CARRI Research Report 2
RESILIENCE IN THE FACE OF GLOBAL
ENVIRONMENTAL CHANGE
Susanne C. Moser
Director and Principal Scientist
Susanne Moser Research and Consulting
Santa Cruz, California
and
Research Associate
Institute of Marine Sciences
University of California–Santa Cruz
Date Published: September 2008
Community and Regional Resilience Initiative
RESEARCH FINDINGS ABOUT COMMUNITY
AND REGIONAL RESILIENCE
One of the commitments of the Community and Regional Resilience Initiative
(CARRI) is to understand what resilience is and how to get there, based on research
evidence.
As one resource for this effort, CARRI has commissioned a number of summaries of
existing knowledge about resilience, arising from a number of different research
traditions. This paper is one in a series of such summaries, which will be integrated
with new resilience explorations in several CARRI partner cities and with further
discussions with the research community and other stakeholders to serve as the
knowledge base for the initiative.
For further information about CARRI’s research component, contact Thomas J.
Wilbanks, wilbankstj@ornl.gov, or Sherry B. Wright, wrightsb@ornl.gov.
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Community and Regional Resilience Initiative
COMMUNITY AND REGIONAL RESILIENCE INITIATIVE
Oak Ridge National Laboratory’s (ORNL) Community and Regional Resilience Initiative
(CARRI) is a program of the Congressionally funded Southeast Region Research Initiative.
CARRI is a regional program with national implications for how communities and regions
prepare for, respond to, and recover from catastrophic events. CARRI will develop the
processes and tools with which communities and regions can better prepare to withstand the
effects of natural and human-made disasters by collaboratively developing an understanding of
community resilience that is accurate, defensible, welcomed, and applicable to communities
across the region and the nation.
CARRI is presently working with three partner communities in the Southeast: Gulfport,
Mississippi; Charleston/Low Country, South Carolina; and the Memphis, Tennessee, urban
area. These partner communities will help CARRI define community resilience and test it at the
community level. Using input from the partner communities, lessons learned from around the
nation, and the guidance of ORNL-convened researchers who are experts in the diverse
disciplines that comprise resilience, CARRI will develop a community resilience framework that
outlines processes and tools that communities can use to become more resilient. Of critical
importance, CARRI will demonstrate that resilient communities gain economically from
resilience investments.
From its beginning, CARRI was designed to combine community engagement activities
with research activities. Resilient communities are the objective, but research is critical to ensure
that CARRI’s understanding is based on knowledge-based evidence and not just ad hoc ideas—
we want to get it right. To help with this, CARRI has commissioned a series of summaries on
the current state of resilience knowledge by leading experts in the field. This kind of interactive
linkage between research and practice is very rare.
In addition to its partner communities and national and local research teams, CARRI has
established a robust social network of private businesses, government agencies, and nongovernmental associations. This network is critical to the CARRI research and engagement
process and provides CARRI the valuable information necessary to ensure that we remain on
the right path. Frequent conversation with business leaders, government officials, and volunteer
organizations provide a bottom-up knowledge from practitioners and stakeholders with realworld, on-the-ground, experience. We accept that this program cannot truly understand
community resilience based only on studies in a laboratory or university. CARRI seeks to
expand this social network at every opportunity and gains from each new contact.
www.resilientUS.org
CARRI Research Report 2
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Community and Regional Resilience Initiative
LIST OF RESEARCH PAPERS BY NUMBER
CARRI Report 1: Susan L. Cutter, Lindsey Barnes, Melissa Berry, Christopher Burton, Elijah
Evans, Eric Tate, and Jennifer Webb, Community and Regional Resilience:
Perspectives from Hazards, Disasters, and Emergency Management,
September 2008.
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CONTENTS
Page
RESEARCH FINDINGS ABOUT COMMUNITY AND REGIONAL RESILIENCE ....................... iii
COMMUNITY AND REGIONAL RESILIENCE INITIATIVE ............................................................v
LIST OF RESEARCH PAPERS BY NUMBER...................................................................................... vii
LIST OF FIGURES .....................................................................................................................................xi
LIST OF TABLES .......................................................................................................................................xi
1. INTRODUCTION ................................................................................................................................ 1
2. THE MEANING OF RESILIENCE IN THE FACE OF A RAPIDLY CHANGING
AND UNCERTAIN WORLD ............................................................................................................. 2
2.1 Definitions of Resilience to Global (Climate) Change ........................................................... 2
2.2 Emerging Understanding of Resilience ................................................................................... 5
3. INSIGHTS FROM THE STUDY OF GLOBAL CLIMATE AND ENVIRONMENTAL
CHANGE .............................................................................................................................................. 7
3.1 Vulnerability ................................................................................................................................ 7
3.2 Adaptive Capacity, Adaptation Options, Barriers, and Limits .......................................... 10
3.3 Criticality, Thresholds, Irreversibility and the Dangers of Abrupt Climate Change ...... 13
3.4 Social Capital and Learning .................................................................................................... 17
3.5 Governance Systems and the Role of Institutions................................................................ 20
3.6 Knowledge-Action Systems and the Role of Science in Enhancing Resilience ................ 24
3.7 Stakeholder Engagement—Promises and Pitfalls ................................................................ 27
4. SUMMARY AND SOME PROMISING RESEARCH FRONTIERS ............................................ 30
4.1 Summary of Insights vis-à-vis the Four CARRI Dimensions of Resilience ...................... 30
4.2 Additional Insights Relevant across the Four Resilience Dimensions .............................. 32
4.3 Promising Future Research Directions .................................................................................. 34
5. REFERENCES ..................................................................................................................................... 34
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LIST OF FIGURES
Figure
1
Page
Frameworks depicting two interpretations of vulnerability to climate change:
(a) outcome vulnerability; (b) contextual vulnerability .................................................... 8
LIST OF TABLES
Table
1
2
Page
Selected definitions of the concept of resilience ................................................................. 3
Promises and pitfalls of stakeholder engagement processes.......................................... 28
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1.
INTRODUCTION
Between adrenalin-rushing science fiction movies like Roland Emmerich’s The Day After
Tomorrow (2004) on the one hand and the sober, yet increasingly somber, scientific reports of the
Intergovernmental Panel on Climate Change on the other (e.g., IPCC 2007a,b), a shelf of
academic books has been filling up over the years that focus on the possible demise of human
civilization in the face of environmental catastrophe. Maybe the most prominent of these
captured the popular imagination and spawned significant scientific debate: Jared Diamond’s
Collapse (Diamond 2005). It attempts to explain why certain past societies have fallen to ruin in
the face of various stressors. Far from mere fin de siècle (or début de siècle, as it were) pessimism,
what Diamond’s and other non-bestselling books (e.g., Costanza, Graumlich and Steffen 2007;
Girardet 2007; Homer-Dixon 2006; Jensen 2006; Linden 2006; Martin 2006; Schellnhuber et al.
2006; Schwartz and Nichols 2006; Kunstler 2005; Ehrlich and Ehrlich 2004; Meadows, Randers
and Meadows 2004; Rees 2004; Cocks 2003; National Research Council 2002; Raskin et al. 2002;
Odum and Odum 2001; Harpin 2000; Leslie 1998; Meadows, Meadows, and Randers 1992;
Tainter 1988; Timmerman 1981; Meadows et al. 1972) share in common is a sense of urgency.
These scholars are taking a serious look at the challenges posed to nations around the globe by
unprecedented environmental degradation, resource depletion, loss of ecosystem services, and
increasing climatic disruption. However conscious we are of the fact, these scholars point to
humans’ intimate dependency on a functioning, plentiful, and stable environment. What if it
were that no more?
In fact, human societies—in both developed and developing nations—grew to their current
state of complexity and interdependence during a relatively stable climate. As catastrophes like
Hurricane Katrina in 2005 illustrated, even in highly developed countries it is far from assured
that the financial and technological means, the institutional capacity and flexibility, or the
political will are available or being employed effectively to avert significant disasters before
they occur or deal with them in a timely fashion if and when they do (Kates et al. 2006).
The most dire (low-probability but high-consequence) projections for the century ahead1
would make any conventional notions of “adaptation” appear rather quaint. Yet, even without
focusing on the most catastrophic scenarios of the world’s climate, oceans, and biosphere over
the next 100 years, the rapid pace of change in a highly globalized world with already
numerous “hotspots” of injustice, poverty, hunger and deprivation, warfare, and extreme
environmental degradation raise serious concerns for individual, community-level, national,
and global well-being (e.g., Leichenko and O’Brien 2008; Bankoff, Frerks, and Hilhorst 2004).
Situations can easily be imagined and are increasingly recognized in the scientific literature
where multiple stressors or crises (environmental and non-environmental, climatic and nonclimatic) converge (e.g., Schneider, Semenov, and Patwardhan 2007; Levins 2006; NRC 2006;
Turner et al. 2003; Holzmann 2001), exceeding the ability of any social-ecological entity to
sustain itself, that is, to recover after the crisis and continue functioning and thriving
(Folke 2006).
1
To name but a few examples: upwards of 6°C of warming, multiple feet or even meters of sea-level rise, loss of
large numbers of species, ecosystems, and the goods and services they provide, widespread “emptying” of the
oceans, stark increases in extreme weather events (e.g., IPCC 2007a; Overpeck et al. 2006; Tol et al. 2006; Millennium
Ecosystem Assessment 2005; Thomas et al. 2004; Ellis 2003; Raskin et al. 2002; Roberts et al. 1999).
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It is this context of a rapidly changing environment, and the question of society’s ability to
adapt to the multitude of interacting stresses, that a substantial research literature has emerged.
In its most recent strategic science plan, the International Human Dimensions Program has in
fact elevated resilience and its related concepts of vulnerability and adaptation as major crosscutting themes deserving of focused research attention over the coming years (IHDP 2007).
The purpose of this report is to distill relevant
Situations can easily be imagined
insights on resilience from the pertinent global
where multiple stressors or crises
change literature to complement critical insights
converge, exceeding the ability of
gleaned from the hazards and ecological literatures
any social-ecological entity to
by other collaborators to the CARRI project. It is
important to realize from the outset that these
sustain itself, that is, to recover after
different bodies of literature do no longer exist in
the crisis and continue functioning
isolation from each other as topics, theories,
and thriving.
research project, and disciplines, and investigator
networks—especially since the 1990s—cross-fertilize each other and are slowly converging (e.g.,
Janssen et al. 2006a,b). The selection of literature cited herein is therefore by necessity somewhat
arbitrary, and the clear demarcation of different bodies of literature is increasingly difficult,
especially on topics such as disastrous weather events and the aggravation of extremes by
climate change. Several distinct insights and contributions from the human dimensions of
global change field can be identified however.
In Section 2 I review definitions and the emerging understanding of resilience in the social
sciences. Section 3 discusses a number of aspects feeding into resilience, such as vulnerability,
adaptive capacity, social capital, and so on. In the concluding Section 4, I point to some
promising research frontiers on resilience in the human dimensions field.
2.
THE MEANING OF RESILIENCE IN THE FACE OF A RAPIDLY
CHANGING AND UNCERTAIN WORLD
The concept of “resilience” emerged out of ecology in the early 1970s, and over the ensuing
years, has evolved within that field and has been adopted and adapted in varying ways by
researchers in other disciplines (for recent reviews, see Brand and Jax 2007; Folke 2006; Gallopín
2006). Here I will focus primarily on conceptualizations in the social sciences, especially in fields
concerning themselves with global change. By necessity, however, this compilation and review
will overlap with understandings of resilience in the ecological sciences, in part due to the
history of the concept, in part due to the interaction of key researchers with and within the
Resilience Alliance, and in part because the emerging wisdom focuses on resilience of closely
coupled, and mutually interacting, human and natural systems (or social-ecological systems). In
later sections of this report I will draw on insights from physical climate change research, which
must feed into our growing understanding of stability, change, and transformation of socialecological systems.
2.1
Definitions of Resilience to Global (Climate) Change
Several researchers recently offered insightful comparisons of different definitions and
helpful reviews of the evolution of the concept of resilience, and of related concepts such as
adaptation, adaptive capacity, robustness, transformability, vulnerability, and the latter
concept’s commonly discussed components of exposure, sensitivity (or resistance), and coping
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capacity (e.g., Adger 2006; Folke 2006; Gallopín 2006; Smit and Wandel 2006; Brand and Jax
2007; O’Brien et al. 2007). Gallopín (2006: 301)—after his careful read of the literature—
concluded that all these concepts have no generally accepted meanings or relationship to each
other, even though “these concepts are related in non-trivial ways. If care is not used, the field
of human dimensions research can become epistemologically very messy.” And Brand and Jax
(2007), even more critically, found resilience to be used ambiguously already, a development
they mostly deplored, suggesting that the ambiguity in the term’s use—while possibly enabling
cross-disciplinary communication—actually threatens to deprive resilience of conceptual clarity
and practical relevance.
