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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 a number of limitations in the current scenario storyline development methods. 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. Copyright © 2010 John Wiley & Sons, Ltd. This article is categorized under: Assessing Impacts of Climate Change > Scenario Development and Application Integrated Assessment of Climate Change > Integrated Scenario Development
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Advanced Review
Developing qualitative scenario
storylines for environmental
change assessment
Mark D. A. Rounsevelland 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
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:
School of Geosciences, University of Edinburgh, Edinburgh EH8
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
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
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
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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Advanced Review
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.
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 (
target), the Millennium Development Goals by 2015
(, 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 ( 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
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
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
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
Scale Issues
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
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
Normative Scenarios and Bayesian Belief
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
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
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.
Differences Between Existing Scenario
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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Advanced Review
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
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
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
Storyline Method
Saliency (Relevance for Decision
Makers’ Needs)
Credibility (Scientific Adequacy
of the Methods and Evidence)
Legitimacy (Unbiased
Incorporation of Divergent Values)
Compromised when the
focus has low policy relevance
method, described in a vast
body of research
on the beliefs of the scenario
analysts involved
Difficult to address
uncertainties in trajectories
toward the desired future
on the visions of the scenario
analysts involved.
relevant and based on
without alternatives and
uncertain developments
Based on current
values and beliefs
of stakeholder mental models
and internal consistency
consulted, but dependent on
those individuals
leading to communication
representation of uncertainty
communication issues due to
Scaling methods
thematic resolution enhances
the relevance to local
scaling introduces new process
information or is simply a
graphical representation
stakeholder acceptance of
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
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
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
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?
1. MA. Ecosystems and Human Well-Being: Findings
of the Scenarios Working Group of the Millennium
Ecosystem Assessment. Washington DC: Island Press;
2. EEA. Land-Use Scenarios for Europe: Qualitative And
Quantitative Analysis on a European Scale.EEATech-
nical report 09/2007. Copenhagen: European Environ-
ment Agency; 2007, 256 pp.
3. ESPON. Scenarios on the territorial future of Europe.
Report of the ESPON project; 2007. Available at: www., (Accessed March 22, 2010).
4. Naki´
Fenhann J, Gaffin S, Gregory K, Gr ¨
ubler A, Jung TY,
Kram T, et al. IPCC Special Report on Emissions Sce-
narios (SRES). Cambridge: Cambridge University Press;
2000, 600 pp.
5. Cash DW, Clark WC, Alcock F, Dickson NM,
Eckley N, Guston DH, J ¨
ager J, Mitchell RB. Knowl-
edge systems for sustainable development PNAS 2003,
6. Bradfield R, Wright G, Burt G, Cairns GV, der Heij-
den K. The origins and evolution of scenario techniques
in long range business planning. Futures 2005, 37:
7. von Reibnitz U. Scenario Techniques. Hamburg:
McGraw-Hill GmbH; 1988.
8. Kahn H, Wiener AJ. The Year 2000: A Framework for
Speculation on the Next Thirty-three Years.NewYork:
Macmillan; 1967.
9. Raubitschek R. Multiple scenario analysis and business
planning In: Lamb R, Shrivastava P, eds. Advances in
Strategic Management.Vol.5.London:JAIPressInc.;
614 2010 John Wiley & Sons, Ltd. Volume 1, July/August 2010
WIREs Climate Change Developing qualitative scenario storylines
10. Meadows DH, Meadows DL, Randers J, Behrens WW
III. Limits to Growth.NewYork:UniverseBooks;
11. Mesarovic M, Pestel E. Mankind at the Turning Point:
The Second Report to the Club of Rome.NewYork:
Dutton; 1974.
12. Wack P. Scenarios: uncharted waters ahead. Harv Bus
Rev 1985, 5:7289.
13. Wack P. Scenarios: shooting the rapids. Harv Bus Rev
1985, 6:139150.
14. Linneman R, Klein HE. The use of multiple scenar-
ios by US industrial companies: a comparison study
1977–1981. Long Range Plann 1983, 16:94101.
15. Galer G. Preparing the Ground? Scenarios and political
change in South Africa. Development 2004, 47:26 34.
16. Segal N. Breaking the Mould: The Role of Scenarios in
Shaping South Africa’s Future.SunPressStellenbosch;
2007, 95 pp.
17. Sunter C. The World and South Africa in the 1990s.
Human and Rousseau and Tafelberg: Cape Town;
18. Kahn H, Brown W, Martel L. The Next 200 Years:
AScenario for America and the World.NewYork:
Morrow; 1976.
19. WCED (World Commission on Environment and
Development). Our Common Future. Oxford, UK:
Oxford University Press; 1987.
20. Meadows DH, Meadows DL, Randers J. Beyond the
Limits: Confronting Global Collapse, Envisioning a
Sustainable Future. Post Mills, VT: Chelsea Green Pub-
lishing Company; 1992.
