Introduction to Socio-Ecological Resilience
Summary and Keywords
In recent years, the notion of resilience has grown into an important concept for both scholars and practitioners working on disasters. This evolution reflects a growing interest from diverse disciplines in a holistic understanding of complex systems, including how societies interact with their environment. This new lens offers an opportunity to focus on communities’ ability to prepare for and adapt to the challenges posed by natural hazards, and the mechanism they have developed to cope and adapt to threats. This is important because repeated stresses and shocks still cause serious damages to communities across the world, despite efforts to better prepare for disasters.
Scholars from a variety of disciplines have developed resilience frameworks both to guide macro-level policy decisions about where to invest in preparedness and to measure which systems perform best in limiting losses from disasters and ensuring rapid recovery. Yet there are competing conceptions of what resilience encompasses and how best to measure it. While there is a significant amount of scholarship produced on resilience, the lack of a shared understanding of its conceptual boundaries and means of measurement make it difficult to demonstrate the results or impact of resilience programs.
If resilience is to emerge as a concept capable of aiding decision-makers in identifying socio-geographical areas of vulnerability and improving preparedness, then scholars and practitioners need to adopt a common lexicon on the different elements of the concept and harmonize understandings of the relationships amongst them and means of measuring them. This article reviews the origins and evolution of resilience as an interdisciplinary, conceptual umbrella term for efforts by different disciplines to tackle complex problems arising from more frequent natural disasters. It concludes that resilience is a useful concept for bridging different academic disciplines focused on this complex problem set, while acknowledging that specific measures of resilience will differ as different units and levels of analysis are employed to measure disparate research questions.
Global climatic and environmental changes affect the well-being of people everywhere. Forced displacement due to conflict and natural disasters and endemic poverty challenge the coping capacity of communities and states around the globe. More intense natural hazards—such as super typhoons, heavy rains, or droughts—are already being felt as the world approaches two degrees Celsius of global warming. These severe weather-related events cause the destruction of livelihoods, loss of lives, and displacement. Such events and shifting climatic patterns reveal the “underlying fragilities” of communities that turn “shocks and stresses into humanitarian crises” (ODI, 2016). How communities respond and adapt to these stresses and perturbations is captured in the concept of resilience.
Resilience offers a means to understand how human and natural systems cope with shocks. A resilient system is one that is able to withstand, adapt to, or transform in the face of changing pressures. Conversely, a system which is not resilient is likely to be seriously negatively affected by changing pressures. It will not be able to adapt or transform and may collapse as a functioning system entirely. When applied to communities, this typically results in a humanitarian catastrophe that necessitates outside—national and international—assistance.
Resilience breaks down silos by providing a “conceptual umbrella under which different disciplines can come together to tackle complex problems with more holistic interventions” (Levine, 2014a). Resilience frameworks are crossing the boundaries that have traditionally distinguished development assistance from climate change adaptation and humanitarian aid, and are inspiring multidisciplinary approaches to improving peoples’ ability to prepare for and reduce their vulnerability to disaster. Resilience captures both the structural and economic strengths of a community or society, as well as the social networks and processes that determine whether a community or society can successfully adapt to a changing environment. The idea is that strengthening the resilience of all people at all levels across the whole disaster cycle will lessen the impacts of a disaster, reduce disaster-related losses, and lead to faster recovery and the ability to “build back better.” Ultimately, sustainable development and resilience are inextricably linked (Cutter et al., 2008). Efforts to make development sustainable are likely to make those societies more resilient, and societies that invest in resilience measures also lay the foundation for more sustainable development.
This article introduces and explores the concept of resilience, addressing the following questions:
□ How has resilience been defined, and what is its relationship to other concepts?
□ How has the positioning of resilience changed in the international agenda and in relation to disaster management?
□ How is resilience measured?
□ Is resilience useful to policy and decision-makers?
Despite decades of research and theory-building, there is today no universally accepted definition of resilience. The concept of resilience continues to evolve, even as it has gained in popularity and significance in the international agenda. The focus here is on the role of resilience in disaster management, including a discussion of how resilience is currently being measured and, finally, how resilience could be taken forward as a useful and practical concept, grounding it firmly in local contexts.
Defining “Resilience”: Complex Concept, Multiple Definitions
Evolution of “Resilience”
Resilience is a complex, multifaceted term that has evolved in meaning as it has gained prominence across a number of different fields (Alexander, 2013). The term originated in ecological theory as a measure of the ability of a system to absorb changes or shocks from a disturbance and yet still maintain its internal relationships (Holling, 1973). This early interpretation centered on the persistence of relationships within a system, where they maintain a steady state or equilibrium. The system avoids crossing a threshold into a potentially new and irreversible state. Early resilience studies focused on the time it took for a system to return to its original state as a measure of resilience. The shorter the time to return to the original equilibrium, the more resilient a system was. To give an example of an ecological system whose resilience was overcome, the loss of summer polar sea ice due to global warming is almost certainly irreversible: it has crossed a threshold from which it is unable to return to its previous state (Rockström et al., 2009).
Over time, the term “resilience” came to influence fields outside of ecology, particularly the social sciences (Adger, 2000; Turner et al., 2003). Understandings of resilience also broadened to reflect a greater appreciation that living systems are dynamic and continually developing, that global systems are changing rapidly, and that returning to a previous state or equilibrium might not be a long-term viable strategy. Systems might need to transform and adapt in the face of change (Wisner et al., 2003; Smit & Wandel, 2006; Joakim et al., 2015). Transformation describes responses that produce radical or nonlinear positive changes in systems, and thus can be a powerful means of addressing root causes of risk (Wisner et al., 2003). The challenge is how to direct this transformation in such a way that the new equilibrium is better able to withstand the shocks anticipated to be a part of global climate change, among other global challenges.
To be able to guide positive transformation necessitates understanding the systems holistically, so that positive changes occur throughout. This means taking into account the numerous influences of both the human and natural world, which are inextricably linked. This is the basis of the conceptual frameworks of coupled human and natural systems (CHANS) (Liu, 2007a, 2007b) or socio-ecological systems (SES) (Berkes et al., 2008). These frameworks attempt to bridge the disciplines of environmental and social sciences and understand multiple feedback loops among the different variables (ecological and social) and multiple scales (local to global) in a system. The socio-ecological school of thought put a greater focus on renewal, regeneration, reorganization, innovation, social learning and development following a disturbance as means to describe how systems move from one state to another (Folke, 2006; Birkmann, 2006; Pelling, 2011). Systems lacking resilience and unable to cope with change could face dramatic negative consequences due to even small disturbances (Adger, 2006). In attempting to understand the complexity of systems, socio-ecological studies encounter both their strengths and weaknesses as a school of thought. As the concept of resilience has embraced complexity and broadened (with the addition of a multiplicity of associated terms), it better reflects a complex reality. However, both in theory and in practice a holistic framing of resilience is more challenging and requires more time to understand, particularly in relation to disasters.