Table 1 lists a number of the definitions of resilience offered in the social science literature. It
also identifies whether these conceptualizations concur more with an understanding of
resilience as the capacity to return over a short period of time after disturbance to a prior
(relatively stable) state (engineering resilience, emphasizing qualities such as efficiency, control,
constancy, stability, and predictability) or with resilience as the capacity to self-organize into a
new configuration after disturbance (ecological resilience, emphasizing qualities such as
persistence, adaptiveness, variability, sustainability, regime shifts, and unpredictability)
(Holling 1996).
Table 1. Selected definitions of the concept of resilience
Author (year)
Timmerman
(1981)
Adger (2000)
Centre for
Community
Enterprise
(2000)
Abel and
Langston
(2001)
Chenoweth
and Stehlik
(2001)
Brock, Mäler
and Perrings
(2002)
Adger (2003a)
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Definition of Resilience
Type of
Resilience
A measure of a system’s capacity to absorb and recover from the
occurrence of a hazardous event; virtually synonymous with
“elasticity”; reflective of a society’s ability to cope and continue
to cope in the future.
The ability of groups or communities to cope with external
stresses and disturbances as a result of social, political, and
environmental change. (Notes that resilience of ecosystems on
which humans depend is a necessary, but insufficient, condition
for social resilience.)
Intentional action to enhance the personal and collective
capacity of its citizens and institutions to respond to, and
influence the course of social and economic change.
Engineering
The ability to persist through future disturbances.
Engineering
The ability to “respond to crises in ways that strengthen
community bonds, resources, and the community’s capacity to
cope.”
The transition probability between states as a function of the
consumption and production activities of decision makers.
Ecological?
The ability to persist (i.e., to absorb shocks and stresses and still
maintain the functioning of society and the integrity of
ecological systems) and the ability to adapt to change,
unforeseen circumstances, and risks.
Hybrid
Engineering
Ecological?
Ecological
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Community and Regional Resilience Initiative
Table 1. (continued)
Definition of Resilience
Quinlan (2003)
Resilience consists of (1) the amount of change a system can
undergo and still retain essentially the same structure, function,
identity, and feedbacks on function and structure, (2) the degree
to which a system is capable of self-organization (and reorganize after disturbance), and (3) the degree to which a
system expresses capacity for learning and adaptation.
Distinguishes two types of social resilience: (1) a social system’s
capacity to facilitate human efforts to deduce the trends of
change, reduce vulnerabilities, and facilitate adaptation… often
related to the effectiveness of social institutions to serve society
in adapting and innovating in the face of novel conditions; and
(2) the capacity of a [social-ecological system] to sustain
preferred modes of economic activity.
The amount of change or disruption that is required to
transform the maintenance of a system from one set of mutually
reinforcing processes and structures to a different set of
processes and structures.
Maintenance of natural capital (as the basis for social systems’
functioning) in the long run.
The capacity of a system to absorb disturbance and reorganize
while undergoing change so as to still retain essentially the
same function, structure, identity, and feedbacks..
The capacity of linked social-ecological systems to absorb
recurrent disturbances… so as to retain essential structures,
functions, and feedbacks; resilience reflects the degree to which
a complex adaptive system is capable of self-organization
(versus lack of organization or organization forced by external
factors) and the degree to which the system can build capacity
for learning and adaptation.
The capability of a system to maintain its function and structure
in the face of internal and external change and to degrade
gracefully when it must.
The return or recovery time of a social-ecological system,
determined by (1) that system’s capacity for renewal in a
dynamic environment and (2) people’s ability to learn and
change (which, in turn, is partially determined by the
institutional context for knowledge sharing, learning, and
management, and partially by the social capital among people).
The ability of the system to withstand either market or
environmental shocks without losing the capacity to allocate
resources efficiently.
The capability to retain similar structures and functioning after
disturbances for continuous development.
Kofinas (2003)
Anderies,
Janssen and
Ostrom (2004)
Ott and
Döring (2004)
Walker et al.
(2004)
Adger et al.
(2005)
Allenby and
Fink (2005)
Gunderson
and Folke
(2005)
Perrings (2006)
Liu et al.
(2007)
4
Type of
Resilience
Author (year)
Hybrid
Ecological
(1) and
engineering
(2)
Ecological
?
Ecological
Ecological
Engineering
Hybrid
Engineering
Hybrid
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2.2
Emerging Understanding of Resilience
What becomes quickly apparent from Table 1 is that most definitions adopted into the social
sciences are derivative of the ecological theories from which resilience first emerged, though
Adger (2000) warned of uncritical adoption, with clear influences of the hazards literature that
has shaped much of the debate on vulnerability, risk, and disaster management. The sample of
definitions also suggests that conceptual consensus in the social sciences is not in sight.
What may be reflective of larger societal discourses and values is the general division of
definitions into those where resilience is understood as the capacity to stay more or less the same
in the face of external or internal pressures, risks,
uncertainties, changes and surprises and those
An increasing number of writers seem
where resilience is the capacity essentially to stay
to adopt an ecological or hybrid view
alive but change along with those forces of
in which resilience is seen as the
transformation. An increasing number of writers
capacity to withstand change for
seems to adopt an ecological or hybrid view in
some time but also, past a certain
which resilience is seen as the capacity to
point, to transform while continuing or
withstand change for some time but also, past a
certain point, to transform while continuing or
regaining the ability to provide
regaining the ability to provide essential
essential functions, services,
functions, services, amenities, or qualities (see,
amenities, or qualities.
e.g., Walker and Salt 2006). Independent of the
particular perspective adopted, normative
judgments frequently color these writings, whether they are made explicit or implicit, and it is a
non-trivial question to ask who prefers (or decides) that a system remain the same or change,
and change to what.
Table 1 uncovers a number of other divisions that reflect further conceptual ambiguities,
disciplinary differences, and challenges in delineation of “what is resilient to what” (Carpenter
et al. 2001) that must be clarified. The authors cited above refer to constituent processes and
concepts such as persistence, absorption, recovery, renewal, learning, coping, adapting,
transformation, and vulnerability—on neither of which there is much clarity or unanimity of
meaning. Insights from the global change literature on these and related concepts are discussed
in Section 3. Investigators also distinguish risks, shocks, hazardous events, stresses,
disturbances, and gradual changes, which not only may mean different things to different
researchers but also imply rather different demands on what a system is exposed to and what it
must be able to handle. The global change literature, maybe more than any other field, has
highlighted the need to look at the interplay of gradual and punctuated change (e.g., Folke
2006). Some researchers focus on external forces, others on internal forces of change, or on
environmental versus social changes that affect the entity in question. These distinctions are
partly a function of drawing boundaries around a system for purposes of investigation, partly
of disciplinary expertise, and partly reflecting the wisdom that emerges from multi- and
interdisciplinary collaborations which allow the broad range of relevant forces of change to be
considered.
Table 1 also suggests that researchers differ on how they conceptualize the entities that are
(or aren’t) resilient: some view social systems as embedded in an environmental context to
which one must respond; others configure human systems as coupled to natural systems
(through flows of materials, energy, and information); and yet others focus on deeply
integrated, inseparable social-ecological systems. To date, there is little convergence toward
either of these perspectives, although the dominance of thinking emerging from the Resilience
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Alliance pushes the field into the social-ecological direction (e.g., Berkes, Colding, and Folke
2003; Westley et al. 2002; Berkes and Folke 1998). What is critical here to note, however, is that
the conceptualization of the entity at risk of change has important implications for the location
of transformative forces, for that of the resources available to build and maintain resilience, and
for the interactions of the entity in question across scale, that is, to others that influence or are
being influenced by it.
The conceptualization of the entity at risk of
Finally, embedded in the definitions
change has important implications for the
offered in Table 1 are subtle differences
location of transformative forces, for that of the
on the temporal dimension. Clearly all
allude to a system’s persistence over
resources available to build and maintain
time. Yet some researchers refer to an
resilience, and for the interactions of the entity in
ability to deal with events as the occur
question across scale.
or trends that are evident at present
while others imply preparedness for future shocks or changes, many of which cannot be
predicted. Those interested in the uncertain future evoke mechanisms of foresight and
predictive capacity, social memory, learning, and adaptation. Some researchers emphasize the
ability to deal with one-time stresses, while others focus on repeat occurrences of or ongoing stress.
These differences have important implications for an assessment of when a system is
considered resilient and when no more. They, again, may reflect influences from the hazards
field in which recovery trajectories after disaster have been the focus of discussion for many
years.2
In summary then, because of the conceptual ambiguity and fluidity of resilience and its
many related concepts, an easy synthesis of meanings and relationships is not possible. It is
clear, however, that resilience is scale, context, and disturbance specific (e.g., Walker et al. 2004;
Gunderson and Pritchard 2002). Thus it is not merely an inherent characteristic of a given
social-ecological system. Rather, resilience is an emergent property that arises from the
interaction of a particular system, its wider environment, and the forces that act on both. For
example, an extreme drought—viewed at a continental scale—may fall well within the range of
conditions that the larger bioregion or the agricultural industry can endure without significant
alteration. At the level of a specific ecosystem or a single farm, however, the resilience of each
may be exceeded. So while a farm may
Resilience is scale, context, and disturbance
have been capable of dealing with a rapid
loss of farm workers, a drop in crop
specific. Thus it is not merely an inherent
prices, a flood, and a raging insect
characteristic of a given social-ecological
infestation, it went bankrupt when the
system but rather an emergent property that
extreme drought hit. Farms in a
arises from the interaction of the system, its
neighboring state, exposed to the same
environment, and the forces that act on both.
drought, fared better because of
significant differences in agricultural
policy.
In the following section, I will discuss in greater detail important insights for the study of
resilience from human dimensions research. In particular, the enormous literature on
vulnerability and adaptation is relevant here, but smaller subsets of that literature hold
additional critical insights.
2
The complementary reports prepared by Susan Cutter and Kathleen Tierney to the CARRI project discuss these
matters in more detail.
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3.
INSIGHTS FROM THE STUDY OF GLOBAL CLIMATE
AND ENVIRONMENTAL CHANGE
Despite the lack of an unequivocal conceptual definition of resilience and its relationship to
other key concepts such as vulnerability, sensitivity, adaptive capacity, and so on, the global
change research community has produced a number of invaluable insights that should be
considered in the exploration of community or regional resilience, much less in any potential
policy interventions aimed at enhancing resilience in the face of global environmental change
and extreme events.
3.1
Vulnerability
Vulnerability studies have their historical roots in largely separate fields, such as the
hazards tradition in geography, risk and disaster studies, and the poverty/hunger reduction
and livelihood and development studies, with more recent fields emerging around climate
change impacts and adaptation, and in the context of environmental management. (For some
recent critical reviews, see, for example, O’Brien et al. 2007; Adger 2006; Eakin and Luers 2006;
Füssel and Klein 2006; Thomalla et al. 2006.) The purpose of the discussion here is not to
provide yet another summary or attempt at synthesis but to explore the implications of using
key approaches to vulnerability for the understanding of resilience. Toward this end, I refer
particularly to the extremely helpful recent papers by O’Brien et al. (2007) and Gallopín (2006).
A persistent fault line runs through global change studies when it comes to the
understanding of vulnerability. On one side of this divide are those who view vulnerability as the
context of or initial condition characterizing a social, ecological, or social-ecological system which
will then experience a hazardous event such as a storm or a drought, or a long-lasting threat
such as sea-level rise or higher average temperatures. On the other side of the divide are those
who view vulnerability as the outcome or net impact of any such threat after the exposed system has
experienced a disturbance and done all it could to reduce the impacts. O’Brien et al. (2007),
building an Kelly and Adger (2000), term the former a “human-security framing,” which sees
“contextual vulnerability” as a starting point for analysis, and the latter (somewhat
unfortunately) a “scientific framing,” which views “outcome vulnerability” as the end point of
analysis. The latter is exemplified by the framing of the Intergovernmental Panel on Climate
Change (Parry et al. 2007; McCarthy et al. 2001), while the former is more common in the
hazards tradition within geography, political ecology, and poverty and development studies.
Figure 1 depicts the differences.
One important difference between these two framings and conceptualizations is that in the
“scientific” framing, climate change is depicted as the primary (and sometimes still sole)
external factor or disturbance exerting force on an exposed system, from which impacts,
responses, and remaining vulnerability follow in linear causal fashion. In the “human security”
framing, on the other hand, climate is one of several environmental and socio-economic factors
that both shape the conditions for a system’s vulnerability and exert pressures and
perturbations on it. The relationships are complex and multi-directional. The respective benefits
and drawbacks of either formulation are still hotly debated in the global change research
community, a debate that somewhat resembles that witnessed for years in the hazards
community where researchers questioned the wisdom of focusing on a single versus multiple
hazards in the context of monitoring, preparedness, vulnerability, risk, and hazards
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Figure 1. Frameworks depicting two interpretations of vulnerability to climate change:
(a) outcome vulnerability; (b) contextual vulnerability. Reprinted with permission from Climate Policy
and Earthscan Ltd. Source: O'Brien, K. L. et al. 2007. Why different interpretations of vulnerability matter
in climate change discourses. Climate Policy 7 (1): 73–88.
management.3,4 Increasingly, arguments by human dimensions researchers are accepted that
vulnerability—just like resilience—is never just to one thing yet threat-specific, multidimensional, and context-specific (e.g., Turner et al. 2003; O‘Brien and Leichenko 2000). Clearly,
from the perspective of overall regional or community resilience, it would seem too limited and
imprudent to only focus on climate-related hazards.