21. Rotmans J. IMAGE: An Integrated Model to Assess
the Greenhouse Effect. Dordrecht, The Netherlands:
Kluwer; 1990.
22. Rotmans J, Hulme M, Downing TE. Climate change
implications for Europe: an application of the ESCAPE
model. Glob Environ Change 1994, 4:97124.
23. Burrows B, Mayne A, Newbury P. Into the 21st
Century: A Handbook for a Sustainable Future.Twick-
enham, UK: Adamantine; 1991.
24. Milbrath L. Envisioning a Sustainable Society: Learning
our Way Out.Albany,NewYork:SUNYPress;1989.
25. Raskin P, Chadwick M, Jackson T, Leach G. The Sus-
tainability Transition: Beyond Conventional Develop-
ment. Stockholm Environment Institute Stockholm;
26. Raskin P, Gallopin G, Gutman P, Hammond A,
Swart R. Bending the Curve: Toward Global Sustain-
27. Raskin P, Banuri T, Gallopin G, Gutman P,
Hammond A, Kates R, Swart R. Great Transition: The
Promise and Lure of the Times Ahead. Boston: Stock-
holm Environment Institute/Tellus Institutes; 2002.
Available at: (Accessed March 22,
28. UNEP (United Nations Environment Programme).
Global Environmental Outlook.London:Earthscan;
29. EEA. Scenarios as Tool for International Environmen-
tal Assessments.EnvironmentalissuereportNo.24.
Copenhagen: European Environment Agency; 2001, 31.
30. Alcamo J. The SAS approach: combing qualitative and
quantitative knowledge in environmental scenarios. In:
Alcamo J, ed. Environmental Futures: The Practice
of Environmental Scenario Analysis.Amsterdam,The
Netherlands: Elsevier; 2008, 123150.
31. Carpenter SR, DeFries R, Dietz T, Mooney HA,
Polasky S, Reid WV, Scholes RJ. Millennium ecosys-
tem assessment: research needs. Science 2006, 314:
32. Alcamo J, ed. Environmental Futures: The Practice of
Environmental Scenario Analysis.Amsterdam:Elsevier;
2008, 224 pp.
33. Millett S. The future of scenarios: challenges and oppor-
tunities. Strategy Leadersh 2003, 31:1624.
34. Bishop P, Hines A, Collins T. The current state of
scenario development: an overview of techniques. Fore-
sight 2007, 9:525.
35. Borjeson L, Hojer M, Dreborg I, Ekvall T, Finnve-
den G. Scenario types and techniques: towards a user’s
guide. Futures 2006, 38:723739.
36. Van Notten PWF, Sleegers AM, van Asselt BMA. The
future shocks: on discontinuity and scenario develop-
ment. Technol Forecast Soc Change 2005, 72:175194.
37. Godet M, Roubelat F. Creating the future: the use and
misuse of scenarios. Long Range Plann 1996, 29:
38. Godet M. Integration of scenarios and strategic man-
agement: using relevant, consistent and likely scenarios.
Futures 1990, 22:730739.
39. Van Notten PWF, Rotmans J, Van Asselt MBA, Roth-
man DS. An updated scenario typology. Futures 2003,
40. Wilkinson A, Eidinow E. Evolving practices in environ-
mental scenarios: a new scenario typology. Environ Res
Lett 2008, 3:045016.
41. Lorenzoni I, Jordan A, Hulme M, Turner RK,
O’Riordan T. A co-evolutionary approach to climate
change impact assessment. Part I. Integrating socio-
economic and climate change scenarios. Glob Environ
Change 2000, 10:5768.
42. Lorenzoni I, Jordan A, O’Riordan T, Turner RK,
Hulme M. A co-evolutionary approach to climate
change impact assessment. Part II. A scenario-based
case study in East Anglia (UK). Glob Environ Change
2000, 10:145155.
Volume 1, July/August 2010 2010 John Wiley & Sons, Ltd. 615
Advanced Review
43. Kuhlman T. Scenarios: driving forces and policies.
Helming K, Perez-Soba M, Tabbusch P, eds. Sustain-
ability Impact Assessment of Land Use Changes.Berlin,
Germany: Springer; 2008, 131157.
44. Schwartz P. The Art of the Long View, Planning for the
Future in an Uncertain World.Chichester:JohnWiley
45. Van der Heijden K. Scenarios: The Art of Strategic Con-
46. Metzger MJ, Rounsevell MDA, Van den Heiligenberg
HARM, Perez-Soba M, Soto Hardiman P. How per-
sonal judgement influences scenario development: an
example for future rural development in Europe. Ecol
Soc 2010. Available at: http://www.ecologyandsociety.
