03rd April 2012

WORKING PAPER Work Package 1 Early Discussion and Gap Analysis on Resilience Deliverable 1.1 Authors Joern Birkmann

UNU-EHS

Denis Changseng

UNU-EHS

Jan Wolfertz

UNU-EHS

Neysa Setiadi

UNU-EHS

Nuray Karancı

METU

Gözde Koçak İkizer

METU

Christian Kuhlicke

UFZ

Anna Kunath

UFZ

Gunnar Dressler

UFZ

Hugh Deeming

UoN

Maureen Fordham i

UoN

Contract Number: 283201 Project Acronym: emBRACE Title: Building Resilience Amongst Communities in Europe

Deliverable N°: 1.1 Due date: 2012-03-31 Delivery date: 2012-04-04

Short Description: The development of the resilience concept across a range of disciplines (i.e. psychology, organisations and institutions, ecological and socialecological systems, and critical infrastructure) is discussed and the tensions between these approaches explored.

Practical perspectives taken from the concept’s

application by the UK and US civil protection sectors are described. The concepts of community and social capital are also briefly discussed in terms of their relevance to resilience research. A typology of resilience is presented.

Lead Beneficiary: United Nations University – Institute for Environment and Human Security (UNU-EHS) Partner/s contributed: UNU; METU; UFZ; UoN Made available to: 2012-04-04

Version Control Version

Date

Name, Affiliation

0.1

12-03-30

Joern Birkman (UNU)

0.2

12-03-30

Hugh Deeming (UoN)

0.3

12-03-30

Denis Changseng (UNU)

0.4

12-04-03

Hugh Deeming (UoN)

Acknowledgements Funding for this report was made available by the European Commission under the 7th Framework Programme – Grant Agreement No 283201.emBRACE

Contact:

Technical Coordination (Administration) Centre for Research on the Epidemiology of Disasters (CRED) Institute of Health and Society Université catholique de Louvain 30 Clos Chapelle-aux-Champs, Bte 30.15 1200 Brussels Belgium T: +32-2-764.33.27 E: [email protected] W: www.cred.be

Technical Coordination (Science) School of the Built and Natural Environment, University of Northumbria Newcastle upon Tyne NE1 8ST, UK T: + 44 (0)191 232 6002 E: [email protected] W: www.northumbria.ac.uk

Information given in this emBRACE Working Paper Series reflects the authors’ views only. The Community is not liable for any use that may be made of the information contained therein.

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About emBRACE The primary aim of the emBRACE project is to build resilience to disasters amongst communities in Europe. To achieve this, it is vital to merge research knowledge, networking and practices as a prerequisite for more coherent scientific approaches. This we will do in the most collaborative way possible.

Specific Objectives  Identify the key dimensions of resilience across a range of disciplines and domains  Develop indicators and indicator systems to measure resilience concerning natural disaster events  Model societal resilience through simulation experiments  Provide a general conceptual framework of resilience, tested and grounded in cross-cultural contexts  Build networks and share knowledge across a range of stakeholders  Tailor communication products and project outputs and outcomes effectively to multiple collaborators, stakeholders and user groups

The emBRACE Methodology The emBRACE project is methodologically rich and draws on partner expertise across the research methods spectrum. It will apply these methods across scales from the very local to the European. emBRACE is structured around 9 Work Packages. WP1 will be a sys-tematic evaluation of literature on resilience in the context of natural hazards and disasters. WP2 will develop a conceptual framework. WP3 comprises a disaster data review and needs assessment. WP4 will model societal resilience. WP5 will contextualise resilience using a series of Case studies (floods, heat waves, earthquakes and alpine hazards) across Europe (Czech Republic, Germany, Italy, Poland, Switzerland, Turkey and UK). WP6 will refine the framework: bridging theory, methods and practice. WP7 will exchange knowledge amongst a range of stakeholders. WP8 Policy and practice communication outputs to improve resilience-building in European societies. ii

Partners

 Université catholique de Louvain (UCL) - Belgium  University of Northumbria at Newcastle (UoN) - UK  King’s College London (KCL) - UK  United Nations University Institute for Environment and Human Security (UNU), Bonn  Accademia Europea per la Ricerca Applicata ed il Per-fezionamento Professionale Bolzano (EURAC) - Italy  Helmholtz-Zentrum Fuer Umweltforschung GMBH - UFZ (UFZ) Germany  University of York (SEI-Y) - UK  Stockholm Environment Institute - Oxford Office Limited (SEI-O) - UK  Swiss Federal Institute for Forest, Snow and Landscape Research WSL (WSL) - Switzerland  Middle East Technical University - Ankara (METU) - Turkey

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Table of Contents SUMMARY ..................................................................................................................... 1 1.

HISTORICAL DEVELOPMENT AND THEORETICAL PERSPECTIVES OF

THE CONCEPT OF RESILIENCE ................................................................................ 8 2.

RESILIENCE PERSPECTIVES FROM DIFFERENT DISCIPLINES ............... 10 2.1

PSYCHOLOGICAL RESILIENCE PERSPECTIVE ..................................................... 10

2.1.1

Life, Health, Child Development, Psychology, War and Terrorism......... 10

2.1.2 Mental Health, Disaster Preparedness and Mitigation ................................ 14 2.2 ORGANIZATIONAL AND INSTITUTIONAL PERSPECTIVE ........................................... 16 2.2.1 Resilience and Organisations ...................................................................... 16 2.2.2 Resilience and Institutions ................................................................... 20 2.4 ECOLOGICAL AND SOCIO-ECOLOGICAL RESILIENCE PERSPECTIVES ...................... 21 2.6 CRITICAL INFRASTRUCTURE RESILIENCE PERSPECTIVES ...................................... 25 2.7 PRACTICAL PERSPECTIVES ON RESILIENCE .......................................................... 27 2.7.1 UK Civil Protection Doctrine and the “Resilience Agenda” ............ 27 2.7.2 An Operational Framework for Resilience of the U.S. Homeland Security 30 3.0 EXISTING TENSIONS IN DIFFERENT CONCEPTUALIZATION OF RESILIENCE................................................................................................................ 32 4.0 PROBLEMATISING THE CONCEPT OF ‘COMMUNITY’ ................................... 35 5.0TYPOLOGY & CHARACTERISTICS OF RESILIENT SYSTEMS........................ 40 6.0 RESILIENCE MODELING METHODS ................................................................. 48 7.0

PRELIMINARY FRAMING QUESTIONS FOR CASE STUDY RESEARCH /

PILLARS OF A FRAMEWORK .................................................................................. 52 8.0

REFERENCE LIST ............................................................................................ 55

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WORKING PAPER 1.1 Embrace Work Package 1 Early Discussion and Gap Analysis on Resilience Summary What is resilience? Despite its popularity in political and policy circles much debate remains and indeed contradictory applications. Resilience as a contemporary concept brings together, in varied ways and with different priority, sets of empirical concepts that have long been the focus of social analysis. To this extent the novelty of resilience is in the re-prioritisation of existing social and social-ecological categories and through the emergence of a new, compound concept and policy ambition. For example, anthropological literature on community studies has long focused on the apparent contradiction of continuity and change, i.e. that communities able to persist into the future and cope with the rise of colonialism, industrial and late modernity necessarily change and embrace some elements of the new in order to maintain core functions. Tradeoffs in culture, economic base, family structure, etc., are integral to this and can force tensions between short-term and long-term gain. The use of rifles and later skidoos in North Canadian communities enabled a short-term increase in the value, status and productivity of hunting, but without strong institutional constraints to prevent over-hunting has also contributed to ecological decline and the undermining of hunting as a cultural and livelihood mainstay. So, much of the ‘content’ of contemporary concerns with ‘resilience’ have long been studied, similarly there are cases where the term of resilience is being used to describe outlier concepts to the focus of this report. Most common here is the confusion between resilience and resistance that has been used in some engineering literature. We acknowledge this in the analysis presented below but our focus is primarily on those variants of resilience that argue for continuity through change. What is to be continued, what is to change and how these are determined under contrasting epistemological lenses is the aim of our analysis, through which we generate an integrated view to frame and test through empirical work in Embrace. In addition, the theory of resilience and the concept also underscore that crises can be an important trigger for change and reorganization, which clearly differentiates resilience from other concepts, which mainly view crises and disaster as purely negative events. In this working paper, we reviewed some of the main existing concepts on resilience from psychological, ecological and social-ecological, organizational and institutional, critical infrastructures, as well as practical perspectives. A summary of the core concepts on resilience is provided in the Table 1.

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The contemporary framing in climate change and resource management literature of resilience emerged most notably from ecological science. The term resilience was introduced by Holling (1973) as the capacity to persist within such a domain in the face of change. He proposed that ‘‘resilience determines the persistence of relationships within a system and is a measure of the ability of these systems to absorb changes of state variables, driving variables, and parameters, and still persist’’. Some important key terms emerging from this field are the theory of “surprise” (sudden change in a system), multiple equilibria, tipping points, adaptive renewal cycle and panarchy (cross-scale interaction, especially in terms of processes of revolt and remember ). His work was contrasting the single equilibrium view referred to as “engineering resilience” that dominated the mainstream ecology, which interpreted resilience as the return time after disturbance. Up to present time, this perspective has influenced further empirical work as well as other scientific disciplines, especially in the discourse of sustainability, resource management (and importantly adaptive resource management) global environmental change, and disaster risk reduction. Consequently, the original meanings or definitions have undergone considerable extension, modification and change. There has been no convergence of various resilience definitions in one particular perspective; however there has been a dominance of Resilience Alliance and its journal Ecology and Society that has effectively argued for and demonstrated the utility of resilience from this socialecological systems perspective (Moser, 2008). Resilience is firstly concerned with the disturbance that impacts a system (e.g. social-ecological system) and its effect on functional processes within this system and its sub-components. Secondly, resilience research examines whether the system has capacities to reorganize itself in the face of stresses through processes such as revolt and remember, in order to maintain its fundamental functions. In the perspective of social-ecological systems, other characteristics of resilience, regarding learning and adapting were also highlighted (Berkes et al., 2003; Folke, 2006). Thus, one widely used definition of resilience in this field involves: i) response to disturbance, ii) capacity to self-organize, iii) capacity to learn and adapt (Folke, 2006; Parry et al, 2007). Further discussions emerging from social science perspectives link resilience with e.g. social learning, social capital, foresight and anticipation, reflective capacity of agencies or organizations, as well as linkage with social vulnerability and the issues of entitlements, capabilities, freedom and choices or of justice, fairness and equity. Concerning how to deal with various definitions and concepts, Brand and Jax (2007) suggested to treat resilience either as a “descriptive” concept (explaining the state of a system based on specific theoretical basis, e.g. ecology) or a "normative" concept (as a way of thinking using a broader meaning across disciplines to identify a set of ideal systems properties) and as a “boundary object” (platform to link various actors and interests). Resilience, in the SES lens, has been a hybrid concept, compared to the “descriptive” original ecological resilience concept of Holling. The more “normative concept” of social-ecological resilience tends to incorporate specific values, e.g., cultural diversity. However, ecological and social-ecological resilience has a theoretical and analytic approach, since it can explain processes of destruction and reorganisation linked to different temporal and spatial scales. The existing social-ecological system approach was acknowledged as being a useful analytical basis for managing social-ecological systems; it has a solid theoretical basis and considers social-ecological systems and its interplay with disturbance as a complex dynamic system rather than linear thinking. It is also in line with sustainable thinking (Turner, 2010). However, it is still criticised as being too “reductionistic” in terms of handling the complex social or human systems. Moreover, in the recent policy discourses, resilience is still often used in relation

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to resistance against change rather than progressive and dynamic as it is in SES thinking (Brown, 2011). Also, a question to what extent resilience is supportive to transformation is addressed. However, one has also to acknowledge that resilience theory goes beyond resistance, when focusing on learning, reorganization and particularly on the notion that crises can be seen as opportunities for change and renewal or even transformation, since in these times - as Berkes et al. (2003) formulate it - control is weak and uncertainty is high, which opens the space for innovations (see Berkes et al., 2003) In contrast to the resilience school presented above, the concept of resilience was also developed in the psychological perpective. Research has been of interest in health, life and personality adaptation, child development, psychiatry, sociology, terrorism, and military. It relates to the capacity to choose a vital and authentic life, and also describes a process of overcoming the negative effects of risk exposure (recovery to a pre-exposure status), coping successfully with traumatic experiences (avoiding harm), and avoiding the negative trajectories associated with risks. In this sense the construction of resilience in psychological literature is consistently conservative – it is interested in mitigating change and the return to a pre-impact status of assumed maximum psychological health. There is some work that has positioned resilience as a mechanism for or in comparison with alternative approaches that could aim for improved psychological health and wellbeing. For example, it is highlighted that resilience can be strengthened by enhancing your resilience core which is made up of five essential characteristics of resilience. These are: 1) Meaningful life 2) Perseverance 3) Self reliance 4) Equanimity and 5) Coming home to yourself –existential aloneness. A strong resilience core gives a person the ability to structure his or her life in a resilient way. On the other hand, a large number of psychological researches have focused on positive emotions and successful resilience and adaptation. For example, positive emotions promote flexibility in thinking and problem solving, counteract the psychological effects of negative emotions, facilitating coping and enhanced well-being and play an important role in recovery process. Furthermore, research in the context of psychological resilience has shifted from individual-internal capacity (i.e. factors that contribute to health and well being) towards an external (i.e. takes into account the influences of social context, both proximal and distal well being) and multi-level perspective. There is also a shift in thinking away from negative outcomes to protective factors (i.e. positive emotion, perseverance). Additionally, there is a change in understanding to protective processes rather than protective factors. In this context, the conceptualisation moves away from a static, individual trait to a dynamic process operating at multi-interdependent levels and scales. Therefore, resilience is evaluated in two broad but interrelated domains, which are (a) resilience in terms of mental health and development outcomes (the psychological domain) and (b) psychological factors at the individual and community levels that are related to disaster preparedness/mitigation, and terrorism (individual, the social, economical, and physical domain), and thus are related to resilience (preparedness, protective actions, mitigation behaviours are assumed to lead to resiliency). It is also key to highlight that the importance of preparedness in hazard adjustment challenges our thinking that disaster preparedness might both be a direct predictor of resilience and a mediator between the aforementioned psychological variables (e.g., personality) and a resilient outcome. This assumption deserves to be investigated within a testable comprehensive model.

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Current gaps in psychological research include lack of theoretical models combining variables from studies addressing (a) mental health and development and (b) simultaneously, development of psychometrically sound resilience scales and inventories that allow assessment of those models in cross-cultural contexts and different kinds of disaster events, and investigation of a broad range of relevant variables in resilience research. Specifically, addressing ethnic/cultural variations and longitudinal research on impact of previous disasters on psychological resilience would prove valuable in reaching a more comprehensive picture. It is interesting to note that within organisational research the differentiation between anticipation/planning and resilience is also present, particularly in operational terms and with regard to so called “High-Reliability-Organisations”. However, anticipation/planning is more about the control of established actions and far less attention is paid to finding of solutions of new problems. Thus, resilient organisations should be flexible and consider broadening their systems of information gathering and processing to incorporate new data on unexpected circumstances and causal relations. On the other hand, a resilience-based strategy can be seen as appropriate to adapt to unexpected developments, however, it is confronted with a deficit of implementation and acceptance. In this context the institutional aspect deserves greater attention. It bridges the gap between the micro and macro level aspects. This includes understanding the static and dynamic characteristics of institutions, particularly addressing institutional change and development process, and the different perspectives and architecture of institutions (i.e. mix institutions, polycentric and multilayered architecture etc.) in order to enhance resilience for different kinds of risks In addition, resilience research in the context of critical infrastructures highlights that physical and social systems must be: (1) robust (2) redundant (3) resourceful, and (4) capable of rapid response. In this regard, resilience can be conceptualised as encompassing four interrelated dimensions: (1) technical, (2) organisational (3) social and (4) economic. Additionally, there is growing interest, particularly at the European level regarding how to strengthen the institutional and governance aspects at various levels to improve critical infrastructure resilience; particularly considering the unknown and ambiguous risks which can affect critical infrastructures. On the other hand, it is highlighted that the key challenge and gap is to address the quantification and measurement of resilience in all its interrelated dimensions. In this first report, we also highlight the practical perspectives on resilience by providing an example in the case of UK Civil Protection Doctrine and the “Resilience Agenda” and the U.S Department of Homeland Security which views resilience as the aggregate result of achieving specific objectives, particularly in the context of critical systems and their key functions. This should help us to understand that this discussion of resilience is not just an abstract exercise. It is important to provide a substantive example of where the concept has been operationalised in a way that has informed policy and generated changes in practice that have been suggested to have led to more ‘resilient’ communities. However, in general it is found that clear criteria and parameters of resilience for specific uses still need to be defined. Resilience in this context is seen as a guiding vision, rather than a strong analytic and theory based tool or concept.

