4.1. Delphi round one
Of the experts interviewed 12 defined community resilience in terms of adaptive capacity (a situation characterised by flexibility), 5 defined the concept in terms of coping capacity (a process characterised by stability) and 4 defined it in terms of a combination of coping and adaptive capacity (Table 2).
Table 2
Interviewees’ definitions of community resilience
Category | Scale of influence | Direct quote of community resilience definition | Experts |
Coping capacity | Community | The ability of the community to bounce back after undergoing some climate-induced disaster. | A |
The ability of a community to withstand shock or bounce back from a climate change disaster that have occurred over a period of time. | C |
The ability of the community to withstand shock or disaster or negative impact of climate change and to withstand such disaster. | H |
The ability of a community to bounce back to its original state after a climate change event. | N |
Unspecific | The concerted efforts to get results during an environment issue. | F |
Adaptive capacity | Community | The capacity of community to cope or resist the risk to climate change. Capacity to adapt to the impact of climate change. | E |
The ability of an area or community to work against a particular problem. To put in place measures of combating a particular problem which may be affecting their communities. | G |
The ability of the community to withstand the impact of climate change. How equipped the communities are to adapt to the impact of climate change. | I |
The ability of the community to understand and be able to guard themselves on the impact of climate change. | J |
The ability of a particular community to withstand the severity of the adverse impact of climate change. The capacity of the society to adjust and readjust to the adverse impact of climate change. | K |
The ability of the community to put up adaptive measures in place against climate change. | L |
The ability of the community to adjust and adapt to the impact of climate change. | M |
How the community can resist the impact of climate change? It just to make them take precautions, prepared and to plan for the impact of climate change. | O |
The ability of a community to apply the available resources to adapt, respond to, withstand, and recover from adverse situations. | R |
It means the ability of the community to utilise the available resources to respond to and respond to negative situations and disaster. | S |
Community resilience is the ability of communities to prepare for anticipated hazards, adapt to changing conditions and withstand and recover rapidly from disruption as a result of climate change. | T |
Community resilience is the sustained ability of a community to utilise the available resources to respond to and recover from adverse situations. | U |
Coping and adaptive capacity | People-centred | How people are able to adapt or cope with climate change. | B |
Community | The way communities tend to guide against further disaster or coping and adaptive strategies of communities to deal with disaster. a feedback mechanism of the community to get back to itself after a climate event. The ability of a community to adjust or readjust themselves from prevailing situations or the environmental problems they face. | D |
The ability of the community to adapt to the impact of climate change. Putting things in place to reduce the effect of climate change on communities. How communities are able to cope with the impact. | P |
The ability of a community to adapt and cope during a disaster and to return to its previous state. | Q |
The questions asked during the interviews were based on how the experts understood community resilience and how it is measured Hence indicators which are relevant to measuring community resilience and reducing the impact of climate change were identified and subsequently categorised into the following eight elements: infrastructural; training and awareness; environmental; social; economic; demographic; institutional, and health and fatality (Table 3). Interviewees most frequently referred to infrastructural and training and awareness elements.
Table 3
Elements and their indicators for measuring community resilience identified by the experts
Elements | Indicators | No. of experts |
Infrastructure | Resilient infrastructure and maintenance | 15 |
Adequate domestic and industrial waste facilities | 2 |
Disaster management centre | 21 |
Training and awareness | Learning and awareness | 18 |
Adequate resource monitoring and feedback mechanism | 5 |
Environment | Renewable energy | 6 |
Sustainable agricultural practices | 17 |
Social | Community engagement and empowerment | 10 |
Inter-community relationships | 2 |
Economic | Adequate livelihood | 9 |
Access to credit | 1 |
Ecological fund | 5 |
Demographic | Education | 9 |
Institutions | Enforcement of good land use planning | 3 |
Equal distribution of responsibility | 7 |
Synergy and harmonisation of policy | 3 |
Health and fatality | Access to health assistance and facilities | 4 |
4.2.2. Delphi Round Two (Survey)
The indicators for measuring community resilience identified in round one of the Delphi study formed the basis of the survey conducted in round two of the Delphi study. The data from the survey was analysed based on the resulting Weighted Average (WA), Standard Deviation (SD) and Interquartile Range (IQR) as presented in Table 4. These different methods can be used to measure the importance of each indicator and achieve consensus (Murphy et al. 1998; Bailie, 2011). This method of weighting is acceptable for consensus (Hasson et al., 2000). Weighted average was used for understanding the experts opinions on the significance of the indicators (Greatorex and Dexter, 2000), hence their range from 3.75 to 4.65 shows that all the indicators were significant. In addition, these indicators were significant since more than 70% of experts were in agreement (Diamond et al. 2014; Slade et al. 2014; Musa et al. 2015).