47. Spangenberg JH. Integrated scenarios for assessing bio-
diversity risks. Sustainable Dev 2007, 15:343356.
48. Reginster I, Rounsevell MDA, Riguelle F, Carter TR,
Fronzek S, Omann I, Spangenberg JH, Stocker A,
Bondeau A, Hickler T. The effects of alternative socio-
economic and environmental policies on European land
use from 2006 to 2080. Land Use Policy.Inpress.
49. Foran T, Lebel L. Informed and fair? Water and
trade futures in the border regions of mainland
southeast Asia. USER Working Paper WP-2007-02
Unit for Social and Environmental Research, Chiang
Mai University, Chiang Mai, 2007. Available
at: pubdoc.php?
doc=3730. (Accessed March 22, 2010).
50. Zurek M, Henrichs T. Linking scenarios across geo-
graphical scales in international environmental assess-
ments. Technol Forecast Soc Change 2007, 74:
51. Schr ¨
oter D, Cramer W, Leemans R, Prentice IC, Ara ´
MB, Arnell NW, Bondeau A, Bugmann H, Carter TR,
Garcia CA, et al. Ecosystem service supply and human
vulnerability to global change in Europe. Science 2005,
52. Westhoek HJ, van den Berg M, Bakkes JA. Scenario
development to explore the future of Europe’s rural
areas. Agric Ecosyst Environ 2006, 114:720.
53. Audsley E, Pearn KR, Simota C, Cojocaru G, Kout-
sidou E, Rounsevell MDA, Trnka M, Alexandrov V.
What can scenario modelling tell us about future Euro-
pean scale land use, and what not? Environ Sci Policy
2006, 9:148162.
54. Berry PM, Rounsevell MDA, Harrison PA, Audsley E.
Assessing the vulnerability of agricultural land use and
species to climate change and the role of policy in facili-
tating adaptation. Environ Sci Policy 2006, 9:189204.
55. Rounsevell MDA, Ewert F, Reginster I, Leemans R,
Carter TR. Future scenarios of European agricultural
land use. II: projecting changes in cropland and grass-
land. Agric Ecosyst Environ 2005, 107:117135.
56. UNAIDS. Aids in Africa: three scenarios to 2025.
Available at:,
2005. (Accessed March 22, 2010).
57. WBCSD (World Business Council for Sustainable Devel-
opment). Exploring Sustainable Development.Sum-
mary brochure. Geneva: WBCSD; 1997. Available
exploringscenarios.pdf. (Accessed March 22, 2010).
58. WBCSD (World Business Council for Sustainable
Development). Energy 2050: Risky Business.Geneva:
WBCSD; 1999. Available at: http://
(Accessed March 22, 2010).
59. WBCSD (World Business Council for Sustainable Devel-
opment). Biotechnology Scenarios 2000–2050.Geneva:
WBCSD; 2000. Available at:
(Accessed March 22, 2010).
60. Patel M, Kok K, Rothman DS. Participatory scenario
construction in land use analysis: an insight into the
experiences created by stakeholder involvement in the
Northern Mediterranean. Land Use Policy 2007, 24:
61. Volkery A, Ribeiro T, Henrichs T, Hoogeveen Y. Your
vision or my model? Lessons from participatory land
use scenario development on a European scale. Syst
Pract Action Res 2008, 21:459477.
62. Lebel L, Bennett E. Participation in building scenarios
of regional development. In: Norberg J, Cumming GS,
eds. Complexity Theory for a Sustainable Future.New
York: Columbia University Press; 2008, 207– 222.
63. Lebel L. Multi-level scenarios for exploring alterna-
tive futures for upper tributary watersheds in mainland
Southeast Asia. Mountain Res Dev 2006, 26:263273.
64. Kok K, Patel M, Rothman DS, Quaranta G. Multi-scale
narratives from an IA perspective: part II. Participatory
local scenario development. Futures 2006, 38:285– 311.
65. Andersen I-E, Jaeger B. Scenario workshops and con-
sensus conferences: towards more democratic decision-
making. Sci Public Policy 1999, 26:331– 340.
66. Wollenberg E, Edmunds D, Buck L. Using scenarios to
make decisions about the future: anticipatory learning
for the adaptive co-management of community forests.
Landsc Urban Plan 2000, 47:6577.
67. Kok K, Biggs R, Zurek M. Methods for developing mul-
tiscale participatory scenarios: insights from Southern
Africa and Europe. Ecol Soc 2007, 13:8.
68. Abildtrup J, Audsley E, Fekete-Farkas M, Giupponi C,
Gylling M, Rosato P, Rounsevell MDA. Socio-economic
scenario development for the assessment of climate
change impacts on agricultural land use. Environ Sci
Policy 2006, 9:101115.
69. Saaty TL. The Analytic Hierarchy Process.NewYork:
McGraw Hill; 1980.
