Social vulnerability and adaptive capacity of a fishery dependent community in vietnam

xi Abstract Social vulnerability in this study is defined as the current exposure of a community to climate change impacts.. The community is protected by islands, but is still exposed t

MINISTRY OF EDUCATION AND TRAINING

NHA TRANG UNIVERSITY

_

FULL NAME OLOWE OLUMIDE SAMUEL

THESIS TITLE Social vulnerability and Adaptive capacity of a Fishery-dependent Community in

Vietnam: A case study of Xuan Tu Village, Khanh Hoa Province

KHANH HOA, 2018

MINISTRY OF EDUCATION AND TRAINING

NHA TRANG UNIVERSITY

FULL NAME OLOWE OLUMIDE SAMUEL

THESIS TITLE Social vulnerability and Adaptive capacity of a Fishery-dependent Community in

Vietnam: A case study of Xuan Tu Village, Khanh Hoa Province

Topic allocation Decision

Decision on establishing the

Committee:

Supervisors: Dr Akhmad Fauzi

Dr Nguyen Lam Anh

Chairman (full name):

Faculty of Graduate Studies:

Hoang Ha Giang

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UNDERTAKING

I undertake that the thesis entitled: “Social vulnerability and Adaptive capacity of a Fishery-dependent Community in Vietnam: A case study of Xuan Tu Village, Khanh Hoa Province” is my own work The work has not been presented elsewhere for assessment until the time this thesis is submitted

Olowe Olumide Samuel

30th April, 2018

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ACKNOWLEDGEMENT

I would like to express the deepest appreciation the Norwegian Programme for Capacity Development in Higher Education and Research for Development and Nha Trang University for the opportunity to learn and research in Vietnam My special thanks go to

Dr Nguyen Lam Anh and Dr Fauzi Akhmad for their continuous academicals support towards the completion of this research work Their guidance helped me in all the time of research and writing of this thesis A special thanks to Dr Ngan Nguyen for her immeasurable support towards the collection of the data for this research, in terms of language verification and assistance I will also like to thank Phuong, Pin Pin, Ngan for sacrificing their study time to volunteer to be my research team Also, Chau, Ali Swaleh and Tomas N’lukaku, Sandra Wassman, Gabi Salcher and Ayotunde Aina’s efforts towards the completion of my research is duly appreciated Last but not the least, I would like to thank

my family: my parents and sisters for their moral support throughout the postgraduate journey

Olowe Olumide Samuel

30th April, 2018

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Table of Contents

UNDERTAKING iii

ACKNOWLEDGEMENT iv

List of abbreviations vii

List of Tables viii

List of Figures ix

Abstract xi

Chapter 1 1

INTRODUCTION 1

1.1 Background of the study 1

1.2 Problem Statement and Rationale 4

1.3 OBJECTIVES 5

Chapter 2 6

LITERATURE REVIEW 6

2.1 Climate change in Southeast Asia 6

2.2 Vietnam’s Vulnerability to Climate change 7

2.3 Climate Change and Fishery-Dependent Community 8

2.4 Global and Vietnam’s actions on Climate Change 9

2.5 Concept of Vulnerability 10

2.6 Adaptive Capacity and Perception to Climate Change 12

2.7 Assessment of Vulnerability and Adaptive Capacity 15

Chapter 3 19

METHODOLOGY 19

3.1 Study Area 19

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3.2 Conceptual Framework for Assessment 21

3.3 Data Collection 23

3.4 Data Analysis 24

3.4.1 Social Vulnerability index 24

3.4.2 Adaptive Capacity Framework 28

3.4.2.1 Adaptive capacity index 29

Chapter 4 30

RESULTS AND DISCUSSION 30

4.1 Report on Preliminary survey 30

4.2 Respondents characteristics 31

4.2.1 Livelihood 32

4.3 Perceptions to climate change 35

4.4 Social Vulnerability index of Xuan Tu village 40

4.5 Adaptive capacity index 43

4.6 Adaptation measures and Barrier 44

Chapter 5 48

Conclusion and Recommendation 48

5.1 Conclusion 48

5.2 Recommendation 48

List of References 50

Appendices 1

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List of abbreviations IPCC : Intergovernmental Panel on Climate Change

NTP-RCC: National Target Program to Respond to Climate Change SD: Standard Deviation

SVI: social vulnerability index

UNFCCC: United Nations Framework Convention on Climate Change WHO: World Health Organization

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List of Tables

Table 2 1 Conceptual framework with goals - 16

Table 3.1: summary of 2009 disaster 20 Table 3 2: Dimension and Indicator of vulnerability _ 25 Table 3 3 : Vulnerability categorisation table _ 28 Table 3 4: Indicators of Adaptive Capacity _ 30

Table 4 1 Respondents Characteristics 31 Table 4 2 Percentage perception of respondent 35 Table 4 3: vulnerability dimension rankings 41 Table 4 4 Adaptive capacity ranking matrix 43

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List of Figures Figure 3 1: Map of Xuan Tu village (Designed at https://www.arcgis.com/) _ 19 Figure 3 2: Conceptual Framework for this study 23 Figure 3 3: Adaptive Capacity Framework _ 29

Figure 4 1: Livelihood of Xuan Tu _ 33 Figure 4 2 Monthly income per livelihood (Vietnamese Dongs) 34 Figure 4 3 Impacts of climate change on livelihood activities 34 Figure 4 4 Means of information _ 36 Figure 4 5: Perceived changes _ 37 Figure 4 6: Temperature trend (10 years) 37 Figure 4 7 :Precipitation trend (10 years) 38 Figure 4 8: Perceived negative climate impacts (10 years) 40 Figure 4 9: Sub-index of vulnerability 41 Figure 4 10: Sub-index of Adaptive Capacity _ 43 Figure 4 11: Adaptation strategies 45 Figure 4 12: Barriers to Adaptation _ 46

x

APPENDICES

2 Meteorological data from nearest weather station 61

xi

Abstract

Social vulnerability in this study is defined as the current exposure of a community to climate change impacts The case study uses historical data on climate variables and household survey to determine the index of social vulnerability using indicator-based approach and composite method of aggregation The adaptive capacity, perception to climate change and barriers to adaptation was assessed The case study area is called Xuan Tu, a community located on the edge of Van Phong Bay of the South China Sea in Khanh hoa province of Vietnam The community is protected by islands, but is still exposed to hazard such as coastal erosion and storm which has intensified lately