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Interestingly, the concept of resilience has been adopted and extended in various ways, which sometimes generate different meanings to the original concept. Therefore, there are certain levels of tensions in the different conceptualization of resilience. In this context, we outline various perspectives or tensions focusing on: (a) framing the goal ( descriptive, normative or hybrid, and also the consideration of subjectivity for various context and practical uses (b) system of interest (i.e. social (human) or ecological (environmental) or both, (c) (c) scale of analysis (i.e. individual to society, scale the development pathways and tipping points should be addressed, as well as the need to address cross-scale interactions), (d) (d) characteristics of disturbance (i.e. source, awareness, severity, exposure, and temporal dimensions, and (e) (e) approach or mechanism (either anticipatory or recovery (pre-or postevent) to achieve resilience in conceptualizing resilience. Furthermore, we provide a brief overview of the mathematical methods used to model resilience (see section 5). In this context, some advantages and disadvantages of twelve modelling methods are discussed. It is important to understand that each definition of resilience applies a theoretical model and each theoretical model is transferred to several mathematical methods. These methods depend on certain levels of assumptions. Any violation of these assumptions tends to weaken the preciseness of the result and even render it totally useless. In addition, only mathematical methods with reasonable computational time are used. Hence, one has to be aware and pay attention to the limitation of the mathematical methods as a necessary step to progress from theory to action. In this context, we describe the: frequency of use of each respective model, provide examples on how the model has been used and applied and finally also describe which time and spatial scales are used in the model as well as the computation speed of various models. In terms of informing the principal emBRACE aim – to understand how community resilience to natural hazards can be developed – the opportunity is also taken to briefly discuss the concept of community and how it has been employed, and problematised, within DRR literature (Hoggett, 1997). Notwithstanding this critique and building on UK civil protection sector practice, it is suggested that to understand this complex and contested term, then using a typology of five community types may be useful (i.e. geographic, interest, circumstance, supporters/practice and identity). From this perspective, social capital theory (e.g. Coleman, 1990; Putnam, 2000) has also been applied in DRR work (e.g. Murphy, 2007, Cordasco, 2006), as its explanation of the differing capacities and limitations of socially bonding, bridging and linking networks and the importance of trust and reciprocity in developing network relations, does provide an important lens through which community resilience may be explored. It is important to understand, however, that each of these network attributes can have negative as well as positive ramifications for inter and intra network resilience, as well as for the resilience of the wider community. It is also always important to explore networks to find out exactly who it is within them that has the greatest potential as a resilience builder (e.g. in terms of their bridging, linking and facilitating capabilities) (Pelling, 2008; Wenger, 2000).

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Finally, in our early discussion and gap analysis on resilience in section 6, we raise the following key framing questions1 for the case study research and pillars of a framework:

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How to frame the goals of the different conceptualization of resilience considering the purpose as well as the standpoint of the observers? Including scale and time frames as well as purpose and ideology, and accepting the same actor might have contradictory perspectives –e.g. play multiple roles and be involved in trading –off, e.g. resilience and transformation, or scales of action.

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How to assess trade-offs between the "goal" of resilience, e.g. when is sustaining status quo (absorbing the disturbance) better off than selforganization or than timely adaptation, or allowing systems failure for transformation? Including the role of canonical and shadow systems, decision-making and providing scope for adaptive experiments.

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How to define the ideal balance between anticipatory and response strategy in the light of performance and reliability? How to integrate resilience in the adaptive disaster risk management cycle? Important and related is to understand the costs and benefits of different phasing of acts within resilient systems – i.e. what system etc is allowed to fail, which is supported, which is open to transformation, the order of changes or stasis might then influence subsequent actors or perceptions of risk. Cybernetics made some play of this.

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How to position resilience among other objectives like performance, reliability, efficiency and equity (transparency) etc.?

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What are the existing options to enhance resilience: rapid recovery options, foresight and timely adaptation, learning method? Who are the groups that can make this happen, acknowledging that we are interested in sustainable processes of learning not one of capacity fixes.

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How can we define appropriate system(s) for resilience analysis considering positionality and priority that emBRACE project will provide.

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Which time-scales should be used or need to be addressed in resilience analysis? It is pointed out that case studies should help to draw such an answer. Overall the Embrace project is interested in evolving levels of resilience over time to draw out the interplay of structure and agency (and institutions) or following child psychology of interior and context conditions.

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How to measure identify internal stressors?

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How to address the measurement of resilience in all its interrelated dimensions, i.e. economic, technical, social and organizational? How do we move from a vague description and conglomeration of adjectives towards a systematized and coherent assessment of tangible and intangible aspects of resilience building?

Complete list of questions in chapter 6.0

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How to address current gaps in psychological resilience research to include an examination of multi-disciplinary studies that examines dynamics of resilience across the lifespan and effectiveness of the different measures of resilience and programs? In is suggested that we should draw out the generic theory and transferable theory and then apply to our problem sets. For example psychology and emotions are a gap in disasters and so we would do well to extend analysis into this realm but we should be wary of trying to build a comprehensive theory of resilience. It is therefore necessary to draw out common lines and then explore how these have been conceptualised in the problem contexts of psychology, resource management etc. There are already some useful points where work in one area shows gaps in another and these should be strongly emphasised in developing the analytical framework for the case study work.

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How cultural-specific is resilience? This includes organizational culture as well as ‘national’ culture?

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How can we clarify a definition from various perspectives of resilience in order to inform research, policy, and practice? Empirical research suggests that recovery or growth is different from resilience. Should EmBrace consider these pathways in its analysis? Is disaster preparedness both a direct predictor of resilience and a mediator between the aforementioned psychological variables (e.g., personality) and a resilient outcome?

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1. Historical Development and Theoretical Perspectives of the Concept of Resilience By Neysa Setiadi & Denis Chang Seng In light of the dominant trends of global and environmental change – including natural hazards and disasters – the use of the word “resilience” has become more and more popular. Boin et al., (2010) view the resilience concept in popular and professional discourses as a function of a rising need for resilience; where it gives hope to face unpredictable threats in complex societies. On the other hand, we emphasize that resilience might be a response to an increasing appreciation of uncertainties and the contingency of decision-making. Before we discuss resilient systems in more depth, the state-of-the-art of how resilience is defined and conceptualized in various scientific and practical perspectives will be shown. In this regard, it is important to bear in mind the historical development processes of the concept. The following is a brief description of the historical development which was extracted and summarized from several papers containing extensive review on the concept, especially from Folke (2006), Berkes et al., (2003), and Brand and Jax (2007), Lorenz, & Daniel (2012). For further reading, we recommend to refer to those papers. One of the theories and concepts that advanced the effort to understand the interaction of humans and their environment was the systems theory. Earlier challenges to the idea of linear causality and reductionistic science go back to general systems theory developed in 1930s and 1940s (von Bertalanffy, 1968), which emphasizes connectedness, context and feedback. With the science of complexity (Berkes et al., 2003; Costanza et al., 1993; Kauffman, 1993; Holland, 1995; Levin, 1999), a new understanding of systems is emerging and highlights attributes such as nonlinearity, uncertainty, emergence, scale, and self-organization. Cybernetic theory which drew on revolutionary theory to connect analysis of social and natural systems had also made progress in providing a framework that recognized social context as a mediating pressure on the environment, shaping risk and adaptation (Pelling, 2010). Considerable amount of insights from systems theory has advanced many works in disasters field and also influenced the development of resilience concept. The contemporary framing in climate change and resource management literatures of resilience emerged most notably from ecology in the 1960s and early 1970s through studies of interacting populations like predators and prey and their functional responses in relation to ecological stability theory (Holling, 1961; Morris, 1963; Lewontin, 1969; Rosenzweig, 1971; May, 1972). The term resilience was first introduced as a descriptive ecological term (Holling, 1973) as a way to understand non-linear dynamics, such as the processes by which ecosystems maintain themselves in the face of perturbations and change (Gunderson, 2000). He introduced resilience as the capacity to persist within such a domain in the face of change and proposed that ‘‘resilience determines the persistence of relationships within a system and is a measure of the ability of these systems to absorb changes of state variables, driving variables, and parameters, and still persist’’ (Holling, 1973, p. 17). Holling´s work provided a considerable added value to the understanding of complex ecological and social systems. He introduced important key terms in his “science of surprise” (1986) that a system exceeding its tipping point may suddenly flip to other domain of attraction. His work also provided new insights on the adaptive renewal cycle

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and “adaptive management” of the ecosystem (see further discussion in Section 2 on Ecological & Social-Ecological Resilience Perspective). The Volume of ‘‘Sustainable Development of the Biosphere”, edited by Clark and Munn (1986), including Holling´s chapter became a source of inspiration and incorporated as a discourse in many works of others (Folke, 2006), also in close connection with complex systems theory (Rapport et al., 1985; Steedman and Regier, 1987; Baskerville, 1988; Edwards and Regier, 1990; Robinson et al., 1990; Kay, 1991; Kayet al., 1999), a major synthesis by Turner et al. (1990) of the earth as transformed by human actions, which continued into research on uncertainty and surprise (Kates and Clark, 1996), social learning (Clark et al., 2001) sustainability science (Kates et al., 2001), and risk (Kasperson et al., 1995) and vulnerability in human–nature systems (Turner et al., 2003), work on systems science and sustainability (Gallopin, 2003) and research at University of East Anglia by Tim O’Riordan and colleagues on, e.g., the precautionary principle and social resilience (O’Riordan and Jordan, 1995; Adger and O’Riordan, 2000; Adger et al., 2001). The resilience from an ecological perspective also influenced other scientific disciplines such as anthropology, ecological economics, environmental psychology, cultural theory, human geography, the management literature, property rights and common property research, other social sciences, as well as recent adaptation and risk research (Birkmann, 2011) and positioning resilience alongside, transition and transformation as modes of climate change adaptation (Pelling, 2011). However, especially in the early stage, the single equilibrium view that dominated main stream ecology led to the interpretation of resilience as return time after disturbance, referred to as engineering resilience (Holling, 1996). Engineering resilience focuses on behavior near a stable equilibrium and the rate at which a system returns to steady state following a perturbation, i.e. the speed of return to equilibrium. The engineering interpretation of resilience exists to date in many facets of ecology (McManus and Polsenberg, 2004). The resistance to change is often addressed in terms of recovery, which is the time it takes to return to the previous state following disturbance. We term this understanding of resilience ‘resilience as resistance’ On the other hand, in the context of health and psychology, early researchers have used the term resilience in epidemiology (see Garmezy, 1973) to describe physiological status when studying who gets ill, who doesn't, and why, to uncover the risks and the protective factors that now help define individual resilience. Recent research in the context of health and development address resilience at population level (e.g. Sun & Stewart, 2007). The trade-offs are further discussed in section 3.

In addition, a large proportion of resilience research is routed within the discipline of development psychology with children and adults. Emmy Werner (1982) was one of the early scientists to use the term resilience in the 1970s to study a cohort of children from Kauai, Hawaii. It has been suggested, however, the resilience concept can also be found in the literature covering the study of children’s individual competence as far back as the 1940s and ‘50s (Comfort et al., 2010). More recently, psychological resilience is increasingly being used in the context of disaster risk reduction (e.g. Paton & Johnson, 2001; Lindell & Perry, 1992 etc.), military war and terrorism research at population level and also various inter-dependent levels (Bonanno et al., 2006; Sun & Stewart, 2007; Meredith et al., 2011). Furthermore, resilience has also been of interest in the geophysics-seismic engineering, safety, contingencies and critical infrastructures (e.g. Bruneau et al., 2003; Boin & McConnell, 2007; Fritzon, A. et al., 2007; O’Rourke, 2007; Hellström, 2004; De Bruijne & Van Eeten, 2007). The research work by Paton and others from the DRM/R and critical infrastructures are elaborated in section 3.0, however this informs us that there might be

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a bridge or gap from psychology, critical infrastructures to other forms of resilience and we need to explore if so why the bridging is limited. Overall, it is important to acknowledge that many discourses about resilience, e.g. socialecological resilience, infrastructure resilience and psychological resilience developed mainly in parallel, therefore the development of the concept has not just one starting point, but is characterized by different triggers that often evolved in disconnection from each other.

2. Resilience Perspectives from Different Disciplines 2.1 Psychological Resilience Perspective 2.1.1 Life, Health, Child Development, Psychology, War and Terrorism By Denis Chang Seng Some of the key characteristics associated with psychological resilience include:-the capacity to choose a vital and authentic life (e.g. Gail, 2010), individuals with no posttraumatic stress disorder symptoms (PTSD) or who exhibit at least one symptom after a stress or shock (terror attacks) (Bonanno et al., 2004), the ability to maintain and recover emotional well-being (Ong et al., 2006), good social developmental outcomes despite high risk status, sustained competence under stress(Werner, 1992), a process of negotiating, managing and adapting to significant sources of stress or trauma ( Fergus et al., 2005), a process of overcoming the negative effects of risk exposure, coping successfully with traumatic experiences, and avoiding the negative trajectories associated with risks (Garmezy, 1984; Luthar and Ciccchetti, 2000, Masten and Powell, 2003, Rutter, 1985, Werner, 1992). Therefore, it is important to consider how each might be translated in a natural disaster resilience context for identifying gaps in DRM psychology analysis and in moving towards a holistic framework. Regardless of the range of definitions of psychological resilience, there is a common understanding that resilience is a two dimensional construct produced by the interaction of nature of exposure and the positive adjustment outcomes or protective factors of undertaken in response to that risk or adversity(e.g. Luthar and Cicchetti, 2000). Psychological resilience analysis in this literature review have focused on health, war and terrorism, military, life and personality adaptation, child development, psychiatry, sociology and natural disaster management. Gail (2010) in ‘Discovering your resilience core’ argues that resilience can be strengthened by enhancing your resilience core which is made up of five essential characteristics of resilience; these are: 1) 2) 3) 4) 5)

meaningful life and purpose perseverance self reliance equanimity and coming home to yourself–existential aloneness.

A strong resilience gives a person the ability to structure his or her life in a meaningful way (meaningful - based on her and his judgement). Meaningful life-implies having a sense of one’s own meaning or purpose in life. Life without a purpose is futile and aimless. It is the foundation and most important characteristics of resilience. Perseverance is the determination to keep going despite difficulties, discouragement,

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repeated failures, rejection and disappointment. Equanimity is the balance and harmony of an individual. Self reliance is the self belief, with a clear understanding of your capabilities and limitations gained from experiences, practice and developed problem solving skills while existential aloneness is learning to live with oneself and having the ability to go it alone if necessary. In this context, a reliable and valid tool to measure resilience is the Resilience Scale. Key problems are related to administering the resilience scale and its interpretation. The concept of resilience core is reflected in the typology of psychological resilience in figure 3. On the other hand, a large body of psychological research has focused on emotions. Positive emotions have a wide range of effects on individuals (Lyubomirsky, King, and Diener, 2005, Pressmann and Cohen, 2005). Positive emotions promote flexibility in thinking and problem solving (Fredrickson and Branigan, 2005, Isen, Duabman, and Nowicki, 1987), counteract the psychological effects of negative emotions (Fredrickson and Levenson, 1998, Ong and Allaire, 2005), facilitating coping and adaptation (Folkman and Moskowitz, 2000a, 2004), build enduring social resources (Fredrickson and Branigan, 2001, Keltner and Bonanno, 1997), and spark enhanced well-being (Fredrickson, 2000, Fredrickson and Joiner, 2002). It plays an important role in recovery process. Fredrickson (1998, 2001) broaden–and–build model of positive emotions raises the possibility that positive emotions are important facilitators of adaptive recovery, restorative function, guarding individuals from negative emotions as well as quelling the after-effects of such emotions. Recent research shows that positive emotions are crucial component of trait resilience (Tugade and Fredrickson, 2004, Tugade, Fredrickson, and Barrett, 2004). A growing number of studies show that individual differences in psychological resilience predict accelerated recovery from stressful situations (Fredrickson et al., 2003, Tugade et al., 2004). The role of emotions at an individual level is also illustrated in figure 3. Current research directions tend towards an emphasis on the social-ecological context in which people experience stresses and the identification of resources used for coping. These concepts have been captured in relation to resilience in Antonovsky's salutogenic model (Antonovsky, 1987, 1996) and Bronfenbrenner's ecological model (1979). Sun and Stewart (2007) place emphasis on: (a) the salutogenic and (b) socio-ecological context perspectives of resilience (see figure 3 in section 4). The salutogenic model side-steps the whole notion of risk exposure as a prerequisite for being labelled resilient and places emphasis on factors that contribute to health and wellbeing and in this way deploys a similar strategy to Disaster Risk Reduction (DRR) and Climate Change Adaptation (CCA) studies of ‘generic’ adaptive capacity as a component of resilience. The salutogenic model focuses on factors that help identify coping resources of children, which may contribute to resilience and effective adjustment, notwithstanding adversity and risk. This is useful in highlighting the importance of social context and of time in individual pathways, with healing being faster or slower depending on individual conditions, but also on the quality of the therapeutic environment. For emBRACE this emphasizes the need to consider aspects of the social and cultural context, and of history in understanding the derivation of contemporary expressions of resilience at all scales. On the other hand, the socialecological perspective on resilience, emphasis is toward an ecological approach, which takes into consideration the influences of social context, both proximal and distal. For example, in the case of school children, it would be useful to consider the influence of teachers, and parents, not only children in isolation (McLoyd, 1998). This advance is formalized in Bronfenbrenner's ecological model (1979, 1989). It specifies that well-being is affected substantially by the social contexts in which people are embedded and is a function of the quality of relationships among individuals’, family and institutional systems. The added value of the child psychology is to make us realise that we need to study the effect of changing contexts over time – not just the current one. It would also

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presumably ask us to look at contexts before any traumatic event and if not then this is a gap in the literature.