70. Kok K. The potential of Fuzzy Cognitive Maps for semi-
quantitative scenario development, with an example
from Brazil. Glob Environ Change 2009, 19:122133.
616 2010 John Wiley & Sons, Ltd. Volume 1, July/August 2010
WIREs Climate Change Developing qualitative scenario storylines
71. Bringezu S, Saurat M, Haines-Young R, Rollet
A, Svensson M. FORESCENE Final Report. Avail-
able at:, 2009.
(Accessed March 22, 2010).
72. Charniak E. Bayesian networks without tears. AI Mag
1991, 12:5063.
73. Uusitalo L. Advantages and challenges of Bayesian net-
works in environmental modelling. Ecol Model 2007,
74. Castelletti A, Soncini-Sessa R. Bayesian Networks and
participatory modelling in water resource management.
Environ Model Softw 2007, 22:10751088.
75. Aspinall R. An inductive modelling procedure based on
Bayes’ theorem for analysis of pattern in spatial data.
Int J Geogr Inf Syst 1992, 6:105121.
76. Tucker K, Rushton SP, Sanderson RA, Martin EB,
Blaiklock J. Modelling bird distributions—a combined
GIS and Bayesian rule based approach. Landsc Ecol
1997, 12:7793.
77. Bacon PJ, Cain JD, Howard DC. Belief network mod-
els of land manager decisions and land-use change.
J Environ Manage 2002, 65:123.
78. Aalders I. Modelling land-use decision behaviour with
Bayesian belief networks. Ecol Soc 2008, 13:16.
79. Jensen FV, Nielsen TD. Bayesian Networks and Deci-
sion Graphs.2nded.IEEEComputerSociety,Springer,
New York; 2007, 463.
80. O’Neill BC. Conditional probabilistic population pro-
jections: an application to climate change. Int Stat Rev
2004, 72:167184.
81. O’Neill BC. Population scenarios based on probabilistic
projections: an application for the Millennium. Ecosyst
Assess Popul Environ 2005, 26:229254.
82. Settele J, Hammen V, Hulme P, Karlson U, Klotz S,
Kotarac M, Kunin W, Marion G, O’Connor M,
Petanidou T, et al. ALARM: assessing Large-scale envi-
ronmental risks for biodiversity with tested methods.
Gaia 2005, 14:6972.
83. Busch G. Future European agricultural landscapes-
What can we learn from existing quantitative land
use scenario studies? Agric Ecosyst Environ 2006, 114:
84. Rounsevell MDA, Reginster I, Ara ´
ujo MB, Carter TR,
Dendoncker N, Ewert F, House JI, Kankaanp ¨
mans R, Metzger MJ, et al. A coherent set of future land
use change scenarios for Europe. Agric Ecosyst Environ
2006, 114:5768.
85. Carter TR, Jones RN, Lu X, Bhadwal S, Conde C,
Mearns LO, O’Neill BC, Rounsevell MDA, Zurek MB.
New assessment methods and the characterisation of
future conditions. In: Parry ML, Canziani OF, Palu-
tikof JP, van der Linden PJ, Hanson CE, eds. Climate
Change 2007: Impacts, Adaptation and Vulnerabil-
ity. Contribution of Working Group II to the Fourth
Assessment Report of the Intergovernmental Panel on
Climate Change, Cambridge, UK: Cambridge University
Press; 2007, 133171.
86. De Vries JM, Petersen AC. Conceptualizing sustainable
development. An assessment methodology connecting
values, knowledge, worldviews and scenarios. Ecol
Econ 2009, 68:10061019.
87. Parson EA. Useful global change scenarios: current
issues and challenges. Environ Res Lett 2008, 3:045016.
88. Hulme M, Dessai S. Predicting, deciding, learning: can
one evaluate the ‘‘success’’ of national climate scenar-
ios? Environ Res Lett 2008, 3:045013.
89. Bryson J, Piper J, Rounsevell MDA. Experiences of
using scenarios in three European environmental policy
institutions. Environ Policy Governance.Inpress.
90. Rashkin PD. Global scenarios: background review
for the millennium ecosystem assessment. Ecosystems
2005, 8:133142.
91. Rothman D. Environmental scenarios—a survey. In:
Alcamo J, ed. Environmental Futures: The Practice
of Environmental Scenario Analysis.Amsterdam,The
Netherlands: Elsevier; 2008, 3765.
92. UNEP (United Nations Environment Programme).
Global Environmental Outlook 4. Valletta, Malta:
Progress Press Ltd.; 2007. Available at: http://www. (Accessed March 22, 2010).
93. Gallop´
ın GC, Rijsberman F. Three global water scenar-
ios. Int J Water 2000, 1:1640.