Table 4
Rating result by 20 experts of the importance of community resilience indicators round two
Indicators | WA | SD | IQR | Rank |
Resilient infrastructure and maintenance | 4.65 | 0.93 | 0 | 1 |
Learning and awareness | 4.6 | 0.83 | 1 | 2 |
Educational status | 4.45 | 0.83 | 1 | 3 |
Adequate resource monitoring and feedback mechanisms | 4.45 | 0.69 | 1 | 3 |
Enforcement of good land use planning | 4.4 | 1.14 | 1 | 5 |
Community engagement and empowerment | 4.35 | 0.75 | 1 | 6 |
Sustainable agricultural practices | 4.35 | 0.75 | 1 | 6 |
Synergy and harmonisation of policy | 4.3 | 0.98 | 1 | 8 |
Adequate livelihood | 4.25 | 0.91 | 1 | 9 |
Ecological funding | 4.2 | 1.06 | 1 | 10 |
Inter-community relationships | 4.15 | 1.27 | 1 | 11 |
Adequate domestic and industrial waste facilities | 4.05 | 1.10 | 2 | 12 |
Disaster management centres | 4.05 | 1.00 | 1 | 12 |
Access to healthcare assistance and facilities | 4.05 | 1.19 | 1 | 12 |
Equal distribution of the responsibility | 4.05 | 0.95 | 1 | 12 |
Access to credit | 3.95 | 1.23 | 1.25 | 16 |
Renewable energy | 3.75 | 1.33 | 2.25 | 17 |
Standard deviation and interquartile range are complimentary resulting in their combined use in previous studies (Musa et al. 2015). Standard deviation is used in measuring consensus (Holey et al. 2007) as it determines how far each response is from the weighted average (Rayens and Hahn, 2000). Standard deviation, which uses all the data in the survey, measures outliers and how far each observation is from the mean (Murphy et al. 1998; Rayens and Hahn, 2000). Furthermore, the standard deviation of the individual response to each indicator (≥ 1) was calculated in this study. A standard deviation between 0 and 1 is considered a strong consensus while that more than 1 reflects a weak consensus (Goldman et al. 2008). The standard deviation analysis in this research shows that only 59% of the experts agreed, indicating that consensus was not reached among the expert group on the 17 indicators within Delphi two. As indicated in Table 4, the standard deviation analysis identified seven indicators for which there was no consensus as follows: Adequate domestic and industrial waste facilities (SD = 1.10 > 1); Access to credit (SD = 1.23 > 1); Renewable energy (SD = 1.33 > 1); Enforcement of good land use planning (SD = 1.14 > 1); Ecological funding (SD = 1.06 > 1); Inter-community relationships (SD = 1.27 > 1); and Access to healthcare assistance and facilities (SD = 1.19 > 1).
The Interquartile range less than or equal to one (< 1 or = 1) is considered as strong consensus whereas an IQR more than one (> 1) is considered a weak consensus (Murphy et al. 1998). The IQR is very important as it is computed by using data lying along the first quartile (25%) and the third quartile (75%), and measures the mid-spread or the middle 50% of responses (Musa et al., 2015). Similar to the findings of the standard deviation, the IQR shows that there was no consensus for three out of the 17 community resilience indicators. These were adequate domestic and industrial waste facilities (IQR = 2 > 1); Access to credit (IQR = 1.25 > 1); and Renewable energy (IQR 2.25 > 1) (Table 4). The main purpose of using a Delphi method is achieving a significant level of consensus from the expert panel on each of the community resilience indicators, which this Delphi round failed to achieve.