The concept of resilience offers an interdisciplinary approach to global challenges which had previously been discussed separately: climate change adaptation, disaster risk reduction, sustainable development, and vulnerability (Levine et al., 2012). In understanding the resilience of a complex system, elements such as the system’s diversity, connectivity, adaptability, resistance, persistence, robustness, transformability, flexibility, and ability to reorganize are explored (Walker et al., 2004; Zobel, 2011; Kafle, 2012; Restemeyer et al., 2015).1 The idea of measuring resilience in terms of the speed at which a system returns to equilibrium still holds currency, but it is more nuanced. Feedback loops determine the magnitude and speed of change of the system as a whole and the speed by which the system can transform and still retain some of its original identity and structure (Lockwood et al., 2015). The outcome is not simply a return to the status quo, as Redman points out: “The end result it is not predetermined and may ultimately resemble the system’s preexisting conditions or be different, i.e., regime shift” (Redman, 2014). This could involve tipping into a new, more desirable state, through creative transformation, captured in the idea of “building/bouncing back better” (Gupta et al., 2010).
Resilience activities may focus on identifying and offsetting proximate causes of risk, or they may be focused on the root causes of risk. Pelling looks at the relationship between proximate and longer-term activities in the resilience-transition-transformation framework (Pelling, 2011). Here “resilience” is taken back to its original meaning of stability, persistence, and maintaining the status quo. “Transition” refers to incremental change, while “transformation” means radical change. The reason these three terms are distinguished, it is argued, is that resilience “can slow down more profound change as incremental adjustments offset immediate risks while the system itself moves ever closer to a critical threshold for collapse” (Pelling, 2011, p. 24). Systems which are resilient or transitional in this framework remain “limited to protecting existing system properties, even where these are associated with the structural causes of risk, which can build pressure for eventual, catastrophic system collapse” (Pelling, 2011). Transformative choices might be the only real means by which to address structural or root causes of risk, and to consider in particular who or what is the subject of change (Pelling, 2011; Cutter, 2016a).
Influenced by a multitude of interlinking factors and elements, resilience is about avoiding long-lasting negative development consequences through resisting harmful change, or adapting to change in a timely and efficient manner. Figure 1 offers a representation of different forms of resilience or ways a system might respond to exogenous shocks. The visual representation of resilience in Figure 1 goes beyond linking the core terms of resilience (absorptive capacity, adaptation, transformation, etc.) in diagrams (Venn diagram, hierarchy, flow chart, scale) (Birkmann, 2006; Nelson et al., 2007; Bene et al., 2012), and specifically avoids attributing any characteristics or components of resilience, which depend on local circumstances.
The original state (system equilibrium, or stable strategy) represents a stable state where system structure and function are suited to the environmental context and to changing dynamics within the system. When a severe event shocks the system, in scenario A the system “bounces back better” and the system functioning and structure shifts positively so that a similar future event would only cause a minor disturbance to the new state. This system is highly resilient and is capable of continually adapting to change. In scenario B, the system returns to the original state and there is no adaptive transformation. This corresponds to the conception of resilience in which systems are assumed to be stable and the change can be controlled to bring the system back to the original equilibrium. In scenario C, the system takes a long time to return to the previous state, and while it does eventually recover, it only returns to the original equilibrium. This system exhibits less resilience than scenario B. In scenario D, the system loses all functionality and does not return to the original state, and is therefore not resilient.
The axes show the time it takes (x-axis) to return to the stable strategy and the strength of the system functioning and structure (y-axis). The point along the y-axis at which the system originates gives some indication of how resilient the system is. The impact of the event can also be captured by how much system functioning is lost (decrease in y). Finally, the intensity of the change needed to return to a stable strategy can be shown by the increase in system functioning and structure, as the new stable strategy moves higher along the y-axis (as in Scenario A). The graphic conveys the idea of resilience as the ability of a system to better anticipate, absorb, and recover from a shock and adapt successfully so as to improve the system for future events (Cutter, 2016a).
Resilience does not have an internationally agreed-upon definition. A literature review conducted by Stein (2013) found sixty different variations of a definition for resilience from 1996 to 2013, showing how popular this term is and how divided scholars are over how it should be defined, some of which are presented in Table 1. The United Nations Office for Disaster Risk Reduction (UNISDR), among the foremost international agencies tasked with disaster preparedness, defines resilience as: “The ability of a system, community or society exposed to hazards to resist, absorb, accommodate to and recover from the effects of a hazard in a timely and efficient manner, including through the preservation and restoration of its essential basic structures and functions.” The Stockholm Resilience Centre, one of the leading research institutions focusing on resilience, defines it as “the capacity of a system, be it an individual, a forest, a city or an economy, to deal with change and continue to develop.” Which follows very closely “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” (Walker et al., 2004). These definitions are much broader and more general than that of UNISDR, and leave out the dimension of time it takes to adapt to change. A more comprehensive definition is proposed by the Resilience Alliance: “the capacity of a social-ecological system to absorb or withstand perturbations and other stressors such that the system remains within the same regime, essentially maintaining its structure and functions. It describes the degree to which the system is capable of self-organization, learning and adaptation.” Societal or community resilience has been defined as the ability of social, organizational, or economic systems to protect themselves against, react effectively to, and recover from the occurrence of a shock with minimal reliance on outside aid (Zobel, 2011; Frazier et al., 2013). Continuous development and transformation are emphasized by Folke, who writes that resilience is about “how to persist through continuous development in the face of change and how to innovate and transform into new more desirable configurations” (Folke, 2006). The common themes which unite these varying definitions include absorbing disturbance to a point past which reorganization occurs to deal with the change effectively in a timely manner, so that the system retains essentially the same identify and function and can continue to develop (Walker et al., 2004; Lei et al., 2014).
Table 1. Definitions of Resilience
Field of study
“Measure of the persistence of systems and of their ability to absorb change and disturbance and still maintain the same relationships between populations or state variables.”
The focus is on the persistence of an existing system
Adger et al. (2000)
Human Geography/Social Resilience
“The ability of groups or communities to cope with external stresses and disturbances as a result of social, political and environmental change.”
Human agency is introduced
Carpenter et al. (2001)
“The magnitude of disturbance that can be tolerated before a socioecological system (SES) moves to a different region of state space controlled by a different set of processes.”
The focus is on returning to equilibrium, and is influenced by stable strategies from ecology
Bruneau et al. (2003)
Three parts: Reduced failure probabilities Reduced consequences from failure; Reduced time to recovery.
Persistence and recovery to the original state are the core elements
Walker et al. (2004)
“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.”
Persistence and reorganization are equal strategies
“Persist through continuous development in the face of change and how to innovate and transform into new more desirable configurations.”
Continuous development and transformation are viewed as persistence of a system
Cutter et al. (2008)
“Resilience is the ability of a social system to respond and recover from disasters and includes those inherent conditions that allow the system to absorb impacts and cope with an event, as well as post-event, adaptive processes that facilitate the ability of the social system to re-organize, change, and learn in response to a threat.”
Absorbing up to a point at which a system should learn and reorganize
Norris, et al. (2008)
“A process linking a set of adaptive capacities to a positive trajectory of functioning and adaptation after a disturbance.”
The focus is what happens after a disturbance, rather than holistically across the disaster cycle
Gunderson, L. (2009)
Ecological: “Two meanings; one is defined as return time following a perturbation, the other as the amount of disturbance to shift regimes.” Human community: “Multiple meanings, but primarily refers to return or recovery time. Limited application to regime shifts.”