The attributes that inhere within the individual include a variety of coping skills; for example self-efficacy2, sense of community, problem solving talent, confidence, trust, autonomy. Therefore, research in the context of psychological resilience has shifted from individual-internal capacity (i.e. self-efficacy, sense of community etc) towards an external (collective–efficacy, belongingness, connectedness, empowerment, access to resources and services, justice, equity, etc.) and multilevel perspective (i.e. family, unitorganisation, community level-environment), as well as a shift in thinking away from negative outcomes (i.e. negative emotions and depression) to protective factors (i.e. positive emotion, perseverance) to protective processes. In this context, the conceptualisation moves away from a static, individual focus to a dynamic process operating at multi-interdependent levels and scales (e.g. Zautra et al., 2010; Paton and Johnson, 2002; Bonanno, et al., 2006; Sun & Stewart, 2007; Meredith et al., 2011 etc). However, analysis of dynamic processes operating at multi-interdependent scales also poses new challenges to such research activities in the sense that the causal links between processes at the level of an individual and at family or community level have to be proven. Hence, there is still a gap between the general wording of such interrelations and interdependencies and the evidence based assessment of the same. A mix of strategies that, for example, accommodates public hazard education, community development and social psychological factors, which facilitate the relationship between risk perception and risk reduction behaviour, is critical. Other researchers have described three, i.e. (a) compensatory-, (b) protective-, and (c) challenge-resilience models (Fergus, Zimmerman, 2005), which they suggest explain how promotive factors operate to alter the trajectory from risk exposure and negative outcomes. Social perceptions of risk that shape risk behaviour have been studied from different perspectives, e.g. history, sociology and psychology of risk, economics and political science. It has been found that there are distinct factors, which can influence and determine risk perceptions and the decision making that shapes behaviour change. These include: (1) Interpretation of danger, understanding and knowledge of the cause (e.g. Lorenzoni and Pidgeon, 2006; O’Connor, 2000; Bostrom et al., 1994 etc.) (2) proximity, exposure, direct personal threat, personal experiences with notable recent serious consequences (e.g. Quarantelli, 1996; Goltz et al., 1992; Whitmarsh, 2007; O'Connor, 1999; Weber, 2006; Mortreux and Barnett, 2008; Renn et al., 2010 etc.) (3) People’s priorities (e.g. Lorenzoni and Pidgeon, 2006) (4) Experimental factors (e.g. Leiserowitz, 2006) and (5) Environmental values (e.g. O'Connor, 1999). However, risk perceptions in the context of climate change and their influence on social responses to climate-change associated hazards are indeed complex and intriguing, e.g. in terms of ‘belief’ and non-belief’ (O'Connor et al., 1999). It has been suggested that raising concern about climate change is a necessary but not sufficient condition for desirable or appropriate protective or mitigating behaviour to be adopted on the part of the general public (Weber, 2006). Weber suggests that ways should be found to induce intuitive reactions towards the risk of climate change. However, other authors argue that activities to increase levels of concern about climate change need to be undertaken carefully, not by “evoking visceral images” (Ibid: p.2), or even in terms of persuasion or

2

People's beliefs in their capabilities to exercise control over their own functioning and over events that affect their lives (Bandura, 1994)

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advocacy, but in ways that allow people to make reasoned choices on credible and comprehensible information (Fischoff, 2007). In addition, studies have revealed that regardless of fore-knowledge – coupled with high levels of concern and objective perceptions about hazards and vulnerability – people’s responses to environmental hazards may still be biased or sub-optimal. In effect, a person may be aware of a hazard and know about mitigation measures, but may still be constrained from appropriate action because of behavioural weakness and indecision, lack of money, community or social values, legal or bureaucratic impediments, or a host of other factors (e.g. Palm & Hodgson, 1993). In addition, a study, related to mapping risk perception factors of natural hazards in Europe, found that risk factors and the perceived magnitude of a disaster plays little role in the risk perception of natural hazards (Heitz et al., 2009; Haimes, 2004, Miceli et al., 2008). Informational factors such as the type and source of information have a significant but low impact on risk perception, with the perceived trustworthiness of authorities being the most influential variable that determines that impact (Heitz et al., 2009). Interestingly, personal factors such as age (Barberi et al., 2008; Siegrist et al., 2006, Grothmann et al., 2006 etc), gender (e.g. Barberi et al., 2008; Plapp et al., 2006 etc), educational level (Miceli et al., 2008; Plapp and Werner, 2006; Armas, 2008; Barberi et al., 2009), had little or no significant influence on risk perception. However, other studies found some relationship between risk perception, risk experiences and educational degree (e.g. Setiadi, 2011). As suggested above, experience, or lack of experience, of hazards/disaster is a powerful predictor of risk perception (e.g. Plapp and Werner, 2006; Felgenttreff, 2003). Context factors such as economic factors do not seem to influence risk perceptions, with the exception of home ownership. In this context more open questions are raised, suggesting further research is needed. Overall, the large body of research shows that perception of risk plays an important role in influencing individual and collective adaptive and resilience behaviour. Current Gaps and Open Questions Currently, there is very limited qualitative work exploring why certain expressions of resilience are held beyond that of statistical association. In addition, psychological resilience research should include multi-disciplinary studies that examine dynamics of resilience across the lifespan of systems This review demonstrates the complexity related to psychological resilience and also the intricacy of working within multi-layered world. In addition, one important question to ask is; how to address the issue of lack of comparable research on risk perception in the context of DRR and CCA, and how to solicit concern regarding climate change and policy strategies to address the dominant (and sometimes polarised) modes of human behaviour e.g. ‘believers’ and ‘non believers’. Furthermore, it will be interesting to investigate the relationships between psychological emotions and risk perceptions.

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2.1.2 Mental Health, Disaster Preparedness and Mitigation By Nuray Karancı & Gözde İkizer In an attempt to understand resilience from a psychological perspective, there have been numerous efforts to understand and define the resilience concept in the last decade. The literature review suggests that resilience is evaluated in two broad but interrelated domains. These are: (a) resilience in terms of mental health outcomes (the psychological domain) and (b) psychological factors at the individual and community levels, which are related to disaster preparedness/mitigation (individual, the social, economic, and physical domain) and thus are related to resilience (preparedness, protective actions, mitigation behaviours are assumed to lead to resiliency) (e.g., Lindell & Perry, 1992; Mulilis & Duval, 1995; Paton, 2000; Paton, 2004 etc) Firstly, psychological resilience has long been viewed as an ability to bounce back to previous levels of functioning following difficult experiences, adversity, disasters, etc., through the use and/or conservation of individual and community resources. Resilient individuals have been assumed to withstand adverse life circumstances and to maintain a stable equilibrium. Personality variables, a priori beliefs, identity complexity, capacity for positive emotions, and comfort from positive emotions combined with exogenous variables are recognized to be associated with resilience in individuals experiencing traumatic life events, disasters, etc. Psychological resilience (the lack of or minimal significant psychological distress after adversity) has been mostly differentiated from chronic or delayed dysfunction following adverse life events, which is indicated by the presence of mental distress symptoms. However, resilience continues to be equated by some researchers with the concepts of recovery and post-traumatic growth (Karanci & Erkan, 2007; Schaefer & Moos, 1998; Tedeschi et al., 1998). There have been attempts to distinguish resilience from the concepts viewed as analogous, through identifying differences and similarities between them. Research revealed that for some individuals a resilience trajectory, as distinct from a recovery trajectory is observed (Bonanno, 2005; 2008), which suggests that recovery or growth is different from resilience. For recovery or growth there needs to be an initial decline in functioning and significant psychological distress. In contrast to recovering individuals, who tend to experience sub-threshold levels of psychopathological symptoms, resilient individuals have been assumed to be generally able to maintain levels of healthy functioning across time. It would be important for resilience research to consider and to systematically investigate these pathways. Furthermore, researchers continue their extensive efforts to delineate whether resilience and vulnerability, a concept that has been long studied by psychologists, are discrete terms or different ends of the same continuum, and their efforts seem to be culminating in the notion that resilience is to be understood and defined separately as a concept (e.g. Manyena, 2006). Recent studies underscore that bouncing back signalled returning to the original position and did not reflect the reality of changing circumstances and new possibilities; thus they suggest that ‘bouncing forward’ may better define what was brought by a disaster, i.e. “disaster resilience could be viewed as the intrinsic capacity of a system, community or society predisposed to a shock or stress to ‘bounce forward’ and adapt in order to survive by changing its non-essential attributes and rebuilding itself” (Manyena et al., 2011: pp.419). Such a perspective is interesting, but it could be suggested that this phrase bears an implicit message that resilient communities are such because they strive to regain, and even accelerate, some sort of pre-event trajectory. Would not arguments focussed on the adaptive nature of resilient ‘systems’ be better illustrated by the inclusion more divergent path alternatives?

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Secondly, models emphasizing the need for preparedness, mitigation or protective actions (individual/community/institutional/governance) for resilience, stress certain psychological factors (e.g. risk perception, personal responsibility, self efficacy and collective efficacy, trust, active coping strategies, social embeddedness, community participation), which are important in facilitating preparedness and mitigation and thus in fostering resiliency. Use of available resources and the promotion of their availability, are conceptualized as preventing and mitigating both the disruption in mental health outcomes and social, economic and physical destruction following a hazard activity, and also in moderating the relationship between protective motivation and behaviours. This necessitates the understanding of resilience in terms of psychological factors related to disaster preparedness/mitigation, which is mainly represented in social psychological models. Since resources are also assumed to be crucial in models of resilience from a mental health perspective (clinical psychology), individual and community efforts to prepare for disasters and to mitigate the impact of them are clearly important for building a resilient outcome. A number of models cited in the literature address this issue and link several socio-demographic variables to risk perception and protective motivation, which may then lead to intention to prepare or actual adaptive behaviors (Ajzen, 1985; Lindell & Perry, 1992; 2011; Mulilis & Duval, 1995; 1997; Paton, 2000; 2003; Paton et. al., 2005; Rogers, 1975; 1983). Delineation of these models broadly suggests that perceptions and appraisals regarding risk, threat, vulnerability, and personal responsibility are crucial for understanding behaviour, cognitions and emotions that are related to resilient outcomes. Moreover, in addition to psychological resources, which have been emphasized in studies of resilience in terms of mental health outcomes, these models underline the importance of resources, e.g. beliefs of self-efficacy and outcome, knowledge about skills and coping. The evident importance of preparedness in hazard adjustment gives rise to thinking that disaster preparedness might both be a direct predictor of resilience and a mediator between the aforementioned psychological variables (e.g., personality) and a resilient outcome. This assumption deserves to be investigated within a testable comprehensive model. Despite valuable efforts to define psychological resilience with an extensive focus on psychological well-being and functioning after adversity, certain gaps still exist in the literature. Current gaps include lack of theoretical models combining variables from studies addressing psychological well-being at the individual level (i.e. Clinical) and engagement in adaptive behaviours to increase resilience (i.e. Social Psychology) simultaneously; development of psychometrically sound resilience scales and inventories that allow assessment of those models; evaluation of these general models in crosscultural contexts and different kinds of disaster events; and investigation of a broad range of relevant variables in resilience research. Specifically, addressing ethnic/cultural variations and longitudinal research on impact of previous disasters on psychological resilience and adaptive behaviours would prove valuable in providing a more complete picture. A move towards the creation of a resilient world requires the integration of the dimensions of psychological resilience into the broader framework of a resilience model.

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2.2 Organizational and Institutional Perspective By Christian Kuhlicke, Anna Kunath and Gunnar Dressler

2.2.1 Resilience and Organisations In his seminal publication ‘Searching for Safety“, Wildavsky distinguishes between anticipation and resilience3. Resilience is, for Wildavsky, the “capacity to cope with unanticipated dangers after they have become manifest, learning to bounce back” (quoted in: Sutcliffe & Vogues, 2003: p.96; Wildavsky, 1988/1991: p.77). While anticipation focuses on avoiding and mitigating known and specific hazards, resilience describes the capacity to deal with yet unknown and unspecified hazards. If at all, anticipation would be suitable if one has complete and valid knowledge about underlying causalities and the extent and damaging potential of a hazard, as well as possible solutions to avoid threatening events or to mitigate their impacts. However, as such knowledge is in most cases rarely if ever available, resilience is proposed as the superior strategy: “The mode of resilience is based on the assumption that unexpected trouble is ubiquitous and unpredictable; and thus accurate advance information on how to get out of this in short supply. To learn from error (as opposed to avoiding error altogether) and to implement that learning through fast negative feedback, which dampens oscillation, are at the forefront of operating resiliently” (1991, 120). Some authors (Boin et al., 2010) have developed a set of principles based upon the work of Wildavsky (Barnett, 2001 cited in Pelling, 2003 – The Vulnerability of Cities: natural disaster and social resilence). These are:    

 

The homeostasis principle: Systems are maintained by feedbacks between components parts which signal changes and can enable learning. Resilience is enhanced when feedbacks are transmitted effectively. The omnivory principle: External shocks are mitigated by diversifying resource requirements and their means of delivery. Failures to source or distribute a source can then be compensated for by alternatives. The high flux principle: The faster the movement of resources through a system, the more resources will be available at any given time to help cope with perturbation. The flatness principle: Overly hierarchical systems are less flexible and hence less able to cope with surprise and adjust behaviour. Top-heavy systems will be less resilient [NB. this principle does not align with some other resilience theories, e.g. Panarchy (Gunderson and Holling, 2002)]. The buffering principle: A system which has a capacity in excess of its needs can draw on this capacity in time of need, and so is more resilient. The redundancy principle: A degree of overlapping function in a system permits the system to change by allowing vital functions to continue while formerly redundant elements take on new functions.

Within organisational research the differentiation between anticipation/planning and resilience is also present, particularly in operational terms and with regard to so called

3

Wildavsky thoughts are based on the initial work of Holling (1973).

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“High-Reliability-Organisations” (HRO) 4. Weick and his colleagues (Weick, 1993; Weick et al., 1999; Weick & Sutcliffe, 2007) revealed that within such organisations a preoccupation with known hazards and threats might be the reason for catastrophic developments, particularly when it is accompanied with a focus on past successes and their reproduction through well known actions, instruments and routines. In this sense they were critical to approaches that claim to be able to plan for future hazards and that attempt to anticipate future situations within a rational planning process. In this sense anticipation/planning is more about the control of established actions and less about the finding of solutions of new problems. In their work Weick et al. developed their own principles, which bear relevance in their interpretation of what constitutes a resilient organisation, e.g. (1) improvisation and ‘bricolage’5, (2) virtual role systems, (3) the attitude of wisdom, and (4) respectful interaction are important aspects that might make organisations more resilient (Weick, 1993, 638 ff.). In another publication (“Managing the unexpected: resilient performance in an age of uncertainty”) Weick and Sutcliffe summarise some of the key insights of decades of research on organisation by outlining principles for a resilient performance of organisations. Key principles are:     

A preoccupation with failure, a reluctance to simplify, a sensitivity to operations a commitment to resilience and a deference to expertise6 (2007).

There is furthermore an overarching concept Weick and Sutcliffe repeatedly emphasize: mindfulness. They define mindfulness formally as a “rich awareness of discriminatory details” (ibid. 32). More generally “[m]indfulness conveys a mental orientation toward continually refining and differentiating categories, an ongoing willingness and capability to invent new categories that carve events into more meaningful sequences, and a more nuanced appreciation of context and way to deal with it. In contrast, a tendency toward mindlessness is characterized by a style of mental functioning in which people follow recipes, impose old categories to classify what they see, act with some rigidity, operate on automatic pilot, and mislabel unfamiliar new context as familiar old one” (Weick and Sutcliffe, 2007, 88). Other authors have identified a range of other strategies that contribute to resilience (for an overview cf. de Bruijn et al., 2011: 23.ff.) such as structural flexibility, redundancy or slack (Grabowski and Roberts, 1999), high-performance relationships (Gitell et al., 2005; Sheffi, 2005) and improvisation (Crossan et al., 2005; Rerup, 2001). It should be apparent that resilience, from this perspective, is not simply an outcome of some kind of capacity, it is rather a quite challenging process: “To be resilient is to be vitally prepared for adversity which requires ‘improvement in overall capability, i.e., a generalized capacity to investigate, to learn, and to act, without knowing in advance

4

HRO operate in a environment that is prone to risks and hazards and where any mistake may have catastrophic consequences both for the organisation as well as the surrounding environment. Classical examples are aircraft carriers or nuclear power stations. 5 Bricolage: the construction or creation of a work from a diverse range of things that happen to be available, or a work created by such a process. Weick suggests the following requirements are essential for successful bricolage in organisations: (1) intimate knowledge of resources (2) careful observation and listening (3) trusting one's ideas (4) self-correcting structures, with feedback. 6 They also developed an audit tool aiming at assessing the capacity of an organisation to perform resiliently. It might be of interest for some of the work in the case studies.

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what one will be called to act upon” (Wildavsky, 1991, 70; quoted in: Vogues & Sutcliffe, 2007, 3476). In this sense, a resilient organisation should be willing and able to broaden its systems of information gathering and processing to incorporate new data on unexpected circumstances and causal relations. An ability that would be based on (1) “optimal” group social capital within the organization; (2) the ability to loosen control in terms of direct surveillance and formal bureaucratic procedures, thereby fostering a high degree of trust and “open communication” between organizational members; and (3) the ability to utilize “organizational slack” (for details see: Hutter, 2011; Hutter & Kuhlicke, 2012, under review). Interesting in this context is also the question of what exactly an organisation is and how it should be conceptualized in research, because the definition of an organisation has implications for how resilience is framed. In this regard, the conception of an organisation differs not only across scientific fields but is also the result of historical developments. Scott (2003), for instance, identifies three major approaches:  Organisations understood as rational systems considers an organisation as the result of a clear delineated set of well-defined rules, roles and relationships that are created to achieve a set of specific objectives. This formalized structure makes it easy to perceive who belongs to the organisation and who does not and how authority and responsibility is distributed within the organisation. Information is communicated through well-defined communication channels that often follow a hierarchical order (i.e. scalar chains) and work is delegated between individuals. This clear structure is promoted with the main goal of efficiency in mind.  The natural systems approaches focus on informal structures that emerge through human interaction and that evolve spontaneously within an organisation in response to the work environment. The informal organisation represents more closely how people actually work together and it is a result of cultural and social norms, preferences, interests and relationships amongst members of the organisation.  The open system perspective puts organisations in the context of their environment in which they operate and with which they interact. Organisations are conceived “as a throughput model, obtaining resources from the environment, processing them and distributing the output back to the environment” (Baum 2002) Research has shown that informal structures not only complement but often enhance the formal structure and increase the performance of the organization (e.g., Chang Seng 2010; Zagorecki et al., 2010; Fischer et al., 2007, Ostrom 2005; Ostrom 1990; Mehta 1999 etc). Especially regarding the exchange of information within and between organisations, informal structures seem to play a crucial role. Information can be seen as a core resource when dealing with surprise and reacting efficiently in an uncertain environment. Hierarchical information exchange networks (i.e. scalar chains), however, often restrict the exchange of information (cf. also Pelling et al., 2008). In a simulation model, Zagorecki et al. (2010) have shown that allowing the emergence of informal communication links between agents both within and in-between disaster relief organisations increased their efficiency in matters of response time. With regard to organisational resilience and high-reliability organisations, these emergent organisational structures can be seen as crucial contributors to enhancing system resilience.

