foremost difference between both scenario models
is in the use of probability. La Prospective identi-
fies the most probable scenario as well as illustrating
less probable upper and lower limit scenarios using
numerical analysis of a broad range of potentially rele-
vant factors based on experts’ views.37 Although these
methods have proved successful in strategic decision
making in public policy and business,38 they may
be less appropriate for global environmental change
science due to their narrow scope.
METHODS IN SCENARIO STORYLINE
DEVELOPMENT
Types of Scenarios
The literature contains a large number of different
and at times conflicting definitions, characteristics,
principles, and methodological ideas about scenarios,6
which has led to the development of many scenario
typologies.6,39,40 The environmental sciences tend to
apply one of three different concepts in scenario story-
line development, which are termed here exploratory,
normative, and business-as-usual (BAU).
Exploratory scenario storylines relate most
closely to the intuitive-logic model discussed above.
They describe plausible, but alternative socioeconomic
development pathways that allow scenario analysts to
compare across a range of different situations, gener-
ally from 20 to 100 years into the future. Exploratory
scenario storylines typically adopt a coevolutionary
stance41,42 in which multiple assumptions about dif-
ferent development pathways lead to potentially very
different outcomes over long-term time horizons.
Although this is the most common use of exploratory
scenario storylines, they can also be used to identify
different development pathways that lead to similar
or converging scenario outcomes. This effect, known
as equifinality, can provide valuable insight into the
robustness of a given future with respect to alterna-
tive scenario storyline assumptions. Equifinal scenario
outcomes are rarely discussed in the literature. An
important example of exploratory scenario story-
lines in environmental assessment is the IPCC Special
Report on Emissions Scenarios (SRES).4
Normative scenario storylines are framed
around desired futures or outcomes and in this sense
have parallels with La Prospective School of scenario
thinking. The storyline itself is a description of the
series of events and causal relationships that lead
from the current world condition to the desired future
world. Inherent to this way of thinking is that very dif-
ferent pathways may exist that converge on the same
desired outcome. Policy scenarios are often normative,
for example, the Convention on Biological Diversity
target of achieving a significant reduction in the cur-
rent rate of biodiversity loss at the global, regional,
and national level by 2010 (www.cbd.int/2010-
target), the Millennium Development Goals by 2015
(www.un.org/millenniumgoals), or the European
Union’s target of 20% renewable energy consumption
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WIREs Climate Change Developing qualitative scenario storylines
FIGURE 1|The five generic stages in scenario development.46
by 2020 (ec.europa.eu/agriculture/bioenergy/index en.
htm). This reflects the needs of policy to achieve
desired outcomes over relatively short-time horizons
within a decision process that is often mediated by the
political context.
BAU scenario storylines (sometimes termed con-
ventional wisdom or extrapolations) are typically used
in short-term policy analysis to explore the conse-
quences of relatively well-known, near-term changes
in regulatory contexts.3They assume that broader
trends will have little influence on future worlds
because over short-time horizons the policy effects
are thought to dominate. The value and plausibil-
ity of these scenario storylines decrease through time
into the future, although they are commonly used
to define a reference case against which other types
of exploratory or normative scenario storylines are
compared.3,43
Although business management textbooks dis-
cuss scenario methods44,45 and provide an in-depth
overview of the practice of environmental scenario
analysis,32 explicit descriptions of the methods are
surprisingly rare in the scientific literature and can lead
to confusion, especially when concepts are also poorly
defined. Figure 1 provides a summary of five generic
stages in scenario development46 as used consistently
throughout this article.
Drivers and Scenario Logics in Exploratory
Scenarios
In exploratory scenarios, storylines describe the qual-
itative assumptions about drivers. Drivers are the
underlying causes of change, which derive from a
number of broad categories sometimes referred to
as STEEP: Social, Technological, Economic, Environ-
mental, and Policy governance.6Storyline assump-
tions and the relationships between different drivers
are structured and described within what is com-
monly termed the ‘scenario logic’. The scenario logic
provides order to a range of potentially divergent
issues and in doing so allows comparison across dif-
ferent narratives. Importantly, the scenario logic seeks
to establish internal consistency between the various
statements and assumptions that underpin a storyline.