The research within the community shows that they moderately vulnerable to climate change due to its higher sensitivity compare to the exposure and adaptive capacity The factors that aid the village’s capacity to cope was also identified using sub-index calculation and the result proved that economic factor aids in the medium level adaptive capacity The adaptive capacity can also be linked to the higher education level and perception level of the community members The assessment shows that institutional (local government and organizations) support in terms of financial capacity and climate awareness was low Based on the index calculation, recommendations was also put forward for use in planning an adaptation policy

However, the result may be bias as the household survey started after typhoon Damrey, which made landfall on November 3, 2017 In Xuan Tu village, it led to death, destruction of shelter, aquaculture cages, fishing boats, and coastal erosion which prevent movement in certain parts of the village Therefore, during the period of data collection, the respondents were in reconstruction period, and therefore, only a few percentage of the villagers responded to the interview and therefore their response may have been influenced by the extreme event

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Chapter 1 INTRODUCTION 1.1 Background of the study

Over the last decades, there has been an acceptance of the fact that climate change and its related extreme events is real, except for few skeptical minds, the acceptance has led to a general consensus that climate change is harmful to the present and future generations of human as well as the environment which we depend on (Tapan Kumar et al., 2017) Climate Change is a natural phenomenon, however, human induced climate change is a major source of concern because of its negative consequences which is already been observed and predicted to happen These negative consequences include variation in the precipitation and annual rainfall, melting on the Antarctica which will have a profound effect on the hydrological cycle, ocean current as well as the sea level rise (IPCC, 2014) Other negative impacts includes the increase in temperature which will affect the inland water bodies, agriculture and in the sea will lead to thermal expansion and a consequent rise in the sea level According to IPCC, (2014) ‘the last three decades has been successively warmer at the Earth’s surface than any previous decades since 1850 and the global average of land and ocean surface temperature has shown a warming of 0.85OC And also there is the 26% increase in ocean acidification since the beginning of the industrial era which has decrease the pH of ocean surface water 0.1 The global sea level rise from the period 1901 to 2010 ranges from 0.17 to 0.21m, this signifies that the rate at which the sea level rise since the mid-19th century has been larger than the mean rate during the previous two millennia’ The negative impacts of climate change cannot be overemphasized as it is affecting and will continue to affect the ecosystem services which human being relies on The aforementioned negative impacts and projected impacts such

as increased flooding, storm intensity, cyclone and drought will greatly affect human wellbeing and food security In terms of wellbeing, the reduction in economic livelihood and increase in health problems will affect the human states The four dimensions of food security according to the Food and Agriculture Organization includes Availability,

to cope is also different from the least developed countries, small island states, developing countries and developed countries

Vietnam is considered as one of the most vulnerable countries to be impacted by climate change, the projected impacts includes sea level rise, increased frequency of typhoons, and floods (Emilinda et al., 2014) Vietnam’s average temperature has increased about 0.5-0.7oC in the past 50 years and the sea level has increased by 20cm in the same period (Japan's Ministry of the Environment, n.d.) and annual temperature has increased in the southern climate zones and the rainfall in dry and wet seasons has increased by 20% in

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the south central region from the past 50 years (Le Minh NHAT, n.d.) Vulnerability of coastal zone of Vietnam was attributed to low coastal elevation which is below 1m and are developed for tourism and economic purposes (Boateng, 2009) Boateng (2009) reported that, the Red River delta in the north and the Mekong river delta in the south are the highest risk areas and also, settlements and farms in the inlets and estuaries of the central coastline are also vulnerable, however, with no flood risks Vietnam is facing threats from climate change and has limited capacity to adapt due to its top down governance and policy ( Nguyen, et al., 2017) The capacity to manage resilience in Vietnam is usually on major cities while local communities are always at the rope’s end, and as personally observed during the typhoon damrey which made landfall in Khanh Hoa province in the 3rd of Novermber, 2017

Vulnerability assessment of one the tools in formulation of climate policy (fusel) Adaptation to climate change has been linked to technological advances which is mostly useful in mitigation plans (Nguyen, et al., 2017) As Gamble et al., (2008) pointed out, the involvement of human in highly significant in addressing climate change vulnerability and adaptive capacity, hence formulation of policy that will affect tthem positively However, there are still uncertainties in defining vulnerability and its assessment due to its difference in geographical settings and timing (Adger, 1999) Social scientists, researchers are either assessing vulnerability in terms of social and physical vulnerability Leurs et al (2003) stressed that vulnerability assessments are issues and sectors specific and the variables chosen must be related to this and this could be called social vulnerability is about due to its current assessment, identification of root problems and in formulation of policy that will fit the social well-being of the research location The benefits in this vulnerability assessment outweighs that of others (Jha, Bloch, & Lamond, 2012; Nguyen et al., 2017) This study uses social vulnerability assessment using empirical research to calculate a composite index in analysis the level of vulnerability and the ability to cope of a community in Khanh Hoa province, Vietnam

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1.2 Problem Statement and Rationale

The problem observed from literature and personal observation in south central coast of Vietnam flooding resulting from extreme rainfall and typhoon in provinces such as Quang Ngai, Binh Dinh, Phu Yen, Khanh Hoa, Gia Lai, Dac Lac and Ninh Thuan provinces The Marinae typhoon in these provinces in 2009 led to loss of lives, property and migration Disaster Management Working Group (2009) During the course of this thesis, two more storms were observed; Typhoon Damrey and Typhoon Kirogi The former was the worst to hit the country in years and from a personal field observation, I was able to see the destruction which led to loss of lives, aquaculture farms, boats for shipping and structures and these damages are mostly in the coastal areas where the sources of livelihood is fishery-based Located in the north of Khanh hoa province, Xuan

