Editing IPCC:AR6/WGII/Chapter-8 (section)

== 8.5 Adaptation Options and Enabling Environments for Adaptation with a Particular Focus on the Poor, Different Livelihood Capitals and Vulnerable Groups ==

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This section focuses on adaptation at household and community scales, including options, capacity and enabling environment, which include actions required towards building resilience. The emphasis is on the decision-making space and governance including the role of the state, private sector and other actors. Successful adaptation requires not only identifying adaptation options and assessing their costs and benefits, but also exploiting available mechanisms for expanding the adaptive capacity of human and natural systems ( [[#Klein--2014|Klein et al., 2014]] ). At the same time, developing suitable responses to hazards for communities and users of climate services is important in ensuring the success of adaptation measures. But despite this, knowledge about adaptation options, including possible actions that can be implemented to improve adaptation and reduce the impacts of climate change hazards, is still limited.

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=== 8.5.1 Adaptation Options to Climate Change Hazards Focusing on Vulnerable Groups ===

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In light of the severe adverse consequences of climate change for the poorest populations, whose livelihoods are frequently dependent on vulnerable ecosystems, it is essential to enhance knowledge about sustainable and appropriate adaptation strategies and measures, as well as recognise and respond to limits to adaptation as reported in AR5 ( [[#Somorin--2010|Somorin, 2010]] ; [[#Noble--2014|Noble et al., 2014]] ; [[#Connolly-Boutin--2016|Connolly-Boutin and Smit, 2016]] ). There is increasing evidence on the adaptation options that enhance the ability of different socio-ecological systems to become resilient in the long term in ways that do not exacerbate poverty and inequality, and on which adaptations may have little or no impact, or even adverse effects (maladaptation). Analysis of climate hazards can provide an indication of required adaptation strategies, however, most important is the focus on exposure and vulnerability. The novelty of the AR6 is the assessment of existing response capacities to cope and adapt to climate changes and associated hazards. There is increasing knowledge about the differential adaptation options within and across social groups and the influence of (enabling) conditions that enhance or limit these options.

From the analysis in the IPCC AR5, there is ''high agreement'' that engineered and technological adaptation options are still the most common adaptation responses. However, there is increased recognition of the value of ecosystem-based, institutional and social measures, including the provision of climate-linked safety nets for those who are most vulnerable ( [[#IPCC--2014a|IPCC, 2014a]] ). Climate adaptation measures are increasingly integrated within wider policy, development strategies and spatial planning frameworks. Such integration streamlines the adaptation planning and decision-making process and embeds climate-sensitive thinking in existing and new institutions and organisations across scales and levels.

In past decades, a number of categories of adaptation options have been identified and are discussed in [[#8.5|Section 8.5]] . Adaptation options are categorised in various ways, such as in terms of grey and green adaptation or hard and soft measures ( [[#Depietri--2013|Depietri et al., 2013]] ; [[#Chambwera--2014|Chambwera et al., 2014]] ; [[#Grimm--2015|Grimm et al., 2015]] ). Grey measures refer, for example, to technological and engineering solutions to improve adaptation of infrastructures or to protect a specific land use or city from adverse consequences of climate hazards ( [[#OECD--2018|OECD, 2018]] ). Accordingly, ecosystem-based approaches, including natural infrastructure, can provide an effective complement or substitute for traditional built (or ‘grey’) infrastructure. For example, watershed restoration can protect sources of drinking water and reduce the need for subsequent treatment. Green measures often encompass ecosystem-based (or nature-based) approaches. These make use of the multiple services provided by ecosystems to improve resilience and adaptive capacity or to reduce risk. Soft adaptation measures include policy, legal, social, management and financial measures that can alter human behaviour and support adaptive governance, contributing to improved adaptation capacity, increased awareness, and change in values and actions on climate change issues.