The most commonly used method for the construction
of scenario logics in environmental change assess-
ment is the matrix approach, with the IPCC SRES
storylines4being perhaps the best known and widely
used example. The SRES storylines are framed around
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two axes that reflect alternative future world ori-
entations. One axis describes regional versus global
strategies that reflect alternative visions of global con-
nectivity and attitudes to geopolitical cooperation.
The other axis describes a world based on policy lib-
eralization and free markets in contrast to a world that
attaches high importance to environmental and equity
issues. The axes reflect both a continuum of possibili-
ties along each axis, but also an enormous number of
possible scenarios that derive from different combina-
tions of the two axes within the scenario space created
by the matrix. In practice, the axes create four quad-
rants that reflect scenarios ‘families’ with similar, but
variable attributes and these families are often used
in subsequent analyses. Given the inordinate number
of scenario possibilities that exist within each family,
‘marker’ scenarios are commonly used as an exemplar
of a scenario family. The four SRES marker scenar-
ios are labeled: A1 (global economic), A2 (regional
economic), B1 (global environmental and equitable),
and B2 (regional environmental and equitable). One
of the major criticisms of a matrix approach is that
the axes create polarization in thinking about con-
cepts that are not necessarily mutually exclusive. For
example, the economy–environment axis of the SRES
storylines excludes worlds that apply free market
solutions to environmental problems or environmen-
tally orientated worlds that support strong economic
growth.
Although being the commonly applied method,
the matrix approach is not a prerequisite for the
creation of exploratory scenarios. Several examples
exist of storylines that simply reflect alternative
world visions based on specific themes for which
there is no cross-referencing as with the matrix
dimensions.1,2,47,48 Such approaches commonly
involve participatory approaches that seek to avoid
the constraints that a matrix would impose on the
imagination of participating stakeholders. Participa-
tory approaches may also be used, however, to identify
the key uncertainties to be explored in a matrix
approach.49
Scale Issues
Awiderangeofglobalscenariostorylineshavebeen
developed for environmental assessment in different
application domains (see Appendix 1 for a list of
the principal examples). Global storylines are used
increasingly to define the boundary conditions for
regional environmental change assessments in which
regional narratives are interpreted from the global
storylines. The global to regional interpretation pro-
cess commonly involves a description of drivers that
are more pertinent to the scale level of analysis.
This reflects that different human and physical pro-
cesses occur at different scale levels and that stake-
holder interests also vary across scales.50 Examples
of regional storyline interpretations from global
scenarios include the ATEAM51,EURuralis
52,and
ACCELERATES53,54 scenarios, which were all to
some extent based on interpretations of the SRES nar-
ratives. These interpretations tend to disaggregate the
global scenario storyline assumptions in geographic
terms (all the above examples were undertaken for
Europe), but also in thematic terms, for example,
regional studies may focus on specific sectors such as
agriculture53,55 or health,56 or disciplinary domains
such as demography or sustainable development.57–59
Appendix 2 provides a summary of published, regional
scale scenario development exercises. These examples
are striking in highlighting the regional disparities in
scenario development with most studies undertaken
in Europe and Africa, some in Latin America, but
nothing for the rest of the world.