Tu village possess all the traits of a fishery based livelihood due to their occupation which is into aquaculture and fishing According to IPCC and Badjeck et al (2010), fishery-based society are vulnerable to climate change Therefore, the village also suffered from the typhoon Marinae event of 2009 and that of 2017 Other Typhoon or extreme storm events within this years did not make landfall presumably due to its location in the south china sea area Despite the numerous findings that the reality of climate change poses a great threat to human livelihood, fisheries-based livelihood people have not been adequately represented in vulnerability studies (M Islam et al, 2013) The negative impacts of climate change are expected to affect the fishery-based communities’ socio-economic livelihood (Badjeck et al., 2010) While some researches existed on the vulnerability of fisheries community, most are basically on national level whereas small scale fishery based communities are more vulnerable to the negative impacts of climate change (IPCC,2007) and in Vietnam, most vulnerability assessment are based on the Mekong region Therefore, it’s imperative to study the fishery-based livelihood of Vietnam, especially in coastal areas, as this will give insight on the overall vulnerability

of the country A vulnerable community can adapt and cope with climate variability if the households perceived that climate change is an extreme phenomenon, the perception of people to climate change will help in developing an efficient adaptive strategy There is

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an interaction between perception and adaptive capacity to climate change; a shared communities’ perception on climate change will give insight on their preparedness and provide an understanding of the vulnerability of the community and it will also help in decision making However, perception to climate change can also be said to be related to the demographic components of the community and these demographic components may include gender and education The education of people in an environment may increase their perception to climate change due to their exposure and access (Ayesha constable, 2013) Therefore, the knowledge of the demographics characteristics will give insight on the exposed group and most vulnerable group in the fishery-dependent community This study will therefore examine the vulnerability and adaptive capacity of households using local knowledge gained through household questionnaire survey, key informant interview and field observation The knowledge will be used in analyzing their socioeconomic vulnerability based on their livelihood and adaptive capacity in relation to their perception All these will based on the framework adopted which operates on the premises that vulnerability is a function of exposure, sensitivity and adaptive capacity 1.3 OBJECTIVES

The aim of this research is to assess the socio-economic vulnerability and adaptive capacity of a coastal community in the South-central Province of Vietnam to climate impact and variability in other to inform policy makers on the right adaption plan to mitigate against future climate events and ensure moderate response to the current climate extremes, therefore the paper attempts to:

1 To assess the socio-economic vulnerability of coastal human populations to the increasing and emerging threats of climate change

2 To assess the adaptive capacity of a fishery-dependent coastal community in South-central part of Vietnam (Khanh Hoa)

3 To assess the community’s perception to the emerging threats of climate change to their livelihood

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Chapter 2 LITERATURE REVIEW 2.1 Climate change in Southeast Asia

Climate change impacts has been continuing environmental hazardous events in the past decades and therefore cannot be considered as an event for the future (Fulco et al., 2007) Presently the world’s climate is changing, global warming has hit the third successive record year (NOAA/NASA, 2017) and it has been most intense in North America, Europe and Northern Asia since 1979 (Fulco et al., 2007) The impact of climate change has been predicted to be felt in every world’s continent, especially in the global south which includes Africa, South America and Asia Asia is the largest and most populated continents in the world (Wikipedia) Asia coastline includes global range

of shore types; tropical and subtropical and low lying area, 40% of the world’s coral reef

is supported by Asia, especially in Southeast Asia (Burke et al., 2011) The impacts of climate change in most of Asia’s non- Artic coastal ecosystems is difficult to ascertain due to the severe pressure caused by non-climate impacts (Hijioka et al., 2014), however

it has been projected that climate change will cause decline in coral reefs Guldberg et al., 2007) erosion and coastal flooding due to increased rise in sea level (Hijioka et al., 2014) The rise in sea level will inundate low-lying coastal areas and consequently challenging the communities adaptation response to changes, which may cause physiological and behavioral responses from species and could upset the entire biological communities and ecosystem integrity (Chou, 2014) These projected impacts may have negative consequence on biodiversity in terms of decline in marine resources; fish species could reduce in population and in size (Cheung et al.,2009) Southeast Asia is

(Hoegh-a home to (Hoegh-about 563 million people with (Hoegh-annu(Hoegh-al popul(Hoegh-ation growth of 2.2% over the l(Hoegh-ast decade Asia Development Bank data from 2008 concluded that 18% people are living below poverty line of 1.25USD per day while 44% live below 2USD poverty line Many

of the region’s poor are in the coastal area and in the low-lying deltas, most often, these are small holder farmers, fishermen and poor households which are most vulnerable to climate change impact (Asian Development Bank, 2009) Due to the rise in development,

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economies and population increase, Southeast Asia produces 12% of the world’s greenhouse gases at the century (Asian Development Bank, 2009) According to ADB, 79% of the total population in Southeast Asia living within 100km of the coastal area and are dependent on the coastal and marine resources for their livelihood especially aquaculture, these makes the region vulnerable to climate change impact However, the eastern coast areas, which are susceptible to cyclones are less vulnerable due to their high adaptive capacity and effective management, although Bangkok and Jakarta has high adaptive capacity, but it is not enough to moderate the extreme vulnerability due to high population density and exposure (Anshory et al., 2009)

2.2 Vietnam’s Vulnerability to Climate change

Vietnam is considered as one of the most vulnerable countries to be impacted by climate change, the projected impacts includes sea level rise, increased frequency of typhoons, and floods (Emilinda et al., 2014) Vietnam’s average temperature has increased about 0.5-0.7oC in the past 50 years and the sea level has increased by 20cm in the same period (Japan's Ministry of the Environment, n.d.) and annual temperature has increased in the southern climate zones and the rainfall in dry and wet seasons has increased by 20% in the south central region from the past 50 years (Le Minh NHAT, n.d.) Vulnerability of coastal zone of Vietnam was attributed to low coastal elevation which is below 1m and are developed for tourism and economic purposes (Boateng, 2009) The author in assessing the impact of climate in Vietnam reported that, the Red River delta in the north and the Mekong river delta in the south are the highest risk areas and also, settlements and farms in the inlets and estuaries of the central coastline are also vulnerable, however, with no flood risks Vulnerability in Vietnam is attributed to high exposure to hazard and low adaptive capacity due to low income and proper infrastructure which might serve as support (Emilinda et al., 2014) WHO assessment pointed out that rise in sea level could affect the conditions of millions of people, forcing resettlement of coastal communities Most works on assessment of vulnerability in Vietnam are done on the Mekong and Red river delta due to their higher susceptibility to flood (Pamela et al., 2016; Vo, 2014) and

