Community Resilience to Climate Change Theory, Research Section III Identifying & Evaluating Resilience

SECTION III IDENTIFYING EVALUATING RESILIENCE for measuring assessing resilience Case studies using different approaches to identify indicators 88 Identifying Evaluating Resilience Considering the difficulty in pinning down an agreeable interpretation of resilience , choosing the best metrics for evaluating it can also pose a challenge . After all , how can you evaluate the state of something when you are not completely sure what you are looking for ?

Still , it is often important to measure ( quantitatively ) or assess ( qualitatively ) resilience in order a particular plan of action , or to determine the effects of a past effort . There are no universal indicators of resilience that is , the specific system features targeted for evaluation . They are chosen ad hoc by the researcher , based on the research at hand , and often have to do with her theoretical or disciplinary leanings . For example , an ecologist may judge the resilience of an urban wetland system by its function and presence of biodiversity an urban planner may consider flooding and infrastructure damage within the same system . Similarly , an engineer may consider a city resilient to extreme heat if roads can withstand high temperatures a public health official may emphasize access to air conditioned space for vulnerable populations . Depending on one perspective and interests , framing and methods will vary . This section provides multiple case studies in which researchers sought to frame , identify ( via a series of chosen indicators ) and assess or measure resilience . Methods range from quantitative to qualitative indicators from general to local . The cases come from both the global north and south , address numerous hazards , and frame resilience in terms of economic prosperity , food security , vulnerability , adaptation , and more . The purpose is not to advance one methodological framework for identifying and evaluating resilience all have their advantages and disadvantages but to offer some potential avenues that you might take . Remember , resilience is a flexible concept , and different situations may call for different approaches to evaluating it . However , it is always helpful to clarify the following details before undertaking an evaluation I want to evaluate the resilience of to 89

READINGS INCLUDED Open access articles Full text included , Deeming , Forrester , 201 ) community resilience to natural hazards the emBRACE framework . Natural Hazards and Earth System Sciences , 17 ( 12 ) 2321 , Kind , Kaiser , 2019 ) Indicators for monitoring urban climate change resilience and adaptation . Sustainability , 11 ( 10 ) Jones , 2018 ) Subjective measures of household resilience to climate variability and change Insights from a nationally representative survey of . Ecology and Society , 23 ( James , 2013 ) Measuring household resilience to floods A case study in the Vietnamese River Delta . Ecology and Society , 18 ( 2018 ) Assessing Vulnerability to Urban Heat A Study of Disproportionate Heat Exposure and Access to Refuge by Status in Portland , Oregon . International Journal of Environmental Research and Public Health , 15 ( ALTERNATIVE SELECTIONS Full text not included May be accessible through your university or elsewhere , 2019 ) Mapping urban resilience for spatial first attempt to measure the vulnerability of the system . 11 ( 2331 . Shaw , 2015 ) An indicator based approach to assess coastal communities resilience against climate related disasters in Indian . Journal of Coastal Conservation , 19 ( 2016 ) Assessing the resilience of a system lessons from a evaluation of a South African pastoral system . Ecology and Society , 21 ( Quinlan , Peterson , 2016 ) Measuring and assessing resilience Broadening understanding through multiple disciplinary perspectives . Journal of Applied Ecology , 53 ( van , 2017 ) Chapter resilience through understanding vulnerability . In . Building a climate resilient economy and society ( MA Edward Publishing . 90

STUDENT EXERCISES To be completed after assigned reading ( Select a podcast ( 60 minutes or less ) and listen to an episode of your choice . Some relevant podcasts you might explore Climate One America Adapts Climate Connections ( Now , consider what you have read and heard . As a practitioner attempting to identify or evaluate climate resilience , what approach might you use and why ?

You can choose from approaches presented in readings podcasts , or propose your own . What do you think is the relationship between RESILIENCE and VULNERABILITY ?

Is evaluating VULNERABILITY equivalent to evaluating RESILIENCE ?

instructors We suggest that students be given the opportunity to read each other is responses prior to class . This will alleviate the need for students to summarize for each other what they have written , and leave more class time for deeper , exploratory discussions . FOR INSTRUCTORS CLASSROOM ACTIVITIES ( Provide or real world climate change scenario include location , key actors , concerns , outcomes , and other relevant details . Discussion Prompt Within the context of this scenario , what would you identify as resilience INDICATORS ?

How would you go about assessing ( qualitative ) or measuring ( quantitative ) resilience in this case ?

Why ?

91 Community Resilience to Natural Hazards emBRACE Framework by Sylvia , Thomas , Hugh Deeming , Maureen , John Forrester , Sebastian , Christian , Mark , Lydia and Stefan This article was originally published in System Sciences , 17 ( 12 ) 201 This work is licensed under a Creative Commons Attribution ( BY US ) license ABSTRACT The level of community is considered to be vital for building disaster resilience . Yet , community resilience as a scientific concept often remains vaguely defined and lacks the guiding characteristics necessary for analysing and enhancing resilience on the ground . The emBRACE framework of community resilience presented in this paper provides a heuristic analytical tool for understanding , explaining and measuring community resilience to natural hazards . It was developed in an iterative process building on existing scholarly debates , on empirical case study work in five countries and on participatory consultation with community stakeholders where the framework was applied and in different and for different hazard types . The framework resilience across three core domains ( i ) resources and capacities , ii ) actions and ( iii ) learning . These three domains are as intrinsically conjoined within a whole . Community resilience is influenced by these integral elements as well as by forces comprising disaster risk governance and thus laws , policies and responsibilities on the one hand and on the other , the general societal context , natural and disturbances and system change over time . The framework is a graphically rendered heuristic , which through application can assist in guiding the assessment of community resilience in a systematic way and identifying key drivers and barriers of resilience that affect any particular community . INTRODUCTION Community resilience has become an important concept for characterizing and measuring the abilities of populations to anticipate , absorb , accommodate or recover from the effects of a hazardous event in a timely and efficient manner ( Patel et , 2017 , 2013 and Ross , 2013 Deeming et , 2011 Walker and , 2011 ) This goes beyond a purely systems understanding of resilience ( Armitage et , by incorporating social subjective factors , perceptions and beliefs as well as the wider institutional environment and governance settings that shape the capacities of communities to build resilience ( and Harvey , 2015 , 2005 , 1999 ) Many conceptual and empirical studies have shown that the community level is an important scale on which to build resilience that can enhance both the and wider population level outcomes ( et , 1998 Cote and Nightingale , 2012 Nelson et , 2007 Ross and , 2011 ) Yet , the community remains poorly theorized with little guidance on how to measure resilience building processes and outcomes . Both terms resilience and community incorporate an inherent vagueness combined with a positive linguistic bias and are used with increasing frequency both on their own as well as in combination ( Patel et , 2017 Mulligan et , 2016 Brand and Jax , 2007 , 2012 et , 2011 ) Both terms raise , as Norris et al . 2008 ) put it , the same concerns with variations in meaning . In resilience research we can detect a disparity whereby the focus of research has often lain at either the larger geographical scales ( regions ) or , as in psychological research , at the level of the individual , extending to households ( Ross and , 2014 , 2005 ) Across these scales and sites of interest , resilience is consistently understood as relational . It is an property of and technological systems with individuals and their imaginations . As a relational feature , resilience is both held in and produced through social interactions . Arguably , the most intense interactions that are of direct relevance to those at risk are at the local level , including the influence of actors and institutions . It is in this space that the community becomes integral to resilience and a crucial level of analysis for resilience research ( Cutter et , 2008 Walker and , 2011 and , 2006 ) The idea of community comprises groups of actors ( individuals , organizations , businesses ) which share a common identity or interest . Communities can have a spatial expression with geographic boundaries and a common identity or shared fate ( Norris et , Following the approach of Mulligan et al . 2016 ) we propose to apply a dynamic and understanding of community , including community as a concept ( inhabitants neighbourhood ) as and communicative community within a spatially extended network ( members of crisis management in a region ) as an imagined community of individuals who may never have contact with each other but who share an identity or interest . 92

Considering the conceptual vagueness and variations of community and resilience , only afew approaches have tried to characterize and measure community resilience comprehensively ( Cutter et , 2014 et , 2010 Mulligan et , 2016 ) Thus , the aim of this paper is to further fill this gap and elaborate a coherent conceptual framework for the characterization and evaluation of community resilience to natural hazards by building both on a systems understanding of resilience and on an empirical , perspective specifically including the subjective variables and how they link to broader governance settings . The framework has been developed within the European research project in an iterative process building on existing scholarly debates and on empirical case study research in five countries ( Germany , Great Britain , Italy , Switzerland , Turkey ) using participatory consultation with community stakeholders , where the framework was applied and in different regional and cultural and for different hazard types . Further the framework served as a basis for guiding the assessment of community resilience on the ground . The paper is structured as follows the next section provides an overview of key themes and characteristics of conceptual on community resilience and identifies gaps and open questions in the current conceptual in the context of natural hazards . In Sect . we present the methodology for the development of the framework of community resilience . In Sect . A the emBRACE framework is introduced along its central elements and characteristics and illustrated by examples from the case study research . Section discusses the between the framework elements as well as the application and of the framework and reflects on the results , methodology and further research . CONCEPTUAL TENSIONS OF COMMUNITY IN DISASTER RESEARCH AND POLICY Both the concept of community and resilience are contested and this in different fields of research and policy . This chapter therefore does not aim at providing a comprehensive overview of different strands of research ( for more details see et , 2018 ) the ambition is rather to present a heuristic framework for understanding , explaining and assessing community resilience to natural hazards . Therefore , we present here central strands of research that influenced the development of the emBRACE framework of community resilience . Alexander etymological resilience journey ( 2013 ) shows that the word looks back on a long history of multiple , interconnected meanings in art , literature , law , science and engineering . Some of the uses invoked a positive outcome or state of being , while others invoked a negative one . In synthesis , before the century , the core meaning was to bounce back ( 2710 ) However , since influential publication ( 1973 ) on Resilience and Stability of Ecological Systems the idea of restricting resilience above all to the ability of ecosystems to bounce back to a state and , by implication , assume a more or less stable environment , came under increasing pressure . Therefore , another of the tensions surrounding the concept of resilience in the context of disaster risk reduction concerns its relation to social change and transformation . A divide is emerging between those that propose resilience as an opportunity for social reform and transformation in the context of uncertainty ( and Tanner , 2014 Brown , 2011 et , 2011 and , 2013 , 2014 and , 2015 et , 2016 ) and those that argue for a restriction of the term to functional resistance and stability ( Smith and Stirling , 2010 Klein et , 2003 ) Limiting resilience to narrow interpretations of robust infrastructure would promote local disaster risk reduction that fails to address the need for social change and learning . of disaster resilience need to account for multiple entwined pressures , development processes , and climate change see et , 2015 ) to learn and adapt and to innovate existing risk management regimes on the community level . At the heart of this divide is the gradual translation of resilience from its firm base in the natural sciences to the social sciences , which brings with it a set of inherent ontological and epistemological challenges that become particularly prominent in discussions of community resilience . Rooted in ecology , resilience through the lens of Holling ( 1973 , 1996 ) emphasized the concept of ( multiple ) of systems in the face of disturbances . This focus on returning to or progressing towards stability domains laid the foundation for the bouncing back narrative that continues to shape resilience policy and discourses , particularly in the area of disaster risk management and emergency planning . When discussing resilience in the context of community , however , a range of questions arise that shed light on the difficulties of translating ideas from the natural to the social sciences . These concern , amongst others , the character of disturbances in social systems ( who gets disturbed by what or by whom ?

the intentionality of human action ( what role for purposeful interventions ?

the overarching goals of resilience ( what is desirable ?

challenges with system boundaries ( who is part of a social system ?

and the role of power ( who is empowered to act , participate , transform ) Besides the differences in scope of the definition between bouncing back and societal change , there is another tension about whether resilience is a normative , an analytical ora more descriptive concept ( 2014 Mulligan , 2016 ) While , early on , resilience was employed as a descriptive concept in ecology that attempted to integrate different notions of stability ( withstanding , recovering and persisting ) its thematic expansion to the analysis of systems goes hand in hand with a strong normative orientation or even prescriptive elements of how resilience ought to be organized ( Brand and Jax , 2007 ) which is also increasingly applied as a policy goal to promote disaster risk reduction at all scales ( United Nations Office for Disaster Risk Reduction , 2015 , 2007 ) The notion of resilience is meanwhile an integral element at the international policy level to both the Framework for Action and the Framework for Disaster Risk Reduction ( United Nations Office for Disaster Risk Reduction , 2015 , 2007 ) as well as to national and local 93

discourses on disaster risk reduction , in the UK National Community Resilience Programme ( National , 2012 ) or on the level of local authorities in the UK ( Jacobs and , 2017 Shaw , 2012 ) However , simply transplanting a descriptive concept established in ecology to a normative idea of how societies should be governed through resilience is not necessarily a step forward since there is the risk that the role of physical shocks is and the relevance of political economic factors ( Cote and Nightingale , Even if the systems approaches take into account political or economic factors , they tend to do this with a focus on functions and structures of institutions and tend to neglect the wider political , historical and cultural ( ibid ) As an implication , as Lewis and argue ( 2012 ) attempts to make communities more resilient can actually result in a contrary situation , as they put them in a less tenable situation . This arises because governance approaches have to be neglectful of social conflicts , inequalities and power ( and , 2008 , 2012 and , 2013 et , 2014 ) underestimate the relevance of social institutions and political struggle ( Hayward , 2013 , 2015 ) or be unheeding of the challenges associated with the idea of community participation ( and Tanner , 2014 et , 2013 ) In addition to underestimating the relevance of political and interpretational aspects , resilience itself is shaping the way disaster risk reduction is organised and how responsibilities between public and private actors are distributed . In the UK , for example , resilience is part of a agenda in which responsibility for disaster risk reduction is intentionally devolved from the national to the local level ( Department for Environment , Food and Rural Affairs , 201 Deeming et , This creates opportunities but is also contested and can provoke resistance by activists ( et , 2016 ) Despite this increasing critical engagement with resilience , the notion is here to stay ( Norris et , for the conceivable future , not only as a theoretical concept but also as a policy tool for promoting disaster risk reduction . As such , it will have direct implications for communities . Based on these arguments , we identify three gaps that characterize existing resilience and are related to conceptual challenges for a comprehensive community resilience framework . First , there seems to be insufficient consideration and reflection on the role of power , governance and political interests in resilience research . Secondly , many resilience still seem to fall short of exploring how resilience is shaped by the interaction of resources , actions and learning . Due to the conceptual influence of the Sustainable Livelihood Framework ( of some approaches ( Chambers and Conway , 1992 , 1998 Ashley and Carney , 1999 and , 2001 ) resilience concepts tend to be focused on resources but fail to systematically explore the interaction of resources with actions and learning and how understanding these variables might then usefully illustrate disparities in how social equity , capacity and sustainability ( key considerations of the approach see Chambers and Conway , 1992 ) manifest . Third , an explicit description of learning and change is largely absent in the literature that characterizes community resilience . So far , resilience as a theory of social change seems to remain rather vaguely specified ( Cote and Nightingale , 2012 ) A resilience framework which accounts for these conceptual challenges is necessarily focused on the prospects of social reform and incorporates many soft elements that are notoriously difficult to measure . We thus agree with the need to resilience ( Carpenter et , 2001 ) that existing framework measurements ( Cutter et , 2008 ) often fail to systematically include those challenges that we consider of critical importance for community resilience . FRAMEWORK DEVELOPMENT AND METHODS USED Developing an , and framework for characterizing and measuring the resilience of European communities calls for the application of a multifaceted approach that adopts methodological processes . Therefore , we applied a complementary research strategy with the purpose of investigating resilience on different scales , from different perspectives and by applying different research methods as well as integrating the viewpoints of distinct actors . The research team came from different disciplinary backgrounds and it was the intention that no single disciplinary approach would dominate . Rather , a democratic process of consensus building was employed to arrive at methods and outputs acceptable to all . A first strand of this research strategy included intensive structured literature reviews . The first sketch of the community resilience framework was informed by the early review the different disciplinary discussions on resilience into thematic areas . As the project continued , specialized literature reviews complemented this first review by focusing on different aspects of the emerging framework and considering more recent publications . Throughout the project , developments in the literature were closely monitored and literature reviews were continuously updated ( et , 2018 ) A second strand involved empirical case study research in five European countries investigating community resilience related to different hazard types on different scales . The five case studies comprised multiple Alpine hazards in South , Italy and , Switzerland earthquakes in Turkey in central Europe combined fluvial and pluvial floods in northern England and in London . A and quantitative were adopted in the case study research in order to develop community resilience framework . The outcomes of this research have been used to inform the conceptual framework at different stages of the development process and helped to illustrate how the framework can be applied and adapted to different hazard types , scales and socioeconomic and political ( et , 2016 et , 2016 et , 2015 , 2011 , Taylor 94

et , 2011 Deeming et , Ji ' A third strand saw three participatory workshops with stakeholders in case studies in , England Van , Turkey and , Germany in order to add the perspectives of different community stakeholders on the local and regional scales to the framework development . The aim of the participatory assessment workshops was to collect , validate and assess the local appropriateness and relevance of different dimensions of community resilience and indicators to measure them . With the selection of case studies in different countries and different types of communities , we took into account that different cultures and communities conceptualize and articulate resilience differently . The workshops allowed discussion with local and regional stakeholders about how resilience can be assessed . This was both a presentation and revalidation of the first results of the case study and involved working together with the stakeholders . It was also a starting point for further development of the framework . A fourth strand involved internal review processes with project partners as well as external experts on community resilience . THE emBRACE FRAMEWORK FOR CHARACTERIZING COMMUNITY RESILIENCE The emBRACE framework community resilience as a set of intertwined components in a framework . First , the core of community resilience comprises three interrelated domains that shape resilience within the community resources and capacities , actions and learning ( see Sect . These three domains are intrinsically conjoined . Further , these domains are embedded in two layers of processes and structures ( see Sect . first , in disaster risk governance which refers to laws , policies and responsibilities of different actors on multiple governance levels beyond the community level . It enables and supports regional , national and international civil protection practices and disaster risk management organizations . The second layer of processes and structures is influenced by broader social , economic , political and environmental context factors , by rapid or incremental changes of these factors over time and by disturbance . Together , the constitute the heuristic framework of community resilience ( see Fig . which through application can assist in defining the key drivers and barriers of resilience that affect any particular community within a population . Figure . The emBRACE framework for community resilience to natural hazards ( source own illustration ) Context change disturbance Disaster risk governance Laws , policies , responsibilities Actions Learning perception protection . Critical social i ' a ' Dissemination , Community resilience Resources and capacities lui Financial Physical 95

domains of resilience resources and capacities , action and learning Resources and capacities The capacities and resources of the community its members constitute the first domain of the core of resilience within the community . Informed by the Sustainable Livelihoods Approach ( SLA ) and its iterations ( Chambers and Conway , 1992 , 1998 Ashley and Carney , 1999 and , 2001 ) as well as the concept of adaptive capacities ( 2011 ) we differentiate five types of capacities and resources . This approach also addresses in parallel the need identified by Armitage et al . 2012 ) for material , relational and subjective variables as well as the subjective dimension of resilience ( see Sect . Natural and capacities and resources relate to the protection and development of ecosystem services . This includes but is not limited to the role of land , water , forests and fisheries , both in terms of for exploitation as well as more indirectly for personal of community members . resources can also refer to cultural heritage resources , to local public services , amenities and to the availability of access to obs and markets . capacities and resources for the importance of political , social and power dynamics and the capacity of community members to influence political . Here , institutions such as the rule of law , political participation and accountability of government actors are of critical importance . Participation in governance can be both formal , for example through elections and interest representation , and informal , for example empowerment and resistance in political . Therefore , power dynamics in community resilience include both empowerment and resistance as well as cooperation and learning ( related to the differentiation between power to and power with see , 2016 Allen , 1998 ) Therefore , structural social resources are also inherent within the structural and cognitive of social capital ( and , 2001 ) networks and trust . Social capital refers to lateral relationships between family , friends and informal networks but also to more formal membership in groups , which may involve aspects of institutionalization and hierarchy . Cognitively defined trust relationships can assist in collective action and and thus seem for the development and maintenance of community resilience ( and Yang , 2008 ) Operating within the framework disaster risk governance domain , however , it should be acknowledged that mutual relations as might be expressed between community members can be differentiated from trust in authority wherein hierarchical power differentials introduce an element of dependency to the relationship ( 1999 ) Financial capacities and resources refer to monetary aspects of disaster resilience . This includes earned income , pensions , savings , credit facilities , benefits and importantly access to insurance . The role of financial capacities raises questions about availability of and access to individual and public assets and about the distribution of wealth across social . The causal relationships that underpin the role of financial resources for community resources are not linear . Increases in available financial resources are not necessarily beneficial for community resilience , for example if income inequality is high and financial resources are concentrated in a very small and particular segment of society . Physical capacities and resources for community resilience include adequate housing , roads , water and sanitation systems , effective transport , communications and other infrastructure systems . This can also refer to the availability of and the access to premises and equipment for employment and for structural hazard mitigation ( both at household and community scales ) Finally , human capacities and resources focus at the individual level , integrating considerations such as gender , health and , education and skills and other factors affecting . Psychological factors are also accounted for here , including , belonging , previous hazard experience , coping capacities and awareness . These factors together can be understood to impact on individuals perceptions of risk and resilience but also as of the leadership that drives collective action . From the case study in Turkey , having good governance , specific disaster legislation , supervision of the implementation of legislation , coordination and cooperation , being a civic society , having mutual trust , having moral and cultural traditional values , etc . and human ( gender , income , education , personality characteristics ) resources and capacities were the most pronounced ( et , 2018 ) In one of the participatory workshops an earlier version of the framework was discussed with local stakeholders regarding the case study on flooding in northern England . It revealed that for the participants , and human capacities and resources were most important for characterizing their community resilience . Indicators measuring , for example , and as well as willingness to stay in the region and engage in associational activities were proposed to describe the degree of community spirit and solidarity that was considered to be crucial for their community resilience in a region that is threatened by population loss and demographic change . Actions Within the emBRACE framework , community resilience comprises two types of actions civil protection and social protection . The civil protection actions refer broadly to the phases of the disaster management cycle , preparedness , response , recovery and mitigation 96