While some researchers have recommended the use of interquartile range to measure consensus (Alshehri et al. 2015; Musa et al. 2015), the results of this research suggest not to rely on the technique wholly. The IQR gives a clear view of the overall data by removing the outlying values and by measuring the dispersion based on two values from the dataset (Giannarou and Zervas, 2014). However, the standard deviation is a more substantial measure of distribution as it considers every value in the data (Goula, 2013). Therefore, the use of the standard deviation method in the current research helps in investigating further the range of indicators where consensus is weak since the interquartile range technique may overlook those indicators.
4.2.3 Delphi Round Three (Survey)
In addition to the 17 community resilience indicators identified in round one of the Delphi study, the expert panel identified three more indicators as significant in round two. These are communicating information in local languages; the role of faith-based organisations; and exhibition programmes to showcase local produce. As a result, the final round (Delphi three) consisted of a rating of the 20 indicators by the 20-member expert group using a 5-point Likert scale. In the analysis, the weighted average was between 4.10 to 4.70 showing that they were all important. Likewise, the standard deviation ranged from 0.47 to 0.99, while the inter-quantile range were all ≤ 1 indicating that consensus was reached on all 20 indicators (Tables 5 and 6).
Table 5
Rating result by 20 experts of the importance of community resilience indicators round three
Community Resilience Indicators | WA | SD | IQR | RANK |
Learning and awareness | 4.9 | 0.31 | 0 | 1 |
Communicating information in local languages | 4.85 | 0.37 | 0 | 2 |
Sustainable agricultural practices | 4.7 | 0.47 | 1 | 3 |
Access to healthcare assistance and facilities | 4.65 | 0.59 | 1 | 4 |
Synergy and harmonisation of policy | 4.55 | 0.6 | 1 | 5 |
Adequate resource monitoring and feedback mechanisms | 4.5 | 0.51 | 1 | 6 |
Ecological funding | 4.5 | 0.76 | 1 | 7 |
Adequate domestic and industrial waste facilities | 4.5 | 0.69 | 1 | 8 |
Enforcement of good land use planning | 4.5 | 0.69 | 1 | 9 |
Renewable energy | 4.45 | 0.94 | 1 | 10 |
Resilient infrastructure and maintenance | 4.4 | 0.99 | 1 | 11 |
Adequate livelihood | 4.4 | 0.88 | 1 | 12 |
Community engagement and empowerment | 4.35 | 0.75 | 1 | 13 |
Inter-community relationships | 4.35 | 0.67 | 1 | 14 |
Disaster management centres | 4.3 | 0.86 | 1 | 15 |
Equal distribution of the responsibility | 4.3 | 0.8 | 1 | 16 |
Educational status | 4.2 | 0.77 | 1 | 17 |
Exhibition programmes | 4.15 | 0.75 | 1 | 18 |
Role of faith-based organisation | 4.15 | 0.75 | 1 | 19 |
Access to credit | 4.1 | 0.79 | 1 | 20 |
Table 6
Total community resilience indicators reaching consensus in Delphi two and three
Elements | Delphi two | Delphi three | | |
Total indicators | Consensus of indicators | % | Total indicators | Consensus of indicators | % |
Training and awareness | 2 | 2 | 100 | 3 | 3 | 100 |
Health and fatality | 1 | 0 | 0 | 1 | 1 | 100 |
Environmental | 2 | 1 | 50 | 2 | 2 | 100 |
Infrastructural | 3 | 2 | 67 | 3 | 3 | 100 |
Institutional | 3 | 2 | 67 | 4 | 4 | 100 |
Social | 2 | 1 | 50 | 2 | 2 | 100 |
Economic | 3 | 1 | 33 | 4 | 4 | 100 |
Demographic | 1 | 1 | 100 | 1 | 1 | 100 |
| 17 | 10 | 57 | 20 | | 100 |
4.3. Overall Ranking of all the Community Resilience Elements and their Indicators
As shown from the Delphi results, consensus among the experts on the indicators for measuring community resilience to climate change were established (Table 6). Table 7 shows the consensus from the third and final round of Delphi, with a weighted average ranging from 4.1 to 4.85. Also, the grouped weighted average based on categorising the indicators under the elements were 4.2 to 4.75. The standard deviation is < 1 on each of the indicators ranging from 0.31 to 0.99. Likewise, the IQR was less and equal to 1 on all the community resilience indicators. The final ranking of the community resilience elements and their indicators shows training and awareness as the first and demographic as the least (Table 7).