Adaptation actions frequently include deliberate, coordinated, proactive policy decisions based on the awareness that conditions have changed or will change and that action is required to avert impacts or return to, maintain or achieve a desired state ( [[#Carter--1994|Carter et al., 1994]] ). Governance provides an important contextual framing, particularly in contexts where it is weak or contested (e.g., some of the Sahel zone). In these cases, it can mean that adaptation options stem largely from the local level. Adaptation processes can be categorised as individual, collective, proactive, reactive, autonomous, coordinated or natural ( [[#Chambwera--2014|Chambwera et al., 2014]] ). Apart from governments, other actors, organisations and institutions (including non-state agencies and private industry actors) also play an important part in adaptation processes, and consequently the discussion of enabling environments for sustainable or successful adaptation has to consider these different scales and actors. For example, while autonomous adaptations are mainly undertaken by private actors, triggered by climate change-induced market or welfare changes, planned adaptations can be carried out by both private and public actors. Natural adaptations appear within ecosystems as a reaction to climate change, as well as other factors, and incorporate innumerable possible actions that are context specific, ranging from managerial approaches to technological innovations and ecosystem-based approaches ( [[#Huq--2004|Huq et al., 2004]] ). [[#Sanchez--2017|Sanchez et al. (2017)]] draws attention to preconceived ideas about some adaptation measures that are either considered good or bad without proper evaluation. It is argued that the association ‘hard-bad’ and ‘soft-good’ is not necessarily true; the impacts of adaptation can only be established through a case-by-case assessment. The decision to select a more or less intensive adaptation measure should integrate all approaches, social, environmental, technical and economic, in a multi-criteria analysis. This analysis should value, ''inter alia'' , social and environmental sensitivity, benefits and drawbacks or trade-offs with climate, including all the adaptation options, among them the ‘no action’ alternative.

Adaptation frequently responds to an observed or anticipated ‘trigger’ for response, such as the looming loss of land to sea level rise ( [[#Barnett--2014|Barnett et al., 2014]] ). Identifying adaptation needs stemming from climate risks and vulnerabilities provides a foundation for selecting a sequence of adaptation options that connect through time, a long-term adaptation pathway ( [[#Wise--2014|Wise et al., 2014]] ; [[#Turnheim--2015|Turnheim et al., 2015]] ). National, sectoral or local adaptation plans are ''likely'' to include a number of measures that are implemented jointly from across various categories, including structural, institutional and social options. While structural or physical adaptation encompasses measures for the engineered built environment it also can encompass nature-based solutions, which include ecosystem-based protection measures, for example to buffer risks and hazard exposure to extreme weather events. The category of ‘soft’ adaptation measures—changes in societal values or practices—is often linked to issues of education, information and behavioural changes to support communities within specific adaptation processes to climate change and climate hazards. Institutional adaptation deals with adaptation actions and measures introduced through new legal frameworks, laws and regulations for new institutions or policies for risk reduction and adaptation. This category can also encompass the development of new organisations that have a mandate to support adaptation ( [[#Noble--2014|Noble et al., 2014]] ). The appropriateness and accessibility of adaptation options under these categories for supporting the poor and most vulnerable groups differs. In many cases large-scale structural measures are not affordable for many poor communities. Despite this important potential of Indigenous knowledge for disaster risk reduction of communities, it is often shunned by practitioners ( [[#Dube--2018|Dube and Munsaka, 2018]] ). It is further argued by practitioners that Indigenous knowledge lacks documentation, it is not found in all generational classes, it is contextualised to particular communities and the knowledge cannot be scientifically validated. However, there is also evidence that both local communities and disaster risk reduction practitioners can benefit from the Indigenous knowledge of communities ( [[#Dube--2018|Dube and Munsaka, 2018]] ).

In practice, adaptation refers to initiatives such as a policy, plan, project or decision that are designed to change and/or respond to something in the context of existing risks and hazards. For example, a farmer might adapt to drought by deciding to harvest their crop earlier; a municipality can decide to build a sea wall to adapt to increased flood risk.

The increasing complexity of adaptation practice means that institutional learning is an important component of effective adaptation ( [[#Noble--2014|Noble et al., 2014]] ). It is paramount that approaches to selecting adaptation options continue to emphasise incremental change to reduce impacts while achieving co-benefits. There is increasing evidence that transformative changes may be necessary in order to prepare for climate change impacts and adaptation options in the context of climate hazards ( [[#Noble--2014|Noble et al., 2014]] ). Transformation for some actors at some levels may equate with incremental change and transitions for other actors and scales. While attention to flexibility and safety margins is becoming more common in selecting adaptation options, many see the need for more urgent and transformative changes in our perception and paradigms about the nature of climate change, adaptation and their relationship to other natural and human systems.