( Alexander , 2005 ) which , despite longstanding academic critique ( et , 2002 Neal , 1997 ) are persistent in practice . Resilience actions undertaken by the community can be related to these phases ( weather forecasting and warning as preparedness action ) Accordingly , civil protection is focusing on hazard specific actions . We add to this social protection considerations , which include hazard independent resilience actions , measures of vulnerability reduction and building social safety nets ( see Fig . Social protection action includes diverse types of actions intended to provide community members with the resources necessary to improve their living standards to a point at which they are no longer dependent upon external sources of assistance ( Davies et , 2008 ) Social protection has been included as a main component because many resilience building actions can not be directly attributed to civil protection action but are instead concerned with the more general pursuit of and sustainability ( Davies et , 2013 et , 2009 ) For example , the presence of an active voluntary charity sector capable of providing social support ( food banks ) and funding for participatory community endeavours ( a community fund ) and which could be extended or expanded in times of acute , community need were found to factors that provide a certain level of security for all those affected by hazards , either directly or indirectly ( 2005 ) Such social protection measures are not , however , solely by the community and voluntary sector alone , so it is important to understand that these elements also relate to the much broader provision of welfare services ( health , education , housing , etc . which are ultimately the responsibility of national and local government . The inclusion of social protection as a main component of this domain therefore represents an important progression over some other , because it explicitly includes the consideration of how communities manifest resilience through their capacity to deal with and adapt to natural hazards but also their capacity to contribute equitably to reducing the wider risks faced some , if not all , of their membership . In a case study in northern England , social support mechanisms were particularly important across multiple communities ( from hill farmers to town dwellers ) in the aftermath of a flood event ( Deeming et , Key considerations were that , despite evidence of learning and adaption that had occurred between two floods in 2005 and 2009 , the sheer magnitude of the latter event effectively discounted the effects of any physical mitigation and protection measures that had been introduced . Where measures , such as community emergency planning , had been adopted there were significant improvements in the levels and successes of response activity . However , while these actions reduced some damage ( fewer vehicles flooded ) where properties were inundated significant damage still resulted . Accordingly , community champions emerged who were capable of advocating community outcomes and the need for community spaces ( groups or buildings where those affected could learn by sharing experiences and deliberating plans . They proved to be key in driving the recovery as well as the concurrently occurring future mitigation efforts . Much of the support in the aftermath of the flood events was coordinated by particular officers from the statutory authorities , whose normal roles and skills were social rather than civil protection orientated . This emphasised the importance of understanding resilience in framework terms as a process rather than as a simple measure of hazard response capability . Learning Learning is the third integral domain that shapes resilience in the emBRACE framework . We attempt to provide a detailed conceptualization of learning in the context of community resilience . We follow the notion of social learning that may lead to a number of social outcomes , acquired skills and knowledge building via collective and communicative learning ( Mum and Jeffrey , 2008 ) It occurs formally and informally , often in natural and unforced settings via conversation and mutual interest . Further , social learning is said to be most successful when the practice is spread from person to person ( Reed et , 2010 ) and embedded in social networks ( McCarthy et , 2011 ) In this understanding , social learning is an ongoing , adaptive process of knowledge creation that is from individuals through social interactions fostered by critical reflection and the synthesis of a variety of knowledge types that result in changes to social structures ( organizational mandates , policies , social norms ) and , 2015 ) Based on this understanding we social learning as consisting of different elements from the perception of risks or losses , its , to the critical reflection and in order to derive new knowledge which can be disseminated throughout and beyond the community , enabling resilience at a range of societal levels ( see Fig . The first element , risk and loss perception , is the ability of any actor , organization or institution to have awareness of future disaster risk or to feel the impact of a current or past hazard event . Awareness can be derived from scientific or other forms of knowledge . Second , the ability to problematize risk and loss arises once a threshold of risk tolerance has passed . A of risk manifests itself as the perception of an actor that potential or actual disaster losses or the current achieved ratio of risk management are inappropriate . This includes procedural and distributional justice concerns and has the potential to generate momentum for change . Third , critical reflection on the appropriateness of technology , values and governance frames can lead to a questioning of the social contract of the community . Critical reflection is proposed as a mechanism through which to make sense of what is being learned before applying it to thinking or actions . Fourth , experimentation and innovation refers to testing multiple approaches to solve a risk management problem in the knowledge that they will have variable individual levels of success . This can shift risk management to a new efficiency mode where experimentation is part of the cost of resilience and of risk reduction . In this context , innovation can be as processes that derive an original proposition for a risk management intervention . This can include importing knowledge from other places or policy areas as well as advances based on new information and knowledge generation . 97

Fifth , dissemination is integral for spreading ideas , practices , tools , techniques and values that have proven to meet risk management objectives across social and policy communities . Sixth and finally , monitoring and review refers to the existence of processes and capacity that can monitor the appropriateness of existing risk management regimes in anticipation of changing social and technological , environmental , policy and hazard and risk perception . The Turkish case study on earthquakes revealed that an earthquake experience in one region of the country led to learning , mostly by the state , to changes and to the adoption of new legislation and new organization for disaster management . This experience seemed to have very robust effects on attitudes towards disasters , changing the focus from disaster management to disaster risk management ( 2002 ) The same change process seemed to apply to individuals as well but to a smaller extent , in that an earthquake experience led to an increase in hazard awareness and preparedness ( as would be predicted based on classical hazards theory , 1971 ) The Italian case study in the Alpine village of focuses on the perception of risks and losses as one element of resilience learning . The findings reveal that , even though people living in have high risk awareness , many did not expect or prepare for an event . The interpretation of the different risk behaviour profiles shows that people who perceived themselves to be under risk of future landslide events had either personally experienced a landslide event in the past or participated in the work after the landslide event in 2012 . Results from comparing the two groups of inhabitants affected by the landslide event 2012 and not affected in 2012 point in the same direction , showing that personal experience , not only recent but also past experience , together with active involvement in the response phase , lead to a higher risk perception especially when thinking about the future ( et , 2018 ) framing of community resilience Disaster risk governance In the proposed characterization of community resilience with respect to natural hazards , the three core domains resources and capacities , actions and learning are embedded in two frames . The first frame is that of formal and informal disaster risk governance , which comprises laws , policies and responsibilities of disaster risk management at the local , regional , national and levels . From the case study research it became clear that community resilience and its constituent resources and capacities , action and learning processes are strongly interacting with existing formal and informal laws , policies and responsibilities of civil protection and risk management more generally ( flood mapping as per the German National Water Act and the EU Flood Directive ) Responsibilities relate to the actors and stakeholders involved in disaster risk management . The wider ideas of risk governance to the specific context of a community involves focus on the interaction between communities resources and capacities and actions as well as their learning processes . This is related to the specific framework by which responsibilities , modes of interaction and ways to participate in processes in disaster risk management are spelt out . The agendas in the two case studies in , England and , Germany may serve as an example . In both case studies community actions are being influenced by the agenda , which is encompassed , for example , within Making Space for Water strategy for Great Britain and water law in Germany , the latter of which obliges citizens to implement mitigation measures . This explicitly parallels Walker and call to push power down to the local community level where , and leadership in the face of disaster were more likely to occur if local governments felt accountable for their own responses ( 2011 Li ) The case study work showed that this not only relates to local governments ( et , 2015 et , 2016 ) but also to the individual citizens potentially affected by natural hazards ( et , 2016 ) More specifically , et al . 2016 ) found that if the physical and psychological consequences are perceived as being low with regard to their most recent flood experiences , then respondents tend to accept the attribution of responsibility towards individual citizens and also report higher response efficacy ( the respondents have the feeling they can reduce flood risk through their own actions ) if they have taken personal mitigation measures prior to the flood event . In addition , respondents who have taken personal mitigation measures are more likely to report higher response efficacy than those who have not taken such actions and also agree with the responsibility attributed to them . In other words , if respondents took personal mitigation measures before the flood and did not experience severe consequences as a result of the flood , they are likely to agree with statements which support citizen responsibility and report high response efficacy . This shows that resilience action and learning processes are always embedded in the broader formal and informal risk governance settings . Indirect context , change and disturbances As a second framing we consider three dimensions as influential boundary conditions for community resilience first the social , economic , political and environmental context second , social , economic , political and environmental change over time and third diverse types of disturbances . The first dimension of indirect boundary conditions for community resilience is the social , economic , political and context . This includes contextual factors and conditions around the community itself , requiring the expansion of the analysis of community resilience to take into account the wider political and economic factors that directly or indirectly influence the resilience of the community . In different concepts and theories these contextual factors have been addressed , in 98

institutional analysis ( and Weatherhead , 2011 , 2005 ) common pool resource research ( Edwards and Steins , 1999 ) or systems research ( Orach and , 2016 ) The analysis of contextual factors can also expand backward in time and include an analysis of change over time . Therefore , apart from the more or less stable context factors we include social , economic , political and environmental change over time as an influencing force of framing of community resilience . Disaster risk and hazard research scholars ( et , 2010 ) as well as policy change scholars ( Orach and , 2016 ) have identified different dynamics and types of change from gradual , change to rapid and abrupt transformation and from iterative to fundamental changes . This can include social change , economic change and policy change as well as changes in the natural environment , connected to climate change and land degradation . Considering the third boundary condition , a broad variety of disturbances can influence the community and its resilience is partly closely interlinked with the perceived or experienced changes and the specific context factors . As already noted by Wilson ( 2013 ) disturbances can have both endogenous ( from within communities , local pollution event ) and exogenous causes ( outside communities , hurricanes , wars ) and include both sudden catastrophic disturbances ( earthquakes ) as well as disturbances such as droughts or shifts in global trade ( for a typology of anthropogenic and natural disturbances affecting community resilience see Wilson , 2013 ) In line with Wilson we conclude that communities are never stable but are continuously and simultaneously affected and react to disturbances , change processes and various context factors . Therefore , disturbances can not only have severe negative impacts on a community but also trigger change and transformation that might not have activated otherwise . As a result , in empirical applications a differentiation between contextual change over time and disturbances or disturbances that trigger change is not always possible . DISCUSSION AND CONCLUSIONS between the domains and framing Considering the intertwined components of the proposed framework , research can be guided by acknowledging the complexity of the interactions between the resources and capacities , learning and actions domains in shaping community resilience . Therefore , efforts that evaluate these multiple levels their interactions and how they operate in different for different hazards can an enriching evaluation of community resilience . An example of how the emBRACE framework of community resilience helped to reveal the interrelatedness of and resources in the civil protection actions and the importance of social solidarity and trust as important contextual factor is delivered in the case study work in the city of Van , Turkey . Here the exploration of individual resilience after a severe earthquake proved wow influential the contextual factors are . The results indicated that the political context played an important role in shaping survivors of their own resilience . et al . 2016 ) shows that community resilience is facilitated when provision of aid and services is based on equality and trust ( and not nepotism and corruption ) and not hindered by discrepancy of political views among government bodies , community members and . the analysis revealed that the earthquake experience in the region of Turkey in 1999 , 12 years earlier influenced the resilience of the community following the Van earthquake , based on learning processes that resulted , for example , in a change in the public disaster management by state organizations as well as the adoption of new legislation . Thus , especially for the state institutions , the impact of a past disturbance may lead to significant changes in disaster risk management , which in turn are likely to contribute to fostering community resilience in Van and beyond ( et , 2018 ) This example shows how the framework an understanding of the interrelatedness of the three domains and the importance of their interactions in shaping community resilience . Yet , the specific types of relations and are case specific , influenced by various external variables . How to specify these and develop of linkages and relations will need to be investigated in further research . Application and of the framework in assessments The emBRACE framework for community resilience was iteratively developed and refined based on the empirical research of the specific systems within the five case studies of emBRACE thus it is strongly supported by local research findings on community resilience . It was mainly developed to characterize community resilience in a coherent and integrative way . Nonetheless , it was also developed for measuring resilience and is thus a heuristic to be in the form of an assessment . Thus , the framework provides one possible but empirically legitimized structure and route with which to select and conceptually locate indicators of community resilience . Within the emBRACE project community resilience indicators as well as concise , substantial indicators that are generalizable across the case studies ( Becker et , 2018 ) The generalizable key indicators include a wider range of indicators from more quantitative indicators , like the presence of an active emergency coordination body or the percentage of households in the community that subscribed to an system , the domain of civil protection action , up 99

to more qualitative indicators such as trust and the sense of belonging to a community , applying the domain of human and social resources and capacities . Besides identifying and selecting suitable indicators , it is crucial to understand how to develop , integrate , interpret and apply indicators ( 2018 and Tanner , 2011 ) Concrete instructions are needed to provide a useful source of information for proper indicator application in practice and we recommend using some form of guideline for community resilience indicator development ( see for example Becker et , 2015 ) In particular , the possible methods of data collection for the constituent parts of this framework require attention , since they affect not only the methods adopted to the indicators but also the scale of application . Reflections on the results and emBRACE methodology and limits of the findings The term is both ubiquitous and indeterminate . Similarly , community is equally pervasive and prone to common sense understandings which appear to obviate critical discursive engagement . Together , the two concepts represent both a challenge and an opportunity to influence the shape of effective and inclusive disaster risk reduction . The frequently simplistic and bounded uses of community resilience ( across a range of sectors but most particularly in the civil protection and emergency management fields ) limit the reach of risk reduction endeavours through a narrow focus on technical interventions at the expense of recognizing and enabling social transformations . The proposed framework for characterizing community resilience was developed deductively by considering theoretical approaches of resilience from various disciplinary backgrounds and research , and it was also developed inductively based on empirical insights from our case study work . The result is a heuristic that has the potential to guide empirical research as well as disaster management and community development in a more inclusive and expansive way . Research and practice rarely include all elements we have identified but often focus on some specific domains and their interaction in more detail . When guiding disaster management and community development the framework helps to highlight the importance of the multiple factors that are related to community resilience . Whether the framework is to inform scientific or more practical applications , in most cases it will be necessary to adapt the framework to the specific context in which it is applied , cultural background , hazard types or the context . This framework was developed in a European context , and while the research team has drawn upon their wider research knowledge and experience it was not tested outside that geographic boundary . The emBRACE framework was developed as a heuristic device , a strategy based on experience and as an aid to communication and understanding , but it is not guaranteed to be optimal or perfect . The framework should be subject to further research both for further community resilience and applying and specifying the framework in various of community resilience . 100