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Some critique and open questions 

Empirical research seems to point out that while a resilience-based strategy appears as appropriate in facilitating adaptation to unexpected developments, it is confronted with a deficit of implementation and acceptance (it is a rather quixotic approach). Anticipation-based strategy is the accepted and dominant adaptation strategy in most organisations and also in people’s everyday life, even if it might increase their vulnerability in the long run (Kuhlicke & Kruse, 2009). How to close this gap? Furthermore the ideas might be relevant, paradoxically, for a highly formalized environment yet be hardly transferable to the everyday life situations of people at risk.



Until now the predominant approach in the literature when dealing with the elusiveness of resilience has been to distinguish between two (or more) meanings, and to discuss the context conditions under which these meanings are employed, e.g. “resilience as a descriptive concept and a boundary object” (Brand & Jax, 2007). Despite profound differences in how authors understand resilience, they often share the common perception that the different types of resilience are understood as rather static and frequently mutually exclusive entities. It is, however, possible that a better approach might involve the understanding that the very meaning of resilience might change (or better, how an observer observes resilience of a system might change) during the process. Sometimes it might be perceived as being a static and fixed entity, whereas in other phases it might become fluid and more process oriented. What is missing, therefore, is a more dynamic element to the analysis, which focuses on social context conditions before, during, and after a crisis and how the meaning of resilience itself might change under changing context conditions (Hutter & Kuhlicke, 2012, under review).



So far the research has mostly focused on organisations themselves and how they might improve their performance to become more resilient. Yet, such organisations find themselves increasingly as “part of networks of organisations as a result of institutional fragmentation, automation, and liberalization processes creating new challenges and risks – but possibly also opportunities – for HROs (de Bruijne et al., 2011, 24). Scholars have only started to look at the wider implications of this change with regard to the resilience of such organisations.



Although clearly less pronounced, this view on resilience suffers a similar shortcoming to that of the ecological and/or social-ecological discussion on resilience, in that some authors blame such ‘resilience-thinking’ as pursuing a rather reductionist view on the complexity at stake. Since resilience stems from the natural and/or physical sciences, it would be ‘‘inadequate and even false when it is being uncritically transferred to social phenomena, precisely because human systems embody power relations’’ (Cannon & Müller-Mahn, 2010, page missing). As a consequence, such approaches would have the tendency to understand necessary interventions as a rather neutral process that neglects the political dimension of the issue at stake and ‘‘depoliticises the causal process inherent in putting people at risk’’ (2010, page missing). There is hence a tendency to interpret the challenges people are facing predominantly in ‘‘functionalisttechnocratic terms’’ with a strong orientation towards how to change practices and policies (t'Hart, 1993), neglecting that risk and disaster management are very complex and most often politically controversial issues too (cf. also Kuhlicke, 2010).

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There is generally a lack of linking theoretical work and empirical case studies: „The treatise [”Searching for Safety“] earned much praise but never inspired much empirical work and generated only modest theoretically oriented discussion. It is fair to say that we have not moved very far beyond the territory staked out by Wildavsky.“ (Boin et al., 2010).

The following lines attempts to provide some first aspects as to how we might progress in this direction. 2.2.2 Resilience and Institutions Institutions (here understood in a very general way as formal and informal rules and values that members of a group have more or less agreed upon) are a recurring topic in the discussion on resilience, whereas the discussion quite often reinforces the classical divide of micro-oriented studies on the one hand and macro-studies on the other. Research on organizational resilience, for instance, is mostly interested in individual or micro-organizational sense-making processes increasing or decreasing the capacity of agents to come to terms with threatening events (Weick & Sutcliffe, 2007). Sensemaking is usually thought of as being attributed to locally embedded processes of interpretation, action, and learning. In this understanding, sense-making “serves as the springboard into action” (Weick et al., 2005). Studies on the resilience of socialecological systems in many cases rather focus on general aspects and institutions. Institutions are here quite often understood as a static societal manifestation representing “formal constraints (rules, laws and constitutions) or informal ones (norms of behaviour, conventions) that mould interaction in a society […]” (as an example: Badjeck et al., 2009, 211). However, there is also work within SES trying to develop a more dynamic understanding of institutions (see for example Pelling and ManuelNavarrete, 2011; Ostrom, 1990; North, 1990; Keohane and Ostrom, 1995). In line with the latter, more-dynamic perspective on resilience and institutions, it might be worthwhile to consider some of the more recent work on (neo-)institutionalism which is mostly based on the work of Beger and Luckmann and their concept of realization (Berger & Luckmann, 1967). By realising the world it becomes reality: “Knowledge about society is thus a realization in the double sense of the word, in the sense of apprehending the objectivated social reality, and in the sense of continually producing this reality” (1967, 66). As a consequence of this assumption two points need to be highlighted: 



This view on institutions underlines social dynamics as it puts less of an emphasis on institutions per se (e.g. the consequences of a specific regulatory system on the resilience of a specific social-ecological system), but rather on the process of institutionalization. Institutions are in this perspective never fixed. They are rather constantly interpreted, (re-)negotiated and under continuous change at different scales and from different perspectives. This appears as particularly relevant having the dynamic nature of resilience in mind outlined above. The social character of institutionalization as the separation in a micro and macro level of the analysis is misleading: institutions are – per definition – always intersubjectively shared, produced and maintained in daily interactions. This implies that institutions do not simply define actions; institutions and actions are rather mutually influencing each other.

We think that pursuing some of these thoughts might be a worthwhile endeavour to consider. There are some reasons for doing so:

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It might allow us to complement some of the work done by Pelling (Pelling, 2010) on resilience and transformation. We might add some more micro-macro level aspects (i.e. task on psychological aspects and network related aspects in WP 4 and the work done in the case studies WP 5) to his macro-level analysis and hence might get a better understanding of how such transformative processes are taking shape (or not). This leads to the second point:



There is a need to pay more attention to different institutional approaches (formal and informal, bottom-up and top-down), policy centric and multi-layered institutions and organisations, in order to deal with complex, ambiguous and uncertain risk as a strategy to improve societies’ resilience (Chang Seng, 2010). Furthermore, institutional restructuring in the context of critical infrastructures might also be of relevance. It is argued that privatisation; liberalisation and deregulation as part of institutional restructuring does not account for critical infrastructure reliability (see critical infrastructure resilience). Therefore, there is a need to consider and study the impact of macro-structural context and change in resilience



Furthermore and despite the widespread usage of the word resilience (at least in the Anglophone world), this does not mean that organizations are actually committed to resilience, especially in terms of deliberate shifts in power and resource allocations. Furthermore, it does not entail that resilience is actually institutionalized in concrete practices and procedures (such as, for instance, the risk management framework). Changing attitudes towards resilience as institutionalized “myth” is certainly possible but by no means a necessary or ineluctable development. On the contrary, by establishing the ‘myth of resilience’ actors might rather strengthen their own position within a specific setting (cf. also Kuhlicke, 2011). In this sense, by focusing more thoroughly on the process of institutionalisation, we might be better able to understand whether resilience is rather a myth – some kind of talk by organisations – or actual action on the ground making a difference in practices (cf. (Garschagen, 2011; Hutter & Kuhlicke, 2012, under review). To take this aspect into account seems all the more relevant as emBRACE is at the same time analysing and performing this (suggested) shift towards resilience.

2.4 Ecological and Socio-Ecological Resilience Perspectives By Neysa Setiadi As mentioned in chapter 2, the resilience perspective from ecological science was widely adopted and extended by various fields. An important starting point was Hollings work in (1973), which revealed that not only is the population size / number key for the survival of an ecological systems, but so also is the maintenance of the key functions. Holling´s ecological resilience definition (1973) emphasized that resilience involves both a) capacities of a system to absorb disturbance and b) capacities to reorganize while undergoing change, so as to still retain essentially the same function, structure, identity and feedbacks (Walker et al., 2004). At present, the global change research community is dominated by an understanding of social-ecological resilience that goes beyond the “engineering” conceptualization prevalent in parts of the hazards research community. The more “ecological” understanding of an entity able to learn, adapt, and change seems critical against the backdrop of a changing climate and social-ecological environment. A review by Moser (2008) acknowledged the dominance of thinking emerging from the Resilience Alliance

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(following Holling´s school) and pushes the field – in the context of global environmental change – into the social-ecological direction (Berkes et al., 2003). It views resilience and system dynamics in the context of complex adaptive systems, with emphasis on crossscale interplay and the two interacting sides of resilience both sustaining and developing (Folke, 2006). A widely accepted definition of resilience applied to social-ecological systems involves: (1) a response to / capacity to absorb disturbance, (2) a capacity to self-organize, (3) a capacity to learn and adapt (Folke, 2006; Parry et al., 2007). However, this does not necessarily mean that the conditions of the system return to their pre-crisis status, but rather that the crisis and the weak control within a crisis is used by the system as drivers to reorganize and perhaps to change (or transform) (see Berkes et al. 2003). One of the core elements of social-ecological resilience thinking is based on the notion of coupled social-ecological systems. That means ecological and social systems are strongly interconnected as a complex system rather than simple systems. In a complex adaptive system, resilience may be considered as an emergent property of a system, one that cannot be predicted or understood simply by examining the system´s parts (Berkes et al., 2003). Resilience of a system is firstly concerned with the magnitude of disturbance that can be absorbed or buffered without it undergoing fundamental changes in its functional characteristics. The disturbance can be originated from natural as well as anthropological activities. The dynamic interactions between ecosystems and social systems such as in resource use and changes in ecosystems – or even interactions regarding non-material flows - highlight the importance of considering coupled socialecological systems and also puts forward the other characteristics of resilience, regarding self-organization and learning (Berkes et al., 2003). This has also led to a further advancement of the focus on the adaptive capacity, transformability, learning and innovation, in context of integrated system feedback and cross-scale dynamic interactions is the advancement in the social-ecological resilience compared to ecological resilience (Folke, 2006). Holling addresses the necessity of adaptive management of complex adaptive systems in the different phases that a system undergoes. He introduced the adaptive-renewal cycle to capture some commonalities of various kinds of cyclic change, which consists of four phases: exploitation (the establishment of pioneering species), conservation (the consolidation of nutrients and biomass), release (of accumulated capitals due to occurrence of surprise) and organization (renewal) (Holling, 1986). While many theories on the management of natural resources and ecosystems have focused on the exploitation and conservation phases and seek for “optimality” and controlling the stability of the system, Holling´s adaptive renewal cycle emphasized the two backloop phases, release and reorganization (Berkes et al., 2003). Crises have a constructive role to play in resource management by triggering the opportunity for renewal, in systems capable of learning and adapting (Gunderson et al., 1995). In resource management applications, adaptive management is based on social and institutional learning and emphasizes feedbacks from the environment in shaping policy. For further advancement of this adaptive renewal cycle, Garschagen (2010, 2011) suggested the need to supplement with an additional phase of “precautionary reorganization” that leapfrogs the phase of potentially harmful collapse and unplanned release (See Figure 2 – right – in Chapter 4). Moreover, the term panarchy is used to capture the dynamics of adaptive cycles that are nested within one another across space and time scales (Gunderson and Holling, 2002) (See Figure 2 – left in Chapter 4). In ecological systems for example the smallest scale with the fastest speed may be tree crown, the intermediate one the forest patch and the largest and slowest the forest stand (Berkes et al., 2003). The concept of panarchy also brings discussions on institutions in the social-ecological systems. For institutions can

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consist of similarly-cascading influences, only in this context they take the form of operational rules, collective-choice rules, and constitutional rules (Ostrom, 1990, cited in Berkes et al., 2003). The resilience concept in social-ecological systems perspectives are influenced increasingly by the views from social sciences (some mentioned above). Adger (2000) attempted to determine the parallels between social and ecological resilience by focusing on the links between social stability and resource dependency and argued that social resilience is defined as the ability of resource-dependent communities to withstand external stresses and shocks to their social infrastructure, both in the form of environmental variability as well as in the form of social, economic and political upheaval. Pelling (2010) also emphasized the elements in the social-ecological system, namely social learning and self-organization, which are also explored through other literatures such as social movements, participatory and communicative planning (Pugh and Potter, 2003). The acknowledgment that trust and relationships underpin social learning also echoes work on social capital (Adger, 2003, Pelling and High, 2005). Furthermore, Birkmann (2011) has applied the concept of social-ecological resilience to adaptation to extreme events. This means that within the perspective of cascading adaptation processes – defined in this context as first and second order adaptation – ‘resilience’ characterizes those systems that are able to undertake these first and second order adaptation processes in the light of such events. Additionally, in their case study of food security in Bangladesh, Bohle et al (2009) promoted an actor-oriented and agency-based approach of conceptualizing resilience, as a contrast to a system-oriented approach. They started with the definition of socialecological resilience and then incorporated it to address a security concept. A framework with a normative context of entitlements, capabilities, freedoms and choices or of justice, fairness and equity, was proposed. It measured resilience in terms of how peoples´ livelihood vulnerability can be reduced and focuses on empowering the most vulnerable to pursue livelihood options that strengthen what they themselves consider to be their social sources of resilience. The concept of resilience has evolved and has been adopted and adapted in varying ways, thus, it has been frequently redefined and extended into heuristic, metaphorical, or normative dimensions. A review and typology of the definitions of resilience used in sustainability science and based on the degree of normativity was provided by Brand and Jax (2007). They discussed that in the descriptive interpretation, resilience can be a clearly specified and delimited stability concept, which is quantitative and measurable. However, on the other hand the “normative” approach of conceptualizing resilience made the concept become a “boundary object” to be used as a communication tool, capable of bringing different interests together. Brand and Jax (2007) suggested a duality of useage, with on the one hand resilience maintaining its increased vagueness and malleability (normative concept of resilience) to foster communication across disciplines and between science and practice, but on the other hand to determine clear, well defined and specific, characteristics for resilience as a descriptive concept, in order to provide the basis for operationalization and application in various fields. Some Critique and Open Questions Some critiques on the perspective refer to the application of ecological thinking in human systems. Renaud et al. (2010) lay out the importance of recognising different thresholds (tipping points) and states of the social-ecological systems under external shocks. Turner (2010) suggests that most of the hypotheses and core attributes of the framework of social-ecological resilience are derived from examinations of the ecological subsystem

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and laid over the human subsystem and social-ecological system at large, which would not sufficiently address the complex social structures and reflexive agents. Turner also calls for more attention to the tradeoffs between environmental services and human outcomes. With regard to the operationalization of the framework in general, Carpenter et al. (2009) also raises the issue about focusing on the computable and the tendency to believe in dominant models and called for more integrated approach and involvement of multi-disciplines and actors. The need to discuss the transferability of the resilience concept across different cultural, political and social systems, i.e. institutional and organizational environments, was also emphasized and reflected in some recent works (Garschagen, 2011; Garschagen et al, 2010; Baral et al., 2010; Lebel et al. 2006; Kuhlicke, 2010; Hutter et al., 2011). With regard to the recent policy discourses on resilience, Brown (2011) indicated that there are many contradictions, confusions and mixed interpretations of resilience. The concept of resilience in the policy statements is often at odds with scientific understandings of resilience in the social-ecological systems field. Brown also found that resilience is often used to promote business-as-usual, to resist change, and can be viewed as conservative rather than progressive, which contrasts with resilience dynamic meaning in SES thinking. Furthermore she noted that key resilience concepts, such as feedbacks and thresholds are largely absent in the policy literature. She also posed a question to what extent is resilience supportive of transformational change (fundamental change in system´s structure or functions). Addressing the notion of transformation of social - and extended social-ecological – systems, Pelling and Manuel-Navarette (2011) developed a regime transition based on Scheffer et al. (2002) and incorporated the concept of power (using Gidden´s structuration theory) in the adaptive renewal cycle of Holling. Their study emphasizes further the need to address an understanding of resilience which supports transformation rather than rigidity. On the other hand it is also important to acknowledge that the resilience discourse regarding social-ecological systems in the past decade has broadened its focus, particularly in terms of the need to change institutions – thus the rule systems for ecosystem management and the human interactions with nature – in order to move from the management that is concerned with the conservation phase – to a management approach that acknowledges the presence of crises and the need for renewal of ecosystems and resources (see Colding et al. 2003, p. 163). Consequently, it would be misleading to just translate resilience as a concept that conserves existing institutions and rule systems, while being exposed to stressors and change. Resilience of social-ecological systems is going beyond this notion and therewith moves from the former analytic-theoretical concept more towards a value based normative concept. Overall, the social-ecological system’s resilience perspective is very useful for developing an operational resilience framework. It has the advantage of not only focusing on the buffer or bouncing-back capacity of a system, but also on capacity to learn and adapt. Additionally, it is in line with sustainability in the sense that it treats the social and ecological systems equally in a systemic thinking (Turner, 2010). By this, it also provides a space to further incorporate attributes related with social and ecological systems as well as their interactions from recent works in various fields in order to improve the comprehensiveness of the framework. However, to build upon this perspective, Embrace needs to address the aforementioned challenges.

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2.6 Critical Infrastructure Resilience Perspectives By Denis Chang Seng Critical Infrastructure (CI) resilience is defined as chances of a failure, to absorb if it occurs (e.g. performance) and to recover quickly after a shock According, Hellström (2004) has proposed that a following characteristics:   

the ability of the system to reduce the to mitigate for an abrupt reduction of (i.e. re-establish normal performance). resilient system is one that shows the

Reduced failure probabilities Reduced consequences from failures (in terms of lives lost, damage, and negative economic and social consequences) Reduced time to recovery.