Places importance of recovery time in measuring resilience. Adaptation in human systems is not considered.
Plodinec, M. J. (2009)
“Community resilience is the capability to anticipate risk, limit impact, and bounce back rapidly through survival, adaptability, evolution, and growth in the face of turbulent change.”
Resilience as an attribute with adaptability at its core.
Rose, A. (2009)
“The ability of economic entities to maintain function and recover quickly from a disaster.”
The focus is on persistence and maintaining function
“The ideal condition of a community in terms of its capacity to anticipate, prepare for, respond to and recover quickly from the impacts of a disaster.”
A broad definition which acknowledges that community resilience is a relative concept
Zobel et al. (2012)
“The capacity of such systems both to withstand the initial impact of disaster events and to recover from them in a timely manner.”
The focus is on the persistence of an existing system
IPCC (2012) & UNISDR
“The ability of a system and its component parts to anticipate, absorb, accommodate, or recover from the effects of a hazardous event in a timely and efficient manner, including through ensuring the preservation, restoration, or improvement of its essential basic structures and functions.”
Broad definition which focuses on systems persisting
National Research Council (2012)
Hazards and Disaster Management
“The ability to prepare and plan for, absorb, recover from, or more successfully adapt to actual or potential adverse events.”
An all-encompassing definition which captures ability to absorb as well and transform
“Resilience is a function of a society’s ability to react effectively to a crisis with minimal reliance on outside aid.”
The focus is on internal abilities of societies
Lei et al. (2014)
“The ability to resist, absorb, accommodate to and recover from the effects of a hazard in a timely and efficient manner.”
The focus is on the persistence of system, without explicit reference to transformation
Royal Society (2014) “Resilience to Extreme Weather”
“The capacity of individuals, communities and systems to survive, adapt, and grow in the face of stress and shocks, and even transform when conditions require it.”
The dynamism of the system is emphasized
Moberg & Simonsen (2014) Stockholm Resilience Centre
“The capacity of a system, be it an individual, a forest, a city or an economy, to deal with change and continue to develop.”
Broad definition which focus on continuous transformation
Resilience Alliance (2016)
“The capacity of a social-ecological system to absorb or withstand perturbations and other stressors such that the system remains within the same regime, essentially maintaining its structure and functions. It describes the degree to which the system is capable of self-organization, learning and adaptation.”
System persistence through learning and adaptation
As demonstrated by Table 1, alongside socio-ecological definitions of resilience, the concept is used in numerous fields, such as engineering, development, economics, and climate sciences. Within these fields, resilience has also evolved over time in meaning, scope, and attempts at quantification—see the previous excellent overviews, reviews and analyses of the different definitions of resilience (Rose, 2009; Bruneau et al., 2003; Norris et al., 2008; Plodinec, 2009).
Resilience and Other Concepts
The multiplicity of definitions of resilience results in conflation—through overlaps and similarities of definition—with other terms. Most notably, there is contention about where resilience fits with other disaster-related concepts like disaster preparedness, adaptability, and vulnerability, and also how it is distinguished from sustainable development (Pelling, 2011). Another, less contentious view is that the concepts are related and cannot be understood independently from each other (Miller et al., 2010).
Disaster preparedness has been used interchangeably with resilience (Uscher-Pines et al., 2013a), as it contains similar elements of systems, societies, or communities being able to anticipate, respond to, and recover from a disaster. However, disaster preparedness relates more to immediate and often life- and asset-saving activities, and rarely addresses underlying causes of disaster risk. Resilience is longer-term and bridges the whole disaster continuum.
The relationship between resilience and vulnerability is also unclear. In part, this lack of distinction is due to the multitude of definitions provided for both resilience and vulnerability (Joakim et al., 2015). Vulnerability has been defined as a structural issue in some cases and as a measure of exposure to hazards in others (Cutter et al., 2008). Sometimes, vulnerability and resilience are viewed as complementary concepts along a continuum, with vulnerability and resilience at opposite ends (Joakim et al., 2015): reducing underlying vulnerability is a prerequisite to obtaining a resilient state (Miller et al., 2010; Kafle, 2012; Lei et al., 2014; Frazier et al., 2014). Alternatively, they are viewed as distinct concepts in which all combinations of resilience and vulnerability can be matched. Different systems can have high resilience, high vulnerability; high resilience, low vulnerability; low resilience, high vulnerability; or low resilience, low vulnerability, at any given time (Joakim et al., 2015).
Finally, there is a lack of clarity around how sustainability and resilience combine or interact. Sustainability centers on “development that meets the needs of the present without compromising the ability of future generations to meet their own needs” (UNISDR, n.d.). Resilience is also about ensuring positive transformation which does not compromise future well-being. Is resilience the tool through which sustainable development can be achieved? Are resilience and sustainability saying the same thing? It is evident that the lack of an internationally agreed-upon definition is a significant challenge for proponents of resilience.
Further Challenges of “Resilience” As a Concept
While there is a significant amount of scholarship produced on resilience, the lack of a shared understanding of its conceptual boundaries and means of measuring it makes it difficult to see the results or impact or programming designed to promote it (Jones & Tanner, 2015). Its appeal in different fields has meant that resilience has become a buzzword, but the lack of a coherent conceptual framework means that measuring resilience is a challenge.
Measuring resilience is difficult precisely because the term has come to be used to represent numerous different types of programming and projects which are repackaged into generic “resilience-building” programs (Levine et al., 2012). Measuring the concept in practice would help to move resilience beyond repackaging old ideas toward building from and innovating with these ideas to ensure societies can positively transform in the face of disturbance. Resilience seeks to address the underlying social, economic, and political relationships that make some societies more vulnerable to disasters than others. It should not be applied to negative coping strategies and “unacceptable trade-offs that people are sometimes forced to make to guarantee survival” (Levine et al., 2012). There are challenges capturing and measuring intangible processes, such as coping capacity or social networks, which remain ill-defined in the literature themselves (Beauvais & Jenson, 2002; Uscher-Pines et al., 2013b). Resilience also suffers from a level and unit of analysis problem (Uscher-Pines et al., 2013a). While resilience is often thought to include dynamics that are global (climate change, population pressures, natural resource depletion, etc.), it is often quantified using different levels of analysis (country, region, community, household, individual) (Uscher-Pines et al., 2013a). Scholars from different disciplines focus on different dimensions of resilience (for example economic, psychological, environmental, and institutional). If, in practice, resilience is not adding any extra value, then the usefulness of the concept has severe limitations. But this cannot currently be known due to the lack of valid, commonly accepted assessment approaches.
The nature of the elements and feedback loops in a given system is unique to that system, making resilience highly context-specific. Community resilience in particular is largely contextually driven in its potential for recovery and bouncing back better, based on the intrinsic qualities of the community. A resilience factor for one system or community may not be applicable in another. Furthermore, there are trade-offs within systems regarding specific or general resilience. If a system becomes highly resilient to a certain event, it may have reduced its general resilience to other events (Schipper & Langston, 2015). Specific resilience and general resilience may even be mutually exclusive. Common themes exist in the different conceptualizations of resilience, and how these relate in a given environment for different groups helps build the specificity and usefulness of resilience for a given group and context.