The two different framings of vulnerability as either starting point or outcome, however,
have important implications for the understanding of the factors and processes that determine
vulnerability. Gallopín (2006), in his careful exploration of the relationship between
vulnerability, adaptation, and resilience, notes that vulnerability is sometimes taken to be the
antonym, the exact opposite (e.g., in Adger et al.
Vulnerability is sometimes taken to
2005), of resilience, but ―this is by no means clear;
be the exact opposite of resilience,
obviously a resilient system is less vulnerable
but this is by no means clear.
than a non-resilient one, but this relation does not
necessarily imply symmetry‖ (p. 299). To
understand why this may be so, it is helpful to disaggregate vulnerability into its components.
Commonly, vulnerability—most broadly defined as a susceptibility to harm or a
potential for change or transformation—is said to be constituted of three components:
exposure to a perturbation or stress, sensitivity (or resistance) to the perturbation or stress,
and the capacity to respond or adapt (e.g., Adger 2006; Gallopín 2006). These seem logical
enough: a system that is not in a position to be impacted by a threat, that is, is not or
only briefly at risk due to buffering, protection, or geographic location, is less
3The stylized distinction between the two approaches—while still common—should not obfuscate the fact that
many climate impacts researchers, as reflected in the IPCC assessments, increasingly acknowledge the dynamic
nature of vulnerability (what is outcome now is context for the next disaster) as well as the importance of multiple
stressors on adaptive capacity.
4Again, these issues are likely to be discussed more fully in the reports by Cutter and Tierney.
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vulnerable to that threat than one which is subject to or in contact with the perturbation for a
longer time, greater extent or degree. A system that is less sensitive, less reactive, or more
resistant to a threat is less vulnerable than those with a smaller capacity to absorb shocks or
changes. And finally, a system that is capable of autonomous or natural rebounding and
adaptation, or that has the necessary resources to foresee, prevent, limit, deal with, and recover
from the unavoidable effects of a hazardous event is also less vulnerable than one with more a
limited capacity to respond.
Linguistic imprecision and conceptual differences set aside for the moment, it seems clear,
however, that a system that has never been exposed to a particular threat will not have had the
experiences that would allow it to build up ecological or institutional memory and develop an
ability to respond effectively to a present or future perturbation. Thus, a certain level of
exposure—while potentially increasing overall vulnerability—could actually create the
opportunity for experiences that enhance overall system resilience. If on the other hand
exposure becomes so great that the recurrent encounter with the hazard overly sensitizes the
system or depletes it of coping resources, then overall vulnerability would be high and
resilience low.
Sensitivity has a more straightforward relationship to vulnerability and resilience. A high
level of sensitivity, that is, a low capacity to absorb impacts without suffering significant harm
or alteration, may cause a system to react so strongly to a given perturbation that it is quickly
catapulted into an entirely new state or configuration, and thus would be said to have high
vulnerability and low resilience.
Lastly, the relationship between adaptive capacity or response capacity and resilience is
maybe the most ambiguous, despite the fact that many researchers virtually equate resilience
with this third component of vulnerability (Gallopín 2006; Smit and Wandel 2006). Generally,
investigators assume that the greater the ability of a system to respond to a hazardous event or
adapt to changing conditions, the lower its overall vulnerability. Clearly, one could argue that
this amounts to greater present-time resilience. It is unclear, however, that greater resilience in
the future is also guaranteed. Whether or not that holds true hinges on the question whether the
enacted response is considered maladaptive or effective relative to a number of desired
outcomes. It is theoretically possible, to illustrate this point, to garner the resources necessary to
rebuild New Orleans in its historic location and to its previous condition (some would say
grandeur, others would say state of disrepair). Certainly, this would imply a tremendous
response capacity, and hence low vulnerability and high resilience. Whether or not this would
be considered one of the greatest achievements in American history or judged one of the most
foolish goals the country ever pursued, however, is at once a value judgment vis-à-vis social
objectives, and a verdict waiting to be passed by environmental realities. This closer look at
exposure, sensitivity, and response capacity thus illustrates that there is a non-linear and
asymmetric relationship between (components of) vulnerability and resilience.
Several other important insights follow from this examination: Sensitivity and capacity to
respond seem to be inherent properties of a social-ecological system, whereas exposure can be
interpreted as either a system’s quality or a characteristic of the interaction between the system
and the forces that act on it. The literature is rather split on this point, but the choice of
including or excluding exposure in the definition of vulnerability has important implications. If
vulnerability is a function of sensitivity, response capacity, and exposure, then it is “a property of
the relationship between the system and its environment” (Gallopín 2006: 296; emphasis added).
This would make vulnerability an ever-changing, hard-to-predict, and parallel to the
conceptualization of resilience above, possibly an emergent property. If, on the other hand,
vulnerability is a function of only sensitivity and response capacity, with exposure considered
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separately as a property of the relationship between the system and its environment, then
vulnerability is a property of the system in question and, as such, not necessarily a stable, but less
context-sensitive quality.
Moreover, as the discussion above showed, the three components interact and are to some
extent mutually dependent. This makes it logically more difficult, though maybe not
impossible, to pull them apart in the conceptualization of vulnerability. In fact, to tie these
observations back to O’Brien et al.’s (2007) distinction of different schools of thought or
framings of vulnerability, it would be interesting to examine more systematically whether the
climate change literature, which favors the framing of vulnerability as outcome or end-point,
tends to be more interested in the vulnerability of the system, and whether the “geographic”
tradition, which prefers the framing of vulnerability as context or starting point, tends to focus
more on the impacts of various stressors on the internal and external relationships within and
between systems and their environments.
Finally, it is important to emphasize—as numerous writers have done—that vulnerability is
not necessarily always a bad thing, and, surely, resilience not always good (see the reviews in
Folke 2006; Gallopín 2006). Vulnerability interpreted as a potential for transformation or
opportunity for change, while certainly implying
Vulnerability is not necessarily
significant (temporary) risks to existing assets and
always a bad thing and, surely,
interests, may open up opportunities for social
improvement, and certainly for learning and growth
resilience not always good.
(including the learning capacity that increases
resilience).5 Resilience, on the other hand, viewed as the ability to persist around a “stable
attractor” or in a “stability landscape” may produce systems that are trapped in an unhealthy,
unproductive, corrupt, or otherwise undesirable state (see, e.g., Allison and Hobbs 2004).
3.2
Adaptive Capacity, Adaptation Options, Barriers, and Limits
Adaptive capacity is singled out here for additional discussion, despite its mention in the
previous section. This choice is made here, in part, because of the huge volume of literature in
the human dimensions field that focuses on adaptive capacity and adaptation; in part, because
there are—as with the other concepts discussed in this report—important differences in
conceptual understanding, which in turn affect the understanding of resilience; and finally,
because a growing number of investigators emphasize not just adaptive capacity or potential for
adaptation to global (climate) change but the barriers and absolute limits to adaptation. These
critical insights raise big questions about social resilience and hold important political and
policy implications.
Smit and Wandel (2006) and Gallopín (2006) note that researchers in the field commonly use
three different terms—adaptive capacity, coping capacity, and response capacity—sometimes
synonymously and other times differently. There are related differences in the use of the terms
adaptation, adjustment, coping, response, and mitigation. Again, the differences have nontrivial implications for the concept’s relationship to resilience.
In the hazards field and geographic studies of climate change adaptation, writers
distinguish, first of all, two types of responses to hazardous events: adaptation and adjustments.
The principal distinction is how far-reaching or deep the response is. Shorter-term, behavioral,
5
A significant number of writers in the hazards field and policy sciences have written about disasters as
“windows of opportunity” when policy change becomes possible. Empirical reality is a bit more ambiguous about
whether or when hazardous events help create opportunities for policy change and innovation and when they close
them (see, e.g., Moser, 2005a).
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or relatively minor responses, be they incidental or purposeful, would be considered
adjustments, whereas deeper, longer-term, structural changes, including cultural and biological
responses, would be considered adaptations (Burton, Kates, and White 1978, 1993). While—as
Gallopín (2006) notes—such a distinction may sometimes be difficult to make in practice, it has
carried forward from those earlier writings to the present day. Most clearly, this is apparent in
the distinction found frequently today of coping vs. adaptive capacity. Coping capacity typically
refers to the ability to cope or deal with present or near-term hazards and disturbances, akin to
adjustment, and does not typically involve far-reaching structural changes in social-ecological
systems to deal with long-term trends. Adaptive capacity, by contrast, more often refers to the
ability to make various changes, sometimes deep and structural, to help systems better align to
long-term changes in the social and environmental spheres (see, e.g., Smit et al., 2000; Turner et
al. 2003; Adger 2006; Smit and Wandel 2006). Turner et al. (2003) clearly distinguish the two and
consider both as part of a system’s resilience. Numerous other investigators see
coping/adaptive/response capacity as either constituting just one component of vulnerability
(and thus of resilience) or as entirely synonymous with resilience. Gallopín (2006) combines
coping and adaptive capacity into the broader notion of response capacity.6
An important link between those who focus on present-day coping capacity and those who
favor adaptive capacity vis-à-vis long-term changes is the recognition that many actions that
may be taken to cope with hazards today may also be adaptive in the longer term. This
recognition underscores attempts at mainstreaming adaptation into ongoing environmental and
hazards management, planning, and sustainable
Many actions that may be
development (e.g., Klein et al. 2007; Bouwer and Aerts
2006; Klein, Schipper, and Dessai 2005; Huq et al. 2003).
taken to cope with current
This link is strengthened even further through recent
hazards may also be adaptive
work by members of the Resilience Alliance on linked
in the longer term.
adaptive cycles and panarchy (e.g., Gunderson and
Holling 2002; Yorque et al. 2002; Fraser, Mabee, and Figge 2005) and similar insights emerging
earlier from systems theory (e.g., Jervis 1997), and the hazards field (e.g., Clark 1987; Kates
1985): systems are linked across time and space scales such that higher-level, slower, and deeper
changes or adaptations very much constrain the space for less substantial adjustments or coping
options at lower scales, while lower-level activities help shape higher-level changes. In other
words, it may be conceptually helpful to distinguish coping from adaptive capacity, but they
are not entirely independent.
As discussed in Section 3.1 (see also Figure 1), in the climate change field, adaptive capacity,
and adaptation actions are not part of, but antecedent to, vulnerability; that is, they codetermine, together with the characteristics of the disturbance, the ultimate (net or outcome)
vulnerability of an exposed system (Smit et al. 2001; Adger et al. 2007). In the IPCC’s Third
Assessment report, adaptation was defined as the “adjustment[s made] in ecological, social, or
economic systems in response to actual or expected climatic stimuli and their effects or impacts.
This term refers to changes in processes, practices, or structures to moderate or offset potential
damages or to take advantage of opportunities associated with changes in climate” (Smit et al.
2001: 881). This definition was essentially maintained through the Fourth Assessment report,
which stated that “[a]daptation to climate change takes place through adjustments to reduce
vulnerability or enhance resilience in response to observed or expected changes in climate and
associated extreme weather events” (Adger et al., 2007: 720). Or, as Easterling, Hurd, and Smith
6
However, this conceptualization should not to be confused with other writers’ who combine adaptive capacity
and mitigative capacity (i.e., the ability to reduce greenhouse gas emissions) into a society’s overall response capacity
(e.g., Yohe 2001).
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(2004: 2) put it, “adaptation can be viewed as reducing the severity of many impacts if adverse
[climate] conditions prevail. That is, adaptation reduces the level of damages that might have
otherwise occurred.”
In this school of thought, “[a]daptive capacity is the potential or ability of a system, region, or
community to adapt to the effects or impacts of climate change. Enhancement of adaptive
capacity represents a practical means of coping with changes and uncertainties in climate,
including variability and extremes. In this way, enhancement of adaptive capacity reduces
vulnerabilities and promotes sustainable development. … [The] determinants of adaptive capacity
relate to the economic, social, institutional, and technological conditions that facilitate or
constrain the development and deployment of adaptive measures” (Smit et al. 2001: 881–882).7
In a recent assessment, Moser (2008b: 1–2) observes the following trends in adaptation
studies in the human dimensions field, which is quoted here at length:
“Much of the focus in social science adaptation research in the climate and
global change arena to date has focused on the international policy framework,
national-level to place-based strategies in general, technological options and
specific adaptation actions that can be employed by actors at any level of
decision-making. By far the strongest emphasis has been on what potentially
could be done, whether the necessary capacity for adaptation is in place, and—if
wanting—how to enhance it (Smit et al., 2001; Adger et al. 2007). A much smaller
number of investigators has looked at historical examples of successful or failed
adaptation (from the cultural to community levels). Only in the last few years has
there been a growing interest in the degree to which adaptation to anthropogenic
climate change is already occurring, and if not, why not (for specific examples
and a synthesis see Adger et al. 2007). This line of work in particular, together
with critical analyses of the socio-economic and political power dynamics and
inequity issues underlying vulnerability and adaptive capacity (e.g., Adger et al.,
2001; Adger et al. 2006) has brought [the human dimensions research community
more recently] to [a] serious investigation of barriers and limits to adaptation
[…].