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salt water intrusion ( Binh, 2015) Their findings and conclusion is almost in correlation with that of Adger, (1999), who conclude that Vietnam vulnerability is enhanced by institution and economic factors associated with economic transition and lack of knowledge

2.3 Climate Change and Fishery-Dependent Community

Fisheries and aquaculture supply more than 160 million metric tonnes in 2014 for the ever growing human population Fishery trade serve as source employment with an estimated number of 56.6 million people involved, income generation, food security and foreign exchange earnings for large numbers of developing countries, an example of this

is Vietnam who became the third major exporter in 2014 (FAO, 2016) dependent community are often small scale users of the water body for production of fish; either through catching or rearing Fishery-dependent community are often defined

Fishery-in terms of economic capacity and culture Brookfield, et al., (2005) a fisheries-dependent community as a population of people in a specific region whose economic, social and cultural reliance is on fishery activities Fishery-dependent people are always in areas that are at high exposure to natural disasters such as cyclones, tsunami which will not only cause direct impact but also damages to livelihood and local economy (Badjeck, et al., 2013) Aquacultural productivity are also said to be predisposed to climate change, Nguyen, et al., (2012) recorded that the productivity The authors also recorded damages

to aquaculture farms as a result of salt water intrusion which therefore, affects household livelihood Fishery-dependent community are usually small scale fisher-folks who are generally regarded as been poor, however, there a suggestion that the poverty is related to the level of resource and institutional constraint (Béné, 2006) They are also the most vulnerable in terms of economy due to their sensitivity and exposure to natural stress and hazards due to their closely related activities and high occupational risk against their likelihood (Béné, 2008; Béné, 2006) However, some are more vulnerable than each other, a research done on shrimp farmers in Vietnam shows that farmers with higher intensive are less vulnerable in comparison to lower intensity (Quach et al., 2017)

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Despite the importance of this community in terms of local and rural livelihood, there exist few research (Islam et al., 2014), although Béné (2008) attributed this causative factor of this to be because the fishing environment is a data-poor environment As Xuan

Tu village lies in Khanh Hoa province, South central part of Vietnam, there exist no information on the vulnerability of the fishermen and fish farmers in the village

2.4 Global and Vietnam’s actions on Climate Change

Global actions have been made by the international communities to mitigate the effect of climate change by reducing greenhouse gases emissions and enhancing their sinks (IPCC, 2014) One of the most important effort is the one where several countries form parties

to the United Nations Framework Convention on Climate Change (UNFCCC) agreeing to the ‘Copenhagen Accord’ in 2009, which aimed to keep the global average increase in temperatures below 2°C relative to pre-industrial levels to avoid the worst effects of climate change (UNEP, 2013) The parties pledged to reduce GHG emissions by 25 - 40% from 1990 levels by 2020 and also to stabilize global temperature by 2100 (UNFCCC, 2013) The UNFCCC which was created in 1992 as the main forum for international agreement on tackling climate change with major aims in adaptation, finance, mitigation and development of technology for green development In 1997, 186 countries signed the Kyoto Protocol Treaty, a treated developed by the Conference of the Parties (COP), the highest decision making authority on the UNFCCC The Kyoto Protocol is positioned as a more legally binding tool to mitigate greenhouse gas emissions (e.g., The Clean Development Mechanism (CDM)) (UNFCCC 2002) The Kyoto Protocol set a 5% reduction below 1990 levels for the first commitment period (2008-2012) And as of 2015, at the Paris conference 197 countries participated in signing the agreement According to UNFCCC, the Paris Agreement seeks to accelerate and intensify the actions and investment needed for a sustainable low carbon future with aims to strengthen the global response to the threat of climate change by keeping a global temperature well below 2 degrees Celsius above pre-industrial levels and to pursue efforts to limit the temperature increase even further to 1.5 degrees Celsius in 2017, 143

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signatories have ratified the Paris agreements To strengthen local areas and countries adaptive capacity, especially the least developed countries whose needs are of higher priority – a delay means higher vulnerability, the UNFCCC in its seventeenth session acknowledge the importance of National adaptation programmes planning for developing and least developed countries to assess their vulnerabilities, and address adaptation and this has led to the formation of the National Adaptation Plans and National Adaptation Plan of Action for least developed countries These plans are made through participatory process and it includes gender mainstreaming (Least Developed Countries Expert Group, 2012) In Vietnam, the National Target Program to Respond to Climate Change (NTP-RCC), adopted in 2008 serve as the institutional framework for climate change The goals

of this framework is to identify climate change trends in Vietnam as well as broad regional and sectoral vulnerabilities, and sets out legislative, planning, and investment priorities in response to climate change The NTP-RCC identifies nine targets for 2009–

2015, providing financial and technical support for climate change planning across all sectors, the NTP-RCC is predominantly focused on adaptation measures, not mitigation (MONRE 2008) The ministry of natural resources (MONROE) is the national body responsible for implementing the United Nations Framework Convention on Climate Change and the Kyoto Protocol, and is the designated national authority for the Clean Development Mechanism Most of the existing institutional knowledge and analytical capacity relating to climate change is held by MONRE and associated institutes such as the Institute of Meteorology, Hydrology and Environment (ADB, 2013)

2.5 Concept of Vulnerability

The study of communities’ vulnerability to climate change in relation to human system is

a dynamic and contemporary field of research fraught with constantly changing concepts among research (Brooks, 2003) Various authors and literature exists on vulnerability, however there is no generally acceptable definition of Vulnerability (Bergstrand, et al., 2015) IPCC in its fourth assessment report defines vulnerability to climate changes as the “the degree to which geophysical, biological and socio-economic systems are