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Indicators for Monitoring Urban Climate Change Resilience and Adaptation by Daniel , Daniela , Christian Kind , Theresa Kaiser , Christian and This article was originally published in , 2019 . Imps This work is licensed under a Creative Commons Attribution International ( BY ) license ABSTRACT In the face of accelerating climate change , urbanization and the need to adapt to these changes , the concept of resilience as an and positive approach has gained increasing attention over the last decade . However , measuring resilience and monitoring adaptation efforts have received only limited attention from science and practice so far . Thus , this paper aims to provide an indicator set to measure urban climate resilience and monitor adaptation activities . In order to develop this indicator set , a mixed method approach was implemented ( based on a literature review , relevant resilience indicators were selected , researchers , consultants and city representatives were then invited to evaluate those indicators in an online survey before the remaining indicator candidates were validated in a workshop ( and finally reviewed by sector experts ( This thorough process resulted in 211 indicators distributed over 21 action fields based on secondary data . The participatory approach allowed the research team to take into account the complexity and nature of the topic , as well as and parameters . However , it also showed that in order to conduct a holistic assessment of urban climate resilience , a purely quantitative , approach is not sufficient , and additional qualitative information is needed . Keywords resilience indicator monitoring climate change climate adaptation . INTRODUCTION Our society is facing multitudinous different this paper we are focusing on two main challenges climate change and urbanization . In 2015 , billion people were living in cities . By 2050 , the population in cities is projected to reach up to billion people . Urban will continue to grow and are increasingly threatened by the high uncertainty of climate change impacts . In response to these impacts , cities are already implementing climate change adaptation measures in order to prepare for uncertain future changes . Adaptation to climate change and climate variability is not a new phenomenon . However , steadily rising temperatures , increasing magnitude and frequencies of extreme events , such as droughts , floods , storms or intense rainfall , as well as the growth of the global human population pose new adaptation challenges to humankind . In our research , we use the term adaptation as defined by the United Nations Climate Change to Adaptation refers to adjustments in ecological , social , or economic systems in response to actual or expected climatic stimuli and their effects or impacts . It refers to changes in processes , practices , and structures to moderate potential damages orto benefit from opportunities associated with climate change . Furthermore , the ability of adaptation is understood as part of resilience , as described by et al . The concept of resilience can be attributed to Holling and originates from ecology . He described resilience as the measure of persistence of systems and of their ability to absorb change and disturbance and still maintain the same relationship between population or state variables . The original concept of resilience gained increased importance in other disciplines , whereby the definitions of resilience were steadily differentiated , broadened and deepened . There are three main understandings of the character of resilience bounce back which refers to the fast return to an equilibrium state of a system after a shock event , bounce forward which focuses on a system which should have capacities to be adapted to uncertainty and both which addresses the of the capacities for bounce back and bounce forward . et al . analysed 57 academic definitions of urban resilience , with particular regard to these fundamental understandings of urban resilience . The analysis showed that 35 definitions focus on bouncing back , 15 on bouncing forward and only seven see both capacities as elementary for resilience . et al . pointed out that the definitions shifted from an understanding of resilience towards an understanding of resilience . Four main approaches to resilience can be identified disaster risk reduction , 10 , sustainable livelihoods 11 and the approach 12 . Resilience can also be discussed on different scales ( county , region , urban area , city , community and household ) Even though it is important to take action on all scales , in this work we are focusing on in are using the ecological approach . Besides the definitions and understandings of resilience in academia , it is very important to also consider how practitioners interpret resilience . Practitioners and policy makers are a central part of the process . Therefore , it is remarkable that the term resilience is interpreted in a much wider range of ways by practitioners than by academia 13 . Adaptation measures are implemented in different sectors of the city system . Since cities are complex and multifaceted systems , 106

which in turn contain other systems , measuring the success of activities poses a particular challenge . However , measurement is of great importance in order to be able to govern and steer the adaptation and transformation process . Every city has its specific context and needs , and its exposure to risk and vulnerability is dynamic and changes over time . However , it is important to develop measurable indicators for different reasons . Indicators enable monitoring of the process , as they provide regular and impartial feedback . They build an evidence base and make resilience more tangible for decision and policy makers as well as society at large . Furthermore , indicators can help to govern and steer the transformation process because they help to structure the new field of urban climate resilience . Clear indicators are not only important for the general measurement of resilience , but also for the analysis of whether adaptation measures were effective and whether the expected results were achieved 14 . Indicators also contribute to the credibility , transparency and accountability of the measures implemented . This in turn is very important for local policy makers to support further adaptation measures . However , the development of indicators in this context poses particular challenges . In addition to the conceptual challenges of urban climate resilience , context specificity represents another challenge for the development of resilience indicators . Consequently , it is very important to consider how to include context specificity in the indicator set . Another fundamental consideration is in regard to the , dynamic and nature of risk and vulnerability . monitoring of adaptation measures and climate resilience in cities ) a project funded by the German Federal Ministry of Education and Research ( was initiated in order to address the main challenges of ( developing a consistent understanding of resilience for both practitioners and academia , shaping the adaptation and transformation process into a transparent process of governing and steering and ( the use of resilience and adaptation measurements . The aim of is to create oriented for monitoring and evaluating local adaptation measures . As we are focusing on the special needs for cities in Germany , we are working together with 11 other projects of the funding initiative Climate resilience through action in cities and regions of the , who are focusing on change adaptation measures and urban resilience , as well as doing research in municipalities across Germany . projects and cities differ considerably concerning scale ( street , district , city , suburbs and region ) inhabitants and type of adaptation measure ( planning , physical infrastructure , capacity building or greening ) Important commonalities of the projects are their approach , the aim to enhance urban climate resilience and that they conduct research . However , the projects test many different pathways to improve resilience , and is focusing on how to measure the success and impact of different projects and activities with a common set of indicators . In order to ensure applicability , we began to involve the projects at an early stage of our research . The first key step ( Figure Phase ) before developing the indicators was to develop a framework to describe urban resilience . Based on 19 described in the literature 16 , our first draft was developed , which then was modified together with the projects . This process was indispensable as it resulted in a definition of urban resilience that is suitable for all projects so that there was agreement on common basic principles . Based on steps to as shown in Figure , final definition of urban resilience in is as follows The climate resilience of a city depends on the ability of its to anticipate the consequences of extreme weather and climate change , to resist the negative consequences of these events and to recover essential functions after disturbance quickly , as well as to learn from these events and to to the consequences of climate change in the short and medium term , and transform in the long term . The more pronounced these abilities are , the more resilient a city is to the consequences of climate change . All abilities are important . Based on this preliminary work , a approach ( Figure Phases ) was designed to develop the indicators for urban climate resilience on which this paper . 107

Figure . process . Development of an urban climate resilience Development or an urban climate . framework . Workshop ofthe developed urban Resilience projects resilience framework of the developed urban climate 55 oi the Framework based on the oi the urban workshop to workshop Resilience Framework ' toms on at 21 the background at the developed . arr , Review 01495 tunes ( focus on , and context , I Respondents who as ! the ot the one at lhe projects , to extend the set ' above the ' the projects developed on the ground research and the knowledge and at 01 ' or the set based on the oi the set based on expert I am discussions at the . MATERIALS AND METHODS The exponential growth of literature concerning urban resilience contains a multitude of approaches , indicators and methods stressing the resistance of an urban system . The development of the method of this paper was guided by the questions resilience for whom , for what and where 35 . A reflexive approach of input and feedback loops was developed in order to adapt and validate international indicators . A main challenge was to adapt the indicators to the specific context of German communities in the face of climate change . Literature Review Resilience Indicators The selected ( see Figure Phase ) were identified through an extensive literature review using the key search terms resilience , urban resilience , climate resilience , adaptive capacity , urban and learning capacity city ( in German and English ) Based on these and their of resilience , an extensive list of indicators was deduced . These indicators were matched with the framework , developed in steps , which consists of dimensions and action fields ( see Table ) 108

Table . Dimensions and action of the resilience framework . Dimension Action Field Soil and green spaces Environment Water bodies Biodiversity Air Settlement structure Infrastructure Telecommunication Traffic Drinking and wastewater Innovation ' Business Economic structure Research Knowledge and risk competence Society Healthcare structure Civil society Civil protection Participation Governance Municipal budget Strategy , plans and environment As we have the aim to develop a , applicable and transparent indicator set , we firstly reduced the indicators to two indicators per . The two most important selection criteria were ( context specificity of industrial nations , especially Germany , and ( data availability . Context specificity is important because many of the indicators in the literature are suitable for the context of the Global South but not for the Global North , and even indicators that might be suitable for the Global North might not be suitable in the German context . The second therefore important because municipalities have , on the one hand , good access to a lot of data but have , on the other hand , resource problems regarding time , finances and human resources . Action fields without indicators required the development of new ideas within the project . Given the available data , some action fields were difficult to measure without significantly neglecting the complexity of the action field . Survey to Assimilate the Indicators for Context Specificity Based on the literature review ( see Figure Phase ) and the described selection process , an was developed ( see Figure Phase ) The survey was used because , given that the indicators should be transparent and , not only the scientific background is important , but a clear understanding of the indicators in the broad community is important also . The survey was sent to all persons who are working in one of the 11 projects mentioned above . 39 people answered the survey . The main aim of the survey was to measure how participants assess the different indicators . They were requested to rate the importance of every indicator regarding urban climate resilience on a scale from one ( low importance ) to five ( high importance ) Each action field was represented by at least one indicator ( Table ) Besides the rating of indicators , the survey consisted of four chapters First , some general background Second , the context of urban climate resilience Thirdly , the indicators Fourthly , the possibility of extending the set of indicators by indicators without existing data sources , and some final remarks . 109

. Workshop Following the Survey As mentioned previously , the explanatory power of an indicator set of urban climate resilience is hugely dependent on the context , and therefore we discussed the results of the survey again with the 11 projects ( see . Figure Phase ) Moreover , this feedback loop increases the transparency of the process and the robustness of the results . The workshop started with presenting the survey results and then the participants were split into two groups in order to create two independent feedback loops and of the indicator set . For each group , a poster was prepared , listing all indicators included in the survey . The indicators that were ranked lower in the survey were written on the poster in light grey ( compared to black ) for an improved visualization of the survey results . Hence , both groups had the visual results to discuss and were asked to compare each pair in detail and find explanations for the survey results . In addition , the overall set remained visible , which allowed participants to keep the important question of the overall themes in mind . Therefore , indicators could be moved across the could become more important ifthey were deemed a missing piece in the mosaic . The guiding questions for this phase of the workshop were ( Are there enough indicators ?

How many indicators are needed and sufficient ?

Are the selected indicators the right ones or should they be changed ?

And ( is ) are there important gaps in the set that are yet to be filled ?

Finalizing the Indicators Set Step ( see Figure ) we analyzed the results of the workshop . Furthermore , expert interviews with practitioners were conducted with the aim to develop indicators in action fields where literature review nor survey and workshop produced results . On this , we finalized the urban resilience indicator set . RESULTS our review of the academic literature , 19 resilience were analyzed . Based on the indicators of these a list of indicators ( including duplicates ) was generated . The indicator list was used as an important starting point for developing the Indicator Set ( After screening the indicators through the lens of the , some action remained empty and were filled by proposed indicators of the . One to four indicators were selected per action field in order to cover all topics and include sufficient redundancy . Table shows the selected and proposed indicators . able . Delineated indicators and action fields . Survey about Resilience Indicators he survey was structured based on the results of Phase . The survey ( Figure Phase ) was filled out by 39 respondents within the initiative Climate resilience through action in cities and regions of the . The overall mean perceived importance of the indicators was within the complete range from one to five . Considering the complexity of the urban system and the character of the indicator set , this rating was regarded as high . The median of four was also high . The standard deviation of together with the entire evaluation range reflected the diversity of interpretations . Nevertheless , despite this diversity , these core numbers show that the indicators were overall judged as important . Splitting the indicators into the five main dimensions ( Figure ) the median shows that only the indicators within the dimension of economy were rated less important , they are rated in the middle of the range , which might indicate a slight indecisiveness . 110

Table . Delineated indicators and action . Dimension Action Field Indicator Code of A ' mi ' land Ru . bod slum of water bod sun mam 21 seam uf . and Iu ( hun area A . and um . my Cold air of building . i , of given . Sham . is , mi if Traffic for sustainable I ) and Number index Ram uf CU . Sh i . I an ) In sector in ! aI ( I arch . my and Information twat rain and Bibi , yuan vi of hospital 41 , 40 Sham of 65 421 ' Sham ' my 42 Numb . 11 , participation vi fur if Municipal budget , Tax and , Strung ' mi plan nI . change pan of umm ( WI plan ( I , WI and ' Climatic Several reasons could explain this , such as that the indicators selected were not dimension in a satisfactory manner orthat the dimension is perceived as unrelated to urban climate resilience . Those questions were discussed in the workshop ( Figure Phase ) in detail . All top five ranked indicators had a median rating of The mean values ranged from to . Only two respectively three respondents did not rate the indicators , showing the general agreement regarding the importance . Nevertheless , regarding the minimum values , all had a large range from to . 111

The set of five indicators in Table shows that the three dimensions environment , governance and society were seen as particular important . The indicator rated as the most important was the environment indicator cold air parcels . Second and fourth ranked were governance indicators , namely working groups regarding risk , climate change and resilience and strategies against heavy rain and heat in plans . Third and fifth ranked were two indicators from the dimension society . The respondents saw the importance of experience with extreme events in the last five years and citizen information about heat , heavy rain and flooding as particularly crucial for building urban resilience . Figure . Median importance of indicators grouped into dimensions . Environment Infrastructure Governance Economy Society Table . The indicators rated as most important in the survey . Dimension Action Indicator Min . Median Mean Max Environment Air Cold air parcels working group Administration regarding risk , climate change and resilience . Knowledge and Experience with events competence in last years ' Strategy , planned Strategies against heavy rain and environment and heat in plans . Knowledge and Citizen information about heat , competence heavy rain and flooding ' Table it displays the five lowest ranked indicators in context of their relevance related to urban climate resilience . The overall lowest rated indicators were both from the society dimension , namely voter turnout and number of associations . The respondents did not think that they were relevant for measuring and monitoring urban resilience . The third lowest indicator was the infrastructure indicator broadband access . Fourth and fifth were two economic indicators measuring ratio to and share employees in largest sector . 112

Table . Five lowest rated indicators . Dimension Action Indicator Min . Median Mean Max Society Civil society Voter turnout Society Civil society Number of associations Broadband access Economy Business Ration to Economic Shane Employees in largest Figure displays of all indicators . The main tendency has already been shown in a more condensed form previously in Figure . Share of nature conservation and protection areas ( was the lowest ranking in the dimension environment . The second indicator of the action field biodiversity , however , received high approval , which emphasised the perceived importance of biodiversity considerations for climate resilience in the urban context . Settlement structure ( was seen as vital for structural climate change adaptation , similar to the first action fields of soil and green spaces ( Figure . Box plots of all indicators included in the survey ( see Table for indicator codes ) Energy ( indicators , in contrast , not only ranged from a rating of one to , but the of the also show a comparably high range around the middle of the scale . in I ! I ' I . General Workshop Results Regarding the MIS The discussion of the indicators discussion groups yielded important feedback on the overarching attributes and requirements of the MIS . They were mentioned several times from different persons and related to different indicators . Firstly , one important aspect 113

was the size of the municipality and hence the scaling of the indicator . No universal scaling was found appropriate , since the different units and scales required scaling . Nevertheless , the scaling was seen as an important factor in order to reach the goal of acquiring indicators for municipalities and therefore an interpretable result on this level of administrative organization . he overall discussion and feasibility was touched on in many ways from different angles , most prominently regarding availability , numbers of indicators and total effort needed . The balancing of the loss of information related to simpler indicators or vice versa with more complex indicators with higher explanatory power but with an infeasibility to be handled by the target group was seen as a key challenge . Therefore , the participants agreed that the indicators should be based solely on existing data , thereby reducing the overall effort and simplifying the calculations and data management . he idea of detailed describing the data source and calculation of the indicator and helping with the interpretation of the result was raised by participants and received wide support . also help to communicate the meaning of an indicator to uninitiated persons , which was also mentioned as a crucial aspect . he total number of indicators to be feasible was seen at around 25 . Certain gaps were identified during the workshop due to the act that specific expertise related to certain action fields was missing in the room , specifically regarding the action fields energy , wastewater and civil protection . Here , single expert interviews were carried out after the workshop to fill in the gaps . Indicator Specific Workshop Results able summarizes the process of indicator development during the three phases of the survey , the workshop and ending in the set of indicators . The indicators highlighted in grey are those of the initial indicator set that were seen as important by survey respondents and therefore stayed on the list . The indicators highlighted in orange were updated or modified as a result of the survey workshop . The yellow indicators were moved from one action field to another . The indicator degree of soil sealing was inverted to degree of unsealed ground , as sealing is not per se negative , even may even be desirable or unavoidable in urban areas . The cold air parcels was seen as an important factor of resilience but should be updated , adding cold air streams to the indicators . Biodiversity was discussed in contradictory ways , as it was not clear to the participants how it is related to climate hazards . Hence , the workshop resulted in representing urban biodiversity with the and retention areas in order to include flood protection arguments into the indicator of biodiversity . Infrastructure was seen undoubtedly as a key area for achieving urban climate resilience , but also related to secondary data and its inherent complexity most difficult to quantify currently . Accessibility of green spaces was rather seen as an indicator of social justice and less as a settlement structural indicator and hence the second indicator building density , slightly lower ranked in the survey , was included instead . The share of renewable energy indicator focused strongly on climate protection and less on resilience factors , such as robustness and redundancy . These factors were seen to be better covered by the diversity of renewable energy sources . However , it was also argued that even conventional energy should be included in the indicator . This observation was followed by the consideration that no climate resilience can be achieved without climate protection in the long term . Therefore conventional energy sources can not be regarded as a positive contribution to climate resilience in the long term . The action field of telecommunication was deleted in accordance with the participants perception of this as being less important than the other action fields , lacking data and having low to no influence of the municipality . Instead , the action field wastewater treatment was included , as there was agreement on its importance additionally to the supply side . No specific indicator was defined in the workshop due to missing competence in this regard . Transportation was discussed as an important action field for municipalities , but participants agreed that its complexity can not be covered by one indicator . Therefore , the action field remained as an action field of the framework , reminding of the importance of the topic and urging municipalities to consider and discuss it qualitatively . The discussion around the economic dimension reflected the lower ranking of its indicators in the survey . The dimensions environment and infrastructure were seen to be more naturally linked to resilience than the economic dimension . Nevertheless , discussing the importance of a resilient economy for an urban system generated acceptance for the dimension and its components . This example illustrates one very important lesson of the workshop the need for explanation and building a common understanding . Innovation was seen to be covered best by the number of employees in research intensive companies not by the innovation index . The tax income from companies was considered an important resource for the financial ability of the municipality to adapt . This indicator was part of the action field municipal budget in the survey and has since been moved to business . Similar to energy , a diverse economy was considered more robust , flexible and redundant when facing uncertainty of climate impacts . It was also discussed whether there might be sectors with crucial or higher relevance than others , but the group agreed that no single sector could be selected . There was a general agreement on the importance and contribution of society to urban climate resilience , but less agreement on how to measure it quantitatively . Literature shows that the experience with extreme events contributes positively to citizens resilience . In addition , citizen information about heat , heavy rain and flooding ( Table ) was amongst the top five rated indicators . However , regarding the spatial scale of municipalities , it was argued that information is not only provided by the local authority and therefore the indicator was not further considered . Civil society started an intense discussion on how to measure it and if the proposed indicators were adequate . In contrast to the survey , where the indicator voter turnout ranked higher , the workshop participants disliked this 114

indicator , arguing that voter turnout nowadays can not be seen as a proxy indicator for solidarity and community in Germany . The indicator associations was also critically reflected upon as being unable to capture civil society entirely . Still , the participants were in favour of the imperfect indicator associations instead of deleting the action field . In the survey , the dimension governance and its indicators were ranked high , and this result was confirmed in the workshop . Only one change was decided replacing the contact point for participation processes with the number of conducted participation processes . Both were ranked very close in the survey with a mean of and , respectively . Table . Indicator set after the survey , workshop and set . Field Survey Result workshop MIS Soil and green spaces Degree ground Degree at unsealed Degree ground mung , of water bodies same of water bodies Scale of water bodies , and retention areas Air Cold air parcels Cold air panels and flows i ' Building Building hag Sham , energy i of ) I ity of renewable Per energy Per energy consumption supply and Number in springs Number of springs Number of springs ( Including wastewater Ada Se um indicator ) I Innovation index ' mom ) companies intensive companies ' Commercial tax per capita Commercial tax per capita . or business of business ' Number of research projects Number of research my A ' with extreme events with care Number share of . share of share of i ' mum ) Cu rue brigade Fire brigade Fire brigade FI participation mum Municipal Depth per citizen Depth per citizen Depth per citizen . Risk and vulnerability Risk and vulnerability Risk and vulnerability Plan and rain and hear In plans Strategies against heavy rain and hear in plans Strategies against heavy rain and heat in plans Administration working group regarding risk change and resilience working group regarding risk change and resilience working regarding risk . climate change and resilience updated switched action Field no change . Urban Climate Resilience Indicator Set Since even the diverse group of participants of the workshop did not cover all topics of the indicator set , experts were interviewed . Furthermore , the results of the survey and the results of the workshop were summarized and merged . The final set of indicators is shown in Table Sin the column MIS . Compared with the workshop set , the action field of biodiversity was seen crucial in its own right and better approximated by the indicator nature conservation and protection areas . Moreover , wetlands and retention areas were already covered by the state of the water bodies in line with the European Water Framework Directive regarding good ecological and chemical status . Hence , in order to create a balanced set of indicators , it was seen that the latter indicator added thematically more information and another aspect to the overall set . Secondly , the air action field was further developed , as cold air parcels and flows was difficult to interpret . The simple number or share of cold air parcels and streams were not clearly related to resulting air status . The ventilation status including the effects of air streams and cold air production parcels was therefore selected . For the wastewater action field introduced by the workshop , an expert interview recommended the indicator share of adopted sewer system . Another interview was conducted with the lower civil protection agency . The interviewee stressed the importance of 115