A number of investigators have argued that an honest discourse and more
critical examination of our true ability to adapt to climate change is warranted
and overdue, including for highly developed countries (e.g., Pielke et al. 2007;
O’Brien et al. 2006; Moser and Luers 2008; Easterling, Hurd, and Smith 2004;
Adger et al. forthcoming). This urgent call stems from several relatively recent
developments, including:
•
•
•
•
concern with the fast pace of climatic and other environmental changes (and
the specter of abrupt shifts);
a persistent and growing gap between the rich and poor, in any country;
recognition of high societal vulnerability to climate extremes even in
developed countries (e.g., the killer heat wave of 2003 in Europe, Hurricane
Katrina in the United States in 2005, the extreme drought in Australia in
2007);
a growing understanding of system lags in social systems;
7
Note the liberal mingling of adaptation, adjustment, and coping in the two IPCC quotes. Note also the reference
to sustainable development in 2001, but not—expressis verbis—resilience, which only became prominent in the 2007
assessment.
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•
•
impatience with the rather slow response of national and local governments
to climate change impacts to date (i.e., planned adaptation, preparedness);
and last but not least,
a critique (or at least questioning) within the scientific community of the
almost exclusive emphasis on adaptive capacity while neglecting the question
whether this capacity is actually being used and fully realized in actual
adaptation actions.”
From the discussion so far, several important conclusions can be drawn, no matter which
tradition one calls home. First, it seems logical that for a social-ecological system to be
considered resilient over time it needs to have the capacity to cope with present-day, known
risks (historical conditions) and the capacity to adapt to changing conditions (emerging trends
in averages and variability of conditions, including uncertain, unknown, or unpredictable
risks). Enhancing present-day coping capacity will go a long way, but is unlikely to be sufficient
to meet the challenges associated with changing social and environmental conditions.
Moreover, those working from a “human
A social-ecological system does not
security” perspective would argue that it is
never enough to only monitor or project
only need to have the potential or
changing climatic or environmental conditions
capacity to cope and adapt but the
to build response capacity, as social forces are
resources, skills, power, and willingness
equally determinative of vulnerability,
to realize this capacity into real
coping/adaptive capacity, and therefore
actions.
resilience.
Second, a social-ecological system does not
only need to have the potential or capacity to cope and adapt but the resources, skills, power,
and willingness to realize this capacity into real adaptation actions. This frequently means
overcoming significant barriers (e.g., institutional, political, social, cultural, technological, or
economic), and where there are absolute limits, to devise alternative solutions, if possible, that
circumvent these limits. If barriers cannot be overcome, vulnerability—by necessity—will
increase, resilience decrease, positive opportunities will be missed, and negative impacts are
likely to grow more severe or expand in scope. Moreover, resilience will be limited, and the
system may transform into a noticeably different one.
These insights have the potential to modify mainstream assumptions or conclusions about
the relative vulnerability of rich and poor countries and populations, and thereby possibly
affect political debates about how to comprehensively address the risks from climate and other
environmental changes.
In the next section, I discuss insights from the social and the physical sciences which
elaborate on the question of “limits.”
3.3
Criticality, Thresholds, Irreversibility and the Dangers of Abrupt Climate
Change
In the context of risk management, the identification of critical assets and lifelines in a
community or region at risk of being affected by a hazardous event is an essential component of
ensuring resilience (e.g., Moteff 2004). Criticality there is an indicator of prioritization of what is
to be protected in order to assure continued functioning.
In the human dimensions field (including the geographic/political ecological approaches to
hazards that have influenced it), criticality has come to indicate either a level of extreme
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vulnerability and decay of socio-economic conditions (Bohle 2001; van Dillen 2002) or extreme severity
of degradation of the environmental conditions in a particular place or region (Kasperson,
Kasperson, and Dow 2001; Kasperson, Kasperson and Turner 1999, 1995). What researchers
here are concerned with is the “growing disjuncture […] in the[se] regions between the rapid
rates of environmental degradation and the slow pace of societal response” (Kasperson,
Kasperson and Turner 1999: 562). The consequence is further environmental impoverishment in
the region in question, deepening vulnerability of the people depending on that region’s
environment and resources, and an undermining of coping and adaptive capacity for current
populations and future generations. When criticality is reached in a particular area, life-support
capabilities are lost, which increases the demands on other regions to absorb “environmental
refugees” from, or provide resources to, the “critical region” in question in order to make up for
what has been lost there (e.g., food supplies, water). Costs of substitution in resource use and
risk mitigation efforts escalate.
As the different meanings of “criticality” mentioned above indicate, a range of different
approaches to it have been made over the years. Kasperson (2001), for example, notes
“[a] variety of studies has been completed on ‘red zones’ of environmental degradation, ‘critical
regions’ of threat, and ‘hot spots’ of biodiversity loss (see the overview in Kasperson,
Kapserson, and Turner 1995). And a number of different models, analytic approaches, and
methodologies are apparent, including efforts to develop indexes of vulnerability (see GECHS
1999) and an assessment of ‘syndromes’ of climate change impacts (Schellnhuber et al. 1997).”
Kasperson, Kasperson, and Turner (1995: 6) distinguish geocentric approaches where “criticality
is reached when human-induced perturbations have so altered the biophysical system that a
different system, substantially less diverse and more ecologically ‘degraded’, results.” This
definition is maybe the most perfect antonym to resilience currently in use in the ecological
literature. By contrast, anthropocentric criticality focuses (sometimes to the exclusion of the
environmental basis for life and livelihood)
Environmental criticality is reached when
on the social, political, economic, and
technological forces and structures that can
the extent and/or rate of environmental
so undermine the ability of communities to
degradation preclude the continuation
sustain themselves that severe states of
of current human-use systems or levels of
vulnerability and extreme environmental
human well-being, given feasible
degradation result. The integrative approach,
adaptations and societal capabilities to
proposed by Kasperson and collaborators,
respond.
defines environmental criticality as a
“situation in which the extent and/or rate of
environmental degradation preclude the continuation of current human-use systems or levels of
human-well-being, given feasible adaptations and societal capabilities to respond” (Kasperson,
Kasperson, and Turner 1995: 25). This may come closest to being the opposite of socialecological resilience discussed in Section 2.1.
The trajectories of change toward environmental criticality can take a number of different
forms, because of the time lags involved in depleting environmental resources or exceeding
environmental sinks, and the variety of (sometimes ingenious) compensatory mechanisms
societies develop to deal with environmental degradation (e.g., robbing a distant Peter to pay a
local Paul).
Kasperson and colleagues also discuss a number of communalities in the societal response
to approaching environmental criticality: early on societies detect the problem(s) and early
warnings are issued as the problem(s) begin to emerge. Then, as the problems worsen and
periodic crises unfold, the warnings become more frequent and more urgent. The apparent
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damage is eventually followed by one of three responses: maladaptive responses that do not
alleviate the problem and underlying causes, worsen it, or create “collateral damage”; inadequate
responses that only temporarily or partially address the problem; or stabilization and maybe
eventual repair and recovery (Kasperson, Kasperson and Turner 1995: 35). Depending on the
degree of alteration of the social-ecological systems that were affected by the degradation, it
may be possible theoretically, but is practically and in relevant human time frames unlikely, to
return to the prior state (e.g., pristine prairie grasslands after industrial agriculture degraded
soils). The sufficiently recovered or repaired and probably deeply restructured social-ecological
system may then function in a new quasi-stable state and support new life and forms of
livelihood, yet never look the same ecologically.
The study of criticality sheds light on the dynamic nature of vulnerability and
coping/adaptive capacity as social and environmental conditions change (and especially
degrade) over time. One could argue that viewing vulnerability as dynamic, that is, as changing
over time, as researchers of criticality certainly do, offers a bridge between the scientific and
human-security approaches discussed in Section 3.1: if changing environmental conditions and
climatic stimuli affect the outcome vulnerability of a system, this more vulnerable system is
then the starting point that determines the system’s future capacity to deal with threats.
Another important insight from this work on criticality for the study of resilience is the
cross-spatial connectivity of systems.8 Critical regions require resources from other regions to
avert further degradation or even complete decay and disaster. Any single, major disaster in
recent memory illustrates the same point: the local resources available for immediate disaster
response and community recovery are insufficient, requiring that supra-local resources (e.g., via
state and federal disaster declarations, national or international donations and assistance) be
brought in to assist in the response effort. In the climate change context, however, communities
and regions everywhere will require additional resources to deal with the increasing challenges
as the planet warms and its resources are depleted. Thus it is critical to realize that the more
widespread climate change impacts will be in the
future, the less likely it is that communities can rely
The more widespread climate
with certainty on (sufficient, repeated, or sustained)
change impacts will be in the
outside assistance. This may bring about a critical state
future, the less likely it is that
in any one place sooner, increase vulnerability, and
communities can rely with
reduce response capacity and overall resilience more
than one might expect based on past experience.
certainty on outside assistance.
The Intergovernmental Panel on Climate Change
developed its own way of addressing climate change–related “criticality.” The IPCC’s Third
Assessment report was the first to introduce the phrase “reasons for concern”—an approach to
capturing key vulnerabilities in the context of the U.N. Framework Convention on Climate
Change. The reasons for concern identified by the IPCC (Smith, Schellnhuber, and Mirza 2001)
are as follows:
1.
2.
3.
4.
5.
loss of unique and threatened ecosystems;
inequity in the distribution of impacts;
total global aggregate damages from climate change;
extreme weather events; and
large-scale, singular and practically irreversible (low-probability, high-consequence)
events.
8
Other scale-related issues, connections, mismatches, and management challenges will be further discussed by
Wilbanks.
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These were considered “key vulnerabilities” (i.e., net impacts after the initial climate change
impact and—where possible—adaptations) that could undermine the ultimate objective of the
Framework Convention (i.e., they could exceed the natural capacity of species and ecosystems
to adapt, disrupt or threaten food production, and prevent or interfere with sustainable
economic development). In the Fourth Assessment report, Schneider, Semenov, and
Patwardhan (2007) confirmed these five reasons for concern and discussed them with growing
urgency based on the burgeoning literature on ecosystem impacts, socially differential impacts
(within and between developed and developing countries), barriers and limits to adaptation,
extreme events, and rapid or abrupt climate change.
The importance of the IPCC discussions of key vulnerabilities and reasons for concern,
clearly, is their relevance to international policy-making and the challenging issue of defining
“dangerous interference with the climate system” (UNFCCC, Art. 2, http://unfccc.int/
resource/docs/convkp/conveng.pdf). The U.N. did not define that term, thus setting the stage
for an intense debate over the question “what is dangerous”? While it has been widely
recognized that science alone cannot answer this question (e.g., Schneider, Semenov, and
Patwardhan 2007; Risbey 2006; Hansen 2005; Dessai et al. 2004; O’Neill and Oppenheimer 2002),
as it involves numerous value judgments, the systematic review of “vulnerabilities,” the study
of extremes and abrupt climate change in particular (e.g., Lenton et al. 2008; Schellnhuber et al.
2006; Schneider 2004; Steffen et al. 2004; Alley et al. 2003; National Research Council 2002), and
the examination of adaptation options and limits are meant to inform that political debate.
One of the insights one may glean from this debate for the question of resilience is whether
or not resilience is ever an objectively definable state of affairs. Surely, the criteria used to
identify key vulnerabilities would be useful not just at the global level but at the regional and
community level as well, especially in connection with an eye to environmental criticality as
discussed above. As the climate-change-driven changes become more likely to force sudden,
major, and/or irreversible changes on a social-ecological system, permanently undermine the
local or supra-local ecological and environmental resource basis that supports the lives,
livelihood, safety, and well-being of community and regional residents, starkly impact subpopulations differentially such that the social structure of the community is altered, and
diminish or deny access to adaptive resources, one would need to conclude that a community’s
or region’s resilience is significantly decreased and criticality is impending.