Table 7
Community resilience elements and indicators rating results
Elements | Community Resilience Indicators | WA | SD | IQR | Grouped WA | Rank |
Training and awareness | Learning and awareness | 4.9 | 0.31 | 0 | 4.75 | 1 |
Communicating information in local languages | 4.85 | 0.37 | 0 |
Adequate resource monitoring and feedback mechanisms | 4.15 | 0.88 | 1 |
Health and fatality | Access to healthcare assistance and facilities | 4.65 | 0.59 | 1 | 4.65 | 2 |
Environmental | Sustainable agricultural practices | 4.7 | 0.47 | 1 | 4.57 | 3 |
Renewable energy | 4.45 | 0.94 | 1 |
Infrastructural | Resilient infrastructure and maintenance | 4.4 | 0.99 | 1 | 4.4 | 4 |
Disaster management centres | 4.3 | 0.86 | 1 |
Adequate domestic and industrial waste facilities | 4.5 | 0.69 | 1 |
Institutional | Equal distribution of the responsibility | 4.3 | 0.8 | 1 | 4.37 | 5 |
Synergy and harmonisation of policy | 4.55 | 0.6 | 1 |
Enforcement of good land use planning | 4.5 | 0.69 | 1 |
Role of faith-based organisation | 4.15 | 0.75 | 1 |
Social | Community engagement and empowerment | 4.35 | 0.75 | 1 | 4.35 | 6 |
Inter-community relationships | 4.35 | 0.67 | 1 |
Economic | Adequate livelihood | 4.4 | 0.88 | 1 | 4.28 | 7 |
Exhibition programmes | 4.15 | 0.75 | 1 |
Access to credit | 4.1 | 0.79 | 1 |
Ecological funding | 4.5 | 0.76 | 1 |
Demographic | Educational status | 4.2 | 0.77 | 1 | 4.2 | 8 |
The presence of community resilience indicators can actively enhance climate change preparedness and recovery (Plough et al. 2013; Steiner et al. 2016). Also, strengthening community resilience to climate change is critical in the face of uncertainty and the expected increase of climate change impact in the future (Ziyath et al. 2013). The measurement of community resilience indicators is not meant to be used to compare one community against another. Preferably, it should be used as a relative measure within each community to identify better where investments and resources could be effectively applied to address their challenges. As such, this research identified elements and indicators relevant to developing countries that can be prioritised for measuring the effectiveness of current policies designed to support community resilience to climate change.
Figure 1 shows the final eight elements from Table 7, and their associated indicators as developed in the current study for measuring community resilience to climate change, with 20 indicators identified by the experts and five transformative capacity indicators identified from the literature (Ogah, 2021). There are several similarities and differences between the current research and previous ones where, for example, community resilience elements from our work are in-line with that by Cutter et al. (2014), Alshehri et al. (2015) and Qin et al. (2017). Specifically, coping capacity is defined as consisting of seven elements (social, economic, infrastructural, institutional, demographic, environmental and health and fatality) that drive the resources, the capacity to prepare, absorb and recover from an event. The coping capacity indicators focus on short term strategies after a climate event. However, to improve community resilience, it is not simply about the short-term response strategies but nurturing and fostering stakeholders to engage in positive and sustainable strategies that build on the three capacities. The definition of adaptive capacity consists of six elements (training and awareness, social, economic, institutional, infrastructural, and environmental) that drive the processes that aid changes through learning, reorganisation and adaptation of communities to plan and respond to climate event.