94. UNEP (United Nations Environment Programme).
Africa Environment Outlook 2: Our Environment,
Our Wealth. Valletta, Malta: Progress Press Ltd.;
2006. Available at:
aeo2 launch. (Accessed March 22, 2010).
95. UNEP (United Nations Environment Programme).
Latin America and the Caribbean Environmental Out-
look. Available at:
lac2003English.pdf, 2003. (Accessed March 22, 2010).
96. Scholes and Biggs Ecosystem services in Southern Africa:
a regional assessment. A contribution to the Millennium
Ecosystem Assessment, prepared by the regional-scale
team of the Southern African Millennium Ecosystem
Assessment, 2004.
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
Study Horizon Focus Storylines
Global Scenario Group27 2050 Environment,
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
(a) Eco-communalism: Local focus and a bioregional perspective
(b) New sustainability paradigm: Sustainable globalization, changing
industrial society
Global Environmental
Outlook 492
2050 Environment,
Markets First, Policy First, Security First, Sustainability First
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
2050 Business and
FROG!: Market-driven growth, economic globalization, and rapid technological
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
2100 Ecosystems,
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
Study Region Horizon Focus Storylines
Africa Environmental
Outlook 294
Africa 2025 Environment,
Market forces: Market-driven globalization, trade
liberalization, institutional modernization
Latin America and the
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
Southern Africa MA96 Southern Africa 2030 Ecosystems,
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
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
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
... Then, inspired by narrative scenarios from environmental science and policy (Rounsevell and Metzger, 2010;IPCC, 2000), we utilize an elaborate thought experiment to contextualize our framework and aid its further development. Concretely, we use disciplined imagination (Weick, 1989) to create a rich "dystopian" scenario ) of a flood hitting the Dutch coast. ...
... Yet, little theorizing exists about how firms' disaster reactions affect other firms, and how such collective interactions may 'trickle up' to shape community resilience. In what follows, we use an elaborate thought experiment-a narrative scenario (Rounsevell and Metzger, 2010;Shepherd et al., 2018)-to show our theory in context and aid its further development by accounting for such temporal and cross-level dynamics. ...
... Thought experiments are common in science. Plato's description of the utopian city-state in the Republic, Darwin's 'imaginary illustrations' about the Origin of Species, Adam Smith's pin factory in the Wealth of Nations, and Einstein's 'falling elevator' example all left a mark on their respective disciplines (Rounsevell and Metzger, 2010;Kornberger and Mantere, 2020;Zalta et al., 2005). Max Weber is frequently cited as the first to recommend thought experiments for social research (Ragin, 2009, p.151), and scenarios in particular have been used by influential thinkers such as Herbert Simon (see Kornberger and Mantere, 2020). ...
Full-text available
Communities around the world face increasing risks of climate disasters such as floods, hurricanes, and droughts. What drives firms’ heterogeneous responses to a climate disaster, and what could be the consequences for community resilience? To address these questions, we theorize how different aspects of sensemaking (sense of place, time, certitude, and loss) affect firm responses. Then, aided by an elaborate thought experiment—a narrative scenario of a future flood hitting the Dutch coast—we theorize how heterogeneity in firms’ initial responses can trigger sensemaking-sensegiving cycles that spiral a community toward reconstruction or unplanned retreat. Our article advances understanding of firms’ heterogenous disaster responses, the drivers of community resilience, and uncovers potential tensions between organizational and community resilience. We also contribute to sensemaking theory by relaxing the popular assumption that sensegiving requires deliberation. Finally, our article showcases how narrative scenarios of future events can expand the methodological toolkit of organization theory and points to new opportunities for future interdisciplinary work.
... Such scenarios can then be used to frame various modelling exercises, for example, in the quantification of land use, demography and impacts on the energy sector, food system or nature. Exploring potential future societal conditions has been the subject of decades of scenario development work across a large range of disciplines (Rounsevell et al., 2021;Rounsevell & Metzger, 2010). For climate change applications, the Shared Socioeconomic Pathways (SSPs) are the most recent and widely used set of global socioeconomic scenarios, especially within the context of the assessment reports of the Intergovernmental Panel on Climate Change (IPCC) (O'Neill et al., 2020). ...
... Scenario modelling is often assessed with respect to credibility, saliency, and legitimacy (Rounsevell & Metzger, 2010). All three quality criteria are enhanced when researcher-driven and stakeholder-driven methods are combined (Star et al., 2016). ...
... Importantly, the observed equifinality in the UK-SSP scenarios (Rounsevell & Metzger, 2010) does not imply that some scenarios are more likely or plausible than others. The convergent results for some indicators in UK-SSP1 and UK-SSP5 suggest that socioeconomics is an important driver to reduce challenges to climate adaptation. ...