Resilience As a Policy Tool
Ideally, resilience research can aid decision-makers by providing key information. For instance, resilience research helps to identify and prioritize geographical locations which need more investment. Resilience research can also help identify factors associated with a community’s inability to cope with disasters. While broader concepts of resilience may be generally useful as frameworks for discussion, specific measures of resilience will invariably depend on the unit and level of analysis selected to address a research question and the geographic and temporal nature of the question. To find these answers, multiple frameworks have been proposed. Frameworks attempt to combine socio-ecological-economic dynamics on the one hand, but to be generically applicable on the other so as to capture the most holistic possible picture of the system but also to be useful in a number of different contexts. The complex reality of resilience must be reduced into a simplified framework in order to extract answers for critical questions, such as who is likely to be most affected by a disturbance, what makes communities more or less sensitive to a crisis, or what the main drivers of disaster risk are. Resilience research seeks to answer these questions and use examples of best practice from elsewhere to help build resilience—and reduce disaster risk—in other risky locations.
In policy-making, resilience acts as an overarching framework to holistically understand disaster risk and development. Activities undertaken to increase resilience will mean disaster impacts are lessened and disaster-affected communities will have less need for external assistance. Disasters themselves may even offer an opportunity for humanitarian actors to be involved in resilience-building by using recovery efforts to change and address underlying inequities and lay ground for sustainable development, through building back better (Fan, 2013). Resilience as a policy tool becomes more effective if we ask: resilience for whom and under what circumstances (Cutter, 2016a)? To be able to comprehensively answer that question, and if resilience is to emerge as a robust and measurable concept, scholars and practitioners need to adopt a common lexicon on its different elements and to harmonize understandings of the relationships among them.
Significance of Resilience in the International Agenda
Emergence in Different International Agreements
Disaster resilience is front and center on the international agenda as policy makers come to grips with the enormous economic, social, and environmental costs already beginning to take hold as the climate warms. Hundreds of millions of people will be impacted as sea levels rise, driving populations away from flood zones and vulnerable coastal areas. Forced migration will add to social pressures and tax countries’ abilities to manage the conflicts expected as communities struggle to control scarce resources. Little is known about the potential diseases that could tear through urban communities or the rapid loss of species as temperatures rise. As average annual temperatures are rising every year, increasingly severe weather patterns are anticipated that will result in massive disasters. Policy makers are fully aware of these dangers and have moved to address these challenges by focusing on global economic development and building communities that are resilient to these changes.
Principal among these mechanisms is the Sustainable Development Goals (SDGs). The seventeen SDGs are part of the 2030 Agenda for Sustainable Development and were officially adopted in September 2015 at a United Nations Summit. The SDGs are broad-ranging, focused on eliminating poverty and improving global health and education. They also focus specifically on resilience, seeking to “reduce the number of deaths and the number of people affected … by disasters and water-related disasters with a focus on protecting the poor and people in vulnerable situations” (SDG Goal 11.5).
Resilience is also the focus of the Sendai Framework for Disaster Risk Reduction 2015–2030. The Sendai Framework was adopted at the Third UN World Conference in Sendai, Japan, on March 18, 2015 and follows the Hyogo Framework for Action (HFA) 2005–2015: Building the Resilience of Nations and Communities to Disasters. The word “resilience” appears no fewer than sixty-three times in a document that contains fewer than forty pages. Perhaps not surprisingly, resilience encompasses a number of dimensions in this framework, including “health and cultural resilience of people,” “environmental resilience,” “the building of resilience into policies, plans, programs and budgets,” “educational resilience,” “disaster risk resilience of workplaces,” “resilience of national health systems,” “business resilience,” “household and community resilience,” “resilience of critical infrastructure.” Interestingly, resilience is only used twenty-one times in the Hyogo Framework of 2005 and just once in the Yokohama Strategy and Plan of Action for a Safer World of 1994.
Resilience has been the policy and programmatic focus of organizations managing the consequences of global climate change since the millennium. It is the cornerstone of any strategy to deal with the impacts of climate change on society. As use of the term has expanded and enriched dialogue around the concept, it has also significantly expanded so that any operational definition is impossible without including caveats about what kind of resilience is meant, for whom, and from what. Whereas resilience had been used to define the ability of infrastructure to withstand shocks from disaster, it is now applied to every dimension of human society and is meant to include everything from psycho-social resilience of individuals and communities to resilience of livelihoods, cultural systems, economies, and so on.
The Role of Resilience in Disaster Management
How Disaster Risk is Intrinsically Generated
Disasters impact millions of people annually. Despite improvements in weather forecasting and in early warning and communications systems, millions are still vulnerable, some increasingly so, both because of underlying systemic failures (poverty and associated vulnerabilities, including lack of access to adequate health care, education, etc.) as well changing weather patterns associated with climate change. Wisner, Blake, Cannon, and Davis (2003) argue that the “spatial variety of nature provides different types of environmental opportunity and hazard” and that “humans are not equally able to access the resources and opportunities, nor are they equally exposed to hazards” because of class, gender, income, ethnicity, and age (Figure 2). Risk is thus intrinsically created in a system through inequality in resources distribution. Varying exposure, vulnerability, and coping capacity mean that people or communities are differentially able to deal with rapid or slow-onset changes related to disasters.
Even countries that invest considerable resources in disaster preparedness and disaster risk reduction, like the United States and Japan, are imperfectly able to able to cope with the impact of disasters. Notable recent examples include Hurricane Katrina in the United States in 2005 and the Fukushima nuclear accident caused by an earthquake and tsunami in Japan in 2011. Moreover, even in countries like the United States, changing weather patterns bring about more severe storms that are hitting further up the coast, to locations which had previously not felt such events, costing billions of dollars’ worth of damage to property and livelihoods. Hurricane Sandy alone resulted in losses of over 65 billion dollars in the United States in 2012. Disaster management necessitates a committed effort from leaders, in terms of policy and resources, to lessen the intrinsic risks built into societies.
In middle-income countries, disasters can have an even greater impact on lives and property, as there are typically fewer resources to devote to disaster preparedness and disaster risk reduction. For countries like the Philippines, repeated exposure to natural disasters erodes resilience by undermining economic output and negatively impacting livelihoods. The anticipated changes in weather patterns and sea level rise will only increase these costs in the coming years. Typhoon Haiyan, which hit the Philippines in 2013 (the strongest such storm to ever hit land), is considered “the new normal” by disaster managers. Despite generations of people having developed robust traditional methods for coping with natural disasters, shifting weather patterns mean that typhoons are now running through areas of the Philippines traditionally considered typhoon-free. These areas are especially vulnerable as there is generally less knowledge of and fewer resources for dealing with the impacts of severe storms. Furthermore, despite great advances in natural disaster science, many of these findings are not well understood by or effectively communicated to local communities.