Transformative capacity includes two elements (institutional and infrastructural) that involve changes in the deep structures that cause vulnerability and risk (Table 8). Transformative capacity also includes the institutional mechanism, regulations, infrastructure and social protective mechanism that create enabling environment for change. The main difference between the review indicators (Ogah, 2021) and the indicators identified by the experts is that the indicators from the review are more generalised as identified from different publications, context and scale. In contrast, the experts in the current study identified the indicators that are needed for the communities in developing countries and indicators that should be prioritised due to inadequate funding in the implementation of policies.
Table 8
Linking the capacities, elements and indicators of community resilience
Capacities | Elements | Expert indicators |
Coping capacity | Social | Inter-community relationships |
Demographic | Educational attainment |
Institutional | Role of faith base organisation |
Health and fatality | Access to health assistance and facilities |
Adaptive capacity | Social | Community engagement |
Economic | Adequate livelihood |
Exhibition programmes |
Access to credit |
Ecological funding |
Infrastructural | Resilient infrastructure and maintenance |
Adequate domestic and industrial waste facilities |
Disaster management centre |
Institutional | Enforcement of good land use planning |
Equal distribution of responsibility |
Synergy and harmonisation of policy |
Training and awareness | Learning and awareness |
Communicating information in local languages |
Adequate resource monitoring and feedback mechanisms |
Environmental | Sustainable agricultural practices |
Renewable energy |
Transformative capacity | Institutional | Mitigation plan |
Accident planning |
Infrastructural | Access to water |
Access to electricity |
Transportation |
4.3.1 Training and Awareness Element
Training and awareness is one of the most important elements to measure community resilience to climate change in this study. The element was ranked first and emphasised three indicators that contribute to measuring resilience level. The learning and awareness indicators measure the number of awareness campaigns, training programmes and local skills available in communities. Adequate resource monitoring and feedback mechanisms were measured by the number of resources and projects that are monitored, and the number of stakeholders that have access to this information and provide feedback. Furthermore, communicating information in local languages, i.e. the number of agencies that give out information in local languages for communities to be able to prepare for and overcome any sudden occurrence, is an essential indicator that measures community resilience in the face of climate change in developing countries. According to Channa and Ahmed (2010), the availability of information and communication during and after an event is very important. The number of awareness campaigns, training programmes and social skills available in communities have positively contributed to developing community resilience (Norris, 2008). The community as a whole should know about climate change hazards and the effects to which they are exposed, as well as how to plan, prepare, cope and adapt. Training and awareness provide various techniques or knowledge aspects that could be applied to actions to deal with any event.
4.3.2 Health and Fatality Element
For communities to be able to meet their needs and achieve better living conditions, the health and fatality indicator is very significant. It improves sanitation standards, health assistance and facilities, thereby ensuring the health-related safety and general well-being of community members (Orencio and Fuji, 2013; Alshehri et al. 2015; Alam et al. 2018). The overall resilience of a community can rest on the extent to which community members lead healthy lifestyles, have access to hospitals and doctors and are aware of the community’s health-related functional needs. Activities such as sanitation, infection control and awareness, nutritional status and awareness, and health insurance, are indicators that help to improve well-being (Cutter et al. 2014; Alshehri et al. 2015; Ahmed et al. 2016). In this study, the health and fatality indicators such as access to healthcare assistance and facilities, which are measured by the percentage of community members with access to doctors, nurses, clinics and hospitals, serve as community resilience indicators that help to manage climate change in developing countries. Under extreme conditions, the ability or capacity of trained health workers, and the availability of health centres and resources to effectively respond to these events, is vital. Health and fatality element and its related indicators have largely been incorporated into social indicators in most studies (Cutter et al. 2014). However, in this study, it is a standalone element that is key to measuring community resilience in communities.
4.3.3 Environmental Element
By improving green spaces, quality of natural resources and protecting biodiversity, environmental indicators activities can have direct implications for local climate change (Mavhura, 2017). They are, therefore, useful community resilience indicators to manage climate change in developing countries. The identified environmental indicators are renewable energy sources and sustainable agricultural practices. These are measured by the percentage of energy demand serviced by renewable energy sources, and the percentage of people involved in agricultural practices that mitigate the impacts of climate change.