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susceptible to, and unable to cope with, adverse impacts of climate change The term

‘vulnerability’ may therefore refer to the vulnerable system itself, e.g., low-lying islands

or coastal cities; the impact to this system, e.g., flooding of coastal cities and agricultural lands or forced migration; or the mechanism causing these impacts” Thus, the concept of vulnerability can be in terms of sensitivity, adaptive capacity and exposure, however there is a fussy relationship between the three and authors usually have a contextual definition for such terms (Brooks, 2003) Ford, et al., (2006) conceptualized vulnerability

as a function of dynamic exposure and sensitivity as a characteristic of the impact and community and their ability to cope with the exposure The linkage between these definitions is that climate change vulnerability are both in terms of the ecological environment and human systems, which therefore translated that vulnerability is not isolated and in analyzing it, the specific concepts should clearly be stated in relation to its impacts (Kelly and Adger, 2000) The differences in the concepts can be attributed to the different dimensions on which researches are based on, whether in terms of the human society or the direct impact of climate change on the environment Kelly & Adger (2000) noted that some authors defined vulnerability in terms of ‘endpoint’- a residual process after assessing the biophysical process and applying adaptation actions and ‘starting point’ analysis in terms of identifying the degree on sensitivity in a place of limited capacity The starting point can therefore be called social vulnerability, as it is in terms of human sensitivity and the end point which measures the impact of a hazard can be called biophysical vulnerability Leaning on the definition of biophysical from Wikipedia, biophysical vulnerability can be defined as the ecological/environmental impact of natural/human-induced disaster that reduces the capacity of the environment to function

as it would be in a natural state The focus on this research will be restricted to human dimension and how the climate extremes affect their capacity to cope Several authors have worked on social vulnerability of human society (Adger, 1999; Ford et al., 2006; Bergstrand et al., 2015; Lixin et al., 2017) Adger (1999) defined social vulnerability in terms of poverty, inequality and institutions From literatures, Social vulnerability can be simply put as the susceptibility of the human system to climatic stress that exacerbate

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existing stressors such as entitlements (Kelly & Adger, 2000), social status (Brooks, 2003) which therefore reduces their capacity to adjust, cope and adapt to the current impacts Reardon & Taylor, (1996) attributed lack of other source of income as a factor which increases inequality, thereby reducing the capacity to cope with climatic risk Lixin

et al., (2017) further classified social vulnerability as regional, community and individual Social vulnerability is also referred to a result of society’s inequalities and historical pattern of living in the society which has create a huge challenges and barrier to resist climate change (Singh et al., 2014) Generally, the factors affecting social vulnerability are lack of access to information and knowledge, limited access to political power, representation and decisions, society’s beliefs and customs, demographical characteristics such as age and gender (Cutter et al., 2003) There is paucity of research on social vulnerability in a community as most are based on biophysical vulnerability at regional level (Lixin et al., 2017; Thomas E Downing, 2003) Several researches has been done in vulnerability of coastal communities in developing countries Case studies in Bangladesh, Cambodia and Philippines by (CCC, 2009; Didar-Ul Islam et al., 2015; Emilinda et al., 2014; Islam et al., 2014) According to some of the authors, among all the vulnerable group (ethnic groups, the poor, physically challenged) women are more vulnerable, and also coastal communities are more exposed to climate due to exposure to cyclones and other storm events which will constitutes higher vulnerability because large percentage of them are dependent on marine resources

2.6 Adaptive Capacity and Perception to Climate Change

In conceptualizing Adaptive capacity in this context of climate change, the word

‘adaptation- a change in an organism that makes it better to live in a particular place or situation (Merriam-Webster Dictionary) is usually used, however, Eriksen et al., (2005) noted that coping differs adaptation in the sense that coping is the ability to absorb an hazardous event and be less vulnerable and adaptation is a changing measure that is constantly changing (Smit & Wandel, 2006) The IPCC on its working group II Technical Assessment Report further distinguished adaptive capacity from adaptation by

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giving examples of adaptation which are differs in terms of degree of success IPCC defined adaptation in two ways; Autonomous adaptations and Planned adaptation Autonomous is a reactive adaptation to the impacts of any hazard Autonomous adaptations are not related to climatic impacts alone and are usually constrained by governance, social and economic conditions Planned adaptations can be defined as an anticipatory adaptation planned to withstand an unforeseen impact (IPCC, 2001) Adaptive capacity, therefore is mainly the capacity to adapt (Engle, 2011) or can be further clarified as the degree to which a system can absorb and make adjustments which can counterbalance potential damages and use it as an advantage to create opportunities (IPCC, 2001) In this case, it involves using knowledge of previous experience to adapt to present climatic impacts and applying the knowledge for tomorrow’s related impact (Brooks et al., 2005) IPCC also clarified the activities that influences how a society or system can survive, these influences are called determinants of adaptive capacity and they includes economic resources, technology, infrastructure, information and skills, institutions and equity (IPCC, 2001) Yohe and Tol (2001) also set eight determinants of adaptive capacity which are based on system, sectors and locations The determinants are listed below;

 “The range of available technological options for adaptation

 The availability of resources and their distribution across the population,

 The structure of critical institutions, the derivative allocation of decision-making authority, and the decision criteria that would be employed,

 The stock of human capital including education and personal security,

 The stock of social capital including the definition of property rights,

 The system’s access to risk spreading processes,

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 The ability of decision-makers to manage information, the processes by which these decision-makers determine which information is credible, and the credibility

of the decision-makers, themselves

 The public’s perceived attribution of the source of stress and the significance of exposure to its local manifestations”