Participatory Approaches
Although most scenario storylines use the expert judg-
ment of scenario analysts, participatory approaches
based on stakeholder elicitation seek to broaden
the knowledge sources that contribute to story-
line development.60–63 The EEA Prelude scenarios,
for example, used a facilitated stakeholder process
in which the participants themselves had complete
control over the storyline development process.2,61
Careful facilitation and planning are crucial44,45,64
and can lead to important and surprising insights
into the storylines that contribute to the design of
policies better suited to serve the needs of those
concerned.60 These social learning methods can thus
provide immense saliency and richness to scenario
storylines, and become a vehicle for consensus build-
ing and problem solving.65,66 It also enhances the
legitimacy of the resulting scenarios in the eyes of
participating stakeholders.61,65–67 The credibility of
participatory approaches is, however, limited by a
potential lack of diversity among participating stake-
holder groups,65 differences in epistemologies or
knowledge systems and thus in perceptions between
stakeholders,67 and problems with internal consis-
tency. Participating stakeholders do not always have
a complete mental model of the system that is being
described within a scenario storyline, and this lim-
its understanding of the system interrelationships
and feedbacks. As internal consistency in storyline
assumptions is fundamentally important in scenario
development,44 novel approaches have been proposed
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WIREs Climate Change Developing qualitative scenario storylines
to improve the consistency of narrative storylines
that use participatory expert judgment. Attempts have
been made68 to introduce rigor into the interpretation
of regional scenario storylines from global scenario
storylines using a pairwise comparison approach69 to
maintain the internal consistency of storyline assump-
tions across scenarios. The approach was based on an
inconsistency analysis using Saaty rankings to ensure
that the individual qualitative statements of participat-
ing experts were consistent with all other statements
made by the same expert in describing a scenario sto-
ryline. Fuzzy cognitive mapping (FCM) has also been
used as an aid in developing more structured narratives
that better incorporate important feedbacks as well as
making more explicit the system level understanding
of the storyline developer.70 Both pairwise comparison
and FCM also support the translation of narratives
into model input parameters for subsequent scenario
quantification.
Normative Scenarios and Bayesian Belief
Networks
There are several examples of normative scenario
storylines applied to environmental assessment.3,71
Normative scenarios use ‘backcasting’ techniques that
identify the events leading from the current situation
to a desired future outcome, and techniques that attach
probabilities to these events have been developed using
Bayesian belief networks (BBNs).72,73 BBNs provide
aframeworkforgraphicallyrepresentingthelogical
relationships between variables and for quantifying
the strength of these relationships using conditional
probabilities.74 BBNs have been used in a range of land
use change studies focusing on both biophysical75,76
and coupled social–ecological systems,77,78 providing
an appropriate framework for stakeholder consul-
tation and decision support systems by explicitly
quantifying parameter uncertainty.77 BBNs are, how-
ever, acyclic so that temporal dynamics and feedback
loops cannot be easily implemented.73 To do this,
separate networks are required for each future time
slice.79 Furthermore, BBNs work best with discrete
variables, requiring the difficult task of discretiza-
tion of continuous environmental data,79 although
Bayesian hierarchical simulation-based modeling can
provide a solution to this problem.73 Recent work has
nevertheless demonstrated the potential of BBNs in
the construction of sustainability scenario storylines71
that facilitated stakeholder elicitation and communi-
cation, using non-deterministic relationships derived
from expert judgment and model parameterizations
based on probability distributions rather than single
values.71
Exploratory Probabilistic Futures
Although Bayesian methods are explicitly probabilis-
tic, most exploratory scenarios and storylines are
deterministic. They define absolute values for each
scenario parameter assumed from an interpretation of
a single storyline description. Uncertainty is reflected
in different parameter values between scenarios, but
not in the parameter assumptions made for a given
scenario storyline. In practice, however, great uncer-
tainty surrounds any qualitative assumptions about
the future. The method of conditional probabilis-
tic futures has emerged as a means of quantifying
uncertainty ranges in scenario storyline assumptions.
Examples of this method have been reported for
demography and greenhouse gas emissions80,81 and
the method is being applied to climate change sce-
narios. Conditional probabilistic futures are explicit
about the uncertainty surrounding a scenario parame-
ter using probability distributions functions (PDFs).
Technically, various Monte Carlo based sampling
techniques may be used to generate quantitative sce-
narios of different variables from the PDFs using mod-
els, but the theoretical foundation for the definition of
uncertainty ranges reflected in PDFs remains tenuous.
At best, these are expert judgments derived from sce-
nario storyline interpretations; at worst, speculation.
Most environmental scenario storylines, whether
exploratory, normative, or BAU reflect trends in
drivers that steadily evolve into the future, despite
discussion of the importance of surprise events in
the literature, dating back to 1967.8They seldom
account for shocks that might create bifurcations or
path dependency in future socioeconomic trajectories,
although the MA does discuss potential catastrophic
changes and following responses within the scenario
context.1Shocks reflect what are potentially high
impact events, but with a low probability of occur-
rence. Some scenario storyline studies have attempted
to address shocks, notably the scenario storylines
developed by the ALARM project.47,82 These exercises
are framed around thought experiments of what might
happen to human behavior when confronted with
extreme changes in environmental conditions.