Building Resilience As a Long-Term Disaster Management Strategy
The disaster management community has long recognized that preparing for response alone is an inadequate strategy for coping with disasters. Disaster preparedness is at least as important as response, as is a focus on developing sustainable livelihoods, reducing exposure to disasters, and developing economic opportunities away from flood plains and vulnerable coastal systems. These are but a few of the measures needed to reduce property losses and deaths during natural disasters. Whereas eco-friendly development is a long-term process, there is much that high, middle, and low-income countries can do to reduce disaster risk and build more disaster-resilient societies. These measures include supporting the development of empirical research; devoting increased resources to preparedness measures, especially in the form of a professional cadre of disaster managers; expanding disaster training and curricula; establishing multisector agreements for ensuring business continuity during disasters; improving disaster communications; and enhancing the range and quality of disaster finance tools.
As discussed in the section on definitions, resilience is malleable, and no single resilience framework captures every facet of resilience, nor is there any reliable means of measuring resilience, particularly at the community level. Katherine Wuff (2015) notes that “models suggest that community resilience is a function of not only economic development, information and communication, and community competence, but also the degree to which individuals experience strong social support, and have robust social connections.”
Yet, while local communities and local governments are the most affected by disasters and “play a key role in promoting an enabling environment for local adaptation,” very little is known about what kinds of resilience actions lead to the best outcomes with fewer deaths, less loss of property, and increased speed and efficiency of recovery (Uy et al., 2011). In part this is because national level data is often the only level of data available and is inadequate for measuring community resilience (see section “Measuring Resilience”) (Ostadtaghizadeh et al., 2015). All of this points to the need for an investment in research and an emphasis on routine collection of data at the community level. Until this is done, policy makers and government officials will be limited in their ability to design empirically informed disaster preparedness actions and will make decisions about investments with only partial information.
Bridging Humanitarian Response and Long-Term Recovery
The argument for building resilience is obvious: taking a whole of society approach, and in particular supporting the community structures that mean that people can help themselves, will lessen the need for international support. Reducing and minimizing this reliance is becoming more urgent as the shortfall widens between the financing of humanitarian aid and future disaster forecasts. It has been calculated that aid money and the productivity of aid spending must simultaneously double to respond to the growing number of crises and to help people return to normality (Miliband & Gurumurthy, 2015). There is still, however, a question as to what extent humanitarian aid should be involved in resilience building at all.2 Finally, how exactly resilience should be measured, and using what metrics, is crucial to defining the role of the concept in relation to other areas of humanitarian assistance or development.
Challenges of Quantitative and Qualitative Measurements
Broadly, resilience is either measured quantitatively or qualitatively, with quantitative, indicator-based measurements constituting the majority of research frameworks. In attempting to understand a system and the multifaceted nature of resilience, indicators are often chosen which can be used as proxy measures for a variable of interest (Kafle, 2012). Typically, these indicators are socioeconomic factors or biophysical factors.
Indicator-based quantitative measurements suffer from a number of limitations (Levine, 2014b). Firstly, objective indicators, such as socioeconomic factors, do not lend themselves to capturing less tangible elements of resilience like social capital or power relations (Lockwood et al., 2015). Measuring phenomena such as partnerships, self-sufficiency, and social connectedness has been attempted (Uscher-Pines et al., 2013b; Speranza et al., 2014). But in general these factors are neglected in studies or resilience, with easy-to-measure factors, such as income, family size, and number of meals, being favored. Neglecting these more social factors, however, may lead to “interventions that ignore the most important determinants of vulnerability” (Levine et al., 2012). Secondly, indicator selection can be biased, either by the researcher’s agenda or by the availability of data. Often, indicator-based frameworks require large databases of information, which might not exist in all contexts. Thirdly, choosing which indicators to use is very context-specific—what might be a resilience factor in one community might not contribute the same in another (Jones & Tanner, 2015). Quantitative approaches have been criticized for decontextualizing resilience, “making it harder to understand how specific threats shape people’s response to them” (Levine et al., 2012). However, quantitative approaches offer a more systematic and reliable way to measure various dimensions of resilience.
Qualitative frameworks can complement quantitative research by further capturing the intangible processes of resilience, such as social cohesion and how people evaluate their own risk. Qualitative approaches can capture in-depth data on how communities identify and prioritize their risks and perspectives on resilience factors, as well as the “purpose” of a community or system in building its own resilience (Hay et al., 2014; Brose, 2015).
A recent ODI report proposes “subjective resilience” as an alternative measurement related to “an individual’s cognitive and affective self-evaluation of their household’s capabilities and capacities in responding to risk” which allows peoples’ perspectives to be heard in a systematic manner and can complement more traditional indicator based methods (Jones & Tanner, 2015). Increasingly, hybrid approaches, using mixed methods, are the preferred mechanism to research resilience, as they produce richer data than any single method or approach (Miller et al., 2010; Jones & Tanner, 2015).
Overview of Indicators, Metrics, and Frameworks
Disaster resilience assessments fall into three main categories: indices (quantifiable variables of selected characteristics), scorecards (means of evaluating progress toward a goal), and tools (models which give simplified representations of systems) (Cutter, 2016a). A review found that the majority of assessments use indicators or scorecards (Cutter, 2016a). Identifying all the relevant political, socio-ecological, cultural, and economic indicators which are influencing factors for such a broad concept is difficult (Cumming et al., 2005). Along with identifying the numerous factors, it must be established whether they are positive or negative influences on resilience, which is highly context-specific. In trying to understand a system as a whole, the majority of frameworks propose incorporating biophysical and socioeconomic indicators into a single model (Schipper & Langston, 2015). This can involve amalgamating indicators (and indexes themselves) into a composite index (see, for example, the outline in Figure 3). Increasingly, models are designed to “weigh” the indicators according to their influence on the system dynamics (Frazier et al., 2014; Bahadur et al., forthcoming). This type of modeling enables multiple factors, and their unique influences, to be brought together to give a single measure, which can be compared over time or to different contexts.
Identifying clusters of high vulnerability, disaster risk, or low resilience is made possible using spatio-temporal contextualization of resilience through geographical mapping and analysis (Cutter et al., 2008; Frazier et al., 2014). The aim of these models is to aid decision-makers in identifying which indicators influence disaster risk the most, and where resources should be prioritized. Often, the frameworks offer a way of determining the baseline predicted resilience of a community, which aids programming.
Numerous frameworks are on offer to monitor and measure resilience. One analytic review assesses forty-three frameworks which consider resilience in the context of climate change adaptation, disaster risk management, food security, livelihoods, poverty, ecosystems, and conflict (Bahadur et al., forthcoming). An ODI publication identified seventeen different resilience frameworks which were used in an analysis to compare the different proposed indicators (Schipper & Langston, 2015). The frameworks differed in the number of indicators they proposed to measure resilience, from twelve main indicators to more than fifty in some frameworks. Mathematical modeling is also used to predict a community or system’s resilience, as a type of impact assessment (Zobel, 2011, 2014; Zobel et al., 2012). These models define baselines from sets of indicators and then create equations to look at loss and time to return to full functionality (Zobel, 2014), impacts of critical infrastructure failure (Jonkeren & Giannopoulos, 2014), or the magnitude and time line of the disruption (Zobel et al., 2012). These models have not always been validated empirically (Zobel, 2011).