It is virtually impossible to weigh the importance of the physical thresholds and absolute
ecological limits against that of the societal constraints or de facto limits to adaptation. In fact, it
is not known whether thresholds of “danger” also constitute limits to adaptation. As discussed
above in Section 3.2, the study of these barriers and limits to adaptation has only recently
become a concerted research effort. According to Arctic researcher Grete Hovelsrund (cited in
Ham 2007: 1396), “almost nothing is known about the ‘critical thresholds of adaptability and
resilience’—the human tipping points” for certain populations. Related to this point are
findings from some case studies (e.g., Dugmore et al. 2008) where societal collapse did not
simply occur to dramatic or abrupt change or because practiced adaptations were so completely
incommensurate with the magnitude of the environmental change. Rather, catastrophe
occurred because of multiple stresses overwhelming society’s resilience, “because people
missed by a bit, not by much” (Dugmore et al. 2008, phrased use in the presentation).
One interesting and also still relatively new and small strand of social science research has
emerged in response to the specter of extreme events and abrupt climate change, namely, the
investigation of radical societal adaptations needed beyond the gradualism more typically
considered in IPCC assessments and other scientific studies. An urgent call for studies on this
topic was reiterated recently at a conference organized by the Tyndall Centre (Living with
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Climate Change: Are There Limits to Adaptation? London, February 7–8, 2008). Examples of the
kinds of situations one may envision include adaptation to extreme sea-level rise due to a
collapse of the Greenland and/or
Adaptation to extreme or abrupt changes in climate
West Antarctic Ice sheets, a total
faces difficult-to-overcome challenges if such
shutdown of the Atlantic thermochanges are difficult (or impossible) to predict or
haline circulation (THC), extreme
involve trend reversals. Even if abrupt changes are
temperature rises setting off
overwhelming positive feedbacks
uni-directional with existing trends, however, the
between climate change and the
economic costs and societal impacts are likely to be
carbon cycle, ocean acidification,
enormous.
and so on (e.g., Center for
Strategic and International Studies 2007; Goodstein and Doppelt 2006; Tol et al. 2006; Schwartz
and Randall 2003). As Hulme (2003) suggests, difficult-to-overcome challenges for adaptation
lie in the facts that (a) the likelihood of these abrupt or extreme changes cannot be calculated at
present (and maybe never) and (b) precautionary adaptive preparation is difficult whenever the
possibility of a reversal of present climate trends exists (such as with the warming trends over
northern Europe if the THC shuts down). Moreover, even if abrupt changes are uni-directional,
if non-linear extensions of existing trends, the economic costs and societal impacts are likely to
be enormous.
To my knowledge, there is currently no community that is seriously considering such
abrupt climate change scenarios in practical policy planning. Interestingly, however, maybe
because of the general lack of serious consideration of such large-scale events, such scenarios
have found interest among strategic thinkers in the military and security communities (e.g.,
Center for Strategic and International Studies 2007; Schwartz and Randall 2003). It would be an
interesting, and some might argue, an increasingly necessary extension of the community or
regional resilience studies undertaken in the CARRI project to explore one or more “extreme
scenarios” (e.g., a terrorism attack during a hurricane, an extreme-level of sea-level rise, or a
30-year drought) to examine both long-term local social-ecological resilience and—given the
lackluster history of human civility under extended duress—possible complications from civil
unrest and loss of social capital. As Andrew Watkinson put it at the close of the Limits to
Adaptation conference (February 8, 2008), “If we plan for adaptation to 4–5ºC, maybe we’ll have
a chance at hitting [the adaptation needs to the impacts of] 2–3ºC.”
3.4
Social Capital and Learning
As the emerging understanding of social-ecological resilience described in Section 2.2
suggested, resilience means more than just responding to, and bouncing back after, an extreme
event. It also involves the capacity to change and adapt to changing environmental conditions,
and that, in turn, requires the essential abilities to cooperate, learn, and apply the lessons
toward continued resilience under future conditions. Frequently in the human dimensions
literature, these capabilities are (uncritically, and maybe superficially) attributed to, and said to
be made easier by, social capital. This section then focuses on social capital and its role in social
learning and social-ecological resilience.
Debated with great fervor for at least 20 years in economics, sociology, anthropology,
psychology, and political science, social capital has come to mean many things. Even a cursory
review of this literature makes clear that human dimensions researchers interested in the role of
social capital in resilience should be very careful not to adopt the concept uncritically, test their
assumptions about the sources of social capital, direction of causality, and possibilities for
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intervention, and develop a differentiated
Human dimensions researchers
perspective on the impacts of social capital on
interested in the role of social capital
human welfare.
in resilience must be careful not to
Social capital is ambiguously defined—
adopt the concept of social capital
sometimes as the formal and informal structures
and norms that may produce it, sometimes as the
uncritically.
manifest or cognitive outcomes it can engender,
and sometimes as the causal mechanism that translates between structures and outcomes. It can
also vary in complexity, that is, whether it refers to intra- or inter-group relationships, to
horizontal or vertical networks (or both), and to the relationship it has to governance. This
bewildering plethora of conceptualizations and theories underlying them stems from the
recognition that people exist in social relations which affect their social, political, and economic
behavior.
Most often social capital is viewed as in and of itself positive, enabling or facilitating
desirable social outcomes. Yet much of the critique of the concept seems to lie in the observation
that the kinds of social networks and interactions that constitute social capital can just as easily
lead to various forms of social exclusion, disenfranchisement, stagnation, excess claims on
group members, possible restrictions on individual freedom, and downward leveling norms
(see also Portes 1998). Durlauf (1999), for example, in his staunch critique of the predominantly
positive perspectives on social capital explains that “social mechanisms which enforce certain
types of community behaviors logically lead to correlated behaviors, but do not necessarily lead to
socially desirable behaviors” (p. 3, emphasis added). Putnam (1993) himself acknowledged this
problem when he stated that “recognizing the importance of social capital in sustaining
community life does not exempt us from the need to worry about how that community is
defined—who is inside and thus benefits from social capital, and who is outside and does not”
(p. 42). He also argued that to the extent civil associations (or networks of them) are segregated
and do not bridge over common social divides (e.g., age, race, culture, political party affiliation,
gender, etc.), they do not foster social capital or effective functioning of democratic society
(Putnam 1995).
The common distinctions of different types of social capital therefore can be very helpful,
and resilience research should carefully examine which types of social capital are present, if at
all: so-called bonding capital works in horizontal networks, among equals within a community,
whereas bridging capital is vertical, crossing boundaries between communities, different
segments of a population, or—by extension—linking across larger distances and across scale
(e.g., Aldridge, Halpern, and Fitzpatrick 2002; Dolfsma and Dannreuther 2003; Narayan 2002;
Narayan and Pritchett 1999; Uphoff 1999; Uphoff and Wijayaratna 2000; Wallis 1998; Wallis,
Crocker, and Schechter 1998).
In fact, in most cases the delineation of “community” will help sorting the desirable from
the undesirable outcomes: social capital as a within- or intra-community phenomenon (i.e., bonding
capital) appears to produce predominantly
Social capital as a within- or intradesirable outcomes to its members but can or is
even likely to bestow undesirable outcomes on
community phenomenon appears to
those considered “other” or outside, that is, in
produce predominantly desirable
the context of between- or inter-community
outcomes to its members, but can
relations. To overcome those, bridging capital is
bestow undesirable outcomes on those
required (see also Pelling and High 2005; Adger
considered “other.”
2003b; Pelling 1998).
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Wolf, Lorenzoni, and Few (2008), however, present a case in England, where even bonding
or within-community social capital had negative implications for vulnerability and adaptation
within the studied population. Their study was of the elderly and their caretakers and their
perceptions of the vulnerability of the elderly to heat extremes (statistically known to be the
most vulnerable to heat stroke, heat-related illnesses, and even death). Based on the study
population’s self-assessment, the elderly do not perceive themselves as “elderly,” nor as
particularly vulnerable; their caretakers hold similar views. Hence neither took precautionary
measures during recent heat waves in England, nor did they take seriously the health warnings
and advice given by health officials. In other words, the large social capital existent between the
elderly and their trusted caretakers serves to screen out and shield intended audiences from
helpful, potentially life-saving expert information, thus not lowering but increasing that
population’s vulnerability.
It is for all these reasons that a study of the role of social capital in resilience needs to
carefully identify the type of social capital, explore the impacts it can have on those within and
without the group in question, and in fact define what is often too loosely called “the
community.” Moreover, for the study of social-ecological resilience, the distribution of power
within and across communities must be examined carefully to understand whether or not social
capital is a helpful resource in a community or region’s (or any sub-population’s) response
capacity to disturbance (Foley and Edwards 1996).
The distribution of power must be
Against the backdrop of ambiguity in
understanding, social learning is sometimes seen as
examined carefully to understand
an antecedent condition, sometimes as a causal
whether or not social capital is a
mechanism, and yet other times as an outcome of
helpful resource in a community or
social capital. Clearly, this speaks to the dynamic
region’s response capacity to
nature of social capital building: the reservoirs of
disturbance.
knowledge that exist can be drawn on in information
sharing and mutual learning and as a result of this interaction foster further learning. Trust is
essential in supporting this kind of learning; lack of trust can stall it. Certainly in the context of
responding to extreme events, the socially embedded memory and experience with past events
is an important community asset, as is the store of scientific knowledge about possible future
changes. Dense vertical and horizontal networks are critical in spreading scientific and
“indigenous” (i.e., traditional and/or place-specific) knowledge and experience, as well as
novel, innovative solutions for adaptation to a changing environment (e.g., Adger et al. 2005;
Pearce 2005).
Importantly, as the insights from the literature on “communities of practice” suggests, adhoc networks are less useful than well-established ones, for long-term learning and quick
mobilization during extreme events (Lave and Wenger 1991; Wenger 1998). The negotiation of
learning goals and meaning, establishment of rules of engagement, development of the
necessary capacity to meaningfully participate and learn, navigation of relationships where
power and expertise is unevenly distributed, and the building of trust all take time (e.g.,
Armitage, Marschke, and Plummer 2008; Moser 2007). Those interested in fostering learning
must provide the right incentives, help reduce the risks involved in experimentation and
learning, communally specify and negotiate learning goals, choose among different learning
approaches, and measure the outcomes of the learning process (Armitage, Marschke, and
Plummer 2008). Moreover, researchers must recognize the ways in which communities of
practice can be exclusionary, and thereby create injustices in access to information and related
resources (e.g., Moser et al. 2008a; Moser 2007). The exchange of information and social learning
stops at the boundary that is drawn around the social network that is its vehicle. In practice,
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bridges have to be built over the divides between separate networks or communities to ensure
the widest possible spread of knowledge and experience.
A final point is important here. Significant debate has occurred in the literature to what
extent social capital can replace or make up for inadequate government action or the negative
side effects of the market. Clearly, a non-trivial amount of compensatory power lies in social
capital. But investigators across the disciplines have warned that “the face-to-face local
interactions of community are […] not [a] substitute for effective government but rather a
complement” (Bowles and Gintis 2002: 16).
The study of social capital leaves many
Bridges have to be built over the
questions unanswered, some of which are
divides between separate networks or
especially interesting in the context of
communities to ensure the widest
social-ecological resilience. For example,
what is the role of the private sector and the
possible spread of knowledge and
market in social capital? Is it part of or
experience.
separate from civic society, and how can it
be linked most usefully to support—in private-public-civic partnerships—the resilience of a
community (e.g., Daily and Walker 2000)? How can government build or enhance social capital
in ways that truly support long-term resilience of communities (as opposed to, for example,
entitlement or dependence), and when or how is government undermining it? How can the
apparent benefits of social capital be extended beyond the immediate network of people who
are considered “in” the community, especially in times of crisis? Finally, in a globalized and
networked society, it is insufficient to look for social capital only locally/at the community level
(Healy and Hampshire 2003); instead, research must also explore intercommunity ties and nonlocal/scale-free networks (e.g., internet based). Is the nature of social capital in these more
recent social networks fundamentally similar or different from that in more traditional
networks, and how and for which purposes is it useful for enhancing resilience?
3.5
Governance Systems and the Role of Institutions
One definition of social capital offered by Grootaert (1998: 3) offers maybe the broadest,
most encompassing view of social capital as comprising “the social and political environment
that enables norms to develop and shapes social structure. [It includes] the largely informal, and
often local, horizontal and hierarchical relationships [… and] the more formalized institutional
relationships and structures, such as government, the political regime, the rule of law, the court
system, and civil and political liberties.” Much of what in this broad conceptualization is said to
be “social capital” is in the human dimensions community commonly called or included in
“governance.”
Governance in the ecological resilience literature is commonly viewed as “creating the
conditions for ordered rule and collective action or institutions of social coordination. … [it
encompasses] the structures and processes by which people in societies make decisions and
share power” (Folke et al. 2005: 444; see also Lebel et al. 2006). Moser (2008b: 3) invokes a
broader definition that applies to much of the contemporary study of decision-making, policy,
and the role of institutions in the human dimensions field. She defines governance “as the set of
decisions, actors, processes, institutional structures and mechanisms, including the division of
authority and underlying norms, involved in determining a course of action.” This definition
clearly suggests that governance is more than government, and that more than public-sector
players are involved, opening the door to discussions about stakeholder engagement in
resilience management. And while this conceptualization of governance emphasizes norms and
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institutions, and the structural
Conceptualizing governance as the set of
organization of decision-making, it also
decisions, actors, processes, institutional
emphasizes the decision-makers, that is,
structures and mechanisms involved in
the active agents embedded in particular
institutional, normative, and political
determining a course of action brings the
contexts. Thus governance occurs in the
dynamics between those involved in decisionconstant dialectic tension between
making, the qualities of the decision processes,
structure and agency. “As a
and the host of factors that influence decisions
consequence the dynamics between
and decision-makers into sharp focus.
those involved in decision-making, the
qualities of the decision processes
themselves, as well as the host of factors that influence decisions and decision-makers come into
sharper focus” (Moser 2008b: 4).