volunteers across organizations , but as no data were gathered assessing the total numbers of volunteers , the most important one of the fire brigade was considered . Moreover , the municipality may have to consider this important topic even more in the future , as the principle of volunteers may be endangered due to demographic development . Finally , yet importantly , the accessibility of hospitals was with the density of doctors . DISCUSSION The results from the work on indicators for monitoring urban climate resilience presented above yields a number of important insights and respect to previous studies but also for future research and for practitioners in this field . Existing indicator sets are a good starting point , but adapting and extending them forthe context at hand is crucial . There are numerous indicator sets for urban resilience these provided a good basis from which the indicator set could be developed . However , many of the indicators analysed in the literature review were aimed at the context of developing countries . To adapt indicators identified in the review for the German context , four steps were important ( A ) Disregarding indicators that do not allow sufficient distinction cities , literacy rate is favoured as an indicator in many sources , but in Germany the literacy rate is rather high and differences between cities are marginal . Disregarding indicators for which the data availability was rather limited in Germany . Adding new indicators for action fields that are deemed important in the context of but which were not touched upon in the . Focusing on municipalities as the key player for climate change adaptation . These level of municipalities require the set to Lie manageable in terms of data availability as well as size and complexity of the calculations . Step A did not pose any major difficulties . Further , step based on research concerning data availability did not cause problems . step and need to be examined in more detail . First , the workshop clearly stated here the conflicting goals when discussing single action fields . It was felt that one indicator does not reflect the entirety of the topic , but at the same time all action fields were considered important and the total number of indicators should not exceed around 20 , in order to stay manageable , which is far less than the proposed 52 indicators by the City Resilience ( 22 and comparable to the core of by the project Building Resilience Amongst Communities in Europe ( embrace ) 37 or Cutter 43 core of 22 . Since researchers , as well as practitioners , participated in our workshop , we had the impression that researchers tended to prefer larger , encompassing indicator sets . Compared with the scientists , practitioners were more in favour of concise and compact sets . The discussions in the workshop showed that persons with a research background had numerous ideas or new indicators for all dimensions , and advocated for their inclusion . During the workshop and its aftermath , practitioners working in municipalities displayed a different perspective tended to focus more on how to handle the indicators in practice . what some researchers considered a concise indicator set was perceived by practitioners as overwhelming and too extensive . In order to find an adequate balance between a broad coverage and good usability in practice , it is important to involve both researchers and practitioners in the development of an indicator set . This finding is consistent with the literature and is one strength of the current study . and 13 , for example , stress the need for including practitioners in the process . Consequently , the practicability and completeness had to be balanced , leading to the fact that some indicators that were considered important were still sorted out in order to cover all action fields and still achieve a manageable amount of indicators . Second , it was mentioned that the by title were in terms and relation to urban climate resilience , and were consequently rated around the middle . This fact was considered while developing the survey , but an explanation of indicators was removed from the survey in favour of including more indicators covering all action fields and in consideration of the time needed to fill out the survey . However , this lack of explanations meant that the disciplinary background of respondents affected the ratings . Third , indicators from the dimension environment were met with relatively high consensus while indicators from the dimension economy were faced with more diverging opinions . The indicator selection was dependent on the conceptualization of urban resilience and the urban context . The results contribute to the gap between the understanding of urban resilience by scholars and practitioners 13 . This became apparent both in the survey and the workshop and shows that more research is warranted on what characterizes a climate resilience urban economy . Supporting evidence for this can be taken from the fact that much more has been published on climate resilience and environmental issues than on climate resilience and economic issues . Moreover , this discussion displayed the importance of a approach for defining attributes of urban resilience and its measures 44 . Fourth , secondary data was seen as crucial for monitoring purposes in order to reduce resource expenditure by the administration . In other words , The best indicator is inoperable if there is no feasible way to obtain the required 37 . Moreover , there was a strong request from the local administrations for more provision of data from the higher administrations . They argued that data handling , data collection and finances for these activities are lacking . They stressed the need for data provision to be handled at the higher level of administration to avoid scaling and data comparability issues . Hence , data availability for indicators on a municipal level is a strong limiting factor , especially when it comes to indicators concerning infrastructure and social aspects 45 . Parts of the infrastructure related to energy , transport and communication are owned or organized by entities on a higher administrative level , such as the national 116

government or by private entities . This tends to lead to limited data availability when it comes to data with a sufficient resolution on a municipal level . Here it would be favourable if entities in charge of the respective infrastructure made access to data easier and provided data with a resolution that is suitable for analyses on a municipal level . Moreover , the discussion centred around technical measures and physical impacts and less about social drivers and demographic changes . The latter are seen as core aspects of the ability to resist unforeseen threats . Nevertheless , the intense discussion around the proxies suggested by literature displayed vividly the intricacy of social dynamics . New data and methods from the higher administration or databases are needed to better understand and monitor the indicators 43 . Fifth , it is important to mention that a conflict of goals among indicators can arise and can lead to a competition for the scarce resources . These reciprocal processes can not be completely avoided . For example impervious surfaces are seen negative regarding heavy rain , fresh air and heat island effects , but they are necessary for a redundant infrastructure and other urban functions . Another example is provided by and 35 who analysed the negative correlation of park access and management goals , concluding that resilience measures create winners and losers . This also requires transparency of the data and the method of the indicator definition to understand the root causes of the conflicting goals and find adequate solutions . Here the Rockefeller 22 approach seems like a black box because it is difficult to deduce what adaptation measures are used as a data basis , and indicator calculations are unclear . During the workshop , several practitioners mentioned consequently the necessity of transparency and the need for precise communication and language . Sixth , following the previous point , many indicator approaches are used to build a composite index for resilience , vulnerability 18 , or risk . Specifically , at the scale of urban resilience , indexing across the multitude of action fields was discussed critically . The different scales , topics and units appeared to not be logically linkable . Moreover , a combined index value was seen to not tell much about the level of resilience . It was seen as more important to see the contribution of each action field to he overall resilience . Also , considering the next step of adaptation measures , it is more relevant to have a resilience profile displaying specific topics to be addressed in the municipal context . Working at the interface was all sides . The mixed method approach proved invaluable in language , tolerance and understanding . This created an environment that allowed for constructive criticism , which is indispensable for compromise . CONCLUSIONS In his study , we developed an indicator set to measure and monitor urban climate resilience for municipalities , thereby assessing the requirements of indicators and implementing a method for adapting global approaches to the local context . The mixed method approach proved to be essential for the process of indicator development . It provided an adequate frame and time to a mutual understanding across disciplines , researchers and practitioners , which is needed in order to select indicators or accept indicators from different fields of expertise . Transparency in the process and the inclusion of feedback builds acceptance and trust . The concept of resilience provided the required assembly hall and saw climate change as the imperative . Even the of the resilience concept was helpful as it created room for discussion . The number of 21 indicators based on secondary data balanced as well as possible the diverging interests . Amongst the indicators , conflict of goals is unavoidable . Making the conflicts visible is a helpful basis for making informed decisions , which is a strength of this indicator set . In general , the softer and more qualitative aspects of resilience are challenging . They were seen as crucial but very hard to assess by quantitative proxies based on secondary data . Still , representative surveys to cover them in more detail on a regular basis were rejected by municipalities as too expensive and . Developing an indicator set tends to be easier than assessing the significance or validity of an indicator over time and it requires an extended period of observations to be able to make statements about the significance of a certain indicator . Nevertheless , in order to advance this field of research , it is necessary to pursue this path and start inquiries into the significance or validity of the numerous indicators that are permeating the ongoing discussions . In further research , the indicators need to be tested in reality , and there needs to be more research that addresses the validation of the indicators . 117

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Subjective Measures of Household Resilience to Climate Variability and Change Insights from a Nationally Representative Survey of by Lindsey Jones , Emma and Patrick This article was originally published in Ecology Society , 23 ( This work is licensed under a Creative Commons ( license . ABSTRACT Promoting household resilience to climate extremes has emerged as a key development priority . Yet tracking and evaluating resilience at this level remains a critical challenge . Most quantitative approaches rely on objective indicators and assessment , but these are not fully satisfactory . Much of the difficulty arises from a combination of conceptual ambiguities , challenges in selecting appropriate indicators , and in measuring the many intangible aspects that contribute to household resilience . More recently , subjective measures of resilience have been advocated in helping to overcome some of the limitations of traditional objective . However , few studies of quantitative subjective approaches to resilience measurement have been conducted . In this study , we address this gap by exploring perceived levels of household resilience to climate extremes in and the utility of standardized subjective methods for its assessment . A nationally representative survey involving 1291 individuals was carried out by mobile phone in June 2015 among randomly selected adult respondents aged 18 and above . Factors that are most associated with capacities are having had advance knowledge of a previous flood , and to a lesser extent , believing flooding to be a serious community problem . Somewhat surprisingly , though a small number of weak relationships are apparent , most variables do not exhibit statistically significant differences with regards to perceived capacities . These findings may challenge traditional assumptions about what factors characterize household resilience , offering a motivation for studying both subjective and objective perspectives , and understanding better their relationship to one another . If further validated , subjective measures may offer potential as both a complement and alternative to traditional objective methods of resilience measurement , each with their own merits and limitations . Keywords measurement perceptions resilience subjective INTRODUCTION Resilience measurement has soared to the top of the development agenda ( et al . 2011 ) As a result , researchers have proposed many and methods seeking to quantify the resilience of different social systems , whether at household , community , or national levels ( et al . 2005 , 2009 , 2009 , and Barrett 2013 , and James 2013 , and Giuseppe 2011 ) To date , most of these methods have focused on objective indicators and approaches , often centered on observing key socioeconomic variables and other types of capital that support people livelihoods ( and 2017 ) More recently , the advantages of subjective approaches to measuring social systems have been advocated ( Marshall and Marshall 2007 , Jones and Tanner 2015 , Lockwood et al . 2015 , Maxwell et al . 2015 , et al . These methods may offer the opportunity to address many weaknesses that beset traditional objective approaches , such as difficulties with indicator selection , a lack of attention to context specificity , and an inability to take people knowledge of their own resilience into account . However , few quantitative standardized assessments of subjective resilience have taken place ( Marshall 2010 ) As such , little is known about their feasibility as a resilience measurement tool and how they compare with traditional objective methods , particularly when applied at scale . Accordingly , in this study , we propose a simple tool that seeks to measure subjective resilience at a household level alongside numerous characteristics that often form part of objective assessments of resilience . We subsequently apply this tool to investigate the following research question Is subjective resilience connected to particular characteristics of households , and if so , which ones ?

In doing so , we seek to analyze the relationship between objective indicators generally used to signal resilience ( or a lack thereof ) and subjective assessments . If the relationship is weak , this has several potential implications . It could suggest that a more comprehensive assessment of resilience requires accounting for a broader range of objective characteristics , which may in turn suggest additional policy levers that could enhance resilience . Alternatively , it could suggest that intangible characteristics that are difficult to quantify shape perceptions or indeed that subjective measures may not reflect overall resilience well . If the relationship is strong , then this could indicate that subjective measures , which require far fewer resources to administer , could be a useful proxy for 121

( or used alongside ) objective measures , for example , between rounds of an extended household survey and that information about the relative influence of the objective measures on subjective resilience could enhance objective approaches , for example , by suggesting weights that could be used in multidimensional indices . address the research question , we present results from a nationally representative survey focused on the subjective resilience of to flood risk in . To our knowledge , this is the first time that such a tool has been applied nationally . We propose survey questions to explore key capacities , namely the capacities to prepare for , cope with , and adapt to future lood risk . We then assess how these capacities vary across socioeconomic characteristics to understand how subjective resilience is manifest across different household profiles . The choice of methods and wording of questions used in this study leans on earlier theoretical work by Jones and Tanner ( 2017 ) who explore the merits and limitations of assessing subjective resilience at the household evel . It also draws on related methodological insights from earlier work by Marshall and Marshall ( 2007 ) and Maxwell et al . 2015 ) that use similar approaches to examine subjective resilience the former proposes a method of subjectively measuring social resilience in coastal communities in Australia , while the latter sets out principles and guidelines for the subjective measurement of resilience . Based on these exercises , we provide insights into the factors that are associated with subjective assessments of household resilience in and compare these with traditional assumptions , those based largely on objective markers . Last , we present avenues for the methodological refinement and testing of subjective approaches to household resilience . BACKGROUND AND CONTEXT Resilience has its roots in several different disciplinary fields , ranging from mechanics to ecology and psychology ( see Alexander 2013 or a comprehensive historical overview ) However , the term more recent adoption across the sustainability sciences has bolstered its amongst academic and policy communities alike . Indeed , resilience now forms a central pillar in many key international policy such as the United Nations Agenda 2030 , Framework for Disaster Risk Reduction , and Paris Agreement ( United , Though the utility of a broad resilience framing has brought many benefits , it has also contributed to definitional and conceptual inconsistencies in its use ( et al 2015 ) For example , early of resilience in describing social systems leant on ecologic and revolved around the capacity to absorb change and disturbance in order to maintain core functions ( Holling 1973 , Walker et al . 1981 , Odum 1985 ) Subsequent thinking within the field of systems has challenged these when applying resilience to understand human responses to climate risk , encouraging greater recognition of the ability of social groups to adapt and change their core structure and functions ( et al . 2002 , Walker et al . 2004 , 2006 , 2006 , et al . 2017 ) In some cases , it is argued that the complete transformation of a system may be a necessary component of a resilience process ( et al . 2012 , et al . 2015 ) there is broad agreement across disciplines that resilience comprises a range of evolving capacities and processes rather than constituting a static state ( Maguire and Cartwright 2008 ) For example , in the context of community resilience to disaster risk , orris et al . 2008 ) propose that resilience can be broken down into three core capacities robustness ( the strength of a resources ) redundancy ( the extent to which elements are substitutable in the event of disruption or degradation ) and rapidity ( how quickly the resource can be accessed and used ) et al . 2012 ) propose a framework consisting of the capacities to absorb , adapt , and transform . Many other such exist . However , agreement over the exact characterization of resilience is missing amongst the wider literature . These conceptual distinctions matter not only because the capacities needed to support them are different , but they present a fundamentally different conceptualization of what a resilient system constitutes Such wide meanings may end up being contradictory as in the notion of restoring equilibrium and getting away from it by moving to a new state ( Alexander 2013 , as cited in et al . As such , properties such as coping , adaptive and transformative capacities are often used in different ways and in different combinations when framing resilience ( and 2017 ) Indeed , they are frequently used interchangeably with resilience itself ( et al . 2015 ) This lack of definitional and conceptual agreement presents challenges when seeking to track and measure resilience , but these difficulties notwithstanding , a wide range of measurement have emerged in ( and Barrett 2013 , 2016 , et al . 2011 , et al . Most efforts to measure climate resilience use objective criteria , socioeconomic indicators and processes that are considered to support a household ability to deal with risk ( and Langston 2015 ) Objective , in this context , tends to denote of resilience that are based on external judgement and verification ( Maxwell et al . 2015 ) Such approaches tend to be guided by an overarching conceptual framework , usually designed by technical experts or those external to the individual or household themselves , though sometimes these draw on qualitative inputs from intended communities or the piloting of survey instruments ( Jones and Tanner 2017 ) Yet there is no universal acceptance on how resilience can and should be measured and hence a plethora of different objective and indicator lists exist , some contrasting markedly ( et al . 2016 ) One widely used example is the United Nation Food and Agriculture Organization ( Resilience Index Measurement and Analysis model ( RIMA ) which combines socioeconomic variables from five dimensions access to basic services assets adaptive capacity social safety nets and sensitivity to shock . These are then further broken down into dozens of individual indicators ( and Giuseppe 122

2011 ) Given that RIMA is centered around a framework primarily on wider resilience literature , has a list of derived indicators for each characteristic , and relies on extensive surveys to collect externally verified information on household socioeconomic conditions ( 2016 ) the approach can be readily classified within the objective camp of measurement tools . Objective measurement approaches such as RIMA have many strengths , ing the ability to generate composite scores of resilience that can be readily compared across households . However , they also present several clear limitations . Most notably , they rely heavily on resilience characteristics and standardized indicators . This it challenging to capture the nature of resilience factors that make a coastal fisher in coastal Kenya resilient are unlikely to be the same as those for a pastoralist in the northeastern of Kenya . In addition , objective approaches operate on the basis that resilience can be externally determined . Such approaches favor structural at the expense of those on human agency , which may be harder to understand and measure ( Tanner et al . 2015 ) Crucially , they do not take into account people knowledge of their own resilience and how they evaluate their lives . Thus , objective evaluations often require value judgements in the factors that are assumed to make others resilient and simplifying the complex nature of resilience across differing . Ironically , these value judgements mean that many objective approaches to resilience fall short on their own terms . Despite the limitations , objective approaches to resilience measurement remain the norm and dictate to a large degree our of resilience processes at all scales . Though yet to be fully explored in both conceptual and practical terms , subjective methods may offer an alternative and complementary approach to objective assessments of resilience ( Marshall and Marshall 2007 , and James 2013 , Jones and Tanner 2015 , Maxwell et al . 2015 , et al . et al . 2016 ) Subjective evaluations are often used to gain bottom up and grounded insights into people own understandings of resilience and its components . A significant Jody of literature has sought to understand subjective elements of household resilience ( 2009 , et al . 2010 , 2010 , Miller et al . 2010 ) The vast majority of this work is based on qualitative assessments , typically based on ethnographic case studies , interviews , and focus groups or participatory rural appraisals ( PRA ) Although these approaches provide tremendous value , particularly in allowing for depth and nuance , they are difficult to use as a basis for measuring resilience at scale or across . We are concerned with a branch of subjective resilience consisting of standardized and quantifiable methods for evaluating perceived resilience . At its simplest , subjective household resilience relates to an individual cognitive and affective of the capabilities and capacities oftheir household , community , or any other social system to respond to risk ( Jones and Tanner 201 ) If care is taken to design suitable and survey questions , then a household subjective resilience can , in theory , be readily quantified . Standardized subjective indicators can be measured in many ways . Perhaps the most evident and practical way of collecting standardized data is through large household surveys . Although questions might provide rich qualitative detail , questions are more likely to enable the aggregation of of resilience capacities and to facilitate comparison across social groups or time ( 2013 ) Indeed , insights and research from related fields , such as subjective , risk perception , and psychological resilience suggest that that standardized subjective evaluations may help to capture many softer elements of capacities allow comparison across different and permit individuals knowledge of the factors that contribute to their own resilience to be incorporated ( Jones and Tanner 2015 ) Despite its clear potential , relatively little is known about how people evaluate their own resilience using standardized subjective measures , nor whether factors traditionally associated with objective household resilience match those from subjective when assessed at scale . For this reason , in this article we seek insights into these research gaps . We focus on a subset of resilience household resilience to climate extremes . Multiple epistemological entry points for climate resilience exist , though most objective measurement break the concept down into a common series of distinct yet interrelated characteristics ( and Langston 2015 ) Properties such as the capacity of a household to prepare for and reduce the impact of climate extremes ( et al . 2015 ) absorb and cope with disturbances and modify and adapt structures in accordance with changing climatic stimuli ( Jones et al . 2010 ) each commonly feature within the literature . However , myriad other properties and combinations thereof surface in each framework , and each also relies on different interpretations of resilience and its constituent processes and indicators ( and Langston 2015 ) Identifying a common set of observable indicators that relate to a capacity to recover from climate extremes , or their ability to adapt to climate risk has so far proven difficult ( Cutter et al . 2008 ) This is not least because many factors that contribute to capacities are process driven and relatively intangible ( Jones et al . 2010 ) For example , social networks and cohesion , power and , and risk tolerance each help to determine a household resilience ( et al . 2013 , et al . For this reason , we believe that a subjective approach may have value in assessing resilience in this specific context . METHODOLOGY Conceptual approach To explore the feasibility of assessing subjective resilience quantitatively and its links to objective characteristics that often feature in resilience measurement , we added a module of questions to a nationally representative longitudinal telephone survey in 123