Most of these are mainly local and like vulnerability, they varied from community to community (Smit & Wandel, 2006) W N Adger & Vincent, (2005) debunked the claim about economic development; ‘it is frequently assumed that the capacity of societies to adapt to climate risks is based on their economic development, the more economically developed a society, the greater the access to technology and resources to invest in adaptation Yet evidence from traditional societies demonstrate that the capacity to adapt

in many senses depends more on experience and depending on weather-sensitive resources” Adaptive capacity is a norm of every communities, most communities can cope to normal changes in their condition except for extreme events which ranges more than their capacity and because of complexities, some conditions in this coping range can introduce side effect which affects the coping range (Smit & Wandel, 2006) This implies that the reduction of vulnerability in some aspects of the community predispose another sector to state of vulnerability, narrowing the adaptive capacity (Eakin, 2003)

Adaptive capacity has been said to relate to perception Changes in a communities’ environment can be related to the individual perception, a well perceived change by all individuals provides understanding of the communities’ risk assessment influences judgement and decision making (Grunblatt & Alessa, 2017; Oppenheimer & Todorov, 2006) Perception to climate variability is a baseline for developing an designing an effective adaptation policy (Eyasmin, et al., 2017; Temesgen, et al., 2009) Perception is the acquisition and transformation of external stimuli into mental awareness (Ban & Hawkins, 2000) Perception was defined in terms of cognitive factor by (Grothmann & Patt, 2005) The authors used the term ‘relative risk perception’ to define perception as the expectancy of an individual to a perceived unforeseen hazard: ‘the bigger the

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difference between what a person wants to happen or not to happen and what a person expects to happen, the more motivation or ‘energy’ is released for adaptation” Literatures from authors have proved that there is an increase in perception towards climate change impacts such as the increase in precipitation and temperature (ATPS, 2013; Debela, et al., 2015) In Vietnam, the government efforts on adaptive capacity is mainly through the development of provincial socio-economic framework plan and through climate change policies that could prevent disaster Nhuận, et al., (2015) assessment of the adaptive capacity of some coastal urban households in Vietnam to climate change, reported that the adaptive capacity of household is determined by social, human and economic capability

2.7 Assessment of Vulnerability and Adaptive Capacity

Vulnerability assessment tends to answer the questions of actors sensitivity and exposure and how climate change impacted them Assessment of climate change tends to be an informing guideline for decision makers, in terms of social or political context (Tiani et al., 2015) However, there are no specific measurements for vulnerability due uncertainties and the spatial differences (Murphy et al., 2015) Climate change vulnerability is an evolving field which is not restricted to a particular field, it could take several forms into climate, disaster, development or poverty development (Weis et al., 2016), hence the differences in assessment In classifying and characterizing adaptive capacity, authors faced problems due to uncertainty (Adger & Vincent, 2005) The authors argued that the determinants of adaptive capacity which are meant to be indicators of assessment as listed by Yohe & Tol (2001) may not be quantified and can only be qualitatively described There is an increasing need to use and develop indicators for the assessments of climate vulnerability and adaptive capacity in order to give a clear understanding of the processes (Adger & Vincent, 2005), however, indicator based may

be said to be limited in terms of quantity and quality (Tiani et al., 2015) There are many approaches to vulnerability and adaptive capacity assessments, regional approaches tends

to rely on information from global data on climate change but failed in terms of

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interpreting country specific variations (Weis et al., 2016) National-level assessments however, are more appropriate for use in providing information for central institutional policy makers, it also poses challenges in terms of spatial scales- local or community levels may be invisible to national governments (Tiani et al., 2015; Adger & Vincent, 2005) Murphy et al., (2015) defined and illustrated conceptual frameworks as a tool which focus on different elements of problem which leads to research questions, new knowledge and policy response They presented four conceptual framework with goals,

in the table below

Table 2 1 Conceptual framework with goals

In assessing social vulnerability, indexes are used based on two approaches - the deductive approach and inductive approach The deductive approach selects variables deductively to create social vulnerability index based on prior knowledge from existing

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literature while the inductive approach creates social vulnerability index using variables which influences social vulnerability (Yoon, 2012) Social vulnerability index can further be divided into two based on socio-economic status, society education level, demographic composition, political activities The other is based on built environment such as population density, distance to hospital in terms of disaster etc The former is called Socio-economic vulnerability index (SeVI) and the latter is called Built Environmental Vulnerability Index (BEVI) (Holand et al., 2011) Several methodologies exist for measuring vulnerability, Barsley, et al., (2013) reviewed several methodologies

on vulnerability which are mostly based on indicator based Livelihood vulnerability index which targets organizations and policy makers was developed by Hahn et al, (2009) and Coastal vulnerability index (CVI) was created by Gornitz (1990) and was initially used in the east coast of the US to assess sea level change, it has now been developed and generally used in assessing coastal vulnerability Other authors also assessed vulnerability using the GIS system in terms of agricultural systems (Luers, et al., 2003), urban social vulnerability with combination of high resolution images and GIS (Ebert, et al., 2008) The differences in the different methodologies are because of the spatial variation, geographical characteristics and uncertainty in climate variability Moss, et al., (2001) uses the IPCC determinants of vulnerability-exposure, sensitivity and adaptive capacity to develop a Vulnerability Resilience Prototype (VRP) in assessing the future impacts of climate change A more economical tool which combines three important areas- countries sectoral GDP contribution, population near area with less than 5m, access to freshwater was developed by Stanton, et al., (2012) A more participatory approach was developed by CARE intervention The Climate Variability and Capacity Analysis uses stakeholders in the community The usefulness of this has been tested with much success in Africa

Several methodologies has been successfully used in assessing adaptive capacity Gupta

et al., (2010) used the adaptive capacity to wheel to access institutional adaptive capacity ACCRA also uses the Local Adaptive Capacity in Africa to measure local communities’

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adaptive capacity The LAC uses five characteristics such as asset base, institution and entitlements, knowledge and information, innovation and governance to measure adaptive capacity at community level At national level, the National Adaptive Capacity framework was introduced by the World Resources Institute in 2009 The framework was used in identifying the priorities and also for enhancing country’s adaptive capacity The limitation of the NAC is that it doesn’t show how adaptation strategies of farmers could

be assessed

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Chapter 3 METHODOLOGY 3.1 Study Area