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The Shared Socioeconomic Pathways (SSPs) were developed as a framework for exploring alternative futures with challenges for climate change mitigation and adaptation. Whilst originally developed at the global scale, the SSPs have been increasingly interpreted at the national scale in order to inform national level climate change policy and impact assessments, including mitigation and adaptation actions. Here, we present a set of quantitative SSP scenario projections, based on narratives and semi-quantitative trends, for the UK (the UK-SSPs) for a wide range of sectors that are relevant to the UK climate research, policy and business communities. We show that a mixed-methods approach that combines computational modelling with an interpretation of stakeholder storylines and empirical data is an effective way of generating a comprehensive range of quantitative indicators across sectors and geographic areas in a specific national context. The global SSP assumptions of low challenges to climate adaptation lead to similar socioeconomic outcomes in UK-SSP1 and UK-SSP5, although based on very different dynamics and underlying drivers. Convergence was also identified in indicators related to more efficient natural resource use in the scenarios with low challenges to climate change mitigation (UK-SSP1 and UK-SSP4). Alternatively, societal inequality played a strong role in scenarios with high challenges to adaptation leading to convergence in indicator trends (UK-SSP3 and UK-SSP4).
... To our knowledge, no study has yet combined (i) spatially-explicit modelling of LULC in the Kafue study area with (ii) the analysis of proximate causes and underlying drivers of deforestation, (iii) the development of future REDD+ policy-screening scenarios for the year 2040 and (iv) an environmental impact assessment using cropland and forest-related LULC trajectory, carbon stock changes, and forest connectivity as indicators. While scenarios aid in exploring consistent and plausible storylines about future forest cover change and REDD+ interventions (Alcamo, 2008;IPBES, 2016;Rounsevell and Metzger, 2010;Zurek and Henrichs, 2007), land use and land cover (LULC) change models act as a computational tool to support the analysis and visualization of the causes and impacts on environmental functioning in the future (Verburg et al., 2004). ...
... For this study, scenarios were developed following the guidelines of IPBES (2016) and Rounsevell and Metzger (2010) by screening land-use related national policy documents against specific quantitative area targets to develop or protect the Zambian forest landscapes. This further included insights from the analysis of drivers and causes of deforestation in the form of a causal loop diagram. ...
... We used a combination of qualitative policy scenario storylines with quantitative LCM results to investigate the consequences of current actions on environmental functioning (Alcamo, 2008;Verburg et al., 2004). The process of policy scenario development followed the generic stages described in Rounsevell and Metzger (2010). To gather relevant information for the scenario storylines, we screened LULC related policies of Zambia against quantitative targets such as forest area to conserve or protect. ...
Land use and land cover (LULC) dynamics in tropical forests of sub-Saharan Africa are often difficult to quantify and predict, despite rapid forest losses and increasing human population pressure. As deforestation threatens the biodiversity of both flora and fauna, we used LULC change assessment and scenario modelling to analyse whether policy measures can safeguard the multi-functionality of tropical dry forests in western Zambia from 2010 to 2040. Our data comprised information on deforestation and human encroachment due to i.e., agricultural expansion, charcoal production, infrastructure development in the Kafue National Park (NP) and adjacent Game Management Areas (GMAs) (total area: 7,102,147 ha), which is part of the first Reducing Emissions from Deforestation and Forest Degradation (REDD+) focus areas in Zambia. We modelled a business-as-usual scenario (BAU) and four REDD+ policy-screening scenarios with varying levels of protection enforcement and future annual deforestation rates. We quantified scenario impacts on forest cover using three indicators: cropland and forest-related LULC trajectory, forest connectivity, and long-term carbon stock changes in 2040. Scenario results suggested that only under strong enforcement and low demand for agricultural areas, deforestation in Kafue NP and GMAs could be avoided by 93% (40,457 ha) and 1% in carbon stocks could be gained by 2040 in comparison to BAU. Spatial analyses revealed that cropland expansion will continue to encroach protected areas. We highlight that variations in carbon stocks and forest fragmentation were small across scenarios which has implications for land use management and the expected future benefits of REDD+ projects. The combination of GIS, scenario development and LULC modelling helped to identify and locate potential future deforestation and LULC changes. This can support appropriate management pathways of REDD+ induced local and national leakage effects and related decision making.
... way that builds trust(Voinov et al. 2016; Frame et al. 2018), allows end users to develop their understanding of a model(Rounsevell & Metzger 2010; IPBES 2016;Iwanaga et al. 2018), and enables modellers to build in knowledge of the system studied from those whose questions they are answering(Voinov & Bousquet 2010; Landström et al. 2011; Ferrier et al. 2016; Iwanaga et al. 2018). Co-creation is an iterative and challenging reflexive process (Rounsevell & Metzger 2010; Voinov et al. 2016; Frame et al. 2018), especially in the context of integrated models which are often seen as complex, "blackbox" systems with compound uncertainties (Gambhir et al. 2019; Robertson 2021). ...