Governance has been a well-developed focus for many years in the human dimensions field,
though not necessarily for the explicit goal of resilience. Its study has harnessed the insights
from political scientists, economists, decision theorists, and countless others. For the study of
resilience, some of the relevant topics examined over the years have ranged from the role of
institutions (and institutional interplay and fit) in environmental and global change
management; the management of the commons; issues related to collective action and
cooperation; various policies and policy regimes for dealing with climate and other types of
global environmental change; cross-scale linkages of governing bodies and decision-makers; the
role of science (and scientific assessments) in decision-making; the demands on communication;
the challenge of measuring policy effectiveness; and how policies, institutions, and governance
systems themselves change over time (Young 2002).
More specific to the context of vulnerability, adaptation, and resilience, governance systems
can be understood as institutionalized mechanisms for coping with disturbance and change
(Adger 2003a), or as the set of mechanisms that actually link social and ecological systems into a
coupled whole. For example, governments, social networks, or private sector entities (e.g.,
insurance) can provide mechanisms that can be used to spread risk by diversifying patterns of
resource use, encouraging alternate activities and lifestyles, or sharing the costs of extreme
events, or to sustain ecosystem services over time and space. Frequently, these mechanisms are
critical resource to draw upon when individual or local response capacity is overwhelmed in
the wake of a crisis. Thus, linkages of individuals or communities to a wider set of resources
(often provided by government or civic society) increase local resilience. To the extent that
governance systems involve knowledgeable, prepared, and responsive institutions, the
likelihood of preventing, warning of, or mitigating the impacts from extreme events or climatic
change increases, thereby, again, enhancing the resilience of the overall social-ecological system.
Governance mechanisms can also provide institutional memory which can serve as a source of
renewal after crisis and for learning over time.
Any one participant or entity in the governance system, however, can help or hinder the
system from being effective in providing these forms of support trough crisis and change
(Moser 2008b). The pre-crisis quality of interactions, communication, functionality,
inclusiveness, perceived legitimacy, and preparedness often is predictive of in- and post-crisis
behavior. Moreover, if policy ideas, innovations, and adaptation plans existed prior to a crisis, it
is more likely that these will be implemented after the crisis (e.g., Penning-Rowsell, Johnson,
and Tunstall 2006; Moser 2005a), whereas in the absence of such plans, the main focus of
recovery within the governance system tends to be on the reestablishment of the status quo.
And that, of course, does not account for trends in social, environmental, or climatic conditions,
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and hence can obfuscate the ability to
If policy ideas, innovations, and adaptation
learn and adapt to change, and thereby
plans exist prior to a crisis, it is more likely that
undermine resilience in the long run.
In the ecological study of socialthese will be implemented after the crisis,
ecological resilience, the concept of
whereas in the absence of such plans, the main
slow variables is relevant here. Slow
focus of recovery tends to be on the
variables are those that structure a
reestablishment of the status quo. This
system in fundamental ways; they
obfuscates the ability to learn and adapt to
change slowly and thus exert a
change, and thereby undermines resilience in
stabilizing influence on the system.
They also have a great influence on a
the long run.
system’s resilience by bounding the
conditions within which a system can persist (Petersen 2008). Governance mechanisms and
institutional structures may well be considered such slow variables. And again, “slow” neither
implies “good” nor “bad.” For example, bureaucratic procedures take a certain amount of time
to complete—in certain instances, too long to rapidly respond to crisis, and in other cases, too
fast to prevent bad adaptations from getting adopted without fully considering their social and
ecological implications. In other instances, stakeholder participation may be a part of
governance processes. The typically time-consuming process can cause windows of opportunity
to pass unused and therefore pose a barrier to adaptation, or, despite its long duration, result in
better, more equitable, more legitimate, and hence more socially acceptable adaptation policies.
Crises and periods of rapid change are, of course, precisely the times when the relationships
among participants, the resources available, and the overall functionality are most taxed and
may well fail to function promptly, effectively, or justly (the example of New Orleans in the
wake of Hurricane Katrina comes to mind again; see, for example, Wetmore 2007; Kates et al.
2006). Thus, it is far from assured that existing governments, or governance systems, help or
hinder resilience. In part, this is a question of functionality and effectiveness; in part, however,
it is in the stabilizing (and sometimes ossified) nature of institutions, norms, and bureaucratic
systems. They lend stability and impose order, yet sometimes too much so, especially when
rapid or radical change, learning, flexibility and adaptability are warranted. This has led the
research community to become interested in two different yet related concepts: robustness (at the
institutional or organizational level) and adaptiveness (specifically, adaptive management and
governance) (e.g., Dessai and Hulme 2007; Janssen and Anderies 2007; Folke et al. 2005;
Anderies, Janssen, and Ostrom 2004; Lempert 2002).
Robustness of social-ecological system is a concept parallel to resilience (and sometimes
difficult to distinguish). To the extent they can be separated at all, one might say that resilience
refers to a social-ecological system’s overall persistence and ability to cope and adapt over time
while essentially retaining its basic characteristics, whereas robustness refers to similar abilities
of the governance system embedded in it, that is, to the informal and institutionalized mechanisms
for maintaining the system in a desirable state despite internal and external fluctuations and
uncertainty (Anderies, Janssen, and Ostrom 2004; Folke et al. 2005). This institutional focus
brings attention to questions of institutional flexibility, path dependencies, the ability to learn,
that is, incorporate new information and different types of knowledge, accommodate different
stakeholder perspectives, and effectively deal with trade-offs and conflict, but also early
detection and rapid-response capacities, the ability for social and organizational learning, and to
adapt the institutions themselves (e.g., Janssen and Anderies 2007; Anderies, Janssen, and
Ostrom 2004). In other writings, especially on institutional robustness of management systems,
the term can also refer (almost conversely) to such matters as political resolve and
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determination or firmness in the face of protest or reticence (e.g., Gross and Hoffmann-Riem
2005), or the persistence of chains of command and information exchange under stressful
conditions within and across levels of governance (e.g., Dodds, Watts, and Sabel 2003). In the
decision sciences, robustness refers to a related, but slightly more narrow idea, namely the goal
that a chosen policy or course of action may work (be effective, produce the desired outcome)
under a variety of external conditions (e.g., in the face of very different climate scenarios) (e.g.,
Dessai and Hulme 2007; Groves and lempert 2007; Pallottino, Sechi, and Zuddas 2005; Lempert
2002; Lempert, Popper, and Bankes 2002; 2003). In summary, whether robustness comes with
overtones of controllability or flexibility, the overarching goal is always the ability to achieve a
desired outcome or retain a desirable condition.
Anderies, Janssen, and Ostrom (2004) propose the following principles for designing robust
governance systems.
•
•
•
•
•
•
•
Clearly define the boundaries of the social-ecological system so that the costs and
benefits of management options to different parties are unambiguous. This engenders
transparency and trust.
Assign rough proportionality between private benefit and contribution to the
public/common good. This evokes a sense of fairness.
Assign relative weight and responsibility to those involved in decision-making: higher
stakes—greater say. This can produce a perception of greater legitimacy of the entire
governance system but also requires that room is made for the full range of different
“stakes” (e.g., monetary gain vs. survival).
Establish monitoring systems (including the necessary financial resources and social
incentives) to enable the governance system to detect problems early on, to warn of
novel challenges and trends, and to collect data on, interpret, and learn from past
experiments and decisions.
Establish graduated sanctioning mechanisms to increase accountability and retain
fairness in the system.
Build conflict-resolution mechanisms to adjudicate between different interpretations of
the available information, knowledge and value systems, and to ensure compliance.
Formally recognize rights and responsibilities of actors in the social-ecological system to
increase legitimacy and prevent evasion of accountability.
These seven principles may be essential but not suffice to ensure institutional robustness
under stressful or uncertain conditions. Folke et al. (2005) and Moser (2008a) suggest that there
is a need to formally establish additional mechanisms that
•
•
•
•
maintain social/institutional memory to assist learning from experience,
maintain institutional diversity (and at times also mainstreaming procedures for greater
expediency during crises),
engage in systematic experimentation where feasible, and
initialize or improve coordination across levels of governance, across institutional
boundaries, especially across the science-practice boundary through formal bonds,
frequent interaction, clear rules of engagement, and consistent leadership, to build
bonding and bridging social capital and facilitate the sharing of knowledge and uptake
of new information.
These design principles echo the attributes typically considered as constituting “good
governance”—such as participation, representation, deliberation, accountability, empowerment,
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social justice, multi-layered and poly-centric organization, and so on (Lebel et al. 2006). While
highly desirable, one is hard-pressed to find real-world examples where all of these principles
or attributes are realized at present (though some aspects are being realized in certain contexts,
see the case comparison in Lebel et al. 2006). Many questions remain regarding the
measurement of capacities of individual actors and institutions, the relative importance of
specific governance attributes vis-à-vis robustness and resilience, the effectiveness of
participatory processes, the role of experts in governance systems, the processes and
implications of deciding among trade-offs and
setting priorities and goals, and the causal linkages
While good governance is difficult
between governance structures and outcomes for
enough during “normal” times, what
the social-ecological system. And while good
would constitute good governance
governance is difficult enough during “normal”
during crisis times?
times, what would constitute good governance
during crisis times, how much stress a governance
system can take (e.g., from repeated disturbances or ongoing change) before it collapses, and
how governments in particular, and governance systems more generally, fare near and past
physical or social-ecological tipping points remain important questions to be answered. Other
questions that need more serious research attention pertain to the fact that such “good”
governance systems are typically not designed “from scratch” but need to be adapted from
existing structures and procedures. The real-world transformability of institutions, the lag times
and processes involved, the areas and types of intervention required are all critical areas of
ongoing and further research (e.g., Walker et al. 2004; Kemp and Loorbach 2003; Rotmans,
Kemp, and van Asselt 2001). The exact changes in governance that are needed are frequently
unclear, and they must occur in the context of other rapid, and often contradictory, trends (e.g.,
Parris and Kates 2003; Kates and Parris 2003; Speth 1992; Kates 1995). In short, the area of
governance for resilience continues to be an area ripe for empirical testing and experimentation
and for further research. Ultimately, this research cannot evade issues of power, social justice,
and ultimate survival.
3.6
Knowledge-Action Systems and the Role of Science in Enhancing Resilience
Another set of issues to discuss here is the role of science, and that of so-called knowledgeaction systems, in achieving resilience. They have been alluded to in previous sections on social
capital, social learning and governance, as knowledge acquisition and sharing, information, and
decision support play important roles in the development and enhancement of communities’
capacity to cope with extremes, adapt to change, and achieve resilience and sustainability (e.g.,
Clark, Crutzen, and Schellnhuber 2004; Clark and Dickson 2003; Kates et al. 2001; Gibbons 1999;
Lubchenco 1998).
While many case studies now exist on the use of scientific information in decision-making,
many of them coming to rather limited or even disappointing conclusions, Cash et al. (2003:
8086) found that “little systematic
scholarship exists on how to create
In the areas of vulnerability, adaptation, and
institutions that effectively harness S&T
resilience, knowledge-action systems are
for sustainability.” Especially in the
often assumed to exist, but empirical evidence
areas of vulnerability, adaptation, and
suggests that they are at best in the early
resilience in the face of long-term
stages of realization and few can serve as
change, such knowledge-action systems
are often assumed to exist, but empirical
models of effectiveness.
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evidence suggests that they are at best in the early stages of realization, and are much less
effective than what is commonly thought (e.g., Vogel et al. 2007; Weichselgartner 2007). While
knowledge about vulnerability, adaptation, and climate-related hazards has increased
substantially over the years, this knowledge has not effectively entered into decision-making
realms. Damages and losses rise even faster than our knowledge base (Weichselgartner and
Obersteiner 2002).
“Knowledge-action systems” can be understood as institutional arrangements that involve
knowledge producers and knowledge users in an effort to optimize the kind of knowledge that
is produced for use in policy- and decision-making and to integrate different types of
knowledge (scientific-technical, traditional ecological/indigenous, place based, etc.) while
mutually educating technical experts on users’ information needs and decision contexts and
decision-makers and stakeholders on the state of relevant science and the feasibility of desirable
research. In their effort to synthesize the pertinent literature and discern larger lessons, Cash et
al. (2003) found that the effective functioning of such knowledge-action system needs to be
broadly conceived in both process and outcome terms (see also Mitchell et al. 2006; Moser 2007;
Wolfe, Kerchner, and Wilbanks 2001): “effectiveness of scientific inputs needs to be gauged in
terms of impacts on how issues are defined and framed, and on which options for dealing with
issues are considered, rather than only in terms of what actions are taken to address
environmental problems. [Moreover,] perspectives of a decade or more may be necessary to
reliably evaluate the impact of science, technology and ideas on issue evolution” (Cash et al.