Figure 3 1: Map of Xuan Tu village (Designed at https://www.arcgis.com/)

Xuan Tu village covers 800ha in area with the total populations of 2,462 people belonging to 553 households Most occupations by local villagers are fishing, aquaculture, agriculture and other services with 60% of the household income coming from fisheries The fisheries sector, which is headed by men generates more income than aquaculture (US$165 and US$106 monthly respectively) (Nguyen, 2009) The social infrastructures in the village includes internet, telecommunication, electricity and road network with approximately 40% of transport system in the area are concrete roads, however, there are no medical institution in the village ( Hue & Hoang, 2010) Large percentage of women in the village have no specific occupation that could generate

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additional income especially in households whose income are from fishery and with change is expected exacerbate the stressors on Vietnam human communities especially the poor, women and children (Asian Development Bank, 2013), this dependence could cause the women to be vulnerable to climate change impact Van Hung community was chosen because of their dependence on fisheries and aquaculture as their main sources of income (Tran et al., 2013) and also because of their exposure to typhoons and associated flooding According to literature, the storm in 2009 led to remarkable damages to community livelihood which left many houses collapsed, 1000 lobster floating cages was damaged severely and about 60,000 lobsters was lost, to a cost of about 30 billion Vietnamese dong (Van Hung People’s Committee, 2009) The typhoon Damrey in 2017 also resulted in death, ship destruction, cages destruction and loss of shelter (author’s observation) The Khanh Hoa Red Cross society recorded that, the hazardous occurrence led to of loss of life, household damages and destructions of fishery The summary can be found in the table below

Table 3.1: summary of 2009 disaster

1 Human Loss

2 Houses damages

3 Agricultural damage

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aquaculture :

(source: Khanh hoa Red Cross Society)

3.2 Conceptual Framework for Assessment

The conceptual framework is based on the IPCC determinants of vulnerability, which are exposure, Sensitivity and Adaptive Capacity These determinants will serve as the indicators of vulnerability to be assessed Theoretically the study will be framed within a social-ecological system (SESs) paradigm based on the fact that a change in a part of a system will either affect the system negatively or positively Berkes & Folke, (1998) stated that humans are part of the linked systems - humans and nature SESs was defined

as “combined system of both biophysical and social factors that are in continuous interactions in building resilience and sustainability” (Redman, et al., 2004) Biophysical factors include the marine ecosystem, terrestrial ecosystems while the social factors has

to do with humans Climate variability and change has been said to have impact on the social ecological systems Charisma, et al., (2015) stated in their research that the increase in dengue in the Philippines is associated with climate variability Based on the definitions of adaptive capacity, Graham, et al., (2014), noted that adaptive capacity depends on the properties of the SES that helps communities to adjust or recover from extreme environmental conditions In the assessment of TEEB project (The Economics of Ecosystem and Biodiversity), it was concluded that the negative impacts of anthropogenic activities on the ecosystem has caused its capacity to decline (TEEB, 2010) This impacts, however might present new opportunities for developments Connoly-Boutin et al (2010) in their framework described vulnerability of farming communities has been based on two factors; the socio economic impact of climate change

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and human ability to adapt According to them, climate change impacts and human socio economic factors are always in a constant and continuous interaction Adaptive capacity from these can then be defined as the ability of a community to use their social interactions or resources to cope with climate extremes, however , Teferi Mequanite Tensay (2016) noted that adaptive capacity is dependent on perception; before a community can adapt to climate change, they must perceive that climate change is real The framework for this study shows that social vulnerability of the coastal community (C) is a function of the exposures to climate related stress stress such as storms, floods and other linked stressors (A) which will have an effect on the livelihood and dependency which the community will be sensitive to (B) The framework also shows the capacity of the fisher folks to adapt and create opportunity, that is , adaptive capacity (D) is determined by their perception- extents to which they are aware or perceive the changes and the governance or other private institutions efforts The conceptual approach used in this project is thus, a starting point outcome oriented approach that uses indicators and variables to determine social vulnerability and it is more focused on the population The indicators will then be weighed and established into an index to rank the social vulnerability level of the community As stated by Murphy et al, 2015, the research is scalable and cost effective A deviation from this is that it does not rely solely on existing data sources, but other data through questionnaire sampling

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A: (Exposure: mean temperature, precipitation, percentage of storm, and flood)

B (Sensitivity:

Resource dependency, income

diversification)

D: Adaptive capacity

Institutions: government

Sensitivity: Shelter, respondent above age 60, Percentage

of female headed household

C: Social Vulnerability

Perception: awareness of

climate impacts

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to a total of 61 head of households selected randomly The questionnaire survey was conducted from November 2017 to February 2018 and the households were selected based on availability of the household heads while the survey was on Data for Sensitivity and adaptive capacity were obtained using household questionnaires, while exposure data were collected from secondary sources The questionnaire covered details on characteristics of the community, current livelihood and income diversity and formal and informal networks supporting climate hazard reduction and adaptation (Supin & Christy, 2011) Exposure data on climate variables (annual temperature, mean annual rainfall, data

on storms and flood) was extracted from Vietnam’s statistical website and online (desinventar.net) Key informants interview is an in-depth interview with individuals in the community (local head and knowledgeable members on the issues on climate change and environmental organization working in the village was done concurrently with data household survey to buttress the points and enrich the data collected Exposure, sensitivity and adaptive capacity are the determinants of vulnerability, therefore the key informant interview and the household survey will be used in collecting data on these determinants

3.4 Data Analysis

Descriptive statistics including frequencies and percentages were used to summarize the data from the semi structured questionnaire on fisher’s perceptions of climate change and demographic characteristics Where possible, the results will be presented as graphs and tables The data from the survey is then aggregated to determine the percentage in each of the categories and then be used to calculate the vulnerability index

3.4.1 Social Vulnerability index

Indicator based approach was used to create social vulnerability index based on the data, collected using the semi-structured questionnaire The indicator used takes into account the socio-economic and biophysical dimensions in creating a composite index The research area in this study is referred to as the vulnerable system while climate change variability is the stressor (Žurovec et al., 2017) and it is based on the theoretical