From this perspective, therefore, the resilience of a system could be considered as more ‘ontologically robust’ and ‘epistemologically assessable’ dimension than is its exposure to risk. CI resilience is of interest in the geophysics-seismic engineering, safety, contingencies and crisis management fields. In the geophysics-seismic engineering field, resilient physical and social systems must be: (1) robust (2) redundant (3) resourceful, and (4) capable of rapid response (Bruneau et al 2003). In addition, Bruneau et al., (2003) points out that resilience has been conceptualised as encompassing four interrelated dimensions: (1) Technical, (2) Organisational (3) Social and (4) Economic) as illustrated in figure 4. The performance of these systems critically affects disaster resilience for the community as a whole. In this context, CI should be regarded as providing a key contribution in terms of framework development, i.e. that for resilience assessment, one needs a whole systems perspective, which incorporates technology, organisation, social and economic systems. From a governance perspective, particularly within the European context, the use of binding legislation, followed by sectoral approaches, is being pursued to protect specific infrastructures in order to enhance CI. EU Member states opted for improved collaboration and information exchange, common surveillance programs and guidelines, discussions and consultations, spreading of best practices and a one-voice policy regarding impending crises. In addition, Hellström (2004) suggested that through collaboration, social actors would be better able to mitigate the conditions that may lead to the unsafe conditions and dynamic pressures of risk. In this regard, Stoop (2003) suggested an ontology consisting of at least three levels of policy actors in assessing CI. These include: (1) Initiator of components of the system whose interest is on quality, cost-effectiveness (2) the administrators with interest in safety-related procedural verification (3) the public, the rescue, and emergency services, whose interest is primary in safe operations and evidence that an emergency can be managed. In addition, Boin and McConnell (2007) argued that there should be a shift from contingency planning to societal resilience based on: (1) Preparing respondents (2) Business continuity planning (3) Working with the communities and private owners (4) Joint preparation (5) Joint Training (6) Training Leaders (i.e. create expert networks; facilitate systems for the identification of capable partners; train for situational and information assessment; learn how to support and facilitate emerging nodes of coordination; organise outside forces; work with the media; and, when necessary, initiate long-term reconstruction).

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On the other hand, there are certain opposing discourses and tensions regarding the governance approach to CI resilience. For example, the European Union policy approach regarding how to balance the resourcing of prevention and protection resilience versus enhancing a resilient response to breakdowns (Boin and McConnel, 2007; LaPorte, 2007). On one hand, a robustness approach (i.e. ‘bounce-back resilience’) has been proposed to need more investment (JCCM, 1994; 1996). On the other hand, de Bruijne and Esten (2007) argue the need to shift away from crisis management, which is seen as degrading CI reliability. It is argued that privatisation, liberalisation and deregulation as part of institutional restructuring does not account for reliability. Critical Infrastructure Protection (CIP) efforts are apparently very vulnerable in the light of institutional fragmentation and networked forms of reliability. It has, therefore, been suggested that CIP needs to better balance anticipation and resilience. This requires less devoted resources in specific defences against plethora of risks, threats and vulnerabilities and more on the development of generalised resources (Wildavsky, 1988). This implies improving the knowledge base and operating experiences of the relevant organisations, and developing real-life simulation exercises and collecting other forms of intelligence that better illustrate the surprising events. Some Critique and Open Questions It is apparent that research is required to address the quantification and measurement of CI resilience in all its interrelated dimensions, e.g. although it is only one discipline, in terms of CIP, it is particularly interesting that this task has not yet been addressed by the earthquake research community (Bruneau et al., 2003). Until now the predominant approach in the literature shows the difficulty of resilience measurement related to CI. There is a need to carry out additional research, first to identify and quantify performance, measures for resilient systems, and then to access the extent to which various technologies and tools result in improvements in performance. It is a complex process, and scales for measuring resilience at any level. On the other hand, the key problem is how to address individual defence measures, organisational beliefs and rationalisations, institutional designs for crisis management, costs of preparation, and governance frameworks and link them in a shift from contingency planning to societal resilience. In this context, organisational and institutional resilience studies may shed some light on this matter (Link with work of Christian Kuhlicke, Anna Kunath and Gunnar Dressler (UFZ). Finally, a key question to pay attention to is the boundary context of CI resilience. How might it be possible to shift away from crisis management and to determine a better balance between anticipation and resilience in the context of CI? (Also linked with key points raised by Christian Kuhlicke, Anna Kunath and Gunnar Dressler (UFZ), regarding their critique and open questions particularly regarding how any shift to a resilience approach has obstructed by a deficit of implementation and acceptance).

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2.7 Practical Perspectives on Resilience In order to understand that this discussion of resilience is not just an abstract exercise, it is important to provide a substantive example of where the concept has been operationalised in a way that has informed policy and generated changes in practice that have been suggested to have led to more ‘resilient’ communities. 2.7.1 UK Civil Protection Doctrine and the “Resilience Agenda”

By Hugh Deeming (UoN) UK Resilience: A brief summary

In Europe, perhaps the best example to use to illustrate such an approach is the United Kingdom’s civil protection “Resilience Agenda” (Cabinet Office, 2003). Since 2004 civil protection activity in the UK has been conducted under the epithet “UK Resilience”. At this time and guided by the provisions of the Civil Contingencies Act (CCA) 2004, the civil protection regime was significantly restructured in a way that codified existing practice, but which also introduced new statutory duties (O'Brien and Read, 2005). Adopting a process of Integrated Emergency Management (IEM)7 civil protection duties were now carried out by a range of designated ‘Category 1’ and ‘Category 2’ responder’ organisations8 within a framework, which stipulates and encourages locallevel collaboration between these responders in respect to how they conduct all aspects of IEM (HM Government, 2005). Whilst the UK Cabinet Office bears ultimate responsibility for civil protection and there remains an element of regional (i.e. sub-national) oversight, the principal tool through which responders coordinate and carry out their duties and obligations is the Local Resilience Forum (LRF). The LRF operates at the scale of a Police area, which in England are usually county sized (e.g. the Chief Constable of the Lancashire Constabulary chairs the Lancashire LRF) and is responsible for coordinating the delivery of seven CCA-defined duties by its membership. These duties are:      

Co-operation and information sharing Risk assessment Emergency planning Communicating with the public Business Continuity Management (BCM) structures] Advice to Business (on BCM)

[of

responder

organisations

and

In definitional terms it has been agreed that the reorganisation of the UK civil protection sector has brought improvements in relation to its transparency, its promotion of effective multi-agency collaboration (in the face of increasingly complex risks) and its uniform and consistent approach, which is based on the aforementioned subsidiarity to

7

Integrated emergency management (IEM) comprises six related activities: anticipation, assessment, prevention, preparation, response and recovery. (HM Government, 2005) 8 Category 1 responders: e.g. the Emergency Services (Police, Fire & Rescue, Coastguard); Health Services; Local Authorities. Category 2 responders: e.g. the Utilities, Telecommunications and Transport sector; Health and Safety Executive

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the ‘local’ scale (O'Brien and Read, 2005, Rogers, 2011). The operation of the framework is also audited by way of the cabinet Office Capabilities Programme, which has been developed: “to ensure that a robust infrastructure of response is in place to deal rapidly, effectively and flexibly with the consequences of civil devastation and widespread disaster inflicted as a result of conventional or non-conventional disruptive activity and natural disasters” (Cabinet Office, 2009a: emphasis added). However, it has also been argued that in terms of developing ‘community resilience’ the LRF has remained exclusive, with its decision-making processes inaccessible to the population it serves (Alexander, 2003; Walker and Broderick, 2006). More specifically, it was suggested that in its early iteration UK Resilience focused too much on partnership working rather than on community engagement (Twigger-Ross and Scrase, 2006). In effect, the processes adopted in the LRF framework were more transparent to the local population than those employed in the earlier era of “civil defence” (Walker and Broderick, 2006). However, this was a transparency that needs be imagined as mediated though a sheet of impenetrable glass, i.e. for those in the community ‘below’, any actual participation in many of the LRF activities remained essentially impossible.

UK Resilience: defining resilience The criticism that the LRF is disconnected from the ‘communities’ it serves, does not detract from the fact that under the CCA, UK Civil Protection has actively engaged with a particular concept of resilience. It could also be argued that the statutory duties and non-statutory guidance that have resulted from the ‘UK-Resilience’ framework’s introduction have created opportunities for resilience to be built into civil-protection structures, as well as into other agencies and organisations (i.e. through the duty to advise business on BCM); although this latter task remains a challenge (Woodman and Hutchings, 2011). The UK civil protection Lexicon (Cabinet Office, 2010), defines resilience as: "The ability of the community, services, area or infrastructure to detect, prevent, and, if necessary to withstand, handle and recover from disruptive challenges" 9 This precise definition dates back to the publication of the statutory guidance document Emergency Preparedness (HM Government, 2005)10 and as such has nominally underpinned the development of all subsequent resilience work in the sector. Therefore, it has not only guided the development of the LRF framework, but has also underpinned the creation of the National Risk Register and National Security Strategy (Cabinet Office, 2008b, Cabinet Office, 2009c), as well as guidance related to developing contingencies for, (e.g.) the identification of people who might be vulnerable in a crisis; data-protection protocols; cyber-security; the protection of critical national infrastructure (CNI); and preventing violent extremism, (Cabinet Office, 2008a, Cabinet Office, 2009b, Cabinet Office, 2011a, CCS, 2009, HM Government, 2007, HM Government, 2011) However, even though this definition is regarded as overarching by the Cabinet Office (MacFarlane, pers comm), an examination of all current UK Civil Protection guidance,

9

This definition should be understood in the context of the CP lexicon definition of risk management: “All activities and structures directed towards the effective assessment and management of risks and their potential adverse impacts” 10 A slightly different wording appeared in the earlier document Dealing with Disaster: “the ability at every relevant level to detect, prevent, and, if necessary, to handle and recover from disruptive challenges” (Cabinet Office, 2003: p.1)

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which focuses on facilitating multi-agency collaboration (across a range of sectors and hazards) (Deeming and Easthope, 2010), reveals that a total of 21 differing definitions are present within these documents (Deeming & Fordham, forthcoming). Of particular note is the definition, coined in 2010, which underpins the Strategic National Framework on Community Resilience, where ‘community resilience’ is proposed to be encapsulated by: “Communities and individuals harnessing local resources and expertise to help themselves in an emergency, in a way that complements the response of the emergency services.” (Cabinet Office, 2011b: p.4)

What’s in a definition? Taking note of the discussion in the rest of this working paper, it can be seen that the principal Cabinet Office definition of resilience incorporates elements of detection, prevention, resistance, management and recovery, which suggest a presumption of a system’s (e.g. community, services, etc.) ability to ‘bounce-back’. It could also be suggested that this approach focuses on maintaining the business continuity of the responders (i.e. the “robust infrastructure of response”), rather than on building wider ‘community’ based resilience. This suggestion is supported by the implicit nature of the message, within the more recent ‘community resilience’ definition, i.e. that the emergency services approach to resilience building (i.e. the ‘command and control’ exercise of response-focussed activity), is all that apparently matters. Such a limited perspective has been criticised, because it fails to account for the inevitability of the change that does occur after an emergency, beneath the ‘glass floor’ of the LRF. Such change may take the form of property repairs that alter the fabric of affected structures (i.e. through the adoption of 'resilient' or resistant structural measures: Defra, 2008), or health or psychological effects, which can continue to influence individuals, families and communities long after physical structures have been repaired or replaced (Fordham and Ketteridge, 1995, Tapsell and Tunstall, 2008, Whittle et al., 2010). Either way, by institutionalising a particular understanding of what ‘resilience’ involves, in a way that de-emphasises change and focuses on response, it could be argued that the UK civil protection sector approach lies far behind current thinking on the concept. As an example, the Cabinet Office definition of ‘community resilience’ could be understood to be particularly restrictive, in terms of how its use conveys the message about what can be considered to represent ‘resilience’ and what cannot. If only activities that allow individuals and communities to harness “local resources and expertise to help themselves in an emergency, in a way that complements the response of the emergency services” are considered to be ‘resilient’, what does that say about community activities that could be regarded as uncomplimentary to other aspects of the emergency services’ (or other responder agencies’) approaches to civil protection? For example, how should communities who coordinate themselves – i.e. self-organise – in order to advocate for increased spending on local flood defences be characterised by someone using this definition? There is increasing concern in the UK that household insurance against flood risks will soon be unavailable for properties in high risk areas, whilst at the same time spending on the structural measures needed to alleviate some of these risks is becoming subject to increasingly strict funding criteria (EA, 2009). Should not the focus of civilprotection related resilience-building activity encompass the identification of and engagement with some of these wider social issues related to hazard exposure and vulnerability? This is not an easy or straightforward question to answer. However, it has been argued that finding mechanisms and opportunities through which the opening up of UK Civil Protection to greater participation by those who are being ‘protected’ could lead to a

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more encompassing type of resilience emerging (O'Brien and Read, 2005, Twigger-Ross et al., 2011). From this perspective it may be helpful to imagine that deciding how, why and for whom resilience (of what?) is being defined, is actually a ‘boundary’ process (Wenger, 2000: see also Kuhlicke this paper), which holds the power of inclusion or exclusion? Effectively, the current discourse of civil protection assumes that resilience building, whether carried out by individuals, communities or civil protection agencies (and those closely allied to them) needs to be realised through disaster reduction methods (narrowly defined, e.g. response focused). An open question that this realisation begs, therefore, is could a more inclusive institutionalised interpretation of resilience act as a means to facilitate a more fundamental social and political transformation of vulnerability (e.g. poverty reduction and other social equality measures) and to achieve this, who – apart from civil protection professionals and the community itself – would need to be engaged? Finally, it is also important to acknowledge that the definitions used in the UK example, do not refer to a core element of social-ecological resilience, which is the ability to learn and change through crises due the fact that in such crises existing institutions and organisations are weak and confused and there with open the space for innovation (see Holling 2003, p. XVI).

2.7.2 An Operational Framework for Resilience of the U.S. Homeland Security By Neysa Setiadi Another example of the operationalization of resilience is taken from the United States of America. Initially triggered by the Terrorist attack on September 11, 2001, the Department of Homeland Security (DHS) was founded to coordinate and unify the U.S. national security efforts against terrorism and other hazards. In a DHS report (2008) to support the transition to the new administration of President Obama, building resilience was highlighted as one of the top 10 challenges faced by the next secretary. As a followup, concept development was conducted which resulted in an operational framework of resilience (DHS, 2009). The application of resilience here followed a rather more “normative” concept. DHS follows the official definitions of resilience as 1) the ability of systems, infrastructures, government, business, and citizenry to resist, absorb, and recover from or adapt to an adverse occurrence that may cause harm, destruction, or loss of national significance, and 2) capacity of an organization to recognize threats and hazards and make adjustments that will improve future protection efforts and risk reduction measures (DHS Risk Lexicon, 2008). DHS views resilience as the aggregate result of achieving specific objectives (resistance, absorption, and restoration) with regard to critical systems and their key functions, following a set of principles, which can guide the framework’s application through practical ways and means across the full spectrum of national security missions (protection, respond, recover, and prevent). In this context, DHS linked the term resilience with disaster management phases (before, during, and after disasters). The principles of resilience are defined as follows (DHS, 2009): -

Threat and hazard limitation: to attenuate the potential of human threats or natural hazards to inflict damage before the hit is taken Robustness: capability and capacity of critical systems to withstand severe internal and/or external stresses and to maintain key functions impacting American society, economy, and government

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-

-

-

-

-

Consequence mitigation: capabilities and capacities of critical systems and their key functions to control and reduce cascading adverse effects of a damage event and then recover quickly and resume normal activity Adaptability: to recognize that change is inevitable and that it therefore must be able to encounter and adjust to the unexpected without its essential health being threatened Risk-informed planning: deliberate foresight, intentional prearrangements, and the purposeful development and exercise of required capabilities and capacities to effectively cope with each stage of the life cycle of an adverse situation Risk-informed investment: allocation of resources to investments in meeting the resilience requirements of any critical system or key function done in a manner informed by an understanding of risks facing those assets Harmonization of purposes: six principles above mutually reinforcing Comprehensiveness of scope: recognition that resilience encompasses all of America’s national homeland security enterprise, including federal, state, local, and tribal governments as well the private sector, communities, families, and individual citizens, synergistically

The principles of resilience in this context are seen initially as a guide for exploration of alternatives at the strategic level, rather than a strong analytic tool or concept for specific use. For the latter purpose, further criteria and parameters need to be defined. DHS (2009) suggested (e.g.) to use three specific parameters for developing the “resilience profile” of a specific system: (1) function (including key inputs, central operations and principal outputs), (2) latency limit (maximum amount of time allowable for a function to remain a degraded or suboptimal state before it must begin to recover), and (3) minimum performance boundary (the lowest acceptable level of performance for the defined function). The resilience frameworks and principles adopted by the UK civil protection sector and US national security sector provide examples of how the concept can be anchored in the policy-making and planning practices. They provide guiding visions based at the strategic level and parameters that illustrate how resilience can be developed/maintained at the operational level. Noteworthy is also the linkage of resilience objectives with the disaster management (or IEM) cycle. With regard to their operationalization, resilience frameworks should be clear on the level and purpose they serves. This imposes a question to emBRACE as to which level’s and specific purposes our general framework/s will be addressed to?