. To narrow the focus , we concentrated questions on disaster resilience , more specifically , resilience to flood risk . Our survey was based on a standardized and widely used framing of climate resilience ( et al . 2015 , et al . 2015 ) comprising of three core capacities . The first capacity used in our subjective framework relates to a household ability to prepare , more specifically , to anticipate and reduce the impact of climate variability and extremes through preparedness and planning , often by making use of relevant information and early warning ( et al . 2015 ) The second capacity relates to a household ability to recover . This is primarily associated with its ability to absorb and cope with the impacts of climate variability and extremes , often through maintaining core functions or livelihood activities ( and 2003 , et al . 2010 ) The third capacity relates to a household ability to adapt , more specifically , to adjust , modify , or change its characteristics or actions to moderate potential damage or take advantage of new opportunities that arise ( Jones et al . 2010 ) We administered a single question to address each of these three capacities ( Table ) The three items are conceptually distinct , well understood by respondents , easy to use and , as we show below , were found to be relatively independent of one another . Each capacity question used a standardized unipolar scale with four response alternatives . The approach builds on methods used to assess social resilience in individual communities ( see Marshall and Marshall 2007 , and James 2013 , et al . 2016 ) as well as similar approaches used to evaluate subjective capacities in related fields such as subjective ( 2013 ) risk perception ( Mills et al . 2016 ) and psychological resilience ( Connor and 2003 ) Table . questions administered through the national survey . Component of interest question Response items introduction we would like to ask you about what would happen if an extreme your community in the near future . By extreme . I mean one that is likely to your household . or harm your dwelling . or resources . to prepare If an extreme occurred . how hat your scale ( i likely ( Very likely ( Not very would be well prepared in a ?

likely ( Not at all likely . Capacity to recovery If an extreme occurred . how . that your scale ( Extremely likely ( Very likely ( Not very household could fully within ?

likely ( Not at all likely . Capacity to adapt extreme were to become more . how likely ( point scale ( Extremely likely ( 21 Very lik ( Not is it that your household could change its source of income likely ( Not at all likely . livelihood . it needed ?

introduction . I going to ask you about your experience of over the two yea Severity In the last years how serious a problem has been sea . i The most serious problem ( One ol the serious to your household ?

problems of many ( A minor problem ( Not at all a problem In the last years how serious problem has been scale ( The most serious problem One oi the serious to your problems runny ( A minor problem ( Not at all problem Early warning Please think about the last flood that your scale ( No ( Yes ( Household not by a household . Did you about it in in the last two years Although each capacity question is administered via a , as per the approach adopted by et al . we see resilience as multidimensional therefore it is not amenable to being measured via a question . It is important to underscore that none of the three capacity questions should be interpreted as representing resilience overall it is for this reason that we refer to them as capacities throughout . Instead they should be considered to represent several core functions deemed necessary to support household resilience . This study is primarily exploratory . Although we seek to test a research question , given this is a novel area of academic interest with few other studies applied at the national level , we are primarily interested in understanding the dynamics of subjective resilience and working toward further validation and refinement of the tools applied . We hope that future work can build on these research insights and seek more confirmatory and experimental approaches , including the use of scales with numerous , replicative items ( see Jones 2017 ) Survey instrument The questions were administered via a nationally representative survey in , namely the za ( Voices of Citizens ) longitudinal survey managed by the Tanzanian nongovernmental organization and surveying company . The survey is composed of two phases . First , a baseline survey was carried out through traditional interviews using a multistage stratified sampling approach ( 2013 ) A sample of 2000 households in 200 enumeration areas were surveyed in October 2012 , using a sampling frame designed to be representative of the Tanzanian population aged 18 years and older based on the 2012 Population and Housing Census ( 2013 ) At this point , all households were given a mobile phone and solar charger . The second phase consists of a series of mobile telephone surveys with the same sampled households as in the baseline ( Details of 124

surveys to date and the are available at ) In the round associated with this paper results , the survey focused on assessments of political leadership . questions were included in an . Respondents were contacted in July 2015 to take part in the survey through a computer aided telephonic interview ( operated via an managed call center in Dar es Salaam . A total of 1335 respondents out of the potential 2000 from the initial baseline completed this wave of the survey . Questions were administered in and English , with a small financial incentive provided to respondents for their participation ( US 05 mobile airtime credit ) For full details of the sampling procedure , weighting , and data collection see ( date unknown ) For 1334 of the respondents , a wide array of demographic data from the 2012 baseline are available , as well as responses to the resilience questions listed above . We removed an additional 40 of these respondents from the because it was not certain that the same person replied as in the baseline , leaving 1294 matched observations . In the analysis , we describe the characteristics of our sample and then present descriptive statistics on their reported capacities , followed by multivariate analysis . Because the ordinal variables measuring capacities are not normally distributed , we test the equality of proportions rather than means . In the multivariate analysis , we used ordinal logistic models in which we regressed extent to which respondents reported it was likely they could prepare for , adapt to , or transform their livelihoods in the event of severe a range of objective controls to test whether these individual variables were independently able to predict levels of perceived household resilience . Independent variables included the age , gender , education , and household size of respondents , whether they were occupied in farming and whether they lived in an urban or rural area the wealth quintile of the household ( using an asset index ) and household had previous experience ofa flood , believed flooding to be a serious problem for their community , and whether they had known about the last flood that affected them ( within the previous two years ) in advance . Given the are the same across these models , we use a seemingly unrelated estimation technique to account for the correlation in the error terms ( 1999 , 2013 ) Sample characteristics Our respondents to the survey were primarily household heads ( 98 ' the majority of whom were male ( 57 ) 10 They were primarily rural ( 65 ) and occupied in farming ( also 65 ) We defined household wealth status according to an asset index that places households into . 11 Some 93 of households in the poorest asset quintile were in rural areas compared with about 16 of households in the richest asset quintile . Most respondents had primary education ( 61 ) whereas around 13 had at least some secondary education , had a higher education , and just under 10 had no formal education . The mean age of respondents in our sample was 40 years , 37 for females and 42 for men , with a range of between 18 and 89 years old . RESULTS Experience of floods and perception of risk Respondents were asked to report their previous experience of extreme flooding ( see Table 12 ) Overall , 32 reported having experienced at least one such event in the past two years . Among respondents with recent experience of severe flooding , 26 reported having had advance warning before . Respondents were also asked how serious a problem extreme , independently of whether they had recently experienced a flood . Most did not report flooding as a serious concern either for their households ( 86 ) or for their communities ( 71 Fig . However , respondents from households that had experienced a flood in the previous two years were far more likely to perceive flooding as problematic close to 40 of the exposed population reported flooding as a serious problem orthe most serious problem for their household and over half ( 54 ) reported it as serious or most serious fortheir community , compared with ' and 17 of those who had not been exposed to a recent flood , respectively . This is in line with previous studies finding experience of past flooding as a strong contributing factor to risk perception ( Mills et al . 2016 ) There were no other , except that respondents from asset poor households were more likely to believe flooding was serious for their communities . Among respondents with recent flood exposure , those who had early warning of that flood were more likely to perceive it as a serious problem , both for their households and their communities , than those who had not ( Fig . Some 57 and 67 of the population who had received advance warning of a previous flood perceived flooding to be a serious threat to their households and communities respectively , compared with 33 and 49 of those that did not have an early warning . Perceptions of resilience and association with experience and perception of risk Respondents assessed their perceived capacities to prepare for , recover from , and change their livelihood strategy in response to an extreme flood event . Most respondents reported a low perceived ability to prepare , recover , or change . Just of the population reported that their households would be prepared in the event of a flood , felt their households were capable of recovering fully within a period , and in 10 people felt their households could change their source of , if needed ( Fig . 125

Association between dimensions of capacities Examination of the relationship between the three capacities reveals that they are only moderately associated . For example , 53 , of respondents who said they were likely to be prepared also said they were likely to recover , compared to just 10 of those who were unlikely to be prepared . Odd ratios show that respondents who were likely to prepare were five times more likely to recover compared to respondents unlikely to prepare ( Fig . Nevertheless , when using the scale , the rank order correlations among Fig . Subjective of capacities to extreme in . Prepare 34 Recover 43 Change 36 10 20 30 40 50 60 70 80 90 100 I Extremely likely I Very likely Not likely I Not at all likely these three types of capacity were all less than ( Fig . The highest correlation ( is between reporting being able to prepare for a flood and to recover from it while the lowest ( is between being able to recover from a flood and to change one way of life in response to it . We also constructed binary variables ( and found very similar correlations . We examined whether these items could be combined to form an index of a latent construct of resilience . The three items did not meet the established threshold for internal consistency ( alpha is , below the commonly accepted threshold of ) However , item selection was also tested by principal components analysis that showed that the three items loaded strongly onto one variable with an eigenvalue higher than ( the threshold recommended by Kaiser rule Fig . This gives some support for constructing an index of perceptions of resilience however , in this paper we focus on analysis of the three components individually to obtain more insights into factors that are associated ( or not ) with each . We defer discussion of the value of a composite index for future work . Factors associated with perceptions of resilience We analyzed the three capacities across a range of variables of interest ( Figs . and , Tables ) Male and female respondents provide very similar responses across the board , though this may not be surprising given that the survey deliberately asks respondents to rate capacities , not individual ones . Fewer farmers than ( and people in rural versus urban areas ) report an ability to recover fully from an extreme flood event within six months . Responses are very similar across occupations and zone with respect to the perceived capacity to prepare for and adapt , though a lower share of farmers and rural residents report that it is extremely likely that they would adapt to an extreme flood . Education is positively associated with the perceived capacity to recover from a flood but not with the capacity to be prepared or to adapt on average . However , far fewer respondents with a higher education believe it is not at all likely they would be prepared for or able to adapt to an extreme flood , relative to those with less education . Wealth quintile is not linked with perceived preparedness but a higher share of respondents in wealthier report that they could recover and change their livelihoods in response to an extreme flood event ( Fig . capacities differ more markedly in line with the recent experience of flooding . Indeed , a higher share of those who had an experience of extreme flooding in the two years prior to the survey reported that they would be likely or very likely to prepare and to recover ( but not to change their livelihood ) For example , of the population with recent flood exposure reported it was not at all likely they would be prepared for or recover fully from extreme flooding within a period , compared with over ( of those who had not experienced a flood . This suggests either that perceptions are influenced by experience of flooding , 126

which in turn builds confidence in their ability to deal with flood risk , or that floods have been experienced in areas where households have higher capacities . Perhaps of most interest , having had early warning is consistently and strongly associated with all three capacities ( Fig . For example , 45 of those with early warning of a previous flood reported it unlikely that they would be prepared for extreme flooding , compared with 70 of those who had not had such a warning . For the capacity to recover , the figures were 57 , and 79 , respectively , while for the capacity to adapt , they were and 51 . In other words , the differences associated with early warning ranged between 22 and 25 percentage points . The most common source of early warning is through local and national radio ( 75 ) with television ( 18 ) and newspapers ( less common . It could be that respondents in more resilient households are more likely to obtain information regarding upcoming extreme weather events , or conversely , that the receipt information improves household resilience ( indeed both mechanisms could be in play , or an unobserved trait could influence both aspects ) But given that the provision of early warning information is such an important policy lever , greater exploration of the hypothesis that making information about flooding available improves capacities is warranted , in line with similar research on risk perceptions of flooding ( et al . 2008 ) Fig . Relationships between capacities and socioeconomic variables . I ) la ) In A III ! a Farm 20 40 60 ( Run ! and Ill ! undue ) Education and Ill ! Urban Primary Run ! warm . Primary Mammary 20 40 60 100 a ) Wall and capacities ly 10 . 50 60 70 ) Multivariate analysis To understand better factors associated with the perceived capacity to be prepared for , to recover from , and to adapt to extreme flooding , and how they relate to one another , we conducted seemingly unrelated using ordinal logistic models with the capacity variables as the dependent variables . Across all the models , it is immediately apparent that the have negligible explanatory power , explaining at most of variation in these capacities . 13 Very few variables display a statistically significant 127

association with any of the capacities ( Table ) Across all the , the only consistent explanator was not having known about the previous flood in all cases , this was associated with lower reported capacities and the coefficients were strongly statistically significant . Examination of the marginal effects reveals the extent of these gaps ( Fig . Interestingly , in all cases , predicted probabilities for respondents who had not experienced a flood or had experienced a flood but did not know about it in advance were very similar ( the differences were not statistically significant ) Meanwhile respondents who had had advance knowledge ofa previous flood were more likely to report preparedness and the capacities to recover and adapt . Fig . Relationships between early warning and capacities . in Early warning 25 26 19 No early warning 14 43 27 Early warning 20 41 16 No early warning 15 52 27 , Early warning 13 24 17 No early warning 18 40 24 10 20 30 40 50 60 70 80 90 100 I Extremely likely Very likely Not very likely Not at all likely Fig . Predicted probability of capacity to prepare , recover , and adapt to an extreme event , based on early warning of that event . Marginal effects computed on the basis of the separate ordinal logistic . prepare Recover 40 an I 40 AS 35 . 35 ' A so , a 15 25 , 15 a , In an . 15 is 15 my my my karma like , mi No flood Flood , no advance warning . Fiona advance warning Other positive ( and statistically significant ) relationships were found between having a higher education and both preparedness and the capacity to recover between household size and the capacity to recover and between wealth quintile and the capacity to adapt ( Table ) The effect of age is negatively associated with reporting preparedness until the age of 35 and positive thereafter . None of the variables had an equivalent effect to having known about a previous flood , with the sole exception of being in the top wealth quintile on the perceived capacity to adapt . 128

DISCUSSION We have proposed a tool to explore perceived levels of household resilience to climate extremes in , and how objective characteristics map onto these assessments . We seek to contribute to a nascent body of literature on the measurement of related capacities . The results of the nationally representative survey point to a logical association between the previous experience of flooding and perceived severe risk associated with flooding at the household and community levels . Respondents who had received advanced warning of flooding in the past were more likely to perceive it as a serious problem , both for their households and their communities , than those who had not . This association could be afunction of the severity of the previous efforts are like to be taken to warn people of more extreme events in areas where floods are more it could also reflect that people who believe flooding is serious are more likely to seek out advance warning . The survey results also suggest that low capacities appear to be a concern in where most reported limited capacities to be prepared for , respond to , or change their livelihood strategies in response to an extreme flood . The scores across the three capacities were fairly similar around of respondents felt they were likely to be prepared in the event of a flood , felt they could recover fully within six months , and A in 10 felt they could change their livelihood if needed . is intriguing , however , that a greater proportion of respondents felt able to change their livelihood strategies than to prepare for , and to a much greater extent , cope with , an extreme flood . This may suggest that perceived levels of adaptive capacity are higher relative to the other two resilience capacities . The share is somewhat lower among people with less education and fewer assets ( though on the wealth differences are statistically significant ) however , fully 30 of respondents without education and of those from households in the poorest asset quintile felt that they would be able to adapt . The results could , in part , be explained by increasing leve of livelihood diversity and flexibility with regards to sources of income and livelihood among ( Hedges et al . 2016 ) In future work , it would be advisable to probe understandings of the adaptive question , including whether people associate it with longer term change rather than coping strategies , and the sorts of livelihood strategies people feel they can adopt . The correlations among responses to the three questions were positive but lower than expected ( less than ) reflecting diversity among households with respect to the three capacities . These moderate correlations ( and the relatively low alpha of ) also point to a lack of internal consistency , though principal components analysis showed that they loaded strongly onto a single factor . To better understand these three components , we treat them separately and defer the question of whether an index of capacities could be useful to research . What is perhaps most interesting is that though a small number of weak relationships are apparent , most variables do not exhibit statistically significant differences with regards to perceived capacities , age , education , occupation , wealth status , and place of residence . This is important given that these factors feature in objective assessments and are typically assumed to be strongly associated with household resilience ( see 2016 ) In this , our findings align with those of et al . who find that among coastal fishing communities in , Vietnam , and Sri , none of the demographic characteristics that they analyzed apart from assets had a demonstrable impact on subjective resilience , which they characterize as individual perception and about their own ability to handle future events ( et al . It is perhaps notable that the strongest relationship we find among the demographic variables is between belonging to the upper wealth quintile and the perceived capacity to adapt . Moreover , our data show that relationships between socioeconomic variables and perceived capacities are broadly similar among respondents who had recently experienced a flood , in the previous two years , and those that had not . Several areas are worth considering . On the one hand , these results could indicate that traditionally measured objective characteristics do not have a strong influence on individual perceptions of a household ability to prepare , recover from , and adapt to climate risk . If replicated in other areas and through different means , this could in turn cast doubt on the suitability of objective characteristics as effective measures of household resilience overall ( Levine 2011 ) On the other hand , a subjective approach to assessing household resilience may be a poor reflection of overall resilience those with a low resilience may perceive themselves to be more resilient than they are , and vice versa . Part of the difficulty in establishing which of these two positions is applicable is that there is no present means of validating one or the other . Both objective and subjective measures are of a somewhat intangible , contextual , and evolving concept . This is similar in many ways to difficulties faced in defining and measuring concepts such as , risk perception , and happiness ( Deeming 2013 ) More needs to be examine the effects and of resilience within subjective survey modules so as to establish the robustness of comparative subjective scores . Additional considerations relate to the validity of the survey questions themselves , response structures , or the means of administering the survey by telephone ( see Leo et al . 2015 ) Each may have affected the results of the survey and explain several of the counterintuitive findings . In addition , several of the variables focus on individual characteristics such as gender and education , making it difficult to differentiate between personal and level dynamics . To confront this mismatch , further qualitative work is recommended , to seek to establish which factors are more closely associated with assessments of preparation , recovery , and adaptation . Ultimately a term cohort study and natural experiment may be needed to effectively assess how well proposed measures of resilience , objective and subjective , measure actual resilience as demonstrated in the face of natural disasters . 129