Taking Resilience Forward
Despite the absence of a single defining framework or consistent methods of measuring resilience, the concept captures the essential ethos of what it means for communities to prepare for and adapt to the challenges posed by global crises. In short, the concept is likely here to stay, and both academics and practitioners will continue to grapple with how best to theorize the term and find robust means of measuring resilience empirically. Given the diversity of definitions and the different units and measures of analysis employed to date, scholars may have to partition the term by asking what kind of resilience (the level of analysis), for whom (the unit of analysis), and from what (the independent variables). The kind of resilience may include structural, livelihoods, health systems, or educational systems; for whom may be either individuals, families, communities, organizations, states, or regions; and from what could refer to drought, storms, floods, or a range of related shocks, such as conflict or financial crises. In short, resilience will always be the outcome variable, some form of exogenous shock the independent variable, and the baseline status of the system a constant variable. Seen in this light, resilience encompasses a multisector, societywide idea that is sensitive to the complexity of ecosystems and human systems as these face exogenous shocks. So, as desirable as it may be, reaching agreement on a single definition of resilience and a cohesive and representative set of metrics to measure it may not be plausible. Instead, we are witnessing many definitions of resilience, with scholars developing many different frameworks for measuring it. Collectively, the varied studies on resilience depict a complex landscape that enriches appreciation for the deeply context-specific nature of resilience, even if they consequently fall short of a unifying theory on what resilience is.
Ultimately, using different units of analysis and measuring different kinds of resilience promises to provide a more holistic understanding of the concept at a macro level. For example, a focus on individual and household resilience will help draw the focus to people and how they cope in real situations. The need for this is echoed in the literature (Hay et al., 2014; Levine, 2014b).3 A focus on community resilience will enable local governments to adapt best practices and set up institutions and policies aimed at enhancing communities’ capacity to adapt to threats. A focus on country-level resilience will be relevant both to national governments and to how individual countries’ resilience affects the broader international system.
A variety of different methodological approaches is suited to the complex nature of the concept of resilience. In some cases, a qualitative approach might be best, for instance as a means of capturing the motives of policymakers, government officials, or individual households in making certain decisions about their investments in disaster resilience. Quantitative approaches are better suited to measuring the complex relationships among economic, social, and political variables as composite measures of resilience. In many instances, studies that employ a mixed-methods approach are likely to be particularly rich in insights into how outcomes are interpreted by the communities being studied.
In addition to building the evidence base on disaster preparedness and developing greater conceptual coherence and operationally valid measures of resilience, greater emphasis on education and training are essential features of a commitment to building resilience, and thus improving disaster management. A better-trained, more professional core of government, private sector, and civil society actors will help ensure that measures being planned for disaster response enhance the longer-term resilience of their communities, or at the very least avoid undermining its resilience. This is particularly important for large-scale disasters, where an influx of large numbers of international aid workers and funding can have unintended economic consequences that pose challenges to local livelihoods. Moreover, well-trained and adequately prepared disaster professionals will require less assistance and will be better placed to lead the response and recovery when international support is needed.
Effective disaster management and preparedness require approach that encompasses the whole of society. No one sector of society (civil society, government, private sector) is independently capable of preparing for natural disasters, particularly in countries that are subject to multiple hazards and frequent and repeated natural disasters. Moreover, with anticipated sea level rise and increased exposure to severe weather events, all sectors of society are required to carefully plan for the long-term challenges ahead. Invariably, the poorest sectors of society are also frequently the most vulnerable to disasters and have the fewest resources to call upon when disaster does strike.
An essential part of disaster preparedness includes building in mechanisms to ensure business continuity. It is imperative for the benefit of the society as a whole that markets continue to function and that people retain their livelihoods. This is as important for psychological reasons as it is for economic ones. Having gainful employment and control over one’s life reduces the trauma associated with disaster and creates the foundation for a more rapid and solid recovery. An area that remains underexplored is risk financing. While disaster risk insurance products are increasingly used to mitigate the impact of disaster losses, far too few people are insured, and there are few fiscal instruments available to vulnerable populations. Once savings have been exhausted, disaster-affected populations need access to easily accessible loans and other options to bridge the gap between loss and recovery.
Global climate change will continue to increase threats to communities globally, and disaster response is an inherently costly and inefficient means for coping with the challenges posed by natural disasters. For populations already made vulnerable by poverty and conflict, the idea of creating more resilient communities is an attractive way of coping with myriad sets of challenges in a holistic and sustainable manner. This explains, at least in part, why the term remains so important to donors, policymakers, and development and humanitarian agencies.
There is much more that countries can do to reduce disaster risk and build more disaster-resilient societies, as outlined in the Sendai Framework and the Paris Treaty and covered broadly in the Sustainable Development Goals. A commitment to extending the empirical evidence base on resilience and fostering continued dialogue and interdisciplinary exchange will help engender a greater understanding of how disaster preparedness practices can result in more resilient communities. Resilience is a concept that will remain core to understanding and framing the way communities understand and prepare for disasters. And while researchers will continue to ask different questions and undertake investigations using different units and levels of analysis, a common lexicon of terms and a common conceptual framework will be all the more important as means of holistically joining disparate studies. If research is targeted specifically toward understanding different kinds of resilience, for whom, and in what circumstances, then the task of building a holistic understanding of the influencing factors becomes more manageable.