4.3.4 Infrastructural Element
Infrastructure is a crucial area for achieving community resilience (Ainuddin and Routray, 2012; Feldmeyer et al. 2019). The ability of these infrastructures to withstand the shock posed by climate change represents the strength of the physical capital of the community. This research reveals that infrastructures are among the community resilience elements identified by experts to manage climate change. Specific indicators include resilient infrastructure and maintenance, which are measured by the percentage of buildings with building codes, sewers, and drains to handle excess water to prevent flooding, and adequate domestic and industrial waste facilities. They are measured also by the number and capacity of waste facilities available, disaster management centres, and the number of recovery centres relative to community size. The availability of physical capital, such as drains, sewers, waste facilities and recovery centres, is necessary for supporting various stages of community resilience starting from climate change mitigation to adaptation (Cutter et al. 2014; Ahmed et al. 2016), thus protecting the community from climate change repercussions. From a different perspective, Ahmed et al. (2016) stated that the development of resilient infrastructure and technologies such as barriers built for floods - seawalls and breakwaters - are substantial infrastructural barriers that are used to protect communities from flood or sea-level rise. However, Cai et al. (2016) observed that the existence of construction codes solely could not contribute to reducing the impact of climate change effect. It can, therefore, be implied that building codes have to be supported with other resilient infrastructures. They also claimed that high-density buildings and roads on lowlands would make communities more vulnerable to flood. However, infrastructural indicators are expensive to strengthen; therefore, the resilience of the physical capital of the community largely depends on the economic health of that community.
4.3.5 Institutional Element
Institutional element influences the capacities of a community to adapt to climate change events and is responsible for initiating and facilitating transformational processes to build resilience (Chung, 2017). This covers the arrangements and experience relating to the management of climate change impact that exists in a community (Feldmeyer et al. 2019). It is based on the development and maintenance of structured involvement and various networks that can contribute to the requirements of the community in planning and preparedness (Irwin et al. 2016). Our study shows that there is a general consensus on the institutional indicators, namely: Enforcement of good land use planning, i.e. implementation of plans on land use that are designed to mitigate the impacts of climate change; Equal distribution of the responsibility for the implementation of policy between the different sectors involved in the policy process; Synergy and harmonisation of policy, i.e. a common standard in regulations in different sectors, constituting of indicators to measure community resilience to manage climate change in developing countries; The role of faith-based organisations i.e. number of faith-based organisations involved in supporting the communities. Every community needs inclusive governance such as government, businesses, organisations and communities in making decisions, coordinating activities and integrated development planning.
Equal distribution of responsibility across government and non-governmental agencies helps to create the opportunity for development and fast track policy activities (Bulkeley, 2010). However, the key to this level of partnership for equal distribution of responsibility with other organisations is the level of coordination and organisation within the community itself (United Nations, 2012). Synergy and harmonisation of policy provide the ability, and builds capacity, to make decisions and implement strategies across a range of responsibilities and services (Tanner et al. 2009). Also, due to the cross-cutting nature of climate change governance, most government departments and agencies are often not able to implement policies that need to address climate change problems. Thus, a good synergy and harmonisation of policy will help to bolster community resilience. Furthermore, the role of faith-based organisations can significantly engage and empower community members to develop resilience (Niaz, 2006). This is important since most developing countries are multi-religious, with high numbers of religious faith-based groups. Overall, the indicators within the institutional element reflect that top-down to bottom-up approaches should be adopted in creating linkages and planning and preparedness to enable communities to cope and recover from an event (Joerin et al. 2012).