2003: 8086).
Their study further suggested that “efforts to mobilize S&T for sustainability are more likely
to be effective when they [consciously and seriously] manage boundaries between knowledge
and action in ways that simultaneously enhance the salience, credibility, and legitimacy of the
information they produce” (Cash et al., 2003: 8086). These three traits are attributions of the
process and products emerging from within the knowledge-action system; they are not intrinsic
qualities but “earned” characteristics. Credibility then involves the scientific adequacy of the
technical evidence and arguments, while salience speaks to the relevance of the information to
the needs of decision-makers. Finally, legitimacy reflects the perception of the involved that the
production of information and knowledge was respectful of stakeholders’ values and beliefs,
unbiased in its conduct, and fair in its treatment of opposing views and interests. As various
studies have shown, these three characteristics of knowledge-action systems and what they
produce are tightly linked, such that efforts to enhance any one typically involves a cost or
reduction in one or both of the others (Mitchell et al. 2006; Cash et al. 2003).
Effective knowledge-action systems function within institutional mechanisms that perform
or facilitate three crucial tasks: communication, translation, and mediation across the sciencepractice, disciplinary, institutional, and value-based boundaries. Active, iterative, and inclusive
communication between experts, policy- and decision-makers, and relevant stakeholders aids
the process by producing familiarity, trust, transparency, and understanding. To the extent this
understanding is hindered by different (scientific or administrative) jargon, language,
experiences, and assumptions, knowledge-action systems must help in the translation between
the science and practice worlds. Often, however, even if linguistic barriers and institutional
differences can be overcome, significant value differences and divergent motivations and needs
remain. The trade-offs between salience, credibility, and legitimacy are read and critical to
address to retain engagement and interaction. To deal with these differences, and sometimes
conflicts, explicit effort in process facilitation, if not mediation, is required (Vogel et al. 2008;
Tribbia and Moser 2008).
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Extensive work on the science-practice interface has found that sometimes the
communication, translation, and mediation between the world of science and that of policy and
practice are best accomplished by an intermediary institution that can perform these functions
and leave the experts and decision-makers on either side doing what each does best, without
having to deeply change their respective norms and expectations (e.g., McNie 2007; Sarewitz
and Pielke 2007; van Kerkhoff and Lebel 2006; van Kerkhoff 2005; Guston 2001; Gieryn 1999;
Jasanoff 1990). What is important then, however, is that both sides are accountable to the
boundary-spanning institution situated between them. Often the collaboration via a boundary
organization is also facilitated by the use of so-called boundary objects, such as models,
simulations, maps, reports, GIS interfaces, or other “products.” They become the focus of
iterative interaction: after initial consultation, knowledge producers create a prototype, which
decision-makers respond to, work with, or try on and then provide feedback or further input
on, as the basis for further refinement, and so on.
What seems to be clearly emerging from
Communication early and often is one of
many experiences of science-practice
the most important ingredients in enabling
interaction, with or without boundary
mutually educational and satisfying
organizations mediating between them, is
interaction between scientists and
that communication early and often is one
of the most important ingredients in
practitioners, but it alone does not
enabling mutually educational and
guarantee proper use of scientific
satisfying interactions (although it alone
information or a socially and
does not guarantee proper use of the
environmentally beneficial outcome.
scientific information or, necessarily,
socially and environmentally beneficial outcomes). The wider governance context, as well as
scientific and contextual uncertainties, and the judgment of those involved will co-determine
ultimate outcomes (e.g., Morgan et al. 2005; Moser 2005a,b; 2008b; Lambin 2005).
Aside from the tension between science and policy or practice, the wider context of
interested parties is critical to consider—and to involve—if there is to be a realistic chance of
science being used for societal benefit in the real world. It may therefore be useful to extend the
bi-polar tension between scientists and decision-makers by the wider set of stakeholders into a
triangle of relationships and interactions. Each set of relationships involves its distinct and
separate challenges and opportunities, expectations and accountabilities, capacities and
limitations (e.g., Armitage, Marschke, and Plummer 2008; Wilbanks 2005).
To understand then whether and when climate-, hazards- or resilience-related information
is used by decision-makers and stakeholders, information services need to be placed into a
larger context. There are many reasons why information is not used in decision-making, or
more generally, why information and knowledge
Action on climate- or hazards-related
do not immediately or necessarily lead to
information typically occurs only if it
behavior and policy change. Arguments range
from cognitive to organizational to interestsufficiently motivates actors to make a
based/social explanations, and all have their
change and simultaneously lowers or
place in the large ongoing discussion of what
constructively addresses existing
constitutes decision support.9 Generally speaking,
obstacles to change.
9
It goes beyond the scope of this report to fully review the vast body of literature on decision support and the use
of scientific information in decision-making. An important recent review of the case study literature is McNie (2007).
A National Research Council panel under the leadership of Bob Correll and Paul Stern, of which the author is a
member, is currently charged with defining what climate-related decision support is and how to implement and
measure its effectiveness.
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action on climate change or hazards-related information typically occurs only of it does two
things simultaneously: first, sufficiently motivate actors to make a change or adopt a new policy
and lower or constructively address existing obstacles to such a behavioral or policy change
(Moser 2008b; Moser and Dilling 2007). Thus, for example, moving out of a hazardous
floodplain in the face of sea-level rise and higher frequency of flooding extremes would
certainly entail many personal and social benefits to motivate such a move (e.g., lower personal
risk and actually experienced property damages; fewer or no life-threatening, scary disaster
experiences; lower public expenses for evacuation, rescue, and clean-up; restored floodplain
ecosystems; and so on). On the barriers or resistance side of the equation, however, heavily
weigh such issues as lack of (safe) alternative space to move to, high cost involved in retreat,
loss of prime land, including property taxes, views, amenities, and access to natural areas,
insistence on private property rights, emotional attachment to place, etc. Without addressing
both motivations and barriers, even the best scientific information cannot help in moving
toward resilience.
Stakeholder Engagement—Promises and Pitfalls10
3.7
The larger societal context is a primary reason for the call for “stakeholder engagement.”
While stakeholder engagement is a time- and resource-intensive endeavor, it has become “best
practice,” especially in place-based research, assessment, and decision support efforts. As a
special case in a broader category of participatory processes, there has been a relatively recent
revival of practical and scientific interest in stakeholder processes (say, in the 1990s), but it is
truly just a revival.
Beginning in the 1960s with popular demand for more participatory engagement of the
public in the decisions of government,11 an extensive volume of scientific research literature has
emerged that describes, reviews, assesses, classifies, and critiques the many different instances
in which publics become involved in technocratic processes (e.g., McNie 2007; Ewing 2003;
Beierle 1998).
This diverse literature covers considerable ground,12 extending from pragmatic and
theoretical discourses about questions regarding the appropriate form of government, and in
particular, the proper role of “the public” in a democracy where an increasingly distant cohort
of scientists and government agents informs and makes decisions about increasingly global,
complex problems (governance of the “risk society”) (e.g., Beck 1995), to related discourses on
participatory processes in conflict resolution around controversial risk assessment and
management issues (e.g., Markus, Chess, and Shannon 2005; Beierle 1998; NRC 1996; Krimsky
and Golding 1992). Other essential insights come from the social studies of science and,
particularly in this context, discussions of the relative merits and limitations of both technical
expertise and lay knowledge (e.g., Mitchell et al. 2006; Jasanoff and Martello 2004; NRC 1996;
Jasanoff 1990; Folke 2004; Berkes 1999), and the co-production of knowledge (e.g., Jasanoff 2004;
Callon 1999).
Public (stakeholder) engagement comprises many types of mechanisms, generally falling
under the three rubrics of public communication, consultation, and participation. These three
types of interactions are distinguished by the direction of the information flow, one-way from
10
This section draws heavily on Moser (2007)—a critical review of the literature on stakeholder processes.
Ewing (2003) notes that the earliest statements about the public’s right for information, procedural justice, and
involvement in decision-making actually go back to 14th century Islamic law.
12
This fact makes a comprehensive literature review nearly impossible. By mentioning some of the contributing
bodies of literature, directions for further exploration are at least charted.
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sponsor to public, one-way from public to sponsor, and two-way between sponsor and public,
respectively. The choice of mechanism(s) should be carefully selected to match intended goals.
What the literature suggests is maybe best captured by paraphrasing Einstein: stakeholder
engagement processes should be as simple (that is, as easy on the organizers and stakeholders
and otherwise minimizing risks and costs) as possible, but not simpler. The promises of
conducting effective stakeholder processes, as well as some of the dangers or pitfalls involved,
are captured in Table 2.
Table 2. Promises and pitfalls of stakeholder engagement processes
Promises and benefits
Pitfalls and dangers
•
Enhanced mutual understanding of
abilities, constraints, concerns, issues
•
Stakeholder fatigue
•
•
Co-production of knowledge
Use and augmentation of each person’s
skills and strengths
Greater balance of social values/concerns
and technical input into decision-making
•
•
A tangible result (e.g., the requested
information, a report, forecast, model)
Reduced vulnerability (i.e., decreased
exposure, and sensitivity, plus greater
coping capacity)
•
Burn-out of the initiators and organizers
Considerable cost in terms of time, staff
resources, and money
Potential for conflict or distrust to increase
rather than decrease as a result of the
process
Reinforcement of previously existing
power dynamics
Little guarantee that the intended goals
(e.g., improved decision-making process,
better environmental outcome) can actually
be achieved
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
•
Greater usefulness of information
Enhanced democratic process
Integration of different ways of knowing
Greater government/industry
accountability
Increased trust in government/industry
Greater buy-in in policy
Sounder basis for decisions
Capacity building on specific technical
skills
Enhanced commitment to institutions,
issues, missions, and goals
Policy changes or better implementation
and enforcement
Improved agency responsiveness
Improved public communication and
outreach
(Adapted from Moser, S. C. 2007. Effective Stakeholder Engagement in the Pacific RISA:
Considerations in the Further Development of Regional Climate Services. A report prepared for The
Center for Cultural and Technical Interchange between East and West, Inc., Honolulu, HI.)
To the extent that any of the dangers or pitfalls manifest, they are typically the results of a
disregard for contextual conditions or constraints, inadequate process implementation, a bad
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match between process and goal(s), inadequate definition of goal(s) and unrealistic assessment
of what can be achieved. Further critical insights from the pertinent literature that are relevant
to the assessment of a community or region’s resilience, vulnerability, and response capacity
include the following:
•
Geographic differences affect which information and knowledge services are needed,
when, and by whom, and consequently, which populations or sectors become
“stakeholders” at any one time. Even during one and the same hazardous event, the
information needs of stakeholders will differ across space, as will the range of
potentially affected stakeholders over time.
•
Varying levels of economic development between and within communities and regions
affect the amount of sustained available human, economic, and technical resources
(time, energy, staff, expertise, money) available for stakeholder engagement processes
(especially during crises), the level of capacity present among potential stakeholders, the
belief among potential stakeholders in the usefulness of a stakeholder process, and
hence the interest and willingness in participating (and remaining engaged over time).
•
Concerted attention and experience in reconciling, negotiating to meanings of, and
integrating local and scientific-technical knowledge is required. To the extent that
different systems of knowledge exist and interact, respect and recognition for them from
all sides is critical for participants to view the stakeholder engagement process as
legitimate.
•
Where educational attainment and research capacities are generally low or vary
markedly among participants, stakeholder engagement may be hampered and/or
require additional time. To ensure a greater likelihood of success, stakeholder capacities
may need to be built first. Self-perceptions of capability, level of understanding, and
empowerment are important in determining individuals’ interest, perceived benefits,
and willingness to participate in stakeholder processes.
•
A functioning governance system (see Section 3.6) will affect the number of stakeholders
in positions of influence, the willingness of government agents to engage in stakeholder
processes, the perceptions among potentially engaged stakeholders of the fairness,
effectiveness, expediency, and (freedom from) corruption of governments and hence of
the likely level of genuine input in a scientific, assessment, or decision-making process.
•
Because of variation in the available human capital and the stability of relationships over
time, “institutional memory” cannot be considered constant or steadily increasing. Thus,
there is an ongoing need for refreshing, rebuilding, or even completely reestablishing
ties between service organizations and stakeholders. There may also be a need to
identify relatively stable contacts inside or outside of traditional governance institutions
that can provide institutional memory and continuity over time.
•
There are many reasons why anyone (potential) stakeholder may get engaged or not
engaged in an issue, and be willing to speak out about their interests or not. Even if
there is a long history of working with stakeholders in the community or region already,
it would be wise to critically reassess whether the “right” stakeholders are involved or
have been overlooked.