In this context, there are many potential adaptation options available for a marginal change of existing agricultural and other livelihood systems, often variations of existing climate risk management. According to [[#Howden--2007|Howden et al. (2007)]] , implementation of these options is ''likely'' to have substantial benefits under moderate climate change for some existing cropping systems. Apparently, there are limits to their effectiveness under more severe climate changes. Hence, more systemic changes in resource allocation need to be considered, such as targeted diversification of production systems and livelihoods. [[#Howden--2007|Howden et al. (2007)]] further argue that achieving increased adaptation action will necessitate integration of climate change-related issues with other risk factors, which implies integrating non-climatic factors, such as climate variability and market risk, and with other policy domains, such as sustainable development. An increasing number of research programmes seek to support adaptation to climate change through the engagement of large-scale transdisciplinary networks that span countries and continents ( [[#Cundill--2019|Cundill et al., 2019]] ).

Based on analysis of different adaptation options, there is ''high agreement'' that the many barriers to effective adaptation will require a comprehensive and dynamic policy approach covering a range of geographical scales and multiple actors across scales, taking into consideration both climatic and non-climatic stress factors ( [[#Eriksen--2015|Eriksen et al., 2015]] ). For instance, from the agricultural perspective, this could imply the understanding by farmers of change in risk profiles to the establishment of efficient markets that facilitate response strategies. It is also important to note that science, too, has to adapt employing a range of approaches, based on the fact that multidisciplinary problems require multidisciplinary solutions. Towards enhancing resilience, a focus on integrated rather than disciplinary science alone could be of utmost importance as well as strengthening of the interface with key stakeholders, ranging from decision makers, practitioners, policymakers and scientists.

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=== 8.5.2 Enabling Environments for Adaptation in Different Socioeconomic Contexts ===

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==== 8.5.2.1 Factors that Support Enabling Environments for Adaptation ====

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This section assesses the literature on components of the enabling environment for adaptation. The point of departure considers findings in both the SR1.5°C report, which notes that adaptation becomes increasingly difficult (and expensive) at temperatures that are more than 1.5°C warmer ( [[#IPCC--2018a|IPCC, 2018a]] ). In addition, ( [[#IPCC--2014a|IPCC, 2014a]] ) underscores that there is no one-size-fits-all approach to adaptation for all contexts, and that mitigation and adaptation must be pursued in tandem.

Climate change affects people inequitably, and everyone does not contribute equally to climate change. A range of economic and non-economic impacts can be experienced. This has led some researchers to call for a more central role for rights-based approaches to adaptation to help secure space for those marginalised from adaptation decision making and to prioritise access to resources and information for those most vulnerable to, or affected by, the social, cultural or economic consequences of climate change ( [[#Bee--2013|Bee et al., 2013]] ; [[#Da%20Costa--2014|Da Costa, 2014]] ; [[#Toussaint--2020|Toussaint and Martinez Blanco, 2020]] ; Box 8.7; [[IPCC:Wg2:Chapter:Chapter-5#5.12|Section 5.12]] ). In terms of international law, the human rights obligations of states have been subject to multiple recommendations relating to climate change by United Nations treaty bodies in the reporting period. More broadly, rights-based approaches rely on the normative framework of human rights, requiring adaptation to be non-discriminatory, participatory, transparent and accountable in both formal (e.g., legal and regulatory) and informal (e.g., social or cultural norms) settings and at international, national and sub-national scales ( [[#Ensor--2015|Ensor et al., 2015]] ; [[#Arts--2017|Arts, 2017]] ). Sovacool et al. (2015) note that unless critical competing interests are addressed during planning, adaptations may fail to achieve the desired outcomes. This is increasingly seen at a political level within efforts to implement the Paris Agreement, in relation to the principle of ‘common but differentiated responsibilities and respective capacities’ (CBDR-RC) (Box 8.7).

The scale of analysis, baseline conditions prior to adaptation and scale of action matter too when assessing the key components of an enabling environment for adaptation. At a national scale, it is well established that low-income countries are less well positioned to manage climate change impacts, being variously attributed to a lack of institutional, economic or financial capacity to adapt effectively ( [[#Tol--2007|Tol and Yohe, 2007]] ; [[#Barr--2010|Barr et al., 2010]] ). It can be particularly difficult to adapt to drought, for example, when it occurs in the pre-conditions of poor water supplies and sanitation (see Box 8.5; [[#8.3.2|Section 8.3.2]] ), and in a context of corruption, governance failure and a lack of accountability. Adaptation productivity in higher-income countries is further supported by better infrastructure and stronger institutions—low adaptation efficiency is linked to lower government spending, higher inequalities in income distribution and poor governance ( [[#Fankhauser--2014|Fankhauser and McDermott, 2014]] ). At smaller scales, even within a single socioeconomic setting, different groups require different kinds of adaptation support and exhibit different vulnerabilities to climate change impacts. Huynh and Stringer (2018) found that households vulnerable to climate change impacts linked to sea level rise and flooding in Da Nang City and Ngu Hanh Son district, Vietnam, had limited access to human, natural, physical, financial and social assets, and lacked a diversified livelihood portfolio. An enabling environment for household-level adaptation would need to address these factors in this context. However, the same authors found that at district scale, different challenges persisted, including obstacles to multidirectional flows of climate information, poor vertical interplay both upward and downward, and a lack of citizen participation in the governance of climate change.