CHALLENGES AND LIMITS
Differences Between Existing Scenario
Storylines
Many of the existing global and regional scenario
storylines map onto one another on the basis of sim-
ilarities in assumptions and the dimensions of the
matrix axes. However, there is often a large diver-
gence between studies even within the same scenario
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storyline group.83 In some cases, even the direction
of change varies for the same scenario storyline83 and
clearly this has implications for the credibility and
legitimacy of these studies. It is worth noting, how-
ever, that the divergence between individual studies
often appears to depend most on whether the sce-
nario storylines were constructed at the global or
regional scales. Regional scenarios are often consis-
tent with one another, whereas global studies are
often more divergent.83 These differences are likely to
arise because the assumptions that underpin the inter-
pretation of regional scenario storylines are different
from those for global narratives. Uncertainties are also
exacerbated by the use of different models to gener-
ate quantitative scenario outcomes. Which of these
sources of uncertainty is the more important is diffi-
cult to gauge. However, it is apparent that storyline
assumptions, as interpretations based on judgments,
are highly dependent on the subjectivity of different
scenario analysts. This can reflect different levels of
knowledge, different world views and perspectives, or
semantics.
The Limits to Knowledge
Scenario storyline assumptions are limited by absolute
knowledge uncertainties. There are simply environ-
mental change processes that we know little or nothing
about. There are also issues of relative knowledge
uncertainties between different scenario analysts. In
practice the level of knowledge as well as the expe-
rience of each individual within a scenario storyline
development process will affect the outcomes of the
exercise. These differences may reflect simple knowl-
edge gaps or a broader issue of the social–cultural
context. Some individuals may simply be unaware of
different issues or refuse to believe them. The subjec-
tive nature of such relative differences is in practice
impossible to avoid, but can be mitigated by scenario
developers being transparent in expressing and report-
ing scenario storyline assumptions. Scenario analysts
are also often subject to ‘axiomatic preconceptions’
and norms in which assumptions become accepted as
‘truths’. An example of an axiomatic preconception
is the commonly cited relationship between political
liberalization and innovation. Within the SRES story-
lines, for example, free markets (as in the A1 family)
are assumed to lead to more rapid rates of technolog-
ical development. There is certainly some evidence for
this in reality, but other examples where the relation-
ship does not appear to stand up to scrutiny, e.g., the
French car industry, have been highly innovative, but
also subsidized.84 Again, axiomatic preconceptions
depend strongly on the experiences of the individ-
ual scenario analyst and their sociocultural context.
Semantics also influence the subjective nature of sce-
nario storyline interpretations. For example, the SRES
storylines distinguish between global and regional
scales, but is a region a continent, a country, or a
sub-national territory? This definition will lead to
very different interpretations of what ‘regionally ori-
entated’ means within an SRES storyline.
Validating Scenario Assumptions
Validating scenario assumptions is problematic.
Returning to the above example: How is it possi-
ble to validate the effect of free markets on the rates
of technological development? Traditionally, scientific
methods involve testing a hypothesis against observa-
tions, and quantitative models follow this procedure
by validating model outputs against observed data.
However, many scenario assumptions refer to worlds
that might exist in the future (plausibly), but which
have never existed in the past. Thus there is no empir-
ical data against which these assumptions can be
tested. A simple example of this is the plausible sce-
nario of dismantling the support mechanisms provided
to European agriculture by the Common Agricultural
Policy. Such a free market situation has not existed
in Europe (at least not over the period for which
observed data exist) and against which the conse-
quences of a free market scenario could be tested.
Moreover, the past (as the source of observation) is
just one realization of many pasts that could, but did
not, occur. So, how can we verify our assumptions
about future worlds that are very different from any-
thing we have observed in the past? One possibility is
to derive validation data setsfromgeographicanalogs
instead of the traditional temporal analogs. By finding
more than one region with similar characteristics, but
differences in a key driver (e.g., the policy context) it
should be possible to understand the effects this driver
has on specific environmental outcomes. In practice,
however, it is difficult to find appropriate geographic
analogs with sufficiently similar characteristics.