... Based on our experience, we reflect on the merits of using illustration-based interviews to support land management visions in general and STREAMLINE specifically. We focus on saliency, credibility and legitimacy which are often noted as three competing priorities in sustainability research in general (Cash et al., 2003), including visioning methods (Rounsevell & Metzger, 2010). ...
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Visions help to understand common ground and tensions among citizens and stakeholders, supporting inclusive land management and conservation solutions to the climate emergency and biodiversity crisis. With careful design and sufficient resource, it is possible to bring together communities and other stakeholders to share perspectives and deliberate desired futures, identifying more acceptable alternatives and avoiding costly delays. We evaluated researcher and participant experiences of illustration-based interviews to understand land management visions using four studies in Scotland, The Netherlands and Spain. These studies used STREAMLINE, a visual mixed-method interview format using thematic illustrated canvases designed to provide an inclusive and creative framing for participants to contemplate their desired future. Participants enjoyed the informal visual format, which reduced pressure, increased comfort through the research process, and helped their thinking and reflection about complex topics. They also valued being listened to and having the opportunity to share their views. Researchers appreciated the ability to triangulate rich qualitative data with a variety of quantitative measure through the mixed-method format and the flexibility to adapt the canvases to suit their research aims. Positive participant experience made facilitation easier and was stimulating for the researchers. The credibility and legitimacy of illustration-based interviews will ultimately depend on specific research design-decisions and testing, which can make the approach more resource intensive than conventional interviews. While organisa-tional barriers should be considered realistically, illustration-based interviews can have high saliency by providing useful and usable insights that strengthen land management policy and planning.
... Based on this framework, LULC change scenarios have been developed to explore the effect of different biophysical and socioeconomic factors on the future of land use [54][55][56] in the Colombian Amazon for the year 2040. For this purpose, three storylines were prepared by a group of 6 experts with wide environmental and scientific knowledge of the region, using interviews 30 . Expert interviews were orientated to briefly narrate events and contextualize factors that should be present and will drive the future of the Amazon in the next 20 years. ...
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Pastures and crops have been expanding at an accelerated rate in the forests of the Colombian Amazon since the peace accords were signed in 2016. The rapid loss of tropical rainforests is threatening the integrity of protected areas and connectivity in the Amazon and other natural regions. In the context of the post-conflict stage, a set of land use and land cover change scenarios were constructed for the Colombian Amazon for the year 2040, using expert coherent narratives. Three scenarios were designed: trend, extractivist, and sustainable development. Historic land use change and driving factors were analyzed throughout 14 transitions between the years 2002 and 2016, based on the interpretation of Landsat images and their relationship with 29 driving factors using artificial neural networks. The Markov chain model was calculated for the transitions, and the change allocation model was parameterized to spatially simulate the scenarios. The results showed that the LULC model calibration and validation were satisfactory (0.91). The sustainable development scenario that considers strong policies for the conservation of forests and implementation of sustainable production projects was the option with greater values for conserved forests and secondary vegetation in recovery, adding ~ 42 million hectares by 2040. The other scenarios showed that the Colombian Amazon will lose ~ 2 million hectares of forests in the trend scenario and ~ 4.3 million hectares in the extractivist scenario, based on the reference year (2016). In the trend scenario, pastures and crops could increase by 48%; and, in the extractivist scenario, these would increase by 117%, changing from ~ 3.9 to ~ 8.6 million hectares. We hope that the scientific contribution of this study will be relevant for informed discussion in decision-making and provide a framework for building a peaceful territory.
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Hydrological extremes, such as droughts and floods, can trigger a complex web of compound and cascading impacts due to interdependencies between coupled natural and social systems. However, current decision-making processes typically only consider one impact and disaster event at a time, ignoring causal chains, feedback loops, and conditional dependencies between impacts. Analyses capturing these complex patterns across space and time are thus needed to better inform effective adaptation planning. This perspective paper aims to bridge this critical gap by presenting methods for assessing the dynamics of the multi-sector compound and cascading impacts (CCI) of hydrological extremes. We discuss existing challenges, good practices, and potential ways forward. Rather than pursuing a single methodological approach, we advocate for methodological pluralism. We see complementary roles for analyses building on quantitative (e.g. data-mining, systems modeling) and qualitative methods (e.g. mental models, qualitative storylines). We believe the data-driven and knowledge-driven methods provided here can serve as a useful starting point for understanding the dynamics of both high-frequency CCI and low-likelihood but high-impact CCI. With this perspective, we hope to foster research on CCI to improve the development of adaptation strategies for reducing the risk of hydrological extremes.