4.3.6 Social Element
The social element consists of the activities and processes which build collaboration between individuals within and outside the community (Cutter, 2010; 2014; Aldrich and Meyer, 2014; Kim et al. 2017). Social indicators support fast and reliable relationships that constitute a network that can help release ideas, lessen losses and improve the community's self-reliability. In the current study there is a consensus amongst the experts that social indicators like community engagement and empowerment are closely linked. That is, the percentage of people involved in community activities and inter-community relationships or working relationships between two or more communities, are among the community resilience indicators that help to manage climate change in the context of Nigeria. Community engagement and empowerment programmes would not only encourage community members to become responsible but also knowledgeable and aware of their community's socio-economic and ecological status (Cutter et al. 2014; Forest and Milliken, 2018). Therefore, community engagement and empowerment processes are significant acts for measuring community resilience. Furthermore, inter-community relationship is generally based upon the relatability among the people living under similar conditions, providing social supports and assistance, especially in case of emergencies (Amundsen, 2012). The more people are involved in community services, the easier it is for the community to adapt to climate change (Khalili et al. 2015). Also, cooperation between two or more communities on climate challenges helps build more robust and broader community resilience and faster recovery following a climate-induced disaster (Amundsen, 2012; Smith, 2012; Islam and Walkerden, 2017). These measures foster bonding, bridging, linkages and connectedness among the community members, which is very important during a climate event (Aldrich and Meyer, 2014). Thus, the larger the membership in the community, the higher the collective action to support community resilience to climate change.
4.3.7 Economic Element
The economic element plays a vital role in the empowerment of communities to become resilient to climate change (Bach, 2015; Kim and Marcuiller, 2016). This element is assessed from the household level to the entire community and includes community finances for various purposes on different levels that can support the community's goal. Also, there is a consensus on the economic indicators, and they are a significant component of community resilience to manage climate change. These include: (i) Adequate livelihood, i.e. the percentage of people living below the poverty line; (ii) Access to credit, measured by the percentage of people with access to credit facilities; (iii) Ecological funding, i.e. the percentage of annual spending from the government for climate change mitigation and adaptation projects; and (iv) Exhibition programmes, i.e. a number of local exhibition programmes to showcase community-based products. One primary reason why people are vulnerable to climate change is related to their economic status (Lo et al. 2015). People who are limited in income or live below the poverty line will find it challenging to put up adaptive measures in place against climate change (Ahmed et al. 2016; Quasim et al. 2016). Furthermore, Qin et al. (2017) posited that improved livelihood of an individual as an intrinsic part of the community would influence the community resilience as its sufficiency would absorb the climate change-related repercussions and accelerate the adoption process. It is assumed that a diversified community livelihood makes the community more resilient and can improve their stability (Norris et al. 2008; Wilson, 2013; Ashkenazy et al. 2017). Hence, the higher the level of finances, the greater the ability of households and community to absorb the impacts of climate change.
Access to credit was considered a significant resource for enhancing the financial ability of communities to adapt (Feldmeyer et al. 2019). Furthermore, funding of ecological projects is necessary for policy activities to succeed, and this responsibility needs to be shared by all those who have a stake (United Nations, 2012). Many developing nations do not have sufficient budgets to support policy activities and cannot provide subsidies or incentives for sustainable plans and preparedness. Thus, these indicators are considered necessary in measuring community resilience to climate change. Also, a community can have education, training and infrastructural facilities; however, if its economy is weak and affecting livelihoods, then all other indicators will not succeed (Norris et al. 2008).
4.3.8 Demographic Element
Demographic element is an integral part of community resilience (Akamani, 2012; Bene et al. 2017). It plays a significant role in collecting the attributes of the community, which is further used in measuring efficiency in the implementation of policy actions. In this research, the demographic element focused on educational status, i.e. the percentage of the population with school leaving certificate is an identified factor that supports community resilience to climate change. There was a consensus among all the experts that a well-informed individual has the knowledge and skills to put adaptive measures in place to enable community resilience. According to Ainuddin and Routray (2012), educational status gives an abstract idea of how educated and informed the people are towards the knowledge transfer and skills that could be useful during emergencies. Thus, the higher the ratio of the educated to uneducated people in a community, the better placed the community is to cope with climate change. In addition, improving and investing in education will save many lives and enhance community resilience (United Nations, 2012). This element was incorporated into the social element in other studies (Qasim et al. 2016; Qin et al. 2017), contrasting our study, where demography is a separate element with its respective indicators to measure community resilience to climate change.