Judgment in Scenario Development
Traditional scenario methods1,51,85 work well when
the processes that are influenced by the storylines are
well understood and can be adequately quantified.
However, when processes are less well understood, as
is the case for social processes and policy implications,
interpretation and judgment become increasingly
important.46 Here, set paradigms and ideologies have
an influence and personal values and beliefs that affect
scenario outcomes should be made explicit, especially
where scenario storylines are used to inform policy
evaluations.86 A consistent analysis of the influence
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WIREs Climate Change Developing qualitative scenario storylines
of personal or political judgment in scenario interpre-
tation is possible when alternative scenario storylines
are interpreted from contrasting perspectives through
explicit ‘belief ranges’.46 Identifying belief ranges can
help to pinpoint the underlying processes leading to
alternative scenario storyline outcomes. The challenge
here is also to develop quantitative modeling tech-
niques that are sufficiently flexible to be able to
quantify judgment-related variations within alterna-
tive scenarios. There is also a strong need for greater
transparency in reporting scenarios that outlines and
reflects on important assumptions that may be open to
political interpretation.87 This is currently rarely done.
Scenarios in Support of Policy
Scenarios can be seen either as ‘products’ that may
be the basis of decision making or as learning
processes88 and both approaches have value in
support of policy. Scenario-based exercises are useful
in providing the potential for policy makers to
visualize future worlds and to help guide and
develop adaptive strategies.87,89 Scenario storylines
can support public policy in much the same way that
Shell and other private sector companies have used
scenarios to explore the implications of alternative
business strategies. The process of raising awareness
and promoting creative and imaginative thinking
about more distant futures can help plan robust
and flexible policy measures to deal with change.89
Exploratory scenario storylines, however, tend to be
static representations of alternative worlds that are
poor at dealing with the response (adaptation) of
people to changing circumstances. The IPCC SRES
scenarios, for example, do not include climate policy
as a driving force and consequently are of limited
value for exploring the effects of alternative policy
options in support of climate mitigation. A number
of scenario methods are being used by policy advisors
and there is a role for scenario exercises in planning
and communications work to develop imaginative
thinking.89 There are, however, key barriers to the use
of scenario storylines in policy arenas, including: the
short-term nature of policy cycles and timescale, the
difficulty that individuals have in imagining different
futures, limited documentation of the scenario
storyline development process, a lack of clarity about
the purpose of a scenario exercise, and limited
relevance (or saliency) to specific policy details.89
COMPARATIVE SUMMARY OF
SCENARIO STORYLINE METHODS
The scenario qualities of saliency, credibility, and
legitimacy5provide an appropriate framework for
the comparison of various scenario storyline develop-
ment methods discussed above (Table 1). There can be
TABLE 1 Comparison of Scenario Methods Regarding Their Saliency, Credibility, and Legitimacy, Based on Definitions in Ref 5
Scenario
Storyline Method
Saliency (Relevance for Decision
Makers’ Needs)
Credibility (Scientific Adequacy
of the Methods and Evidence)
Legitimacy (Unbiased
Incorporation of Divergent Values)
Exploratory
Medium.
Compromised when the
focus has low policy relevance
Medium
.Themostapplied
method, described in a vast
body of research
Low-Medium
.Stronglydependent
on the beliefs of the scenario
analysts involved
Normative
High
.Afocusonspecificdesired
futures
Low-Medium.
Difficult to address
uncertainties in trajectories
toward the desired future
Low-Medium
.Stronglydependent
on the visions of the scenario
analysts involved.
Business-as-usual
High
.Usuallydirectlypolicy
relevant and based on
extrapolation
Low
.Basedoncurrentprocesses
without alternatives and
uncertain developments
Medium-High.