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The resilience of river catchments and the vital socio-ecological services they provide are threatened by the cumulative impacts of future climatic and socio-economic change. Stakeholders who manage freshwaters require tools for increasing their understanding of catchment system resilience when making strategic decisions. However, unravelling causes, effects and interactions in complex catchment systems is challenging, typically leading to different system components being considered in isolation. In this research, we tested a five-stage participatory method for developing a Bayesian network (BN) model to simulate the resilience of the Eden catchment in eastern Scotland to future pressures in a single transdisciplinary holistic framework. The five-stage participatory method involved co-developing a BN model structure by conceptually mapping the catchment system and identifying plausible climatic and socio-economic future scenarios to measure catchment system resilience. Causal relationships between drivers of future change and catchment system nodes were mapped to create the BN model structure. Appropriate baseline data to define and parameterise nodes that represent the catchment system were identified with stakeholders. The BN model measured the impact of diverse future change scenarios to a 2050 time horizon. We applied continuous nodes within the hybrid equation-based BN model to measure the uncertain impacts of both climatic and socio-economic change. The BN model enabled interactions between future change factors and implications for the state of five capitals (natural, social, manufactured, financial and intellectual) in the system to be considered, providing stakeholders with a holistic catchment-scale approach to measure the resilience of multiple capitals and their associated resources. We created a credible, salient and legitimate BN model tool for understanding the cumulative impacts of both climatic and socio-economic factors on catchment resilience based on stakeholder evaluation. BN model outputs facilitated stakeholder recognition of future risks to their primary sector of interest, alongside their interaction with other sectors and the wider system. Participatory modelling methods improved the structure of the BN through collaborative learning with stakeholders while providing stakeholders with a strategic systems-thinking approach for considering river basin catchment resilience
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Abstract Storylines are introduced in climate science to provide unity of discourse, integrate the physical and socioeconomic components of phenomena, and make climate evolution more tangible. The use of this concept by multiple scholar communities and the novelty of some of its applications renders the concept ambiguous nonetheless, because the term hides behind a wide range of purposes, understandings, and methodologies. This semi‐systematic literature review identifies three approaches that use storylines as a keystone concept: scenarios—familiar for their use in IPCC reports—discourse‐analytical approaches, and physical climate storylines. After screening peer‐reviewed articles that mention climate and storylines, 270 articles are selected, with 158, 55, and 57 in each category. The results indicate that each scholarly community works with a finite and different set of methods and diverging understandings. Moreover, these approaches have received criticism in their assembly of storylines: either for lacking explicitness or for the homogeneity of expertise involved. This article proposes that cross‐pollination among the approaches can improve the usefulness and usability of climate‐related storylines. Among good practices are the involvement of a broader range of scientific disciplines and expertise, use of mixed‐methods, assessment of storylines against a wider set of quality criteria, and targeted stakeholder participation in key stages of the process.
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This publication series is produced by the Stockholm Environment Institute's PoleStar Project. Named after the star that guided voyagers through uncharted waters, the multi-year PoleStar Project addresses critical aspects of the transition to sustainability. Scenario analysis illuminates long-range problems and possibilities at global, regional, national and local levels. Capacity building strengthens professional capabilities for a new era of development. Policy studies fashion strategies and actions. The PoleStar System © provides a user-friendly tool for organizing pertinent data, formulating scenarios, and evaluating strategies for sustainable development. For more information, visit on the Internet. The Global Scenario Group was established to carry forward the global aspects of this work. The PoleStar publication series includes: 1. The Global Scenario Group engages a diverse group of development professionals in a long-term commitment to examining the requirements for sustainability. The GSG is an independent, international and inter-disciplinary body, representing a variety of geographic and professional experiences. Its work program includes global and regional scenario development, policy analysis and public education. The diversity and continuity of the GSG offer a unique resource for the research and policy communities. The GSG pursues its objectives through research, publication and collaboration with regional sustainable development projects. This report relies on the scenario framework developed in Branch Points: Global Scenarios and Human Choice (PoleStar #7) to examine alternative global futures. A companion document (PoleStar #9) provides technical details. For reports and more information, visit on the Internet.
This chapter discusses the pros and cons of qualitative and quantitative scenarios and the way they fulfill the different requirements of scenario developers and users. It also describes major international scenario exercises in which combined scenarios have been used. This international experience is distilled into a general procedure for combining qualitative and quantitative scenarios called the “story and simulation” (SAS) approach. In the chapter, the successes and drawbacks of this approach are pointed out and some ideas are presented for producing more scientifically sound scenarios. The qualitative storylines provide an understandable vehicle for communicating the messages of the scenarios and can express the more complex dimensions and interconnectedness of environmental problems. The quantitative scenarios provide a consistency check to the different assumptions of the qualitative scenarios and the numerical data often needed in environmental studies. To capitalize on their advantages, qualitative and quantitative scenarios have been combined in recent international scenario exercises.