•
Clearly defining goals for the stakeholder engagement processes is critical for the
participants, for the planning and implementation of the process itself, and for
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subsequent evaluations of effectiveness. Failing to state the intended goals up front and
clearly, or—in truly mutual, dialogic, participatory processes—failing to involve
stakeholders in setting and (re-)negotiating common goals, can severely undermine the
process. Clearly, however, stating goals up front also can involve delivery pressures.
•
Intended achievements can vary widely, encompassing process goals, direct output
goals, and wider outcomes. The relative weight between process and output/outcome is
context, issue, and stakeholder specific. Neglect of one for the sake of the other is likely
to lead to suboptimal results. However, in setting and evaluating goals, the questions
that must always be asked are “whose goals?” and “who evaluates them?”
In summary, there are many emerging lessons on “best practices” in stakeholder
engagement processes, yet many questions about goals, mechanisms, and effectiveness continue
to be debated in the literature and require further systematic examination.
4.
SUMMARY AND SOME PROMISING RESEARCH FRONTIERS
The topics covered in this report are vast and selectively and incompletely reviewed, and
several others could have been selected for additional discussion. Maybe the highest-level
conclusion that can be drawn from this review is that there is a vast and important social
scientific research base that can be drawn upon for the study of social-ecological resilience, and
there is no reason for the continued separation of epistemic communities as described by
Janssen. In fact, the gain from closer collaboration and integration of knowledge across these
disciplinary and paradigmatic lines could only benefit these neighboring research
communities—and the world, if this knowledge were also effectively communicated across the
science-practice boundary.
At the same time, a closer look at what is and what is inadequately known to date on many
of the involved sub-topics discussed here suggests that the superficial or partial absorption of
knowledge from one area of expertise is likely to result in conclusions that are unhelpful at best,
and outright misleading at worst. For example, the loose use of terms such as vulnerability,
resilience, adaptive or coping capacity, robustness, social capital, or governance can lead to
confusion and inaccuracies, and the relationships between these terms get muddled.
Underlying paradigmatic differences can be profound, implying different perspectives, values,
and ethics. Moreover, many causal connections are far more subtle or differentiated than
commonly acknowledged, the consequences of which for policy and management intervention
can be profound.
4.1
4.1.1
Summary of Insights vis-à-vis the Four CARRI Dimensions of Resilience
Anticipate
One of the key insights from the global change literature reviewed here is that calculating
the risk a community or region may be facing with a focus on just one type of hazard may be
misleading. Differently put, assessing and fostering community or regional resilience to just one
type of risk or disturbance is never enough. Situations can easily be imagined where multiple
stressors or crises converge, exceeding the ability of any social-ecological entity to sustain itself,
that is, to recover after the crisis and continue functioning and thriving. This suggests that
environmental changes do not necessarily have to be dramatic in scope or rate to exceed societal
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capacity to respond and adapt. Multiple stressors or adaptations that simply prove insufficient
in the end can result in large-scale system collapses.
The specter of accelerating global environmental change, however, places the study of
hazardous events and of resilience in a dynamic context. The reality of climate change and other
types of global environmental changes suggests that if community managers simply focus on
returning to the pre-disaster “normal” and assume a static climate or environment, they would
be under-preparing their communities for future events.
Of course, the forecast of extreme events is difficult enough. Accelerating climate change
and the possibility of abrupt changes in climate faces makes this even more difficult as historical
climate variability is no longer an adequate guide to the future. This poses difficult-to-overcome
challenges, especially when such changes are hard (or even impossible) to predict or if they
involve trend reversals. Even if abrupt changes are unidirectional with existing trends,
however, economic costs and societal impacts are likely to be enormous and outside historical
experience.
4.1.2
Reduce
Reducing existing vulnerability is considered a win-win situation vis-à-vis difficult to
anticipate or forecast hazardous events in a rapidly changing climatic and social environment.
While global change researchers would easily agree with this proposition, a persistent fault
line runs through global change studies on vulnerability. On one side of this divide are those
who view vulnerability as the context or initial condition characterizing the system which will
experience a disturbance. On the other side are those who view vulnerability as the outcome,
after a system has experienced a disturbance and done all it could to reduce the impacts.
Adding to the conceptual confusion, vulnerability is sometimes taken to be the exact
opposite of resilience, but that is by no means clear. Its underlying components of exposure,
sensitivity, and response capacity have ambiguous relationships to resilience.
Moreover, vulnerability—most broadly defined as the potential for transformation—
certainly implies risks to existing assets, interests, and people, but it may also open up
opportunities for social improvement, learning, and growth. Communities may be able to
reduce deep-seated vulnerabilities and renew and rebuild better after a hazardous events, if
they are prepared and able to take advantage of their vulnerability and challenges. Resilience,
on the other hand, can produce systems that are “trapped” in unhealthy, unproductive, or
otherwise undesirable states. Thus, vulnerability is not always a bad thing and resilience not
always good. The normative imperative of this dimension—to reduce vulnerability—therefore
should be taken with a grain of salt. CARRI researchers have an important opportunity to
clarify these relationships and not contribute to the misleading use of relevant terms.
4.1.3
Respond
As the experience with hazardous events in light of the global change literature presented
here suggests, communities and regions often draw on resources beyond their boundaries to
avert critical conditions, to help them respond to an immediate crisis, and certainly in the
recovery phase. This brings attention to the importance of cross-space and cross-scale linkages
critical to maintain resilience. The more widespread climate and other global environmental
change impacts will be in a world of finite resources, the less likely it is that communities can
rely with certainty on outside assistance. Critical states may be reached much sooner than
historical experience and even good planning would suggest.
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4.1.4
Recover
An increasing number of researchers in the human dimensions of global change arena seem
to adopt an ecological view of resilience that sees it as not only the capacity to withstand and
bounce back from disturbances for some time but also, past a certain point, to transform while
continuing or regaining the ability to provide essential functions, services, amenities, and
qualities. Thus, for social-ecological systems to be considered resilient over time, they need to
have the capacity to cope with and recover from present-day risks and the capacity to adapt to
changing conditions, including uncertain, unknown, or unpredictable risks. This constitutes an
important extension of what is commonly understood as “recovery.”
Many actions that may be taken to cope with and recover from current hazards may also be
adaptive in the long run. Yet there is also the danger that steps taken during recovery to current
hazards may actually increase vulnerability to even bigger disturbances as a result of climate
change. The strong historical focus on coping, adaptive, or response capacity as an indicator of a
systems ability to recover seems insufficient. A social-ecological system also needs the
resources, skills, power, and willingness to realize its coping and adaptive capacity into real
actions.
Another insight emerging both from the hazards and the global change literature is that
recovery toward a more resilient state is not automatic, nor is it guaranteed. If policy ideas,
innovations, and adaptation plans exist prior to a crisis, it is more likely that these will be
implemented after the crisis, whereas in the absence of such plans, the main focus of recovery
tends to be on the reestablishment of the status quo. This obfuscates the ability to learn and
adapt to change, and thereby undermines long-term resilience.
4.2
Additional Insights Relevant across the Four Resilience Dimensions
Some of the other important findings from this review apply to and integrate across the four
dimensions of resilience as discussed above. First, resilience is scale, context, and disturbance
specific, and as such not merely an inherent characteristic of a given social-ecological system but
rather an emergent property that arises from the interaction of the system, its environment, and
the forces that act on both.
Second, the conceptualization of the entity at risk of change (e.g., a city, a region) has
profound implications for the location of transformative forces, for the resources available to
build and maintain resilience, and for the interactions of the entity in question across scale. For
example, if the focus of study is a city along the Mississippi River, and the disturbance is a
flood, it matters significantly whether this is a localized event or a hazard affecting much of the
Mississippi watershed, what the relationships are—for example, in terms of trade,
transportation, and other lifelines—across the affected and non-affected areas, from how far
away outside assistance may come, and so on.
Third, the global change research community is slowly converging on an understanding of
resilience that goes beyond the “engineering” conceptualization prevalent in the hazards
community. The more “ecological” understanding of an entity able to learn, adapt, and change
seems critical against the backdrop of a changing climate and socio-ecological environment.
A fourth set of insights focuses on the issue of social capital. It is frequently invoked as a
critical element in social-ecological resilience, but it is important not to adopt this concept
uncritically. Social capital can have positive and negative consequences for social interactions,
cohesion, information sharing, power relationships, and so on—all of which are critical in the
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anticipation, vulnerability reduction, response, and recovery phases. Typically, social capital as
a within- or intra-community (bonding) phenomenon appears to produce predominantly
desirable outcomes to its members but can bestow undesirable outcomes on those considered
“other.” Bridging social capital is required to overcome those negative consequences. There are
cases, however, where even the impacts of bonding social capital are ambiguous, negative, or
difficult to predict.
In this context, the distribution of power within and across communities must be examined
carefully to understand whether or not social capital is a helpful resource in a community or
region’s capacity to respond and recover from disturbance. Bridges have to be built over the
divides between separate social networks or communities to ensure the widest possible spread
of information, knowledge, and experience.
Fifth, it is far from assured that
existing governance systems help or
It is far from assured that existing governance
hinder resilience. In part, this is a
systems help or hinder resilience. In part, this is a
question of functionality and
question of functionality and effectiveness; in part,
effectiveness; in part it is in the
it is in the stabilizing (and sometimes ossified)
stabilizing (and sometimes ossified)
nature of institutions, norms, and bureaucratic
nature of institutions, norms, and
bureaucratic systems that their
systems.
responsiveness to current and future
crises must be questioned.
And finally, in support of “good” governance and long-term achievement of resilience in
the face of a rapidly changing climate, science and technology hold a privileged position. There
is great potential for enhancing resilience in making better use of existing and emergent
knowledge. In the areas of vulnerability, adaptation, and resilience, knowledge-action systems
that link science and practice are often assumed to exist, but empirical evidence suggests that
they are at best in the early stages of realization, and few can as yet serve as models of
effectiveness. Thus damages and losses from hazardous events continue to rise even faster than
our knowledge base, and strongest efforts are needed to alter this trend.
Communication is one of the most important ingredients in enabling mutually educational
and satisfying interactions between scientists and practitioners, but it alone does not guarantee
proper use of scientific information or socially and environmentally beneficial outcomes.
Rather, action on environmental change or hazards-related information typically occurs only if
it does two things simultaneously: first, sufficiently motivate actors to make a change or adopt a
new policy and lower or constructively address existing obstacles to such a behavioral or policy
change.
Stakeholder engagement has become best practice in many place-based research,
assessment, and decision-making efforts, yet there is an ongoing debate over the relative merits
of participatory versus technocratic processes. With a growing body of literature demonstrating
with empirical evidence that the input from non-technical stakeholders into assessment and
decision processes actually can improve various outcomes, the balance is shifting toward
acceptance and sometimes enthusiastic embrace of stakeholder processes. The CARRI project’s
three place-based case studies offer a ripe opportunity to show with empirical evidence how
active stakeholder engagement is likely not only to improve the risk assessment but also to
increase the acceptance of policy and management actions that will build greater resilience.
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4.3
Promising Future Research Directions
Selected areas for promising future research that this review highlighted or brought to the
fore include the following.
•
What are the some key social indicators of resilience, and what are some early warning
signs that a system is exhausting its resilience or is nearing collapse?
•
During extended periods of duress, what are the most important structures and
processes, actors, and assets to maintain long-term resilience? What is the relation to
civil unrest and the loss of social capital?
•
In what ways and under what circumstances do actions undertaken to cope with current
disruptions foster or undermine long-term adaptive capacity and resilience?
•
In any one specific context, what are the factors that limit realization of existing adaptive
capacity and therefore reduce resilience?
•
If communities and regions cannot assume outside assistance, how does this change the
assumptions about long-term resilience?
•
What is the relative role of government, civil society, and the private sector in building
regional and community resilience? When are they helping or hindering selforganization, the beneficial use of social capital, and the ability to learn and change?
•
How can a refined understanding of social capital inform interventions at the regional
and local level to support long-term resilience?
•
What does “good governance” under (extended) crisis conditions look like? Therefore,
what aspects of governance should be strengthened in normal times?
•
How can knowledge-action systems for the reduction of vulnerability, adaptation to
climate change, and long-term resilience be established, fostered, and institutionalized?
•
Under (extended) crisis conditions (e.g., abrupt climate change; repeat extreme events),
what is the proper place for stakeholder engagement, and how do the processes need to
be adapted to such conditions? When are stakeholder processes useful, or no longer
useful? How can we better evaluate their effectiveness? Are there limits to realizing our
democratic ideals?
In light of the growing urgency of climate change and other interacting stressors, there is no
time to lose to begin tackling these and many more practice-relevant questions. Maybe like
never before does the scientific community have a crucial responsibility in focusing on them, to
help avert widespread human suffering, astronomical economic losses, and maybe even species
survival.
5.
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