Based on current
values and beliefs
Participatory
High
.Shapedbyrelevant
stakeholders
Low-Medium
.Limitedbythelack
of stakeholder mental models
and internal consistency
Medium-High
.Stakeholders
consulted, but dependent on
those individuals
Probabilistic
Low-Medium
.Increasescomplexity
leading to communication
difficulties
High
.Basedonformal
representation of uncertainty
Low-Medium
.Maybeaffectedby
communication issues due to
complexity
Scaling methods
High
.Increasingthespatialand
thematic resolution enhances
the relevance to local
stakeholders
Low-High
.Dependsonwhether
scaling introduces new process
information or is simply a
graphical representation
Low-Medium
.Dependson
stakeholder acceptance of
methods
The low, medium high classification reflects the opinions of the authors; the scenario storyline methods given in this table are not necessarily mutually exclusive,
but follow the structure of the discussion above.
Volume 1, July/August 2010 2010 John Wiley & Sons, Ltd. 613
Advanced Review wires.wiley.com/climatechange
trade-offs between these attributions (e.g., increasing
scientific credibility can reduce the saliency for pol-
icy), and multiple audiences can have different views
on the scenario development process and outcomes.
Nevertheless, Table 1 summarizes the basic charac-
teristics of the scenario storyline methods that were
discussed previously using these attributes. It demon-
strates that no perfect scenario storyline method
exists for all situations and this in part explains the
diversity of methods used in environmental change
studies. Each method has its strengths and weak-
nesses and the choice of a particular method depends
very much on the context and aims of a particular
study.
CONCLUSIONS
There is a long history of the use of scenarios and
storylines across a range of sectors, but only a rel-
atively short history of their use in environmental
change assessment, notably since the 1970s, but more
so since the 1990s. Environmental studies have tended
to focus on exploratory scenarios using the matrix
logic approach. This does not use the full diversity
of storyline development methods. Environmental
change assessment would benefit greatly from the
methodological experiences of other sectors, prin-
cipally business. In conclusion, we have identified
the following gaps in scenario storyline development
methods, which if addressed could enhance the credi-
bility, legitimacy, and saliency of future environmental
change assessment:
1. The influence of personal beliefs such as political
ideologies should be made more explicit in sce-
nario development and reported transparently
to improve credibility;
2. Alternative pathways that result in the same
(equifinal) future outcomes should be discussed
and compared;
3. Better methods to validate scenario assumptions
such as the use of geographic and tempo-
ral analogs would enhance the credibility of
scenario storylines;
4. Further consideration needs to be given to the
uncertainty that surrounds storyline assump-
tions and the implications of this for quantitative
scenarios, e.g., conditional probabilistic futures
and Bayesian approaches;
5. Stakeholder engagement should be used to bet-
ter define normative visions of future worlds
and the alternative development pathways to
achieve these visions;
6. Participatory methods, with their high saliency
and legitimacy, merit wider application, but
should be developed further to increase their
credibility.
NOTE
aA 2008 film by Franny Armstrong about a man living
alone in a devastated future world in 2055, looking
at old footage from 2008 and asking: why didn’t we
stop climate change when we had the chance?
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FURTHER READING
Bruce-Briggs B. Supergenius: The Mega Worlds of Herman Kahn.NewYork:NorthAmericanPolicyPress;2001.