Adger, W. N. (2000). Social and ecological resilience: Are they related? Progress in Human Geography, 24(3), 347–364.Find this resource:
Adger, W. N. (2006). Vulnerability. Global Environmental Change, 16(3), 268–281.Find this resource:
Alexander, D. E. (2013). Resilience and disaster risk reduction: An etymological journey. Natural Hazards and Earth System Sciences, 13(11), 2707–2716.Find this resource:
Bahadur, A., Wilkinson, E., & Tanner, T. (forthcoming). Measuring resilience: An analytical review.Find this resource:
Beauvais, C., & Jenson, J. (2002). Social cohesion: Updating the state of the research. Canadian Policy Research Networks Discussion Paper No. F22. Ottawa, Canada: CPRN.Find this resource:
Bene, C., Godfrey-Wood, R.Newsham, A., & Davies, M. (2012). Resilience: New utopia or new tyranny? Reflection about the potentials and limits of the concept of resilience in relation to vulnerability-reduction programmes. IDS Working Paper 405. London: IDS.Find this resource:
Berkes, F., Colding, J., & Folke, C. (Eds.). (2008). Navigating social-ecological systems: Building resilience for complexity and change. Cambridge, U.K.: Cambridge University Press.Find this resource:
Birkmann, J. (Ed.). (2006). Measuring vulnerability to natural hazards—towards disaster-resilient societies. Tokyo: UNU Press.Find this resource:
Brose, D. A. (Ed.). (2015). Developing a framework for measuring community resilience: Summary of a workshop. Washington, DC: National Academies Press.Find this resource:
Bruneau, M., Chang, S. E., Eguchi, R. T., Lee, G. C., O’Rourke, T. D., Reinhorn, A. M., Shinozuka, M., Tierney, K., Wallace, W. W., & von Winterfeldt. D. (2003.) A framework to quantitatively assess and enhance the seismic resilience of communities. Earthquake Spectra, 19(4), 733–752.Find this resource:
Carpenter, S. R., Walker, B. H., Anderies, M. A., & Abel, N. A. (2001.) From metaphor to measurement: Resilience of what to what? Ecosystems, 4, 765–781.Find this resource:
Cumming, G. S., Barnes, G., Perz, S., Schmink, M., Sieving, K. E., Southworth, J., et al. (2005). An exploratory framework for the empirical measurement of resilience. Ecosystems, 8(8), 975–987.Find this resource:
Cutter, S. L. (2016a). Resilience to what? Resilience for whom? Geographical Journal, 182(2), 110–113.Find this resource:
Cutter, S. L. (2016b). The landscape of disaster resilience indicators in the USA. Natural Hazards, 80(2), 741–758.Find this resource:
Cutter, S. L., Barnes, L., Berry, M., Burton, C., Evans, E., Tate, E., et al. (2008). A place-based model for understanding community resilience to natural disasters. Global Environmental Change, 18(4), 598–606.Find this resource:
Estoque, R. C., & Murayama, Y. (2014). Social–ecological status index: A preliminary study of its structural composition and application. Ecological Indicators, 43, 183–194.Find this resource:
Fan, L. (2013). Disaster as an opportunity? Building back better in Aceh, Myanmar and Haiti. HPG Working Paper. London: ODI.Find this resource:
Folke, C. (2006). Resilience: The emergence of a perspective for social–ecological systems analyses. Global Environmental Change, 16(3), 253–267.Find this resource:
Frazier, T. G., Thompson, C. M., & Dezzani, R. J. (2014). A framework for the development of the SERV model: A Spatially Explicit Resilience-Vulnerability model. Applied Geography, 51, 158–172.Find this resource:
Frazier, T. G., Thompson, C. M., Dezzani, R. J., & Butsick, D. (2013). Spatial and temporal quantification of resilience at the community scale. Applied Geography, 42, 95–107.Find this resource:
Gunderson, L. H., & Holling, C. S. (Eds.). (2002). Panarchy: Understanding transformations in systems of humans and nature. Washington, DC: Island Press.Find this resource:
Gunderson, L. (2009). Comparing Ecological and Human Community Resilience. Research Report 5. Community and Regional Resilience Initiative, Oak Ridge, TN.Find this resource:
Gupta, M., Velasquez, G., Nag, S., Panda, A., Kuberan, R., Hari, K., et al. (2010). Building back better for the next time: Experiences and lessons learnt from the project “Building resilience to Tsunamis in the Indian Ocean.” Bangkok, Thailand: UNISDR Asia and Pacific.Find this resource:
Hay, A., Gómez-Palacio, A., & Martyn, N. (2014). Planning resilient communities, presented at Critical Infrastructure Symposium, April 7–8.Find this resource:
Holling, C. S. (1973). Resilience and stability of ecological systems. Annual Review of Ecology and Systematics, 4, 1–23.Find this resource:
IPCC (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation. A Special Report of Working Groups I and II of the Intergovernmental Panel on Climate Change [Field, C. B., V. Barros, T. F. Stocker, D. Qin, D. J. Dokken, K. L. Ebi, M. D. Mastrandrea, K. J. Mach, G.-K. Plattner, S. K. Allen, M. Tignor, & P. M. Midgley (Eds.)]. Cambridge University Press, Cambridge, U.K., and New York, NY, USA, 582p.Find this resource:
Joakim, E. P., Mortsch, L., & Oulahen, G. (2015). Using vulnerability and resilience concepts to advance climate change adaptation. Environmental Hazards, 14(2), 137–155.Find this resource:
Jones, L., & Tanner, T. (2015). Measuring “subjective resilience”: Using people’s perceptions to quantify household resilience. Working Paper 423. London: ODI.Find this resource:
Jonkeren, O., & Giannopoulos, G. (2014). Analysing critical infrastructure failure with a resilience inoperability input–output model. Economic Systems Research, 26(1), 39–59.Find this resource:
Kafle, S. K. (2012). Measuring disaster-resilient communities: A case study of coastal communities in Indonesia. Journal of Business Continuity & Emergency Planning, 5(4), 316–326.Find this resource:
Lei, Y., Yue, Y., Zhou, H., & Yin, W. (2014). Rethinking the relationships of vulnerability, resilience, and adaptation from a disaster risk perspective. Natural Hazards, 70(1), 609–627.Find this resource:
Levine, S. (2014a). Political flag or conceptual umbrella? Why progress on resilience must be freed from the constraints of technical arguments. Policy Brief. Humanitarian Policy Group. London: ODI.Find this resource:
Levine, S. (2014b). Assessing resilience: Why quantification misses the point. Working Paper. London: ODI.Find this resource:
Levine, S., Pain, A., Bailey, S., & Fan, L. (2012). The relevance of “resilience”? HPG Policy Brief 49. London: ODI.Find this resource:
Liu, J., Dietz, T., Carpenter, S. R., Alberti, M., Folke, C., Moran, E., et al. (2007b). Complexity of coupled human and natural systems. Science, 317(5844), 1513–1516.Find this resource:
Liu, J., Dietz, T., Carpenter, S. R., Folke, C., Alberti, M., Redman, C. L., et al. (2007a). Coupled human and natural systems. AMBIO: A Journal of the Human Environment, 36(8), 639–649.Find this resource:
Lockwood, M., Raymond, C. M., Oczkowski, E., Morrison, M. (2015). Measuring the dimensions of adaptive capacity: A psychometric approach. Ecology and Society, 20(1), 37.Find this resource:
Miliband, D., & Gurumurthy, R. (2015, July/August). Improving humanitarian aid: How to make relief effort more efficient and effective. Foreign Affairs.Find this resource:
Miller, F., Osbahr, H., Boyd, E., Thomalla, F., Bharawani, S., Ziervogel, G., et al. (2010). Resilience and vulnerability: Complementary or conflicting concepts? Ecology and Society, 15(3), 1–25.Find this resource:
Moberg, F., & Simonsen, S. H. (2014). What is resilience? An introduction to socio-ecological research. Stockholm: Stockholm Resilience Centre, Stockholm University.Find this resource:
National Research Council. (2012). Disaster resilience: A national imperative. Washington, DC: National Academies Press.Find this resource:
Nelson, D. R., Adger, N. W., & Brown, K. (2007). Adaptation to environmental change: Contributions of a resilience framework. Annual Review of the Environment and Resources, 32, 395–419.Find this resource:
Norris, F. H., Stevens, S. P., Pfefferbaum, B., Wyche, K. F., & Pfefferbaum, R. L. (2008). Community resilience as a metaphor, theory, set of capacities, and strategy for disaster readiness. American Journal of Community Psychology, 41, 127–150.Find this resource:
ODI. (2016). Resilience and humanitarian action projects.Find this resource:
Ostadtaghizadeh, A., Ardalan, A., Paton, D., Jabbari, H., & Khankeh, H. R. (2015). Community disaster resilience: A systematic review on assessment models and tools. PLoS Currents, 7.Find this resource:
Pelling, M. (2011). Adaptation to climate change: From resilience to transformation. Oxford: Routledge.Find this resource:
Pelling, M., O’Brien, K., & Matyas, D. (2015). Adaptation and transformation. Climate Change, 133(1), 113–127.Find this resource:
Plodinec, M. J. (2009). Definitions of Resilience: An Analysis. Community and Regional Resilience Initiative, Oak Ridge, TN.Find this resource:
Redman, C. L. (2014). Should sustainability and resilience be combined or remain distinct pursuits?Ecology and Society, 19(2), 37.Find this resource:
Resilience Alliance. (2016). Resilience alliance key concepts.Find this resource:
Restemeyer, B., Woltjer, J., & van den Brink, M. (2015). A strategy-based framework for assessing the flood resilience of cities: A Hamburg case study. Planning Theory & Practice, 16(1), 45–62.Find this resource:
Rockström, J., Steffen, W. L., Noone, K., Persson, Å., Chapin, F. S., III, Lambin, E., et al. (2009). Planetary boundaries: Exploring the safe operating space for humanity. Ecology and Society14(2), 32.Find this resource:
Rose, A. (2009). Economic resilience to disasters. CARRI Research Report 8. Oak Ridge, TN: Community and Regional Resilience Initiative.Find this resource:
Schipper, E. L. F., & Langston, L. (2015). A comparative overview of resilience measurement frameworks, analysing indicators and approaches. Working Paper 422. London: ODI.Find this resource:
Smit, B., & Wandel, J. (2006). Adaptation, adaptive capacity and vulnerability. Global Environmental Change, 16(3), 282–292.Find this resource:
Speranza, C. I., Wiesmann, U., & Rist, S. (2014). An indicator framework for assessing livelihood resilience in the context of social–ecological dynamics. Global Environmental Change, 28, 109–119.Find this resource:
Stein, A. (2013). Definitions of resilience 1996–present: Building resilience for food and nutrition security. Washington, DC: IFPRI.Find this resource:
Stockholm Resilience Centre Resilience Research. (n.d.). What is resilience? An introduction to social-ecological research.Find this resource:
The Royal Society. (2014). Resilience to extreme weather. The Royal Society Science Policy Centre Report 02/14. London: The Royal Society.Find this resource:
Turner, B. L., Kasperson, R. E., Matson, P. A., McCarthy, J. J., Corell, R. W., Christensen, L., et al. (2003). A framework for vulnerability analysis in sustainability science. Proceedings of the National Academy of Sciences, 100(14), 8074–8079.Find this resource:
UNISDR. (1994). Yokohama strategy and plan of action for a safer world: Guidelines for natural disaster prevention, preparedness and mitigation. Geneva, Switzerland: UN. Retrieved from https://www.unisdr.org/we/inform/publications/8241.Find this resource:
UNISDR. (2005). Hyogo framework for action 2005–2015: Building the resilience of nations and communities to disasters. Geneva, Switzerland: UNISDR. Retrieved from http://www.unisdr.org/2005/wcdr/intergover/official-doc/L-docs/Hyogo-framework-for-action-english.pdf.Find this resource:
UNISDR. (2015). Sendai framework for disaster risk reduction 2015–2030. Geneva, Switzerland: UNISDR. Retrieved from http://www.preventionweb.net/files/43291_sendaiframeworkfordrren.pdf.Find this resource:
UNISDR. (n.d.). Terminology. Retrieved from https://www.unisdr.org/we/inform/terminology.Find this resource:
United Nations. (n.d.). UN sustainable development goals knowledge platform. Retrieved from https://sustainabledevelopment.un.org/.Find this resource:
Uscher-Pines, L., Chandra, A., & Acosta, J. (2013a). The promise and pitfalls of community resilience. Disaster Medicine and Public Health Preparedness, 7(6), 603–606.Find this resource:
Uscher-Pines, L., Chandra, A., & Acosta, J. (2013b). Household preparedness is not enough: The challenges and opportunities in assessing community readiness for disasters. Journal of Public Health Management and Practice, 19, S70–S76.Find this resource:
Uy, N., Takeuchi, Y., & Shaw, R. (2011). Local adaptation for livelihood resilience in Albay, Philippines. Environmental Hazards, 10(2), 139–153.Find this resource:
Walker, B., Gunderson, L. H., Kinzig, A., Folke, C., Carpenter, S., & Schultz, L. (2006). A handful of heuristics and some propositions for understanding resilience in social-ecological systems. Ecology and Society, 11(1).Find this resource:
Walker, B., Holling, C. S., Carpenter, S. R., & Kinzig, A. (2004). Resilience, adaptability and transformability in social–ecological systems. Ecology and Society, 9(2).Find this resource:
Wisner, B., Blake, P., Cannon, T., & Davis, I. (2003). At risk: Natural hazards, people’s vulnerability and disasters. (2d ed.). New York: Routledge.Find this resource:
Wuff, K. (2015). What is health resilience and how can we build it? Annual Review of Public Health, 36, 361–374.Find this resource:
Zobel, C. W. (2011). Representing the multi-dimensional nature of disaster resilience. In Proceedings of the 8th International ISCRAM Conference–Lisbon, Portugal, May 2011 (pp. 1–5). Lisbon, Portugal: Information Systems for Crisis Response and Management (ISCRAM).Find this resource:
Zobel, C. W. (2014). Quantitatively representing nonlinear disaster recovery. Decision Sciences, 45(6), 1053–1082.Find this resource:
Zobel, C. W., Melnyk, S. A., Griffis, S. E., & Macdonald, J. R. (2012). Characterizing disaster resistance and recovery using outlier detection. In L. Rothkrantz, J. Ristvej, & Z. Franco (Eds.), ISCRAM 2012 Conference Proceedings Book of Papers: 9th International Conference on Information Systems for Crisis Response and Management (pp. 1–5). Vancouver, Canada: Simon Fraser University.Find this resource:
(1.) Diversity = The range of components of a system; Connectivity = the links between different components in a system; Adaptability = making changes within a system to make it less vulnerable; Resistance = ease or difficulty of changing the system; Persistence = the power to resist attack or other outside force; Robustness = resistance to initial loss; Transformability = transition to a new system when the existing system is untenable; Flexibility = ability to change or compromise without permanent change; Ability to reorganize = capacity to become a new fully functioning system following an event.
(2.) See Levine et al. (2012) for an alternative perspective on the involvement of humanitarian assistance in resilience building. In particular, “Humanitarian crises are rarely without a dimension of conflict (political, if not armed), and the powerful often have their own interest in how the livelihoods of the less powerful are ‘developed.’ Crises provide easy cover for the powerful to advance their own private interests and political agendas (relocating Mozambican peasant farmers from the fertile and flood-prone banks of the Zambezi, settling pastoralist victims of ‘drought’ in the Horn of Africa). Humanitarian actors are not equipped with the necessary political-economy savoir faire to avoid acquiescing in this: the lack of a historical dimension to the current resilience debate raises fears that long-identified and long-analysed mistakes will be repeated” (Levine et al., 2012).
(3.) Hay et al. (2014) propose four key shifts in resilience practice to make the concept more actionable and practically applicable, including a focus on people and continuity of operations, not just infrastructure, examining both shocks and stresses, not just shocks, redefining the concept of failure around people and operations, not just infrastructure, and going beyond prevention, into adaptation, response and recovery. Levine (2014b) also stresses how the focus should not be on how resilience is defined, but on “how people are coping in real situations,” including the constraints and opportunities to cope better.