It is striking , however , that this study finds that the strongest and most consistent relationship is with having had advance knowledge ( presumably through some form of early warning system ) of a flood occurrence . The mechanisms are unclear and will warrant further exploration , but these variables suggest potentially valuable policy levers to enhance resilience through the provision of early warning and ( to a lesser extent ) by raising awareness about the potential severity of extreme flooding . Most importantly , the results provide some confidence to the considerable investments that have gone into early warning systems ( as a means of supporting disaster risk reduction and resilience regionally and globally ( 2000 , Basher 2006 , et al . 2008 ) In particular , our findings underscore the centrality of radio in sharing information and warnings among East African communities . We believe that our study also demonstrates the ability to use subjective measures of household resilience at scale , in a national survey , and to administer them using mobile phone technology , which confers notable advantages in terms of cost , frequency , and accessibility . The latter characteristic could be especially useful following a severe climatic shock . It remains to be seen whether standardized subjective approaches to resilience be used and comparison . Although the former may be relatively straightforward , particularly if panel data are in use , the latter may require considerable thought and validation , both empirical and qualitative , to assess whether internalized notions of resilience mean the same thing across , and if data collected at such scales are meaningful . However , in related work on subjective being , there is some , albeit mixed , evidence that measures are meaningful and valid ( Jam and Ryan 2011 ) If this holds for resilience , then subjective tools may offer some promise in tracing progress in over time and across at local , national , and international levels . CONCLUSION The research presented in this paper represents one of the first efforts to collect nationally representative data on subjective aspects of , namely perceptions of the capacity to prepare for , to recover from , and to adapt to an extreme flooding event . We also explore the for collecting such data via a mobile phone survey , taking advantage of an ongoing panel survey in . We ind that while some factors traditionally associated with household resilience such as asset wealth are strongly associated with assessments , others like levels of education , livelihood types , and degree of urbanization have weak and in some cases nonexistent statistical relationships to subjective resilience . However , receipt of advance knowledge of flood risk appears to be one of he strongest of a household perceived ability to deal with risk , with notable policy relevance . Above all , the research underlines the need for greater recognition of subjective elements of resilience , not only with regard to how psychological and cultural factors may contribute to a household ability to deal with climate risk , but also factoring in people knowledge of their own . Whi the work we have presented suggests the approach we adopt is potentially useful , it is necessarily far from indicative or comprehensive at this stage . Further testing of this instrument and of other efforts to measure perceptions of resilience , alongside objective indicators , is warranted . This includes examining the implications of different definitions and of resilience on scores exploring different scales to measure subjective resilience assessing how subjective resilience changes over time and across and establishing the effects of various cognitive biases . This research also draws attention to a more acute issue facing the study of resilience and capacities , namely the lack of a gold standard of what constitutes against which attempts at its measurement could be triangulated . That such a standard might itself be context specific adds yet an additional layer of complexity to this , yet vitally important , concept . lood risk was chosen specifically given that it is a rapid onset shock that is easily communicable and defined in a survey context . In , flooding is a hazard that affects large areas of with recovery typically occurring immediately after the cessation of a flood . It is worth noting that extensive flooding had occurred two weeks prior to the survey ( May 201 ) affecting areas of Dar es Salaam , Arusha , Tanga , and . et al . apply a question to represent household resilience in its entirety . Here we choose to disaggregate further by examining distinct capacities . support was provided by the Global Resilience Partnership . he individuals and households who participated in this round were assigned weights to adjust for and design error ( date unknown ) The resulting data are intended to be representative of the adult population of mainland not including ( 2013 ) one respondent , baseline information was not available and so the corresponding data were removed . Because the za survey is administered by phone , each time it is conducted , the respondent is asked to give their name . In this round , respondents gave a different name than in the baseline and 32 respondents did not provide a name . We removed all responses . 130

The Whitney statistic ( for two groups ) and the test ( for more than two groups ) were selected as the test best suited to ordinal responses ( following and 2010 ) although it does not permit incorporating the complex stratified survey design . tests do not make assumptions about the underlying distribution of a variable but are less powerful than parametric tests . The sample size is not large enough to permit analysis by subregion apart from by zone ( Sana , personal communication ) The belief that flooding posed a problem to the community and the household were highly correlated we chose to include the ormer because the bivariate analysis revealed stronger relationships with the capacities . We restricted the focus to occurring in the last two years to ensure a relatively recent and consistent frame of reference . 10 Because almost all respondents were household heads , we focused our analysis on the gender of the respondent rather than versus male headship . 11 The wealth index was generated by principal components analysis using the following household assets radio , mobile phone , ridge , sofa set , cooker , motor vehicle , livestock , and water pump ( personal communication ) 12 The statistics presented here are for the population , they incorporate the complex sampling design , while Appendix presents the unweighted data and test statistics for these data . In practice , the differences between the averages derived from weighted and unweighted data are very slight . 13 It is not feasible to compute a measure of goodness of fit for the ordinal that takes into account complex sampling design in . To give an indication of the fit , we computed the Pseudo for unweighted specifications of these regression , which yields values of about . 131

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Measuring Household Resilience to Floods a Case Study in the Vietnamese River Delta by and Helen James This article was originally published in Ecology Society , 18 ( This work is licensed under a Creative Commons International ( license ABSTRACT The flood is a phenomenon in the Vietnamese River Delta ( Although people have experienced the impact of floods for years , some adapt well , but others are vulnerable to floods . Resilience to floods is a useful concept to study the capacity of rural households to cope with , adapt to , and benefit from floods . Knowledge of the resilience of households to floods can help disaster risk managers to design policies for living with floods . Most researchers attempt to define the concept of resilience very little research it in the real context of living with floods . We employ a subjective approach to measure households resilience to floods . Items that related to households capacity to cope with , adapt to , and benefit from floods were developed using both a scale and dichotomous responses . A factor analysis using a standardized form of data was employed to identify underlying factors that explain different properties of households resilience to floods . Three properties of households resilience to floods were found ( households confidence in securing food , income , health , and evacuation during floods and recovery after floods ( households confidence in securing their homes not being affected by a large flood event such as the 2000 flood ( households interests in learning and practicing new farming practices that are fully adapted to floods for improving household income during the flood season . The findings assist in designing adaptive measures to cope with future flooding in the . Keywords impacts floods River Delta resilience vulnerability INTRODUCTION Floods are a familiar and frequent feature of life in the Vietnamese River Delta ( Socialist Republic of Vietnam 2001 ) Among disaster events , flood frequency , damage and mortality were ranked as the second most severe after the impacts of typhoons in Vietnam ( and To 1997 ) Half of the total area ( about million ha ) is annually flooded ( Tuan et al . 2007 ) Floods bring fish , wash farm residuals , deposit silt sediment , purify water , kill pests , and wash alum , which makes the soil of the delta fertile ( Tien Tran et al . 2008 ) It is estimated that the average fish capture in the delta is about 500 per household per year , providing a significant protein source for local people ( River Commission ( 2002 , and Binh 2004 ) Every year , the flood deposits around 150 million tonnes of fertile sediment on paddy fields , so rice farmers achieve good yields after every flood season thanks to water and sediment brought by the flooding ( Tien ) Traditionally , people relied on floods for building their livelihoods in the flood prone region of the delta ( et al . 2009 ) More recently , farmers can develop livelihoods to improve household income during several flood months ( 2008 ) However , some people are vulnerable , while some are resilient to flood events ( et al . 2006 ) The flood can be seen as an external shock if the flood is either too big ' or too small , it exceeds the coping capacity of households . Local people distinguish between flooding that is moderate and small ( Tien ) The flooding of 1998 was thought to have been the smallest flood in the past 80 years ( Figure ) A small flood often does not cause damage to property , houses , crops and other livelihood activities and assets , but it affects rural livelihoods in different ways . Poor people are more likely to lose their income from fishing activities as they can not catch many fish due to low water . The large floods occurred in 1850 , 1937 , 1961 , 1966 , 1978 , 1984 , 1991 , 1995 , 1996 , 2000 , 2001 , and 2002 ( Can Tho University 1995 , Socialist Republic of Vietnam 2004 ) The worst flood , in 2000 , affected 11 million people living in 610 flooded communes , of which million people lived in the 77 most affected ( communes ) where flood levels exceeded more than meters ( et al . 2003 ) In addition , more than houses were inundated households had to be evacuated households needed emergency support and high school students had to stop their studies ( Tien ) About ha of rice crop were completely destroyed and an additional ha of rice were inundated and so had to be harvested immediately ( and Hang 2003 ) The total direct economic cost of the 2000 flood was estimated at million ( in 2000 ) There is additional evidence that a rise in sea level due to climate change will increase the risk of flooding in the , which will affect the livelihoods of millions of people ( et al . 2001 , et al . 2007 , et al . 2008 , Reid 2008 ) Sea level is expected to increase by 75 by the end of the century in Vietnam Delta ( Ministry of Natural Resources and Environment 2009 ) 136

Consequently , the livelihoods of people in the will be vulnerable if measures are not undertaken to cope with and adapt to future flooding . Fig . The highest water levels during different years in the ( Source Tuan et al . 2007 . coo 500 Li 400 I 300 . la . so Resilience has become a useful concept in the study of environmental hazards . The term resilience first originated from the ecological discipline . Holling ( defines resilience as a measure of the ability of these systems to absorb change of state variables , driving variables and parameters and still persist . This concept focuses on the capacity of an ecological system to absorb changes but still maintain its core function . Flood risk managers define resilience as the ability of the system to recover from floods ( In a social system , et al . define social resilience as the ability of a system to absorb external changes and stress , while maintaining the sustainability of their livelihoods . A system in this context may be a region , a community , a household , an economic sector , a business , a population group , or an ecological system ( Brooks 2003 ) Buckle ( refers to resilience as the capacity to withstand loss . Norris et al . define resilience as a process linking a set of adaptive capacities to a positive trajectory of functioning and adaptation after a disturbance . Recently , the concept of resilience has been seen in a linked social and ecological system ( et al . 1998 , 2000 , 2006 ) The resilience concept is concerned with the capacity for renewal , reorganization and development ( 2006 ) creativity ( 2000 , Maguire and 2007 ) and transformation in a system ( Walker et al . 2004 ) and capacity to maintain its identity ( Cumming et al . 2005 ) Although there are various definitions of resilience from different disciplines , three common properties of resilience dominate in resilience literature ( Carpenter et al . 2001 ) The first property is about the speed of recovery at which a system can recover after disturbance . So natural hazard researchers attempt to observe the speed of recovery after disasters as a measure of resilience ( 2001 ) The second is the magnitude of a disturbance relative to a threshold that can be absorbed before a system changes its structure by changing the processes and variables that control it ( et al . 2003 ) The final property is about the capacity to learn from and to create new things from disturbance , and to transform ( et al . 2002 , and 2005 ) Therefore , the conventional approach to measure resilience as the speed of recovery may not capture its full dimensions . Resilience of the system is dependent on several factors such as demographic , social , cultural , economic , political , type of natural hazards , and geographical setting of the place ( 2007 ) However , these factors may vary at different levels of analysis ( Buckle 2006 ) At the household level , access to agricultural land , diversity of income sources , and good housing quality create essential resources for households to cope with annual flood events in and climate change in the coastal province of Vietnam ( 1999 , et al . 2007 ) Learning to live with change and uncertainty , nurturing learning and adapting , and creating opportunities for were found as the important factors for enhancing household resilience in the Cambodian context ( and 2006 ) Marshall and Marshall ( 2007 ) identified four perceived factors that contribute to resilience at the individual level ( perception of risk associated with change , perception of ability to learn , plan and , perception of the ability to cope , and ( is ) level of interest in changes in an Australian context . 137

At the community level , Norris et al . 2008 ) identified four primary sets of capacities that enhance community resilience , including economic development , social capital , information and communication , and community competence . Economic development refers to economic growth , stability of livelihoods , and equal distribution of resources within the population ( 1999 ) Social capital refers to networks of social supports , bonding within community , bridging between communities , and networking between communities and government bodies ( 2003 , and High 2005 , 2007 ) Information and communication refer to the system and infrastructure for informing the public because people need accurate information about danger and behavioral options for them to act quickly . Community competence is about the capacity of the community to learn , work together flexibly , and solve problems creatively . These contributing factors should be measurable in the practical context . Most researchers attempt to define the concept of resilience very little research it in practice . Cumming et al . 2005 ) note that resilience is a multidimensional concept , so it is difficult to in practice . Coping with this problem , they develop a surrogate approach as an indirect way of measuring resilience ( Carpenter et al . 2005 967 ) and ( 2006 ) adopted the surrogate approach to resilience from livelihood perspectives in rural Cambodian villages using a subjective approach . However , and ( 2006 ) only explore the of households and communities in a qualitative manner they do not attempt to quantify resilience indicators at a household level . It is argued that is what people think and feel about their life or subjective ( and 2009 ) The subjective approach was widely accepted in poverty and livelihood studies in developing countries ( Narayan et al . 2000 ) However , little is known about different dimensions of households resilience to floods in a real living with floods context . Knowledge of the ability of households to cope with , adapt to , and benefit from floods reflects their resilience , but there is no study that the concept in the . METHODS Three communes ( Phu , My Tay , and An ) were selected for this study to represent different flood and socioeconomic conditions of the ( Figure ) The socioeconomic conditions and livelihood activities of the three locations are represented in Table . Fig . The River Delta and location ofthe study sites . Source ( editor ) 2012 . Thailand Gull Provincial center Country Provincial um Dismal line Roads Rivers locations 138

The study employed both qualitative and quantitative research approaches to conceptualize household resilience to floods . The three key qualitative data collection approaches for this study included interviews with key informants , focus group discussions ( and field observations . Four and some 10 interviews were carried out in each commune , each covering a range of social classes and gender . Information from the qualitative research was used for designing the structured questionnaires for the household survey in August 2010 . Table . Socioeconomic conditions and livelihood activities in the three study sites , demographic and Selected conditions Phu commune ( My Tay commune Aii ( Population ( number of people ) Population density ( persons per ) 212 637 194 Households Land area ( ha ) 114 Flood depth ( over months ) 11 ) 45 months ) Ill ( The study used a multiple items approach using both scales and a dichotomous response to design questionnaires for measuring household resilience . As noted by de ( 2002 ) it is beneficial to use multiple indicators to measure the complexity of a concept . Multiple items also help to increase reliability and precision of the measure . The multiple item approach using scales was widely accepted in measuring individual resilience to stresses in psychological disciplines ( and Young 1993 , Connor and 2003 , Yu and Zhang 2007 , Baek et al . 2010 , Wang et al . 2010 ) and individual resilience to institutional changes ( Marshall and Marshall 2007 ) As rural households in the have experienced the impacts of annual flood events for years , we argue that using a subjective approach helps to identify the ability of households to cope with , adapt to , and benefit from floods . Ten statements that reflect subjective of rural households were developed to construct households resilience to floods in the . As reviewed in the introduction section , resilience is referred as the capacity of a system to cope with and recover from an external shock . Some people may argue that flood events in the are not external shocks because people have experienced the floods every year . However , we argue that large flood events such as the historic flood in 2000 can be seen as external shocks because they exceed the coping capacity of many people . Some people could cope well with the event , but many people were vulnerable to that flood . Therefore , the statements used in this approach to measure households resilience to floods are related to their coping capacities in the 2000 flood event . The statements related to confidence in securing food , income , and health of family members during historic flood events ( the 2000 flood ) and safe evacuation in future extreme flood events clue to climate change or rising sea levels , and recovery after the flood if they are affected confidence in securing homes in a large flood event such as the 2000 historic flood , and their interest in learning and implementing new ways of living with floods ( livelihoods ) In this analysis , most of the items are more likely to focus on experiences or perceptions of households in coping with floods in the past rather than the capacity to cope future flood events in the context of local climate change scenarios . Therefore , further studies should be carried out to incorporate possible changes in the flood regimes into measures of resilience . The respondents , who represent their households , were asked to rate their agreement with 10 statements . The responses on the first nine items were provided using a scale , while a dichotomous response was applied for the last item ( Table ) The rate was 10075 . The stratified sampling approach was used to divide the total population of the delta into of three communes , based on the existing socioeconomic and natural flood characteristics of the delta . The samples were chosen on the basis of social groups poor , and households . This approach has been widely used in rural development and natural hazard studies in countries ( Smith . 2001 , Tran et al . 2008 ) Within each stratum , five hamlets were randomly chosen and 30 households were randomly selected from the wealth ranking of households in each hamlet . In the case of Phu commune , 50 samples were col as there are only three hamlets in this commune . The total sample size in each case study was 150 . The exception was My Tay commune , for which there were 159 samples . The average age of respondents was 52 years old . The proportion of male respondents was higher than that of female respondents . This may cause biases in terms of differences in perceptions between males and females toward floods . The education level of and their family members was generally low . The average household size was A . The gender ratio of households was 139

equally distributed . Most respondents followed Hao Buddhism , while very few respondents belonged to the Cao Dai or Catholic religion . Poor households account for of the sample , followed by households ( and households ( 288 ) Average household income was 29180 per year ( or . in 2010 ) However , the average income of poor households was 763 per year . For households it was 25530 per year , while households had an average income of per year . The per capita income of each person was an average of per year . Per capita income in poor households was per year . In households , per capita income was , and it was in households . Table . Statements for measuring household resilience to in the Items Statements ( Mean Strongly Disagree Do not Agree Strongly Disagree know Agree I can replace my house quickly when it is affected by . I am confident that my house will not be submerged by the highest in the last 20 years . I am that my house will not 331 32 68 collapse or be swept aw by the highest in the last 20 years . Iain that my household has 37 04 enough rice to eat during the season . I am that my household will not 48 15 need to borrow rice or money from informal sources during the season . I am that my household can find a safe place to evacuate to if there is an extreme event in the ' I am that children and elderly 3856 people are safe during extreme I am that the health ofmy family 375 23 53 3018 members will not be negatively affected by . I want to learn new farming practices to 29 41 cope with . such as . prawn farming , 10 I have used new practices to cope Agree Disagree with such as and vegetables or prawn fainting . using a scale for the nine items disagree . agree nor disagree . agree . strongly agree . was according to the response ( No ) for the ten items . A factor analysis was used for combining related variables into composite variables for components of household resilience to floods . Factor analysis helps us to identify patterns in responses to a set of questions ( de 2002 ) The purpose of this technique is to reduce the large amount of variables to a smaller set of underlying variables by creating factors ( Kim and Mueller 1978 ) The principal component factor method is used in this analysis . There are a methods involving rotation variables including the method , the method , and the method ( Kim and Mueller 1978 ) One of the most frequently used methods is the method , which aims to minimize the number of variables that have a high loading on a factor . This approach was widely used when identifying the factors of the vulnerability analysis ( Cutter et al . 2003 , 2009 ) Because binary variables were not suitable for a factor analysis , each item response was standardized ( before conducting a factor analysis using software . This method was used by identifying underlying factors in measuring social vulnerability to natural hazards ( Cutter et al . 2003 ) Factors will be selected if they have an Eigenvalue greater than one . The results of factor analysis from were also triangulated by using software with the original nonstandardized data . 140

RESULTS Definition of resilience to floods Results from factor analysis indicate that nine of ten statements reliably contribute to the scale , and formed the basis for measuring household resilience to floods ( Table ) The factor analysis in shows that the responses to the statements were best described by three factors that represent three components of resilience . The finding from the factor analysis conducted in showed similar results , including three factors comprising nine items . These total factors in represented of the variance . The first component represents of the variance , including five statements ( lo , relating to securing food , income , health , safe evacuation during the flood season , and recovery after floods . The second component , representing of the variance , consisted of two statements ( and ) related to the level of confidence of households that their houses will not be affected ( submerged or collapsed ) by future floods as large as the threshold flood of 2000 . The third component representing of variance was comprised of two statements ( and 10 ) related to the level of interest in learning and conducting new farming practices for living with floods . Reliability analysis shows that alpha coefficient of factor one is factor two is and factor three is . Table . Factor matrix of household resilience , River Delta , Vietnam , 2010 ( nine standardized items ) Items Statements Factor Factor Factor Factor ' I can replace my house quickly when it is affected by . I am that my household has enough rice to eat during the season . I am that household will not need to borrow rice or money from informal sources during the season ?