Volume 1, July/August 2010 2010 John Wiley & Sons, Ltd. 617
Advanced Review wires.wiley.com/climatechange
APPENDIX 1: RECENT GLOBAL STORYLINES (ADAPTED AND EXPANDED FROM
REF 90). A MORE DETAILED SUMMARY IS PROVIDED IN REF 91
Study Horizon Focus Storylines
Global Scenario Group27 2050 Environment,
development
1. Conventional worlds: Gradual convergence in incomes and culture toward
dominant market model
(a) Market forces: Market-driven globalization, trade liberalization,
institutional modernization
(b) Policy reform: Strong policy focus on meeting sustainability goals
through technology
2. Barbarization: Social and environmental problems overwhelm market
and policy response
(a) Breakdown: Unbridled conflict, institutional disintegration, and
economic collapse
(b) Fortress world: Authoritarian rule with elites in ‘fortresses’, poverty,
and repression outside
3. Great transitions: Fundamental changes in values, lifestyles, and
institutions
(a) Eco-communalism: Local focus and a bioregional perspective
(b) New sustainability paradigm: Sustainable globalization, changing
industrial society
Global Environmental
Outlook 492
2050 Environment,
development
Markets First, Policy First, Security First, Sustainability First
[correspond,
respectively, to 1(a), 1(b), 2(b), and 3(b) above]
IPCC-SRES42100 Climate change A1: Rapid market-driven growth, with convergence in incomes and culture;
rapid technological change
A2: Self-reliance and preservation of local identities; fragmented development
B1: Similar to A1, but emphasizes global solutions to sustainability, relying
heavily on technology
B2: Local technological and policy solutions to economic, social, and
environmental sustainability
World Business Council on
Sustainable
Development57–59
2050 Business and
sustainability
FROG!: Market-driven growth, economic globalization, and rapid technological
change
GEOpolity: Top-down approach to sustainability, with emphasis on technology
Jazz: Bottom-up approach to sustainability,
ad hoc
alliances, innovation
World Water Vision93 2025 Fresh water crisis Business-as-usual: Current water policies continue, high inequity
Technology, economics, and the private sector: Market-based mechanisms;
better technology
Values and lifestyles: Less water-intensive activities; ecological preservation
Millennium Ecosystem
Assessment1
2100 Ecosystems,
sustainability
Global orchestration: A globally connected world with well-developed global
markets and supranational institutions to deal with global environmental
problems and inequity
Order of strength: A fragmented world concerned with security and protection
of regional markets and with little attention for common goods
Adapting mosaic: A fragmented world resulting from discredited global
institutions leads to the rise of local and regional initiatives supporting
common goods
TechnoGarden: A globally connected world relying strongly on technology, also
for solving environmental problems and global inequity
618 2010 John Wiley & Sons, Ltd. Volume 1, July/August 2010
WIREs Climate Change Developing qualitative scenario storylines
APPENDIX 2: RECENT REGIONAL STORYLINES
Study Region Horizon Focus Storylines
Africa Environmental
Outlook 294
Africa 2025 Environment,
development
Market forces: Market-driven globalization, trade
liberalization, institutional modernization
Latin America and the
Caribbean
Environmental
Outlook95
Latin America 2032 Policy reform: Strong policy focus on meeting
sustainability goals through technology
Fortress world: Authoritarian rule with elites in
‘fortresses’, poverty, and repression outside
Great transitions: Fundamental changes in values,
lifestyles, and institutions; sustainable
globalization
Southern Africa MA96 Southern Africa 2030 Ecosystems,
sustainability
African patchwork: Regional fragmentation,
ineffective governance, little investment in health
and education, localized military conflicts
African partnership: Regional cooperation with
strong central governance, political stability and
economic growth, significant development
SRES-based scenarios
:Europe A1:Rapidmarket-drivengrowth;convergencein
incomes and culture; rapid technological change
ATEAM55,84 2080 Global change
vulnerability
A2: Self-reliance and preservation of local identities;
fragmented development
EURuralis52 2030 Rural regions B1: Global solutions to sustainability; heavy reliance
on technology
ACCELERATES53,54 2080 Agricultural land use B2: Local technological and policy solutions to
sustainability
PRELUDE2Europe 2035 Environment Great escape: Contrasts between urban centers and
rural regions
Evolved society: Harmony between environmental
awareness and policy intervention
Clustered network: Social coordination with
expanded infrastructure and compact cities
Lettuce surprise U: Innovation leading to
environmental friendly solutions
Big crisis: Cohesion with a strong government
focusing on sustainability
ALARM48,82 Europe 2080 Biodiversity GRAS: Growth applied strategy with a focus on
economic development
BAMBU: Business as might be usual
SEDGE: Focus on achieving the sustainable European
development goal
FARO-EU46 Europe 2030 Rural development Muskateer: A strong belief that the public sector
must intervene to solve social, economic, and
environmental problems
Marketeer: A strong belief that market liberalization
will achieve solutions to social, economic, and
environmental problems
ESPON3Europe 2030 Spatial planning
Competitiveness oriented future
with market
liberalization and reduced policy intervention
Cohesion oriented future
with increased policy
support to rural regions and the environment
Volume 1, July/August 2010 2010 John Wiley & Sons, Ltd. 619
