Resilience

Community-based approaches existed even before the existence of the state and its formal governance structure. People and communities used to help and take care of each other’s disaster needs. However, due to the evolution of state governance, new terminology of community-based disaster risk reduction (CBDRR) has been coined to help communities in an organized way. Different stakeholders are responsible for community-based actions; the two key players are the local governments and civil society, or nongovernment organizations. Private sector and academic and research institutions also play crucial roles in CBDRR. Many innovative CBDRR practices exist in the world, and it is important to analyze them and learn the common lessons. The key to community is its diversity, and this should be kept in mind for the CBDRR. There are different entry points and change agents based on the diverse community. It is important to identify the right change agent and entry point and to develop a sustainable mechanism to institutionalize CBDRR activities. Social networking needs to be incorporated for effective CBDRR.

Fatalism about natural disasters hinders action to prepare for those disasters, and overcoming this fatalism is one key element to preparing people for these disasters. Research by Bostrom and colleagues shows that failure to act often reflects gaps and misconceptions in citizen’s mental models of disasters. Research by McClure and colleagues shows that fatalistic attitudes reflect people’s attributing damage to uncontrollable natural causes rather than controllable human actions, such as preparation. Research shows which precise features of risk communications lead people to see damage as preventable and to attribute damage to controllable human actions. Messages that enhance the accuracy of mental models of disasters by including human factors recognized by experts lead to increased preparedness. Effective messages also communicate that major damage in disasters is often distinctive and reflects controllable causes. These messages underpin causal judgments that reduce fatalism and enhance preparation. Many of these messages are not only beneficial but also newsworthy. Messages that are logically equivalent but are differently framed have varying effects on risk judgments and preparedness. The causes of harm in disasters are often contested, because they often imply human responsibility for the outcomes and entail significant cost.

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.

The impact of disasters continues to grow in the early 21st century, as extreme weather events become more frequent and population density in vulnerable coastal and inland cities increases. Against this backdrop of risk, decision-makers persist in focusing primarily on structural measures to reduce losses centered on physical infrastructure such as berms, seawalls, retrofitted buildings, and levees. Yet a growing body of research emphasizes that strengthening social infrastructure, not just physical infrastructure, serves as a cost-effective way to improve the ability of communities to withstand and rebound from disasters. Three distinct kinds of social connections, including bonding, bridging, and linking social ties, support resilience through increasing the provision of emergency information, mutual aid, and collective action within communities to address natural hazards before, during, and after disaster events. Investing in social capital fosters community resilience that transcends natural hazards and positively affects collective governance and community health.

Social capital has a long history in social science research and scholarship, particularly in how it has grown within various disciplines. Broadly, the term describes how social ties generate norms of reciprocity and trust, allow collective action, build solidarity, and foster information and resource flows among people. From education to crime, social capital has been shown to have positive impacts on individual and community outcomes, and research in natural hazards has similarly shown positive outcomes for individual and community resilience. Social capital also can foster negative outcomes, including exclusionary practices, corruption, and increased inequality. Understanding which types of social capital are most useful for increasing resilience is important to move the natural hazards field forward.

Many questions about social capital and natural hazards remain, at best, partially answered. Do different types of social capital matter at different stages of disaster—e.g., mitigation, preparedness, response, and recovery? How do social capital’s effects vary across cultural contexts and stratified groups? What measures of social capital are available to practitioners and scholars? What actions are available to decision-makers seeking to invest in the social infrastructure of communities vulnerable to natural hazards? Which programs and interventions have shown merit through field tests? What outcomes can decision-makers anticipate with these investments? Where can scholars find data sets on resilience and social capital? The current state of knowledge about social capital in disaster resilience provides guidance about supporting communities toward more resilience.

The framework presented herein supports a changing paradigm in the approaches used by coastal researchers, engineers, and social scientists to model the impacts of climate change and sea level rise (SLR) in particular along low-gradient coastal landscapes. Use of a System of Systems (SoS) approach to the coastal dynamics of SLR is encouraged to capture the nonlinear feedbacks and dynamic responses of the bio-geo-physical coastal environment to SLR, while assessing the social, economic, and ecologic impacts. The SoS approach divides the coastal environment into smaller subsystems such as morphology, ecology, and hydrodynamics. Integrated models are used to assess the dynamic responses of subsystems to SLR; these models account for complex interactions and feedbacks among individual systems, which provides a more comprehensive evaluation of the future of the coastal system as a whole. Results from the integrated models can be used to inform economic services valuations, in which economic activity is connected back to bio-geo-physical changes in the environment due to SLR by identifying changes in the coastal subsystems, linking them to the understanding of the economic system and assessing the direct and indirect impacts to the economy. These assessments can be translated from scientific data to application through various stakeholder engagement mechanisms, which provide useful feedback for accountability as well as benchmarks and diagnostic insights for future planning. This allows regional and local coastal managers to create more comprehensive policies to reduce the risks associated with future SLR and enhance coastal resilience.