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background that a higher percentage of the villagers are dependent on fishery as main source of income or significant part of their livelihood Natural resources and agriculture are highly sensitive to climate change (Žurovec et al., 2017) In choosing the indicator used for the research, the inductive approach was used based on the data collected, this because there’s no established indicators or framework for quantifying vulnerability to hazard (Cutter, et al., 2010) The indicators were then integrated into sub-indices in relation to the IPCC dimension of Vulnerability The table below shows the dimensions and indicators

Table 3 2: Dimension and Indicator of vulnerability

Vulnerability

relationship with Vulnerability

Exposure Mean annual temperature (10 Years) +

Mean annual precipitation (10 years) + percentage of storm (18 years) + Percentage of food occurrence (18 years) +

Percentage of Fishers above 60 years + percentage of household without hazard resistant shelter

+

percentage of female headed household +

percentage of people with secondary education

-

Percentage of people with access to information

-

of global warming increase the probability of increase in impacts such as heat waves, high precipitation, drought, tropical depression and sea level rise (Carlos and Sang 2015; Parry et al 2005) This factors are positively increasing the vulnerability of a system The sensitivity of a system in this study is dependent on the socio-economic factors such as population and infrastructure Indicators of sensitivity can encompass geographical conditions, land use, demographic characteristics such as female headed houses, and infrastructure, dependency on natural resources and to the extent of diversification (Carlos and Sang 2015) This indicators of vulnerability affects a system, hence the positive functional relationship with vulnerability Adaptive capacity describes the ability

of a system to cope and create opportunity in a climate related events Adaptive capacity

to climate change is dependent on access to loans, technology and information, governance capability, and the distribution of resources Indicators for adaptive capacity compose economic capability, social groups, institutional capacity, and education (Carlos and Sang 2015) Adaptive capacity reduces vulnerability to climate change as it serves

as a base for adaptation strategies to develop, therefore the negatively impact vulnerability

Normalisation of Indicator

Since each indicator is measured using different scales and units, therefore the indicators were normalized so they can be easily compared The normalised indicator value ranges

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from 0 and 1 and its calculated based on the calculation methods of the UNDP (1990) in calculating the Human Development Index (HDI) Prior to nomalising, functional relationship of the indicators and vulnerability are identified – the functional relationship shows the positive and negative correlation of the indicators with vulnerability That is, positive correlation means the indicator has the capacity to increase vulnerability and negative correlation shows the indicator can reduce vulnerability The type of correlation determines the equation to use in normalisation

For positive correlation, the equation is stated thus,

𝑿𝒊𝒋 = 𝑿𝒊 𝑴𝒊𝒏.𝑿𝒋

𝑴𝒂𝒙.𝑿𝒋 𝑴𝒊𝒏.𝑿𝒋

“Equation 3.1: positive normalisation “

And for negative correlation, the equation;

𝑿𝒊𝒋 = 𝑴𝒂𝒙.𝑿𝒋 𝑿𝒊

𝑴𝒂𝒙.𝑿𝒋 𝑴𝒊𝒏.𝑿𝒋

“Equation 3.2: Negative normalisation”

Where Xij is the value of normalised indicator (j) with respect to study area (i), Xi is the actual value of the indicator with respect to (i) and Min Xj and Max Xj are the minimum and maximum values of indicators respectively

Weighing and index calculation

After normalisation, the indicators were then summarized into simple averages to form composite indices using equal weight method This methods assume all indicator variables carry equal weight and it was chosen for this study because of its simplicity and transparency as there are no consensus or justification for the different ranking of the indicators into ranges of importance (Cutter, et al., 2010) Heltberg & Bonch-Osmolovskiy, (2010) noted that weighted averages introduces element of arbitrary choice and regression-based weight are only visible when an objective measure of vulnerability

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outcome exists The normalised indicators were integrated into calculated composite- sub indices in accordance with their belonging to the vulnerability dimensions Arithmetic mean of indicators make up this sub-indices and the final value of the vulnerability index

is obtained by the arithmetic sum of sub-indices (Karen, O’Brien et al., 2004; Žurovec et al., 2017) In quantifying social vulnerability, it must be shown mathematically to express the relationship between the components (Nguyen, et al., 2017), therefore the mathematical expression to calculate the social vulnerability index is;

𝑺𝑽𝑰 = ∑𝟏

𝒏𝑬, 𝑺, 𝑨𝑪 (Ahsan & Warner, (2014))

“Equation 3.3 : Social Vulnerability index “

Where SVI is the social vulnerability index, E is exposure, S is sensitivity, AC is adaptive capacity and n is the 3

The level of vulnerability was then identified using the 3 categorisation based on standard deviations from the arithmetic means of the indicators (Cutter & Emrich, 2017)

Table 3 3 : Vulnerability categorisation table

3.4.2 Adaptive Capacity Framework

Adaptive capacity is defined as the “potential, capability, or ability of a system to adapt

to climate change stimuli or their effects of impacts” IPCC, (2001) defined adaptive capacity as effectiveness of a system to potentially adapt to climatic effects The IPCC also identifies conditions that influences adaptive capacity and this are economic resources, availability of technology, availability of information and trained personnel, adequate social institution and decision making authorities and equity Based on this determinants, the present study developed a framework to access adaptive capacity The variables include the system social status, that is, there access to information, social

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Adaptive Capacity

Percentage of people with quality shelter Access to at least one information service

Economic Capacity Access to Loan

Percentage of people with diversified income

Improved technology per capital income

group, people with higher education and quality shelter Economic resources are the resources or variables that could increase the community’s economic conditions, thereby increasing adaptive capacity Institutions has to do with the qualities of decision makers and civil organization Decisions of institutions and governance affects the ability of a system to adjust to climate change (Maggie & Nicola, 2012)

Figure 3 3: Adaptive Capacity Framework

3.4.2.1 Adaptive capacity index

The indicators of adaptive capacity were selected inductively from the research The procedure for social vulnerability index was also used in the process of normalisation and weighing The indicator chosen all have the positive correlation with adaptive capacity