I am that my household can find a safe 023 place to evacuate to if there is an extreme event in the future . I am that the health of my members 059 will not be negatively affected by . I am that house will not be submerged by the highest in the last 20 , I am that my house will not collapse or be swept away by the highest in the last 10 . I want to learn new farming practices to cope with , such as fishing . prawn . 10 I have used new fanning practices to cope with . such as . prawn . were using a scale for the fu st nine items disagree . neither agree nor disagree . agree . strongly agree . Statements were 011 a binary scale ( All items were standardized into ( Selected factors have greater than . Selected have factor greater than Total is 68 . Interpretation of resilience components Confidence to secure food , income , safe evacuation during flooding , and recovery after floods Results from Focus Group Discussions ( and interviews reveal that participants are concerned with several issues for maintaining livelihoods during and after floods . These include ( capacity to secure food , income , health of family members during the floods , lo ) capacity to find a safe place if evacuated during floods , and ( capacity to recover if houses are affected . 141

Firstly , floods occur for two to six months per year , so they often disrupt the income sources of some social groups . Poor livelihoods rely heavily on collecting fish and aquatic resources , and agricultural wage labor during the flood season . When a large flood event occurs , there are strong winds and giant waves that disrupt daily livelihood activities . So , if households are not confident that they will have sufficient food and income to survive during flooding , they feel that they are vulnerable to floods . Medium and households reported that they are less vulnerable to floods as they have sufficient savings to use during the flood period . A poor woman , aged 26 , living in hamlet , Phu commune , Tam Nong district , Dong province , and a second poor woman , aged 33 , said that poor people worried seven to eight times more during flooding , while households only worried two to three times more . They are concerned about a shortage of income for purchasing rice ( January 2010 ) However , if they can access resources from family members , neighbors , and social networks , they may be confident of securing food and income during the flood season . For example , seasonal migration may provide to send to their family members to help them survive during the flood season . The president of the My Tay commune reported that there were about seasonal migrants in this commune in 2009 . Some poor migrants go to Ho Chi ( City to work in the construction sector , such as builders , to avoid the floods and come back to do agricultural labor in the dry season . Other migrants stay permanently in city , if they find a good job . There seem to be two types of migration push and pull . Some successful migrants send to their family . For example , one man has two sons working in City they send him a remittance each month . He can live well with the floods now . However , migration is not stable for some social groups ( interview on September 2010 ) A poor women , aged 32 , living in Phu commune , said that her husband works for a construction company in city as a builder . income from laboring in is more stable than working in this Phu commune . Some days are off , but some days we work . The job is not secure here ( interview on September 2010 ) in contrast , seasonal migration provides an important opportunity for coping with floods , but it is also a challenge for some people . Some people can not save money or even go into debt because they do not find a good job in city . A poor woman , aged 35 , living in Phu commune , said that during the flood season , most people in her places residential clusters close their houses and go to Ho Chi city to work in the construction sector and work in garment factories . She indicated that Working in city is for survival during the flood season . My husband and I went to and returned to do agricultural labor in the dry season . Life in is also very hard . We returned without any money . We lost networks in the village . We feel life is more difficult than before interview on September 2010 . Child deaths during the lood season were cited as the key concerns of most participants in twelve . Children were recognized as the most vulnerable group , especially during large flood events . Deaths of children were not directly caused by disease , but related to drowning due to lack of supervision from caregivers . Many examples show that children drowned while their parents were doing housework , sleeping at night , and fishing on the . Children deaths were mostly reported in the highest and moderate flood prone regions , whi very few cases were mentioned in the low flood region . importantly , most people said that child deaths were more likely to happen in households who settled in the paddy fields . Poor households , who went fishing during the floods , had to leave their children at home a one or with their brothers and sisters or relatives . Lack of supervision resulted in vulnerability to floods . A primary teacher in Phu commune , aged 41 , recalled that his house floor was submerged in the 2000 flood . He had to remove the wooden to keep the house from being swept away by the floodwater . His family ( himself , wife and little son ) had to survive in the only bed for several days . They cooked , ate and slept , toileted on the bed . Suddenly , his son fell into the floodwater underneath the floor . Luckily he him in time . if he had not grabbed him , his son would have been swept away by the strong waves ( Evacuation during is one of the most important indicators of living with floods at the household level . if the flood submerges homes , having a safe place to which to evacuate provides confidence to cope with floods . in the flood of 2000 , many people could not move out of their homes for several days . They had to stay on the roofs of their houses when the water was rising . Their lives were at risk all the time during flood . A poor woman in Phu commune , aged 35 , said that her house was deeply submerged in the 2000 flood all clothes were wet , while there was no rice to eat . No family members could sleep and they lost weight . Her house was located along the canal banks and was cut off by floodwaters . it was very difficult to find a safe place to evacuate to ( January 2010 ) Recovery after floods was considered another important indicator of coping with floods . Evidence shows that the flood in 2000 destroyed and submerged thousands of homes in the . if someone could recover more quickly they would be more resilient to the impact of the flood . Poor people lived in unsafe conditions ( in simple houses without protective materials inside the flooded fields ) which were easily destroyed by flooding and during storms . 142

Confidence to secure homes that would not be affected by floods such as the 2000 flood As reported by most participants in , the flood in 2000 can be seen as the historical flood . In flood years , many homes were submerged or destroyed by flooding . The flood level in 2000 was considered as the threshold for designing housing structures by most rural households . Through field observation and with participants in three study sites , it was found that both richer households and poorer ones that resided in residential clusters were more likely to be confident that their houses would not be submerged or destroyed by a flood as large as the 2000 flood . This indicator reflects the threshold that rural households can cope with floods in terms of the housing sector . Two items ( items and ) which formed the factor explaining the threshold were included ( Table ) Interest in learning and implementing livelihoods during floods As noted by Paul ( 1984 , 1995 , 1997 ) and Shaw ( 1989 ) floods are hazards as well as resources for development . Some people may see floods as disasters , but others consider floods as benefits ( et al . 2006 ) The large flood event in the led to significant costs to households and communities , but farmers can also benefit from the resources that the floods give to people . In particular , such floods bring abundance of aquatic resources such as fish , crabs , and snails . Many farmers rely on income from collecting fish , crabs , and snails during the flood season for maintaining livelihoods . However , poor people may not have enough financial resources to buy fishing tools ( a small boat , nets , or traps ) which may make them more vulnerable to food insecurity during the flood season . In some cases , they borrow informal credit for purchasing a boat and nets . However , they may incur debt during large floods that may sweep away their nets . The following interview illustrates the ways that people completely adapt to the flood season in the highest flood prone region . A rice farmer in hamlet , aged 45 , Phu commune , has one hectare of rice land . He traps fish during the flood season . He loves the flood season very much because he can earn an extra per day from this activity ( interview on September 2010 ) Interestingly , rural people have adapted to floods using an innovative way for improving their household income in the moderate flood prone region . The golden snails have been seen as pests for rice farmers in the . However , they become resources for people who can collect golden snails for maintaining livelihoods during flooding . Most poor and medium income households engage in these livelihood activities because they require less capital investment as well as labor . In particular , young couples who are poor and landless are more likely to participate in this activity for survival , while households are more likely to accumulate capital by conducting this business . he household income of a farmer in commune , aged 45 , relies on rice farming ( two crops ) and collecting golden snails during the flood season . He said that local people are very interested in livelihood activities during the flood season . He uses a small motorboat to travel to many places in An , Dong , and provinces to collect snails . He can earn a net income of around ( 15 ) per day . He can save at least mil ( in a flood season , which equals the net income rom ha of rice . realized that the water season is a wonderful income season for his family and his neighbors . Fish , prawn , and duck farmers can buy snails , a cheap source of protein to feed their stock . Children and old people in his neighborhood can earn about ( a day to take off the snail shells for him interview on January 2010 . people not only benefit from exploiting the natural fish , crabs or snails from the , but also they create new farming activities that are totally adapted to floodwaters . For example , medium and farmers who have paddy land are more likely to grow prostrate ( a type of aquatic vegetable ) integrate duck and fish farming systems , and cultivate prawns during the lood season . These farming activities were introduced by farmers in 2001 . The activities were first tested on an individual basis and expanded to the community level . The stories that follow show that farmers are more resilient to floods by transforming flooded fields into farming practices . A 61 old man , living in An commune , owns ha of rice land . He grows two rice crops in the dry season and uses an integrated arming system during the water season . In particular , Sau raises ducks and fish in the flooded paddy fields using net fences to eep ducks and fish inside . He started to implement this system five years ago and the system is quite sustainable . He said that after the summer rice crop , he put nursery fish into the paddy fields . Fish eat rice straws , worms , and falling rice husk . Additionally , we adds ducklings and ducks into the paddy fields . Ducks also eat the remaining falling rice husk . After four months , he harvests fish , ducks , and eggs . The net benefit of these resources is much greater than the net benefit of the main rice crop . The fish and ducks make the paddy soil more fertile , so rice farmers apply less fertilizer in the next crop . This system is more resilient to the water season . can gain double benefits from the system . However , the system is not suitable for the landless and poor . It requires land and capital for investment , which the poor can not afford ( interview on January 2010 ) Another man , aged 40 , with nine years of schooling , lives in Dau hamlet , commune and owns ha of rice land . He grows two rice crops in the dry season and raises prawn in the fields in the flood season . He has adopted new prawn arming since 2007 . He uses bamboo fences and nets to keep the prawn inside the fences and uses floodwater for farming prawn . said that the water season is good for prawn farmers like him . Although the system is very risky with the market as well as water 143

environment , it brings enormous benefit . Compared to two rice crops , this farming practice generates greater benefits . In 2007 , he earned a net benefit of 70 million ( from prawn ( interview on January 2010 ) DISCUSSION AND CONCLUSION This study has identified the key characteristics of households that determine the capacity of households to cope with , adapt to , and benefit from floods . As discussed by de ( 2002 ) it is better to use multiple items to measure a multidimensional concept . Although resilience is a multidimensional concept , it can be grouped into three different components in the context of living with floods in the . Three factors found by this study include ( the capacity of households to secure food , income , health of their family members during the flood season , safe evacuation during future extreme flood events , and recovery after extreme floods if they are affected , the capacity of households to secure their homes during large floods such as the historic flood of 2000 , the level of interest in learning and carrying out new livelihoods during the flood season to improve their livelihood security . These three factors are consistent with general resilience theory and practices . A novel point of this study is to identify the capacity to learn from disturbance for genuine adaptation to floods . The ways that farmers use floodwater for growing prawns , fish , eels , and vegetables are very innovative and transformative . The first factor of resilience in this study re to the degree to which households are capable of . This characteristic has been mostly accepted by resilience researchers ( Klein et al . 2003 , Carpenter et al . 2001 , 2006 ) However , it is difficult to translate the term capacity for into the real context of living with floods in the . In particular , the capacity for comprises several dimensions of livelihoods with people being mostly concerned about the impacts of previous flood events . These dimensions are confidence that they have sufficient food to eat during the flood season , confidence that they do not need to borrow informal credit during the ood season and can find a safe place to evacuate to during future extreme flood events and confidence that the health of their family members is secured . Because the flood season often disrupts income streams of some socioeconomic groups , borrowing money from local informal credit is the common way of coping with six months of flooding . Accessing informal credit with high interest rates is the fear of most poor households during the flood season . households are the most vulnerable groups from being in chronic debt with informal credit providers because they do not have land title to borrow against for formal credit to survive during the flood season . However , if households are confident that they will not borrow this type of credit , they may be able to borrow from their relatives , family members , and the banks with low interest . These sources of support are important for them to maintain their livelihoods during the flood season . Health of family members , especially , is the most serious concern during floods . Many children died because of drowning . If households are confident that they can keep their children secure in the face of flooding , they are more likely to be resilient . In particular , rice is the most important staple food for rural households in the . If the households do not have enough rice to eat , they feel very anxious about coping with he flood season . In the developing country context , especially Southeast Asia , food sources are often at the backdoor in nearby and with close neighbors and do not require access to highly developed transport and communications systems . A medium woman , aged LOLO , living in Phu commune , said that a good neighbor used his small ferry to evacuate people , animals , and supply food to people when the large flood of 2000 submerged most houses in the village . He mobilized local resources ( food and clothes ) from the less affected villages to help them . She said that transportation by boat is the most effective means during the large flood season . may help some people to maintain their income during the flood season . But in some cases , migration does not necessarily help some households to improve their income because the living cost in Binh or Ho Chi City is relatively high . So , many migrants reported that they return homes without money and sometimes are in debt . As a result , they become more vulnerable to future flood events . A poor woman in Phu commune , aged 38 , with nine years of schooling , said that she has lived in this village for 30 years . She originated from Cao district of Dong province . She used to live by an internal canal subjected to annual flooding . Her income is mainly from fishing and collecting . However , the floods have been small in the past several years and she could not catch much fish . She decided to go to Binh to work in a factory . However , the salary was not sufficient for her family to survive . She decided to return homes and her livelihood is difficult now . The second characteristic of resilience is related to the amount of disturbance that a system can cope with , while still maintaining its function in terms of the housing sector . This characteristic has been widely accepted in recent natural hazards literature . In this study , the amount of disturbance is seen as the amount or magnitude of flood events in the . The historic flood of 2000 was perceived as the most serious , destructive flood of the last century in the . Thousands of homes were submerged , damaged , and swept away by the flood . Since that event , local people upgraded their house floors or raised the house foundation above the flood level . However , not all households can adjust their home to a certain level of stability because of financial barriers . The capacity to secure their homes 144

so that they would not be affected by floods like the 2000 flood is determined by their or capacity to cope with floods . Those who can upgrade their house are more resilient to the impacts of floods . he third characteristic of household resilience is about their interest in learning and doing new creative things . This is consistent with the third of resilience , namely , the capacity to transform and innovate ( et al . 2002 , Walker et al . 2001 , and 2006 , Marshall and Marshall 2007 ) However , what are the new creative things in this context ?

Many farmers developed an innovative way of living with floods by exploiting the flood benefits as well as carrying out farming activities . These farming allow them to improve their household income and create jobs for local laborers to maintain their livelihoods during flood months . emerging farming practices not only provide income and food security for rural households , but also help to maintain agricultural sustainability . The perception of floods transformed them from natural disasters into beneficial resources for development . he subjective approach of measuring households resilience is used to reflect the actual capacity of households to cope with lood events . Because resilience is a multidimensional concept , the use of multiple items can help to capture a wide range of factors that contribute to households resilience in a specific context . The use of standardized data yielded better underlying factors than the data in this context . While the former approach captured nine items forming three factors , the latter approach only obtained five items forming three factors ( Appendix A ) A standard factor analysis can not deal with dichotomous variables , but the standardized data approach allowed a factor analysis to be carried out with dichotomous responses . This approach was well validated using and software ( Appendix A ) By combining qualitative and quantitative analytical methods , new aspects of resilience among farmers in the have been highlighted . The responses and adaptive behaviors enable some of these farmers to sustain livelihoods during floods and recover quickly afterward . the use of the subjective approach to obtain the perceived capacity at the household level to cope with historical lood events may be prone to some limitations in explaining the resilience of households to future large flood events in the context of climate mange . Although item in Table reflects the capacity to evacuate in a future extreme flood event , it does not capture all the dimensions of resilience in future large flood events . For example , with regard to the level of interest in learning and carrying out new livelihoods , this measure does not take into account future large flood events or very small flood events that may occur due to climate change , which may exceed the capacity of households . This is a key limitation of this research . Therefore , it is important research to integrate climate change scenarios into the questionnaires for assessing the resilience of households in the . is also argued that the of resilience may include demographic , social capital , cultural , economic , and political , aspects of the natural hazards , information , and the geographic setting of places ( 2007 , Norris et al . 2008 ) For example , information and social networks are very vital for people in disaster prone areas to make behavioral decisions . But these factors may be variable at different scales of analysis . The social capital of households is important for accessing resources to cope with annual flood events . some of these factors are not included in the current measures of households resilience to floods within the scope of this research . The current measures of households resilience were more likely to focus on the concept of resilience in the real context of living with floods in the . Some factors such as social capital are often treated as exogenous variables ( Narayan and 1997 ) The resilience properties obtained from the factor analysis from this research will be used as latent variables to investigate their relationships with social capital and socioeconomic variables of households in further analysis . At present , the current measures focus on the experience or perceptions of households in coping with past flood events , but do not permit interpretation of the results in the context of climate change . Further study should be carried out to improve the current measures of resilience in future flooding under predicted climate change scenarios . 145

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Assessing Vulnerability to Urban Heat A Study of Disproportionate Heat Exposure and Access to Refuge by Status in Portland , Oregon by Jackson , Dana , Ryu and This article was originally published in the International Journal Environmental Research and Public Health , 15 ( I This work is licensed under a Creative Commons Attribution International ( BY ) license ABSTRACT Extreme urban heat is a powerful environmental stressor which poses a significant threat to human health and . Exacerbated by the urban heat island phenomenon , heat events are expected to become more intense and frequent as climate change progresses , though we have limited understanding of the impact of such events on vulnerable populations at a neighborhood or census block group level . Focusing on the City of Portland , Oregon , this study aimed to determine which populations experience disproportionate exposure to extreme heat , as well as the level of access to refuge in the form of public cooling centers or residential central air conditioning . During a 2011 heat wave , temperature data were recorded using a collection method , then extrapolated to determine average temperature at the census block group level . factors including income , race , education , age , and English speaking ability were tested using statistical assessments to identify significant relationships with heat exposure and access to refuge from extreme heat . Results indicate that groups with limited adaptive capacity , including those in poverty and populations , are at higher risk for heat exposure , suggesting an emerging concern as it relates to climate change . The paper concludes by emphasizing the importance sensitivity and inclusion , in combination with effectively distributing cooling centers in areas where the greatest burden befalls vulnerable populations . Keywords urban heat vulnerability environmental justice heat exposure resilience . INTRODUCTION Extreme heat poses a to human populations , with numerous implications for public health , economic stability , and quality of life . Past heat waves have had devastating , deadly outcomes worldwide , and such events are expected to increase in intensity , frequency , and duration as climate change progresses . Although human settlements of any type may experience the negative effects of extreme heat , these are and will continue to be most pronounced in urban areas , the development practices of which are highly correlated with rising temperatures . Currently , more than 50 of the world population is located in urban areas , and that figure is expected to reach over 66 by 2050 with so many people potentially at risk of exposure , it is imperative that local governments and planning practitioners recognize varying degrees of vulnerability among urban residents . Urban heat as those above the percentile of historic temperatures 13 an environmental stressor , placing economic , infrastructure , and human health burdens on society . As a stressor , urban heat can create vulnerabilities , which may be understood as a combination of three factors exposure , sensitivity , and adaptive capacity . Exposure refers to an individuals contact with a stressor , either from living , working , or spending time in an affected location . Sensitivity is the point at which exposure becomes dangerous to an individuals health 18 . Finally , adaptive capacity refers to one ability to change exposure or sensitivity , or to cope with an extreme event . Regarding urban heat , indicators believed to enhance adaptive capacity include high income , social cohesion , and knowledge of hazardous environments . Given these conditions , it may be reasonable to categorize extreme heat exposure as an environmental justice issue . The phenomenon central to this study is the urban heat island ( effect , which has been known to researchers since the century , and indicates a strong correlation between urban environments and high temperatures . impervious surfaces and anthropogenic activity within cities portend rising temperatures , as does the relative scarcity of elements such as trees and grasses . A higher frequency of regional extreme heat events , as such , will amplify temperatures , and generate in areas that have greater amounts of heat absorbing surfaces . While early studies focused on the comparative temperatures between urban and regions , the emergence of mobile sensors , highly accurate global positioning systems , and computational software allows for the comparison of spaces , measuring variation in temperature distribution across a single city . Past research has utilized infrared satellite data for this purpose , though traverse measurements ( used in this 149