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3.0 Existing Tensions in Different Conceptualization of Resilience As described above, the concept of resilience has been adopted and extended in various ways, which sometimes generate different meanings to that of the ‘original’ concept. In this section, we outline various perspectives or tensions in conceptualizing resilience based on the literature analyzed. These aspects need to be considered in the development of resilience framework for emBRACE. Framing the Goal Brand and Jax (2007) delineated several approaches to define resilience depending on whether it is descriptive or normative or hybrid. Also, some papers have discussed how to operationalize the concept or whether it might be preferable to use it only as an ‘umbrella’ concept (Klein et al, 2003 cited in Gaschagen, 2011). This would also imply the “subjectivity” in defining resilience for various contextual and practical uses. With regard to the basic understanding of the concept, a review in Moser (2008) underscored that there is the general division of definitions into those where resilience is understood as the capacity to maintain the system (or its major function) in the face of external or internal pressures, risks, uncertainties, changes and surprises (this tends to the “engineering” resilience with the idea of near equilibrium stability), and those where resilience is the capacity essentially to stay alive but change along with those forces of transformation. Moreover, some authors such as Folke (2006), Adger (2000), Gunderson (2010) define it by adopting an ecological (with multiple equillibria for example) or hybrid view, in which resilience is seen as the capacity to withstand change for some time but also, past a certain point (sometimes known as a ‘tipping point’), to transform while continuing or regaining the ability to provide essential functions, services, amenities, or qualities. This will also relate with defining state of return or trajectories of the system of interest, whether it should be back to its previous state or to develop a new one. Furthermore, it is underlined that framing the goal depends critically on the purpose as well as on the standpoint of the observers. This is one of the key tasks to explore further in the coming months. System of interest There are different perspectives in defining the system. The focus is either on social (human) system or ecological (environmental) system or both. The relationship of social and ecological systems is also defined in various degrees (Moser, 2008). Additionally, Bohle et al. (2009) suggested his preference of taking an actor or agent-oriented approach rather than a system-oriented approach. Scale of analysis Scale of analysis is also another aspect related to how the system is defined. For example, in psychological analysis, the unit varies from individual to society, and each would generate different sets of resilience definitions or parameters respectively. Moreover, Renaud et al. (2010) and Garchagen et al. (2011) discussed a) the important to consider shifts in social-ecological systems from both – social and ecological components and b) the question of at which scale the development pathways and tipping points should be developed or analyzed as being one important aspect, rather than applying a deterministic understanding of a monolithic system moving as a whole into one pre-defined direction. One other concern coming from the Resilience Alliance (Walker and Wesley, 2011) is related with the trade-offs between building specific resilience (the

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more robust a system in one way, the less robust it becomes in others) versus general resilience. Also, the Panarchy concept addressed the need to consider cross-scale interactions in social-ecological systems, although the panarchy model is primarily driven by ecological system theories of revolt and remember. Characteristics of disturbance and crises as trigger for changes The question of disturbances takes into account the sources of disturbance, awareness of it, its severity, exposure of the system, and its temporal dimensions. Different characteristics of a disturbance would demand different attributes of the system in order to be resilient to it. For example, resilience, which refers to future shocks or change will pay more attention to foresight, predictive capacity, social memory, learning and adaptation, whereas the present disturbance would focus on coping capacity. In addition it is still discussed as to what extent resilience is encompassed within reorganization and renewal of social-ecological systems, also institutional changes and the notion of transformation. Examples particularly in the newer literature on social-ecological resilience refer particularly to the fact that crises open the space for innovation due to the fact that control is weak and institutional arrangements are revisited (see Holling, 2003). Approach or mechanism to achieve resilience The last aspect is the mechanism of the system to reach resilience, whether it is emphasizing anticipation or recovery (pre-or post-event) or both equally, or whether it uses the knowledge from previous experiences or is anticipating for the unknown. All of these would determine characteristics of a resilient system. Figure 1 (next page) provides an overview of the aspects as well as different attributes used to frame resilience.

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Fig. 1: Various conceptualizations of resilience and its entities (Source: own figure, based on literature review)

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4.0 Problematising the concept of ‘community’ By Hugh Deeming and Maureen Fordham So far, this report, has concentrated on developing a state of the art understanding of the concept of ‘resilience’. However, the authors are fully aware that another concept, which is of foundational importance to the project, has received only a cursory mention. It should, therefore, be fully acknowledged that any attempt to simplify or to take for granted the concept of ‘community’ would be considered inappropriate, given the complexity and contentious nature of that concept’s history (Hoggett, 1997). Indeed, Margaret Stacey’s 1969 critique of the lack of valid definitions of the term was a devastating blow to those formerly operating with a geographically undefined, often unidimensional and romantic notion of community, and signalled a hiatus in community studies for several decades. Thus, ‘community’ is a term that has attracted considerable interest over many decades (even centuries) and has been used by some as a descriptor of some sort of idealised social structure in which people collaborate, share resources and look after each other’s collective interests (Delanty, 2003). Such an interpretation appears at first glance to bear useful relevance for those who are intent on developing DRR and/or ‘resiliencebuilding’ strategies. The truth of what might constitute a ‘community’ in terms of understanding the development of ‘community resilience’ is, however, more problematic. Which ‘community’ is being referred to in this context? Can all communities be equally resilient to hazards (e.g. rural/urban)? When do resilient communities form - before or after a hazard event? All these questions and more need to be considered during the emBRACE project, as such questions will be fundamental in allowing the identification of who may be included or potentially excluded from influencing any of the research activities (e.g. case studies) and/or findings. After a discussion of the history of the community concept, in which he suggests it is inhered in public perception as a: “…highly fluid communitas – a mode of belonging that is symbolic and communicative – rather than an actual institutional arrangement, and that it is variable, capable of sustaining modern and radical social relationships as well as traditional ones” (Delanty, 2003: p.31) Delanty effectively concludes that community should not be considered in terms of geographical boundaries, but in terms of a capacity to communicate. In fact, Delanty’s argument suggests that place is bearing increasingly less relevance to community activity, as (e.g.) new forms of IT and the dispersed social interaction they allow, are resulting in more pluralised community types being constructed around often single issues (e.g. environmental protection, gay rights). Such communities, Delanty claims, whilst important to their individual members, do not require dedicated commitment and as a result do not offer enduring forms of social connectedness. The potential flux in an individual’s membership of such potentially multiple and fragmented communities, he proposes, places the onus on that individual to create their own interpretation of what constitutes ‘community spirit’. Community membership from this perspective is very much an individualised experience, with individuals’ perceptions of what that membership means for them defining their engagement, rather than having that engagement guided by socially-constructed norms and institutions. In terms of Disaster Risk Reduction (DRR), however, whilst communication is fundamental in terms of developing useful disaster contingencies (e.g. networks through which warnings can be transmitted and confirmed: Fitzpatrick and Mileti, 1994), geographical location remains a fundamental predictor of hazard exposure and, therefore, a vital factor in understanding how any population anticipates, prepares for, responds to and recovers from hazard events. However, applying the term ‘community

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of place’ may be regarded by some as a trick, in a sociological sense, because it simply amalgamates an otherwise disparate mosaic of social groups and networks (Marsh and Buckle, 2001) into some sort of useful metric. Such a trick is fraught with danger (literally for some), because by amalgamating society in this way it becomes easier to overlook the fact that within such an artificial social/geographical construction there will be people who undoubtedly have the resources to engage fully in DRR activities, but there will also be many who lack the willingness and/or capacity to cope with hazardinduced disruptions. There will be, despite the best intentions and efforts of those working to increase community resilience, those in such an aggregation, who do not engage or who do not even feel part of any community at all; let alone part of such an ‘imposed’ interpretation of community. In considering a community as being a social something that can exhibit attributes of ‘resilience’, it is also important to acknowledge the decades of research, which has shown that post-event communities can be considerably different from those that existed before. A wide range of hazard events have been shown to lead to the development of therapeutic-community responses within affected place-based populations (Fritz, 1996, Barton, 1969), where previously uncommunicative neighbours and neighbourhoods start to work together in order to recover and to rehabilitate after a shock. Such phenomena can be long-lasting, fuelling sustained efforts to mitigate the risk of event recurrence through the adaptation and adjustment of (e.g.) local governance and planning institutions (Pearce, 2003). However, these altruistic effects can also be relatively shortlived when, for example, inequalities or inequities are identified between how the needs of different social groups in the affected population are accommodated within formal recovery arrangements. One precursor of decline in conviviality and created division within communities has been identified as occurring when affected but uninsured households (i.e. often poor households) have been provided with financial or practical support by public institutions, whilst insured householders have been left dependent upon the vagaries of whatever standard of provision/compensation is deemed appropriate by individual private-sector insurance companies (Fordham and Ketteridge, 1995, Whittle et al., 2010). Far from being ‘therapeutic’, these communities can become ‘corrosive communities’ if toxic contamination is involved (Erikson, 1994: p.236) where, at its most extreme, people may experience a changed sense of self, changed way of relating to others and even a changed world view (Erikson 1994: p.241). Here the spatial aspect of natural hazards too can have a divisive effect, as the hazard affected can feel alienated by the wider [unaffected] community, whose members ‘do not understand’ what their neighbours are going through (Whittle, et al., 2010). Another potentially community-changing effect that results from hazard occurrence is the spontaneous convergence at the scene of sometimes large numbers of outsiders (Fritz and Mathewson, 1957, Wachtendorf and Kendra, 2004). Spontaneous convergence can see people travelling from far afield for a number of identified reasons. They may converge in order to negate their own anxieties about the event’s effects (e.g. by checking on loved ones), or they may provide positive assistance, in the shape of rescue services and support for the affected. Converging ‘helpers’ particularly, have even been found to integrate into the affected community, where they can remain for months or in some cases, years (Solnit, 2009). Less positively, as was seen in New Orleans after Hurricane Katrina, an influx of white volunteer helpers can threaten the identity of a community comprising a majority of ‘people of color’ (Bierria et al 2007: p.40) whilst still making use of ‘images of black women and other people of color to legitimize themselves to funders’ (page 41). A more frequent occurrence is for incomers to converge in order to sightsee (e.g. disaster tourism: Hoving et al., 2010, Garoian and Gaudelius, 2008). Or convergence may occur to exploit the confusing circumstances by (e.g.) profiteering or

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by committing crime (Fritz and Mathewson, 1957)11 . Whilst likely to be rare (Barsky et al., 2006, Fischer, 2006, Tierney et al., 2006, Quarantelli, 2008), such criminal transgressions as do occur can cause additional social pressures (e.g. suspicion) to develop within affected communities that are likely to have already been preconditioned, by the media (Constable, 2008) and by the ‘command and control’ style of the formal response agencies (Dynes, 1994), to expect that widespread criminal behaviour will occur. In fact this ‘myth of looting’ has been empirically revealed to be a largely “false threat” (Wenger and Parr, 1969); with altruism far more likely to be the prevailing ‘community’ phenomenon (Quarantelli, 2008, Solnit, 2009). Clearly, there are many ways to consider what communities are, were, or even, should be. As a starting point there is some utility in using the following five categories as an initial frame: geographical communities; communities of interest; communities of circumstance; communities of supporters (Cabinet Office, 2011: p.12), and communities of identity. Geographical communities are those with identifiable geographical or administrative boundaries (for example, in the UK case: wards, parishes, villages or towns), or arising from other forms of physical proximity (for example, a street or an apartment block). As described above, the geographical community is the boundary of choice for many disaster management functions although, while likely to be affected by the same type of natural hazard (such as flooding) the boundary can contain much variability (for example, in the context of flood risk, properties on raised ground within a flood envelope drawn on a map). Where there is strong identity with any level of community, it appears focused at the most local level (JRF 1996). Communities of interest comprise groups of people who have an association arising from interaction through a shared interest or through their work (examples include sports clubs, parent groups, faith groups, online communities and business groups). Most often these are people engaged together voluntarily to achieve a shared outcome although maybe without a shared world view. Communities of circumstance are formed through the sharing of experience, such as when people are affected by the same incident or circumstances. Individuals within the group may or may not share the same interests or geographical location but develop a community subsequent to the shared experience. Communities of supporters/practice comprise, in this context, communities of people drawn from organisations (both statutory and voluntary) providing disaster-related services and support (including, in the UK disaster management case, inter alia, police officers, fire-fighters, local authority emergency planning officers, Women’s Royal Voluntary Service (WRVS), Red Cross, and flood wardens. The members of this community may also share a geographical location and may be affected in the same way as communities they support. Communities of identity are highly varied and may represent personal characteristics (for example of sexuality, dis/ability) or nationality; less in terms of geography but more to do with ‘imagined communities’ (Anderson 1991). This is a fluid community which may emerge as representing a particular sub-group interest, often highlighting gaps in service

11

An example being the spate of burglaries committed by a travelling criminal, which occurred in Ulverston in

Cumbria, UK, following major flooding in 2009 (BBC, 2010)

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provision or recognition (for example, identifying needs or marginalization of nonheterosexuals in disasters (Gaillard in Fordham 2012: p.429). Social capital Strongly linked to notions of community, there has been growing interest in the role of social capital in disasters. Networks of family, friends (bonding social capital) and beyond (bridging and linking social capital) as well as relations of trust and cooperation are considered useful in building collective efforts to plan for and reduce disaster risk. In terms of DRR, however, the presence of social capital is not necessarily a direct indicator that a network is resilient. For example, whilst it provides an important ‘super glue’ of tightly knit network support (DeFilippis, 2001, Putnam, 2000), bonding social capital has been identified as presenting particular problems, in that during hazard events these tightly bonded networks can have a tendency to defer to the opinions of network seniors, rather than listen to information from people they regard as outsiders. Such behaviour during the run up to Hurricane Katrina was observed to lead to some bonded-network members taking their lead from matriarchal figures rather than the [untrusted] emergency services, which meant that evacuation decisions were delayed, with the result that these family groups became trapped together in the face of the incoming storm (Cordasco, 2006). The weaker ties, which are indicative of the lateral bridging between networks and the hierarchical linking up through networks of influence, are generally considered more valuable in terms of resilience (Granovetter, 1983, Murphy, 2007). This is because they open up the networks to, respectively, more varied sources of information and to the influence of power (Woolcock and Narayan, 2000). However, linking social capital can be limited in efficacy if network members perceive their own interpretation of any given situation is superior to that of the individual/organisation into which they are linked. Buckland and Rahman (1999) describe a case where strong linking social capital led to discord and increased vulnerability to a flood hazard. Their research involved the study of three communities following the flooding of the Red River, North Dakota, in 1997. They found that whilst two of the communities responded to an ‘insensitive’, mandatory evacuation order implemented by the authorities, the residents of the most affluent community, ‘Rosenort’, developed a degree of discord against the order. This resulted in over 100 people remaining in the ‘danger’ zone during the period of highest risk. Buckland and Rahman (ibid.) suggest that this example illustrates that social capital wields a doubleedged sword, i.e. it can foster co-operation by exploiting pre-existing networks and power relationships, but, it can also lead to conflict in decision-making within communities perceived to have a flatter social structure; where the pre-eminence of authority figures linked into the decision-making process is more likely to be questioned. Thinking in terms of social capital as being a facilitator of social learning, Pelling (2008) suggests that due note should always be taken of the private as well as the officially sanctioned social interactions that occur between network members working toward an aspired goal (e.g. greater resilience and/or adaptive capacity). Pelling suggests that the social interaction that occurs within the private ‘shadow systems’ (e.g. informal meetings and ‘water-cooler’ conversations), which exist in parallel to formally institutionalised interactions between stakeholders, can be “a key resource for policy enactment and regulation, as well as innovation and learning” (ibid., p.821). Wenger (2000) also points out the importance of identifying exactly who it is within any network who is actually providing the most effective information flow between networks. These ‘boundary people’ operate at the interface between formal and informal networks, but due to the fact that they tend to act as brokers of ideas rather than as principals who directly contribute to outcomes, they can be organisationally invisible, with the value they brought to any outcome formally unrecognised and underappreciated. As well as the structural ‘network’ aspects of social capital, Putnam (2000) also highlights the importance of cognitive social capital. Trust and reciprocity are regarded as vital in

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defining how people perceive their social environment, with trust being developed with the benefit of people’s actual, long-term (good or bad) experiences in life or their local environment, rather than simply through subjective perception (McCulloch, 2003). In Putnam’s view, high levels of social trust (i.e. the generalised willingness of individuals to trust their fellow citizens) are an indicator the presence of social capital. However, social trust should not be confused with the type of trust that most influences the way people interact with the institutions of DRR; trust in authority. Any trust in authority, which may be evidenced within a particular community, needs to be regarded as conceptually quite distinct from the thick trust afforded to network members or the thin trust that bridges between networks (Pelling, 2003). Trust in authority, which is often afforded because of a person’s role or position in an organisation (Giddens, 1990), tends to hold a much stronger relationship to the truster’s dependency [on that institution/person] than it does to any idea of “I have trust in my relations with you”(Wynne, 1992). Putnam regards norms of reciprocity as an equally important element in developing networks of weaker ties. This is because within these networks, sanctions cannot be directly enforced through tight ‘family’ values or expectations. Therefore, having a norm of generalised reciprocity, which allows favours to be ‘paid forward’, reduces the need for formal agreements, reduces stress and lubricates frictions in the network. While Putnam has been the populariser of social capital, two others have contributed to its conceptualisation and offer alternative perspectives (or tributaries as Foley and Edwards (1999: p.142) have it) that present some utility for the purposes of understanding the disaster-community-resilience nexus. They are described briefly here in order to highlight some possible applications in later empirical studies for the emBRACE project and will be elaborated in subsequent outputs. James Coleman’s (1990) contribution comes out of rational choice theory – characterised as individuals pursuing their own self-interest – which understands social capital as a necessary cooperation between individuals who yet are seeking to achieve their own interests. Coleman (unlike Bourdieu, 1985) recognised the potential for social capital to improve the situation for members of marginalised groups, although his emphasis on the role of close ties, undervalues that of weak/loose ties (Granovetter, 1983, Portes, 1998). Bourdieu’s contribution comes out of a Marxist tradition, although not uncritically. However, Bourdieu’s conceptualisation leads us to understand how social capital functions to reproduce inequality (Field, 2003: p.19)and thus offers a counterpoint to uncritical acceptance of social capital as a good thing (and more of it as being better). This short review is by no means exhaustive but merely indicative of some of those areas which will require further identification and elaboration throughout the emBRACE project and the following iterations of this review of literature and ideas.