study ) can provide a detailed representation of heat exposure at a smaller scale . From an environmental justice point of view , the existing research emphasizes point source pollution , though it has become clear that climate change affects communities differentially and creates novel impacts never before witnessed in traditional environmental research . As such , we argue that climate change is catalyst for injustice . While some of the effects can be easily observed at the national level , particularly in the world poorest countries , there is relatively little understanding of the impact at a more granular scale . Needed are , conceptual , and help us to identify those communities disproportionately affected by , and strategies that can help to reduce vulnerabilities . This study provides new evidence of disproportionate exposure to climate change at a local level , as well as access to refuge , an understudied facet of adaptive capacity . Previous studies indicate a relationship between factors and . Income is quite predictive of vulnerability ( inverse relationship ) though it is possible that other indicators also play a role . If so , urban heat exposure may be framed as an environmental justice or climate justice 44 issue , disproportionately affecting marginalized groups with limited adaptive capacity . This study aims to identify such populations in Portland , Oregon by assessing ( disproportionate heat exposure among groups and ( disproportionate access to refuge ( either public refuge facilities or residential central air conditioning ) resulting in heightened or lowered adaptive capacity . An statistical and spatial analysis will reveal significant , inequitable relationships , validating the application of an environmental justice lens in addressing urban heat resilience . MATERIALS AND METHODS . Study Area Our assessment occurs in a Pacific Northwest city of the United States . The City of Portland , Oregon is located at approximately North , West , at the confluence of the and Columbia Rivers . The city covers approximately 345 square kilometers , with of a population of nearly as of 2016 45 . The City of Park , Oregon is located within northeast Portland and , though an enclave of the City of Portland , has been excluded from the study . Due to the fact that summer temperatures have an average monthly highs of , and for June , July , and August , respectively 46 , Portland offers several advantages to conducting an assessment of disproportionate effects of urban heat . First , historical high temperatures have rarely exceeded 35 , which reduces public concern for heat related illnesses . Second , as of 2013 , fewer than 3575 of households had air conditioning 47 , and communities may not have immediately available private residences to consider refuge from heat waves . Finally , Portland Climate Action Plan ( 2015 ) explicitly addresses the importance of reducing disproportionate exposure to urban heat waves , yet few actions have materialized . Data Three main data types were used in this study , all at the census block group level indicators , distribution of ambient temperatures in the study location , and refuge availability . data used include income ( percent of the population below 50 of the poverty line ) race ( percent of the population who do not as white ) education ( percent of the population over 25 years old without a high school degree or equivalent ) age ( percent of the population over 65 years old that lives alone ) and English speaking ( percent of the population that claims to have poor or no English skills ) Obtained from the Census Bureau American Community Survey estimates , 47 , these data reflect categories into which individuals have . Another , piece of data used to highlight status is presence of affordable housing , obtained from Oregon Metro Regional Land Information System 47 . In order to differentiate low and high categories used in the analysis , a clustering algorithm was used to split each variable 48 . Following an established protocol 13 , we collected approximately temperature readings during one day of an extreme heat event on 25 August 2014 , in Portland , Oregon , when the average temperature during the hottest hour of the day was in the percentile of historic temperatures for the study region . We sampled temperatures for one hour at times during the day ( and ) using vehicle traverses ( cars with a mounted temperature sensor and global positioning system ( in six predetermined sections the city . The temperature sensor consisted of a type ( 30 gauge ) thermocouple in a plastic shade tube ( 12 in length and in diameter ) mounted on the window approximately 25 above the roof of each of vehicles deployed . Each temperature sensor was connected to a device with an estimated system accuracy of and a 90 response time of less than 60 in airflow . A unit on each vehicle paired temperature measurement and location . Based on the results from the temperature collection and subsequent modeling , we created three separate heat surfaces , which are continuous descriptions of variation across the study region , corresponding to the three time periods . The resulting maps consisted of a floating point raster format and contain pixels for each of the three time periods . These three urban heat models were created using random forest machine learning on temperature data collected using traverse measurements . Multiple land uses are included in the model ( tree cover , building volume ) and the temperatures derived are representative of the under ying urban form . Earlier research suggests that evening temperatures can have the greatest impact on 150

human health , in part due to the exposure overnight , when physiological responses can be acute among those with existing health conditions . As a result , this study utilizes the evening temperature model in an attempt to identify areas with prolonged exposure to high temperatures . The model has an of and an of . Using zonal statistics in ( CA , USA ) average temperature was calculated for each census block , ranging from to . This aggregation method simplifies the , however this alteration of the raw data is deemed worthwhile in order to assess relationships with demographic data . Additionally , this is a common practice in geographic analysis . In the context of this study , refuge refers either to public cooling facilities , or availability of central air conditioning in ones home in other words , the availability of coping mechanisms . Public heat refuge data were obtained from the County Office of Aging , Disability and Veterans Services 55 . These include three County cooling centers 33 places to play in the water 59 libraries and 73 community centers . The heat refuges were using Google Earth . Nine out of 33 places to play in the water are not free for personal use , but are treated as such for the purpose of this study . Residential Central Air Conditioning ( data were obtained from the County Assessment Office 55 . Analysis This study assessed multiple facets through the use of mixed spatial and statistical methods , with the aim of identifying not only those hottest areas of the city , but also trends of disparity . Elements considered include exposure of sensitive populations , as well as their ability to cope with heat by accessing refuge . First , heat exposure was determined by mapping data at the census block group ( level . Using the raster package in statistical software , the mean of all pixels falling geographically within an individual polygon was appended onto that data table , resulting in a visual representation of spatial temperature distribution . This indicated areas of the city most exposed to extreme heat . Second , the re between various groups and areas was assessed using the Student method , where for all tests . This method reveals which sensitive groups , if any , are disproportionately exposed to extreme conditions . In each case , two groups are compared those with low adaptive capacity characteristics , and those with high adaptive capacity characteristics . Indicators included in this analysis , of each , and hypotheses tested are as follows . Average low income population Average of high income population Average low income population Average of high income population where Average low income population Mean temperature of low income block group Average high income population Mean temperature of high income block group Average population Average of white population Average population Average of white population where Average population Mean temperature of block groups with large population Average population Mean temperature of block groups with small population Average low education population Average of high education population Average low education population Average of high education population where Average low education population Mean temperature of block groups with large population with less education Average low education population Mean temperature of block groups with small population with less education Average isolated elderly population Average of accompanied elderly population Average isolated elderly population Average of accompanied elderly population where Average iso elderly population Mean temperature of block groups with large population of isolated elderly Average iso elderly population Mean temperature of block groups with small population of isolated elderly Average low English proficiency population Average of English proficiency Average low English proficiency population Average of high English proficiency population where Average low English proficiency population Mean temperature of block groups with large population low English proficiency Average low English proficiency population Mean temperature of block groups with small population with low English proficiency Average population in affordable housing Average of population in housing 151

Average of population in affordable housing Average of population in housing where Average of population in affordable housing Mean temperature within 100 of affordable housing Average of population in housing Mean temperature within 100 of housing Third , this study examined the accessibility of refuge for various populations , broken out into specific racial categories , as well as elderly ( over 65 years ) and young children ( under years ) age groups . The race groups included in the analysis are white black or African American American Indian or Alaskan Native ( Asian Native Hawaiian and other Pacific Islander ( and Hispanic or Latino . Access to public heat refuges was calculated for walking speeds of slow , normal , and fast . Maximum acceptable walking time was set at 15 min , and analyzed based on average walking speeds for sedentary elderly ( average elderly ( and active adults ( 56 . These distances ( and , respectively ) were applied using network distance analysis in to establish heat refuge catchment areas . Additionally , differences in walking access to refuges , temperature exposure , and access to residential central air conditioning ( were assessed for the aforementioned groups using covariance analysis . Using scatter plot function , percentages of residents with specific characteristics were used as variables , and the accessibility of heat refuges , and the prevalence of were used as variables ( Table ) Table . Variables used in covariance analysis . factors represented as variables ( independent ) Heat refuge factors represented as variables ( dependent ) Variables of White of Black or African American of American and Alaskan Native ( of Asian of Native Hawaiian and Other Pacific Islander ( of Hispanic or Latino of residents under age ( young children ) of residents over age 65 ( elderly ) Urban Heat Index ( Central units ( Accessibility to public heat refuges ( fast , average , and slow walking speeds ) First Variable ( Second Variable ( RESULTS Results have been divided into three sections . We begin by providing background on the and its integration with the data . We follow with outputs from statistical analyses , which identify relationships between heat exposure and specific groups . Finally , we identify the accessibility of heat refuge options ( public cooling centers or central air conditioning ) to those who have a low level of adaptive capacity . Ambient Temperature Distribution The model employed shows a concentration of areas to the east side of the city , while the west side of the city is relatively cool ( Figure ) Also , we note two implications of converting heat data to . First , the block groups are not coterminous with the data the boundaries do not exactly overlap , which means that each block group draws from the nearest temperature . Second , since the map is at resolution and the block groups are much larger , all temperature values within a were averaged . Although these limitations may reduce the overall accuracy of the precise temperature in each , our purpose is to evaluate broad relationships between and , rather than a precise assessment . Heat Exposure by Group The results of statistical ( Table ) reveal significant relationships between heat exposure and populations that are , or poor English speakers all of these groups , as well as those living in affordable housing , experience higher temperatures than their wealthy , white , educated , counterparts . Isolated elderly is the only tested indicator that did not significantly correlate with higher temperatures . 152

. Exposure and Access to Refuge The network distance analysis of public refuge access shows that of the city population can access a refuge on foot , depending upon walking speed ( Table , Figure ) These cooling centers are most numerous in North and Northeast Portland , while the farthest eastern and western regions of the city offer fewer options for public refuge . Figure . Comparison of the original raster format of the distribution of ambient urban heat ( left ) and the block urban heat ( right ) Urban Heat Island Model Urban Heat Island Model Census Block Groups ( Table . Results of Student Statistical . Tests which have a greater than are considered to have failed to reject . 95 95 Variable Description Conclusion ti bel . Extreme Poverty 507 , 20043 Reject Ho High Racial of population who do , not identify as , 10 0553 Repel Percent of population without Law Education a high school diploma 1044 0572 Reject or equivalent Isolated Elderly ' 0206 Fail to Reject Ho years old and live alone Pom English of population with . Skins English speaking abilities 2446 10 , 153

Figure . Catchment areas of public heat refuge access for slow , average , and fast speeds . Catchment Areas of Public Heat Refuges Slow Walking Speed i ' Average Speed , Table . Percentage of the city having access to one or more public heat refuges ( cooling centers ) Slow Walking Speed Average Walking Speed Fast Walking Speed Access to Public Refuges Based on the results of covariance analyses , distinct inconsistencies emerge and define disproportionate exposure to high temperatures , and accessibility to and public refuges ( Table is ) The figures in this table represent expected changes in the dependent variable for a increase of the independent variable in question . For example , the value between White and indicates that for a 100 increase in white population , a degree Celsius decrease in temperature would be expected . Table . Results of covariance analysis relationship between factors ( independent variable ) heat exposure , and refuge ( dependent variables ) While Black Asian Hispanic Children Elderly Temperature Change ( single unit increase of indicators Central Air Conditioning ' units ) Refuge Fast Speed ' Average Speed Slow Speed ) Note ( 154

. Exposure to Urban Heat The white and elderly populations have a negative relationship with ( and , respectively ) which is statistically significant . This means that census blocks with a higher number of white residents and older adults as a percentage of the total census block population are more likely to have lower temperatures during an urban heat event . For example , for every 10 increase in the white population , temperatures are lower by on average during a heat event . By contrast , a larger American population , along with , Hispanics , and young children all have a positive linear relationship with . For example , the coefficient for is , meaning that for every 10 increase in , of the total census block population , temperatures are higher by on average . The share of and Asians do not have a statistically significant relationship . This analysis is based solely on demographic characteristics as they relate to temperature and does not explicitly account for the presence of buildings , trees , or other factors which influence urban heat . However , it may be inferred that those groups experiencing the highest temperatures are located in areas which lack infrastructure , or possess built urban features that exacerbate heat . Central Air Conditioning ( Units per Area Only the white population has a significant positive relationship with per area ( On the other hand , only young children have a negative linear relationship with , which is statistically significant . For every 10 increase in white population , of the total census block population , units are likely to be higher by units per square , and for every 10 increase in young children , units are likely to be less by units on average . The share of American residents , Asians , Hispanics , and the elderly do not have a statistically significant coefficient . Public Cooling Centers When assuming the average walking speed , only the American population has a positive relationship with accessibility to public heat refuges . On the other hand , Asians and the elderly have a negative linear relationship with public heat refuges in the city . For every 10 increase in American population of the total census block population , the residents have more access by public heat refuges on average , and for every 10 increase in Asians , the residents have less access by public heat refuges . Other tested characteristics do not have statistically significant relationships with the accessibility to public heat refuges . DISCUSSION This study examined factors in relation to the distribution of urban heat in an attempt to better understand vulnerability based on ( disproportionate heat exposure among groups and ( disproportionate access to refuge ( either public coo ing facilities or residential central air conditioning ) resulting in heightened or lowered adaptive capacity . Overall , indicate that populations with low adaptive capacity characteristics also experience high exposure , and that access to refuge is influenced by status . A series of Students were performed to test the hypotheses that the difference between high and low adaptive capacity were greater than . he results of the study , with the exception of the variable isolated elderly , allow rejection of the null hypothesis , and indicate that populations with characteristics of low capacity do experience than those with high ac capacity within study area . Additionally , the analysis showed significantly higher temperatures in the area directly surrounding affordable housing compared to a random sample ( regular ) housing from similar block as . We focused on isolated elderly specifical because they have historically been disproportionately impacted by heat waves in other parts of the , though similar patterns are not statistically significant in the City of Portland . In fact , the observed of the isolated elderly ( percent of the population years old who live alone ) could be related to the spatial nature of the census block group . A test for spatial conducted using Moran I 56 showed that , while census block with a percent of isolated have statistically significant clustering ( where is random ) they are far more random in spatial distribution than the variables for extreme poverty ( high diversity ( poor English skills ( and low education ( score ue ) This notable difference in spatial shows that bloc groups with high levels of isolated elderly populations are more random distributed than the other variables , thus increasing the chances that they will have a more randomized exposure to extreme heat a less significant Student result . The accessibility analysis revealed that wa king speeds , as they relate to the distribution of cooling centers , greatly affect the percentage of areas in the city having access to heat refuge . At the slower walking speed per hour ) only of residents have access at the average ( per hour ) the percentage increases to and at the fast speed ( per hour ) it increases to . This finding reveals that even in the best case scenario ( fast speed ) less than one third of the population can access a public heat refuge . This may be especially meaningful for with mobility challenges , such as those using wheelchairs , those with 155

health conditions , and bedridden patients , though such groups have not been included in this study . The covariance analysis found racial and disparities in distribution of , and walkable access to heat refuges . Risk factors concentrate on some groups , especially young children . They are more likely to live in census blocks which are hotter during urban heat events , and with a smaller number of units . In contrast , white populations tend to live in census blocks with less effect , and more units . American populations tend to have better accessibility to public heat refuges , which may prove helpful if they are concentrated in census block groups . While analyses focusing on environmental justice have found that communities are disproportionately living near point sources , urban heat and the access to refuge arguably represent novel concern that may further deepen the inequities in society . This study does not offer a complete exploration of the factors which determine why certain groups cluster in areas experiencing higher temperatures . This is a complex question that would require a complete study of its own , though some of the likely contributing factors are known to researchers . Urban development patterns often feature lower rents in areas near large roads and buildings 57 , both of which can amplify urban heat effects . Assuming individuals with limited financial means seek out lower rent , this increases their likelihood of locating in areas with higher heat stress . A second possible factor relates to socialization and , in some cases , spatial isolation of minority communities . Such groups have a history of building social capital by in neighborhoods , as well as being coercively isolated in specific locations this could result in apparently heightened heat exposure for such groups , simply due to their proximity . In the case of Portland , local development practices have typically placed large trees and other in neighborhoods 61 , exacerbating heat exposure of and minority communities who have historically been excluded from these areas . These are multifaceted relationships that differ across cities , and are outside the purview of this study . However , it is useful to consider the underlying causes of physical clustering and resulting exposure . One major drawback to the analyses in this study is the geographic format of the data . The irregular polygon geometry of the census block group data relies on areal aggregation to protect the anonymity of individuals this aggregation of population and heat data into enumeration units can smooth the , eliminating extreme highs and lows in the process of representing the data with a single mean value . This complication is difficult to avoid , as the block group employed in this study are the highest resolution available with the required information . Additionally , the Modifiable Areal Unit Problem ( may introduce error when using enumeration units such as census block groups 62 . A potential alternative to this study would be to create an entirely new survey of randomly sampled households in the region . This potential new study could allow for a analysis similar the one performed here for affordable housing , but for all variables . A survey with a sample size high enough for statistically sound inference and analysis would be time consuming and costly , however it could potentially reveal more accurate or meaningful results . This study is also lacking in a key piece of information which would provide a more complete understanding of vulnerability though exposure and adaptive capacity have been well explored , sensitivity has not , mainly because reliable data on health , genetics , and lifestyle choices are difficult to obtain . For this reason , the definition of vulnerable populations may not be fully accurate because we do not accurately know whether individuals do not , in fact , have access to other forms of refuge ( ductless heat pump , swimming pool , alternative residences , At the same time , at the population level , the present study finds significant associations between high exposure and low adaptive capacity , which provide meaningful direction for decision makers to prioritize those areas and groups that are likely to be at high risk . Next Steps for Practitioners The results of this study may serve as a guide for practitioners in Portland , Oregon , directing attention to those areas of the city most at risk of extreme heat exposure . However , indicators can only reveal general characteristics of a population as such , community engagement in these priority areas will be a key strategy moving forward . These results suggest that practitioners will need to meet with community members directly to better understand what they experience during a heat wave , how they adapt , and what they perceive their needs and strengths to be . Rather than offering strictly external monetary or technological support , sustainable solutions may be reached by working with local organizations and individuals to build internal capacity . Given the diverse nature of marginalized groups exposed to extreme heat , it will be helpful for the City of Portland and County to release materials for such an audience . Information regarding public refuges and heat safety , as well as heat wave warnings should be issued in multiple languages and formats ( print , Messaging tailored to specific groups may also be helpful . It is further recommended that government agencies work with community organizations to disseminate information and provide refuge , as marginalized populations may be wary of government programs . Although this particular study pertains to Portland , the development of inclusive materials and interventions is a best practice for all cities . CONCLUSIONS This study provides compelling evidence that extreme heat exposure is an environmental justice issue . Exposure and adaptive 156

capacity are clearly associated with differences , and many marginalized , low adaptive capacity groups experience disproportionately high temperatures . As populations and populations are presumably to related malady , it is imperative that local governments and practitioners recognize and address social disparities in heat resilience efforts . A detailed local survey process is recommended to overcome limitations of available demographic data , though this study should provide a strong basis for program planning and outreach . Though these results are specific to Portland , Oregon , such relationships likely exist elsewhere , and it is suggested that an environmental justice lens be applied to future study of heat resilience . 157

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