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5.0Typology & Characteristics of Resilient Systems Based on literature review conducted and considering various tensions in the conceptualizations of resilience described above, we tried to classify characteristics of a resilient system (see Table 1). This is only the first attempt and it is intended to expand the table (or change it to an “ontological tree”) based on diverse expertise of the consortium, as well as on further literature study. Also, some resilience frameworks are drafted as a basis for discussion that may move towards the development of a common framework but not take us all the way there. The first graphics (Fig.2) were taken from the ecological / social-ecological perspectives, namely the adaptive renewal cycle and its cross-scale interaction. The figures provide understanding of the complex system. The adaptive renewal cycle used here is the adaptation from Garschagen (2010, 2011), where an additional phase of “precaution” has been added to leapfrog the release and reorganization phase (as an anticipatory action to future shocks). It is suggested to use these as an analytical framework and integrate the attributes of desired resilient system (social, ecological and interaction between both), e.g. memory in the phase “reorganization”, foresight and anticipatory learning in the phase “precaution”, multi-level governance systems and institutions in the “cross-scale interaction”, etc. In contrast, other frameworks were derived from the psychological perspectives (Fig.3), as well as from the resilience concept used in the context of critical infrastructures (Fig.4).

Fig. 2: Left: Adaptive renewal cycle with leapfrog of collapse and release phase through precautionary organization. Source: Garschagen, 2011 (adapted and amended from Gunderson and Holling, 2002; Berkes et al, 2003).Right: Panarchy, a heuristic model of nested adaptive renewal cycles emphasizing cross scale interplay. Source: Folke, 2006 (modified from Gunderson and Holling, 2002)

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NB: The typology of resilience in the context of psychology can be characterized as shown in the figure 3. It shows the two dimensional construct of resili ence consisting of exposure adversity, risk or challenge and the protective forces such as purpose in life, positive emotions, communication, teamwork, collective efficacy operating at individual, family, organization and community levels respectively. It consist of an internal-salutogenic (i.e. places emphasis on factors that contribute to health and well being) and external –social-ecological perspective (i.e. takes into account the influences of social context, both proximal and distal well being. It is affected substantially by the social contexts in which an individual are embedded and is a function of the quality of relationships among individual, family and institutional systems. In this context psychological resilience should be seen as a dynamic process operating at multi-interdependent levels and scales

Fig 3: Typology of resilience in the context of psychology (Source: own figure, based on literature review)

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Fig 4: Typology of resilience in the context of critical infrastructure (Source: own figure, based on literature review) NB: The proposed typology of resilience in the context of critical infrastructure can be characterized as shown in the figure 4. It shows that resilient physical and social systems must be: (1) robust (2) redundant (3) resourceful, and (4) capable of rapid response. In addition, resilience can be conceptualised as encompassing four interrelated dimensions: (1) Technical, (2) Organisational (3) Social and (4) Economic. In the case of technical dimension, robustness, redundancy, resourcefulness, and rapidity includes: (a) proper building codes (b) capability for technical substitution (c) availability of equipment and material and (C) rapid restoration time respectively (as indicated by the flow direction of the arrows). In addition, the typology shows the discourse regarding boundary conditions between response to break down or crisis management resilience and prevention, preparedness resilience characterised with societal resilience, joint operations etc in regards to critical infrastructure reliability and performance. Furthermore, the typology considers the issue of relevance of institutions and governance characterised with both rules and the actors operating at various levels to improve critical infrastructure resilience, particularly considering the plethora of unknown and ambiguous risks.

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Table 1: First attempt of systematizing existing resilience core concepts Disciplinary

Psychology

Ecology & Social-

approaches

Ecological Systems

/

(SES)

Engineering/critical infrastructure

Organization/

Agency-

Practical perspective

Practical perspective

Institution

based

( case study) UK Civil

(case study) U.S.

Theory

Modelling

Protection policy as defined by

Department of Homeland

the UK Civil Contingencies Act

Attributes

Definitions

2004 (CCA) -the capacity to choose a vital

-Capacity to persist within a

and

domain in the face of

authentic

life

(e.g.

Gail

2010),

change; resilience

-individuals

with

traumatic

no

stress

post

disorder

determines the persistence of relationships within a

-Resilience can be understood as the ability of the system to reduce the chances of a shock, to absorb if it occurs (abrupt

-Capacity to cope

-Using identical

-Resilience: "The ability of

with unanticipated

copies of the

the community, services,

dangers after they

individuals.

area or infrastructure to

have become

detect, prevent, and, if

manifest, learning to

necessary to withstand,

bounce back”

handle and recover from

(Wildavsky 1991,

disruptive challenges" (HM

77)

Government, 2005)

Security The ability of systems, infrastructures, government, business, and citizenry to resist, absorb, and recover from or adapt to an adverse

symptoms (PTSD) or exhibit one

system and is a measure of

symptom after a stress or shock

the ability of these systems

(terror attacks) (Bonanno et al.,

to absorb changes of state

2004),

variables, driving variables,

-ability to maintain and recover

and parameters, and still

-Capacity to

-Community Resilience:

Capacity of an organization to

emotional well-being (Ong et al.,

persist (Holling, 1973)

- A resilient system is one

maintain “positive

“Communities and

recognize threats and

2006),

-Capacities of a system to

that shows the following

adjustment under

individuals harnessing local

hazards and make

developmental outcomes despite

absorb disturbance and

(1) Reduced failure

challenging

resources and expertise to

adjustments that will improve

high

reorganize while undergoing

probabilities (2) Reduced

conditions such that

help themselves in an

future protection efforts and

change so as to still retain

consequences from

the organization

emergency, in a way that

risk reduction measures

stress(Werner, 1992),

essentially the same

failures (in terms of lives

emerges from those

complements the response

-

function, structure, identity

lost, damage, and

conditions

of the emergency services.”

and feedbacks (Walker et

negative economic and

strengthened and

(Cabinet Office, 2011)

significant sources of stress or

al., 2004)

social consequences) (3)

more resourceful

trauma( Fergus et al., 2005),

i) response to / capacity to

reduced time to recovery.

(Vogues and

- a process of overcoming the

absorb disturbance,

Bruneau, M. (2003):

Sutcliffe 2007,

negative

effects

ii) capacity to self-organize,

O’Rourke, (2007)

3476)

exposure,

coping

good risk

social

status

sustained

competence a

under

process

managing

of

and

negotiating, adapting

of

to

risk

successfully

with traumatic experiences, and avoiding

the

trajectories

associated

and to recover quickly after a shock (re-establish normal performance).

iii) capacity to learn and adapt

negative with

Resilience as a perspective

risks(Garmezy 1984, Luthar and

to analyse SES (Folke,

Ciccchetti

2006; Parry et al., 2007)

2000,

reduction of performance),

Masten

and

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occurrence that may cause harm, destruction, or loss of national significance

(DHS Risk Lexicon, 2008)

Powell

2003,

Rutter

1985,

Werner 1992).

Goal

-To ensure psychological well-

Framing:

-To ensure critical

-Enhance the

being and social and

Ecology (Holling, 1973) –

infrastructure security,

capacity of

occupational functioning, social

rather “descriptive” to

safe operations,

organization to deal

development and to facilitate

explain the state of

performance and reliability

with anticipated and

protective actions

(eco)system

unanticipated events

In the later development,

possibly exceeding

resilience is seen as a

their established

1) Confirming theoretical results of an ordinary differential equation 2) Guessing the time used to achieve an Equilibrium

perspective to analyse SES

routines and

3) Detecting

No clear description on

(a hybrid concept – including

procedures

possible

desirable state of return or

attractors.

trajectories in the reference

normative aspects)

Rather normative concept. Goal: Enhancing capabilities in all event phases to resist, absorb, and recover or adapt (risk reduction)

paper. Goal: Sustaining and developing To change along while maintaining persistence, learning (emphasizing feedbacks) and adapting, preparing for the unexpected System

-Individual, family, Organization

Dynamic, strongly coupled

-Single to complex

-Organizations and

and community

ecological and social

networks of CI

networks of

systems

-Several

-National Resilience framework

organizations

Critical (infrastructure/economic) systems, society

Both systems should be treated equally Need further incorporation of agents and power relations (in social systems) Scale

-Individual, family, Organization

Cross-scale interaction in

and community groups

the complex system

Disturbance

-Traumatic life events, ,

pressures from

/event

terrorism, war, ,technological

environmental and human

-National –regional -global

-Individual to

-One scaled per

-: National; Local Resilience

organizational

loop.

Forum; ‘community’

-Terrorism, natural

-Could be any

-The evaluation

-CCA-defined “Emergencies”

hazards, cyber attacks

unexpected event

might have to

(i.e. natural, technological

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Stakeholders at all levels, both public and private Terorrism, pandemic, natural

and natural disasters

activities, global

such as discrete

use virtual

hazards and/or civil threats

environmental change,

errors, scandals,

overlay multi

e.g. crisis or disturbance;

“surprise” / unexpected

crises, and shocks,

agents

terrorism). Hazards and

and disruptions of

threats determined at two

routines as well as

principal scales: national

ongoing risks (e.g.

(i.e. National Risk Register)

competition),

and Local Resilience Forum

stresses and strain

(i.e. Community Risk

(Vogues and

Register)

disasters

Sutcliffe 2007, 3476) Mechanisms

Developing protective factors

Before: (social) learning

-Critical Infrastructure

to achieve

and processes.

capacity, anticipatory and

need to be

resilience

Personnel level

reflective learning, detect

(1) Robust (2) redundant

problems, early warning and

(3) resourceful, and (4)

responses, to cooperate,

capable of rapid response

learn, and apply the lessons

with respect to the four

toward continued resilience

interrelated components

under future conditions,

i.e. economic, social,

innovation

organisation, and technical

After: release and

-Response to break down

-Centralized vs.

internal to LRF);

reorganization, system

or crisis management

decentralization

Communicating with the

memory

resilience

-

Perseverance Balance and harmony Self Reliance Existential aloneness Positive Emotions Self –efficacy Sense of community Communication Problem Solving Confidence Trust Autonomy Support Systems Positive Thinking

-Prevention, preparedness

Family Level

resilience characterised

Emotionalities

with societal resilience,

Communication

joint operations etc in

Support

- Institutional and

Closeness

governance aspects.

Adaptability

-Sense-making, improvisation, brickolage, mistake orientation, structural flexibility, redundancy or slack, high-performance relationships, and mindfulness.

-Poly-centricmultilayered, organization, institutions and architectures -Mix-institutional approaches (formal & informal)

Organisation Level -

Positive Command Env

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-Point of

-Law: i.e. Seven statutory

attraction or

civil protection duties under

steady state

the Civil Contingencies Act (2004) for defined responder agencies (i.e. Co-operation and information sharing; Risk Assessment; Emergency Planning; Business Continuity Management (BCM) (i.e.

public; Advice to business(i.e. BCM external to LRF)) . All to be achieved through a process of Integrated Emergency Management (IEM)

Threat and hazard limitation Robustness Consequence mitigation Adaptability Risk-informed planning Risk-informed investment Harmonization of purposes Comprehensiveness of scope

-

Teamwork

Community Level -

Cohesion Belonginess Connectedness Collective efficacy Empowerment Assess Social justice Equity

-Facilitating social and individual resources, empowerment, building social support and networks. Also combating some hindering factors like denial, optimistic bias and fatalism -Resilience is also assumed to be indirectly achieved by preparedness and actions; it entails risk perception, stakeholder perceptions and protective action perceptions. Mode of

-Mostly of qualitative

http://www.resalliance.org/i

-Vulnerability assessment

-Rather qualitative

-Numerical

-UK Capabilities Programme:

Quantitative analysis

assessment

assessments

ndex.php/resilience_assess

for individual and

assessment, though

simulation

http://www.cabinetoffice.go

(mathematical function) to

-Individual level

ment

connected systems

some form of

v.uk/content/capabilities-

develop resilience profile of a

scales/questionnaires, narratives

combination of quantitative

-Mathematical model

quantitative simple

programme

system

from in-depth interviews with

and qualitative assessment

simulations,

quantitative

4 Structural work streams;

key informants, focus groups

of various factors involved in

- The quantification and

assessments are

12 Functional work streams;

with community members and

the system, by means of

measurement of CI

also possible (cf.

6 essential services work

experts.

conceptual framework

resilience in all its

Weick and Sutcliffe

streams

-Telephone interviews for large

(adaptive cycle, panarchy) –

interrelated dimensions is

2007).

population based research -

better overview to assess

a difficult task (Bruneau et

Longitudinal and cross-section

trade-offs between different

al., 2003).

assessments

alternative measures, developing visions and scenarios

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6.0 Resilience Modeling Methods By Jan Wolfertz This final section provides a brief overview on the mathematical methods used to model resilience. Some advantages and disadvantages of the methods are also outlined. Table 2 summarizes twelve modeling methods which include, for example, linear model approximation, ordinary and partial differential equation, bifurcation, and general moment method to finite elements. It also describes the: (1) frequency of use of each respective model (2) additional remarks for each model (3) example of model use (4) time and spatial scale of model (5) and computation speed of models. When data collection is very expensive existing datasets tend to be used. One might think of these as ‘ordinary’ data such as income classes or school grade. Since data is often limited only direct influences have been investigated. All these methods employed are based on linear models or linear approximation. It is underlined that the methods are well known, even if they require interpretation of common distances methods for grouping like principle component analysis (PCA) or central clustering (k-means clustering) or self organizing maps. The drought resilience index is one example (Keil et al., 2007). Whenever one believe to know some inner rule of this system that simplify all the data there are methods to proof how accurate this simplification works For instance, from time series analysis in ecology in the case of carbon dioxide uptake, the idea is to calculate a function out of the changes between those data points in order to get better prediction. The changes refer to a derivation of the function we are examining for. The theory in mathematics is called ordinary differential equations or functions (ODE/ODF). Imagine a plant using different substances for plant growth. If only some substances can be human controlled this leads to ordinary partial derivation equation or function (Herman and Soetaert, 2009). This might be called partial differential equation/function (PDE/PDF). In this context, imagine two different processes one being very slow and one very fast. The fast one might be guessed by ODF and the slow one might be thought as temporary constant. When tipping water out of a bottle the flow will increase if the bottle turns horizontal. However, short before the bottle turn horizontal the flow changes because the air could not enter the bottle whilst the water is leaving. So even temporary constant, for such as the angle of the water bottle, might change the whole system. Those systems are an example of bifurcation. However the real computational problem is to find a simple function explaining the measured data in that way. One of the methods used to compute such a function is called “general method of moments” (gmm). In order to get a quick and more meaningful result the assumed function should fit the data and the expected error of prediction should be zero and the variance should also be minimal. In that case, it is not only the error distance is minimized but also other conditions. However the existence follows some mathematical theorems and also some necessary conditions (Chausse, 2011). All those methods mentioned above handle a system spatial invariant. To handle different spatial effects, other methods developed by theoretical informatics can be used. This method is called “cellular automata”. The space is covered by neighborhoods. Imagine you are an ant. The neighborhood is the range you may notice. There are several rules how an ant behaves. Those rules are the same for all ants. For example if you identify food, you will get it unless already you are already carrying something. The more rules you use the more precise the result will be but the more precise data you will

48 | P a g e

need. If you are using less accurate data, and more ants it will lead to acceptable results (Weimar, 20039; Schonert et al., 2006). Inspired from cellular automata a different approach has been developed. Those methods need less theoretical background and understanding of the subjects to simulate, but need much more time on a computer (“To be computational expensive”). Those methods are called multi-agent methods. In this model it is possible to calculate how long it takes to reach a result. For example it might be optimized to find the shortest way from the ant’s home to a candy just by counting how often a route is used and updating each ant’s information when passing home, because ants using shorter ways will more often pass ant home. This algorithm isvery robust when moving the candy a little bit (Theodore, 2011). Agent based modeling allows for different groups of ants. However a stable result is not guaranteed. This model has been widely used. However to evaluate the result is very complicated because a calculation should run several hundred times (Axtell, 2011). To evaluate the result and counting all as severe assumed violation, e.g. income below minimum subsistence level, “virtual overlay model agents” (VOMAS) has been developed (Niazi and Hussain, 2009). On the other hand, fuzzy logic describes a less precise probability. The way how to calculate these values would take too long. It is proved in a way that the rules of topology hold. This is observed in the case of the intersection and union of cycles without boundary in a plane. It is applied either for storing “experience information”, or to theoretically recalculate the single influence from a change of the final output, the so called “defuzzification”. In this assumption the change of the result is most likely calculated backwards to the virtual change of the input data (Schonert et al., 2006). Fractal geometry describes changes of attractors of infinite often applied functions. The self similarity dimension can be used to detect repeating images. There are some connections to solvable genetic algorithms (GA).Those facts show invariant relations. For instance, genetics algorithm simulates methods from population genetics to optimize a function. In contrast, ‘simulated annealing’ works differently. One starting point is equally probable selected and ‘gradient descanting’ or ‘conjugated ascending’ calculation is used thereafter. With the probability, decreasing with the number of cycles in the program, the optimized value is not chosen and a new starting value is selected. This method assures a global optimum. Finite elements can be used to spatial extension of ODF. Similar regions are collected within local areas and under some conditions the resulting function of those local areas can be glued to the global one (Schonert et al., 2006). Bayes methods are used to get quicker results by reaching a better estimation when using the result before. It works well when the function is locally smooth and it does not change rapidly (Herman and Soetaert, 2009). Yet, it clearly needs to be stated that modelling has a much broader range of application for resilience research, which can be seen in a review of Schlüter et al. (in prep.) on contribution of modelling for this research field. The authors show that different model types and modeling applications are available for (1) enhancing the understanding of the resilience of social–ecological systems at different levels, (2) fostering inter- and transdisciplinary knowledge integration which is indispensable for detecting appropriated adaptation strategies and (3) supporting participatory processes for transformation. Two examples out of this range of model types and applications are: Firstly toy models (also named stylized models) in which purposefully only a very simplified set of variables and

49 | P a g e

processes with respect to the research question is incorporated. They can be used to support thought experiments in interdisciplinary communication and serve as “virtual labs” for rapid hypothesis testing of new adaptation strategies (Seppelt et al. 2009). Secondly participatory modeling approaches are appropriate for stakeholder involvement in supporting collaborative problem framing and social learning (Voinov & Bousquet, 2010). We would also like to mention that complex systems modeling and simulation (e.g., CosMOS12) software is participatory between modelers and domain experts. It is iterative, but any resulting ad-hock simulation is very fast (Forrester personnel communication 27 March, 2012).

Critical Infrastructure modeling: Interdependencies can also be investigated using expert interviews. Scenarios are modeled using agent-based systems (Willingham et al., 2009). Self regulating power management in Belgium is realized by using the physical unit as agents and a VOMAS to dynamically create larger groups of similar units. Two different layers of VOMAS are used to balance the energy within a group and to minimize the costs by attempting to balance the cost weighted groups of level 2(Rigole et al., 2008).A different project tried to indentify critical nodes in the power grid using graphic analysis. Some scenarios of the physical failures of some units where modeled using agent based modeling (Sansavini et al., 2008). In the context of health infrastructure it has been tested by assuming some known interactions as graphs and modeling some requirements for scenarios measuring the flow speed (Hirsch, 2004).

12

http://www.cosmos-research.org/ and also http://weadapt.org/knowledge-base/adaptation-decision-

making/whole-decision-network-analysis-for-coastal-ecosystems)

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Table 2: Summary of Modeling Methods Abr. Lin. Aprox. (e.g Keil et al., 2007).

Name Linear aproximation

Frequency of use Method to describe multiple linear dependencies. This is mostly used for ordinary or survey data. It can also be applied to a local linear approximation of a function.

Remarks Regression, Principal component analysis, confirmatory factor analysis,k-means clustering, self organizing maps.. If more ODF are used one has to ensure that the process is spatially independent and a unique solution exist. Explain un-returnable changes when a dynamic system is changed by a slow parameter A numerical stable methods by referring conditions on the deviation by additional equations Same rules, several Neighborhoods.

Example HDI indicator. DRI indicator

Time scale Assuming all data to be at equal time it is time independent

Spatial scale None

Computation speed Quick

ODE/ODF PDE/PDF (E.g. Herman and Soetaert, 2009).

Ordinary /Partial differential equation or function

Estimate a whole or partial process by measuring the changes

Fluid dynamic, ground water flow. Cell metabolism.

Mostly fast changing processes.

None

If a numerical solution is not fast enough, a closed solution such as a linear equation can be used

BF (E.g. Hansjörg Kielhöfer, 2012)

Bifurcation

Slow onset variable and fast onset variable that interact.

Budworm

Slow for the nutrition in the deposit. Fast for the Budworm population Equal in time

None, everything is assumed as equal.

In a smooth region, it is locally very fast, however if the bifurcation points are close the robustness might be a problem Easy if a local optimum is sufficient. If not restart versions are available.(No guaranty)

GMM (e.g. Chausse, 2011)

General moment method

Estimating an unknown function out of measured points.

CA (e.g. Weimar, 20039; Schonert et al., 2006). ABM (e.g. Axtell, 2011)

Cellular automata

Handle locally similar processes.

None

Very locally assuming the world to be coverable.

Very fast.

Agent Based Modeling

Different groups of agents by simulating some actions.

The existence of a solution or the uniqueness should be thought before.

Time refer to each to the number of circle until the algorithm terminate

None.

Multi Agent Model

Simulation by repeating and common updated results table.

Is robust and fast for small target changes

The Nash equilibrium, Swarm in medical modeling. Evaluating a MAM. Ant algorithm.

If the agents do change with a local parameter. It is mostly spatial invariant.

VOMAS (e.g. Niazi and Hussain, 2009).

Virtual overlay model agent system

Evaluating the results of agents.

FL (E.g. Schonert et al., 2006). FG

Fuzzy logic

Experience storage. Backwards calculation for result perturbation. Using the invariance of self similarity processes to identify unchangeable relations.

Also used for coordinating local agent networks in energy industry. Link CA back to FME.

Mostly time independent. The circle count of the updates may be taken as time equivalent. Not handled by VOMAS itself.

Takes very long and uses much storage. Graphic processor Computing can be used to run PCs. Depending on the agents function. The algorithm converges very fast.

MAM

NONE

NONE

NONE

NONE

Medium. Convergence is not insured in all cases.

VAR (E.g. Hansjörg Kielhöfer, 2010) FEM (E.g. Schonert et al., 2006).

Calculus of variations

Finding shortest way using different speed flows.

Sensitivity of ODEparameter

Finite elements method

Calculation forces along small triangle or octahedrons.

Local Areas where ODP can be solved.

Yes, using different resolution

Fasten algorithm.

Low sum of residuals and expected error of zero and minimal variance Traffic, Plant growth at the river bank.

(E.g. Theodore, 2011).

Fractal Geometry

Energy security. Critical infrastructure. Model influence from plant growth to river velocity. Special Traffic problems. Fractal image compression.

51 | P a g e

Few, but has to refer to additional equations on the searched distribution.

Depends on the agent definition. Mostly spatial invariant.

Algorithm is fast. Limiting factor are the agent function of the ABM below the VOMAS. Medium.

7.0 Preliminary Framing Questions for Case Study Research / Pillars of a Framework By Joern Birkmann, Denis Chang Seng, Jan Wolfertz and Neysa Setiadi, Christian Kuhlicke, Hugh Deeming and Maureen Fordham

-

How to frame the goals of the different conceptualizations of resilience, considering the purpose as well as the standpoint of the observers? Including scale and time frames as well as purpose and ideology, and accepting the same actor might have contradictory perspectives (e.g. play multiple roles) and/or be involved in trading-off e.g. resilience and transformation, or scales of action.

-

How to assess trade-offs between the "goal" of resilience, e.g. when might sustaining a status quo (absorbing the disturbance) be more appropriate than self-organization or than timely adaptation, or even allowing systems failure for transformation? This includes the consideration of the role of canonical and shadow systems in decision-making and in providing scope for adaptive experiments.

-

How to define the ideal balance between anticipatory and response strategies in light of performance and reliability? How to integrate resilience in the adaptive disaster risk management cycle? Important and related is to understand the costs and benefits of different phasing of acts within resilient systems – i.e. what system, etc. is allowed to fail, which is supported, which is open to transformation, the order of changes or stasis might then influence subsequent actors or perceptions of risk. The field of Cybernetics has made some headway in this.

-

How to pay more attention to the trade-offs between environmental services or ecological integrity and human outcomes?

-

How to position resilience among other objectives like performance, reliability, efficiency and equity (transparency) etc.?

-

What are the existing options to enhance resilience: rapid recovery options, foresight and timely adaptation, learning methods? Who are the groups that can make this happen, acknowledging that we are interested in sustainable processes of learning not simply capacity fixes.

-

How can we define appropriate systems for resilience analysis considering the positionality and priority that the emBRACE project will provide?

-

Which time-scale should be used in resilience analysis considering that emBRACE is? It is pointed out that case studies should help to draw such an answer. Overall the emBRACE project is interested in evolving levels of resilience over time to draw out the interplay of structure and agency (and

52

institutions) or is it following child psychology of interior and context conditions. -

How to measure identify internal stressors?

-

How to address the quantification and measurement of resilience in all its interrelated dimensions, i.e. economic, technical, social and organizational?

-

How to assess parameters which are not easily computable but have considerable contribution to resilience, e.g. social network, reflective capacity of organization / agency? How to address current gaps in psychological resilience research to include an examination of multi-disciplinary studies that examines dynamics of resilience across the lifespan and effectiveness of the different measures of resilience and programs? It is suggested that we should draw out the generic theory and transferable theory and then apply to our problem sets. For example psychology and emotions are a gap in terms of DRR research, so we would do well to extend analysis into this realm but we should be wary of trying to build a comprehensive theory of resilience. It is therefore necessary to draw out common lines and then explore how these have been conceptualised in the problem contexts of psychology, resource management, etc. There are already some useful points where work in one area shows gaps in another and these should be strongly emphasised in developing the analytical framework for the case study work.

-

-

How to include and factor in the institutional and governance context to any resilience framework/s?

-

How cultural-specific is resilience? This includes organizational culture as well as ‘national’ culture.

-

How to understand the interplay between emotion and knowledge in framing resilience seeking behaviour

-

The discussion so far has revolved around object, system, discipline (e.g. SES, Psychology, Critical Infrastructure) and there is still a need to move forward in order to evaluate the “moving elements” and “theoretical parts and pillars” (e.g. adaptive capacities, redundancy, robustness), which support these respective interpretations and usages o How to develop such understandings will be fundamental in defining how the work will be taken forward and, therefore, needs early consideration

-

It is vital to have an overview of multi-disciplinary concepts. However, it is also important to understand and to report if and in what context/s concepts have become hybridised as they have entered into practice o This issue may resolve itself during the closer review of the policy and grey that will occur during case-study development (WP5)

-

How can we clarify a definition from various perspectives of resilience in order to inform research, policy, and practice? Empirical research suggests that recovery or growth is different from resilience. Should emBRACE consider these pathways in its analysis?

53 | P a g e

-

Is disaster preparedness both a direct predictor of resilience and a mediator between the aforementioned psychological variables (e.g., personality) and a resilient outcome?

-

In order to apply any resilience concept/s or framework/s to communities in Europe, what do we need to understand in relation to what the term ‘community’ actually represents?

-

How is resilience framed by disaster managers (broadly understood) and what does that framing mean in terms of their expectations of communities before, during and after extreme events? o To what extent does their framing of resilience align with or differ from framings made by community groups or elites?

-

How is social capital understood to influence community resilience (e.g. in terms of the bonding, bridging and linking within and between communities)? o Is there recognition of the negative as well as the positive benefits of social capital, especially for those who are resource poor?

-

Beyond social capital, what are the contributions of other capitals, assets or resources in building community resilience? These are questions to be examined further during the empirical studies.

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8.0 Reference List Social-Ecological Resilience Adger, W. (2000). Social and ecological resilience: are they related? Progress in Human Geography , 24(3), 347–364. Adger, W. (2003). Social Capital, Collective Action and Adaptation to Climate Change. Economic Geography , 79(4), 387-404. Adger, W., & O’Riordan, T. (2000). Environmental Science for Environmental Management. In T. O’Riordan (Ed.). Prentice-Hall, Essex, UK,. Adger, W., Kelly, M., & Ninh, N. (2001). Living with Environmental Change: Social Vulnerability, Adaptation, and Resilience in Vietnam. Routledge, London. Baral, N., Stern, M., & Heinen, J. (2010). Growth, Collapse, and Reorganization of the Annapurna Conservation Area, Nepal: an Analysis of Institutional Resilience. Ecology and Society , 15(3):10. Barnett, J. (2001). Adapting to Climate Change in Pacific Island Countries: The Problem of Uncertainty. World Development , 29(6), 977-993. Baskerville, G. (1988). Redevelopment of a degraded ecosystem. Ambio , 17, 314–322. Berkes, F., Colding, J., & Folke, C. (2003). Navigating Social-Ecological Systems: Building Resilience for Complexity and Change. In F. Berkes, J. Colding, & C. Folke (Eds.). Cambridge University Press. Birkmann, J. (2011). First- and second-order adaptation to natural hazards and extreme events in the context of climate change. Natural Hazards . Bohle, H., Etzold, B., & Keck, M. (2009). Resilience as Agency. IHDP Update , 2, 8-13. Boin, A., Comfort, L., & Demchak, C. (2010). Designing Resilience. Preparing for Extreme Events. In L. Comfort, A. Boin, & C. Demchak (Eds.). University of Pittsburgh Press, Pittsburgh. Brand, F., & Jax, K. (2007). Focusing the Meaning(s) of Resilience: Resilience as a Descriptive Concept and a Boundary Object. Ecology and Society , 12(1): 23. Brown, K. (2011). Lost in Translation? Resilience ideas in international development. Lost in Translation? Resilience ideas in international development . Carpenter, S. R., Folke, C., Scheffer, M., & Westley, F. (2009). Resilience: accounting for the noncomputable. Ecology and Society 14(1) , 14(1):13. Clark, W., & Munn, R. (Eds.). (1986). Sustainable Development of the Biosphere. Cambridge University Press, London.

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Clark, W., Jager, J., van Eijndhoven, J., & Dickson, N. (2001). Learning to Manage Global Environmental Risks: A Comparative History of Social Responses to Climate Change, Ozone Depletion, and Acid Rain. MIT Press, Cambridge, MA. Costanza, R., Waigner, L., Folke, C., & Mäler, K.-G. (1993). Modelling complex ecological economic systems: towards an evolutionary dynamic understanding of people and nature. BioScience , 43, 545555. DHS. (2009). Concept Development: An Operational Framework for Resilience. Prepared for Department of Homeland Security Science and Technology Directorate. Concept Development: An Operational Framework for Resilience. Prepared for Department of Homeland Security Science and Technology Directorate . DHS. (2008). DHS Risk Lexicon. Department of Homeland Security. DHS. (2008). Top Ten Challenges Facing the Next Secretary of Homeland Security. Department of Homeland Security. Edwards, C., & Regier, H. (Eds.). (1990). An ecosystem approach to the integrity of the Great Lakes in turbulent times. Great Lakes Fishery Commission Special publication 90-4. Folke, C. (2006). Resilience: The emergence of a perspective for social–ecological systems analyses. Global Environmental Change , 16, 253-267. Gallopin, G. (2003). A Systems Approach to Sustainability and Sustainable Development. United Nations Publications, Santiago, Chile. Garschagen, M. (2010). Crises Prevention and Climate Change Adaptation in the Coupled SocialEcological Systems of the Mekong Delta, Vietnam: The Need for Rethinking Concepts and Policies. UNU-EHS SOURCE Publication Series , 13/2010, 45-55. Garschagen, M. (2011). Resilience and organisational institutionalism from a cross-cultural perspective: an exploration based on urban climate change adaptation in Vietnam. Natural Hazards . Garschagen, M., Renaud, F., & Birkmann, J. (2010). Dynamic Resilience of Peri-Urban Agriculture in the Mekong Delta Under Pressures of Climate Change and Socio-Economic Transformation.International Conference on Environmental Change, Agricultural Sustainability, and Economic Development in the Mekong Delta of Vietnam, 25-27 March 2010, Can Tho. Gunderson, L. (2010). Ecological and human community resilience in response to natural disasters. Ecology and Society , 15(2): 18. Gunderson, L. (2000). Resilience in theory and practice. Annual Review of Ecology and Systematics , 31, 425–439.

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Gunderson, L., & Holling, C. (Eds.). (2002). Panarchy: Understanding Transformations in Systems of Human and Nature. Columbia University Press, New York. Gunderson, L., Holling, C., & Light, S. (Eds.). (1995). Barriers and Bridges to the Renewal of Ecosystems and Institutions. Columbia University Press, New York. Holland, J. (1996). Hidden Order: How Adaptation Builds Complexity. Addison-Wesley Publishing Co. Holling, C. (1996). Engineering within ecological constraints. In P. Schulze (Ed.). National Academy, Washington, D.C., USA. Holling, C. (1961). Principles of insect predation. Annual Review of Entomology , 6, 163–182. Holling, C. (1973). Resilience and stability of ecological systems. Annual Review of Ecology and Systematics , 4, 1–23. Holling, C. (1986). Sustainable Development of the Biosphere. In W. Clark, & R. Munn (Eds.). Cambridge University Press. Hutter, G., Kuhlicke, C., Glade, T., & Felgentreff, C. (2011). Natural hazards and resilience: exploring institutional and organizational dimensions of social resilience. Natural Hazards . Kasperson, J., Kasperson, R., & Turner, II B. (Eds.). (1995). Regions at Risk: Comparisons of Threatened Environments. United Nations University Press, New York. Kates, R., & Clark, W. (1996). Expecting the unexpected. Environment , 6–11, 28–34. Kates, R., Clark, W., Corell, R., Hall, J., Jaeger, C., Lowe, I., et al. (2001). Environment and development: sustainability science. Science , 292, 641–642. Kauffmann, S. (1993). The Origins of Order. Oxford University Press, New York. Kay, J. (1991). A nonequilibrium thermodynamic framework for discussing ecosystem integrity. Environmental Management , 15, 483–495. Kay, J., Regier, H., Boyle, M., & Francis, G. (1999). An ecosystem approach for sustainability: addressing the challenge of complexity. Futures , 31, 721–742. Klein, R., R., N., & Thomalla, F. (2003). Resilience to natural hazards: how useful is this concept? Environmental Hazards , 5(1–2), 35–45. Kuhlicke, C. (2010). Resilience: a capacity and a myth: findings from an in-depth case study in disaster management research. Natural Hazards . Lebel, L., Anderies, J., Campbell, B., Folke, C., Hatfield-Dodds, S., Hughes, T., et al. (2006). Governance and the capacity to manage resilience in regional social-ecological systems. Ecology and Society , 11(1):19.

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This study has been funded by the th

European Commission on the 7 Framework Programme

Centre for Research on the Epidemiology of Disasters (CRED) Catholic University of Louvain School of Public Health 30.94 Clos Chapelle-aux-Champs 1200 Brussels, Belgium T: +32 (0)2 7643327 F: +32 (0)2 7643441 E: [email protected] W: http://www.cred.be

Northumbria University School of the Built and Natural Environment, Newcastle upon Tyne NE1 8ST, UK

T: + 44 (0)191 232 6002 W: www.northumbria.ac.uk

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