Acknowledging that context and scale matter, it is nevertheless possible to set out the core components of a generic enabling environment (Figure 8.12), linking them to the literature on climate change and recognising how they can support adaptation in different socioeconomic and environmental settings in which different emphases are required. This broad set of enablers requires different emphases according to the specific context, yet the interdependence between them is universally applicable.

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[[File:e9c11d0cdc7da3b271bcb467ecf09d9e IPCC_AR6_WGII_Figure_8_012.png]]

'''Figure 8.12 |''' '''Core components of the enabling environment for adaptation to climate change''' (key interactions are illustrated but there are overlaps, interactions and feedbacks both within and between each item; and different countries have different capacities and starting points in addressing these enablers and the interlinkages between them).

The specific political economy of each country and its underpinning philosophies shape the national political context in which public policy supporting adaptation is developed and implemented. It further shapes the context for private adaptation. Public policy targeting climate change seeks to address market failures, amend policy distortions and offer incentives for private adaptation, as well as provide climate-resilient public goods, climate services and safety nets for the poor and vulnerable ( [[#Fankhauser--2017|Fankhauser, 2017]] ). In some countries that have a more stable institutional context, such policies are more straightforward to develop and implement; while in countries with weaker institutions (e.g., those emerging from conflict), a larger role may be needed for regional economic commissions and transnational networks to support the governance of ‘borderless climate risks’ ( [[#Benzie--2019|Benzie and Persson, 2019]] ), particularly where these countries also are most vulnerable to climate change (see also Figure 8.6). To support enabling conditions in highly vulnerable countries that are also characterised by state fragility (see Figure 8.8), funding and projects designed to support adaptation may need to be modified to effectively promote regional cooperation and transboundary adaptation. Nevertheless, such interventions can also reinforce particularly powerful agendas and fail to assist and empower those with the greatest need to adapt ( [[#Biermann--2010|Biermann et al., 2010]] ; [[#Burch--2019|Burch et al., 2019]] ) neglecting community voices and sovereignty ( [[#Schlosberg--2014|Schlosberg and Collins, 2014]] ). It is therefore important that the relevance of people and community empowerment to effectively achieve vulnerability reduction and climate change adaptation is recognised.

It is also insufficient to consider countries as stand-alone entities, due to links such as those provided by international trade. Taking Europe as an example, the continent has strong links to major trade partners such as India, Indonesia, Nigeria and Vietnam, so failure to assist adaptation in other locations opens up important vulnerabilities through supply chains ( [[#Lung--2017|Lung et al., 2017]] ). Policies seeking to protect national interests alone (e.g., in terms of food security) are seen as causes of negative impacts at a global scale ( [[#Puma--2015|Puma et al., 2015]] ; [[#Challinor--2017|Challinor et al., 2017]] ), with those nations and individuals least able to adapt to evolving climate changes experiencing exacerbation of existing imbalances ( [[#Elbehri--2015|Elbehri et al., 2015]] ). LDCs are projected to suffer greater import losses in more connected networks ( [[#Puma--2015|Puma et al., 2015]] ). In the food sector, poorer net food buyers are anticipated to experience the worst impacts of climate change ( [[#Gitz--2015|Gitz et al., 2015]] ).

Behind each policy are decisions about the magnitude of financial resource investments in specific adaptation actions, and their allocation between different sectors and groups in society, both spatially and temporally. The IPCC has estimated that limiting the rise in global average surface temperatures to 1.5°C would require between USD 1.6 trillion to USD 3.8 trillion of annual investment in supply-side energy systems (those that generate energy) between 2016 and 2050 ( [[#IPCC--2018b|IPCC, 2018b]] ). Resource allocations, however, are shaped by perceptions of the risks of climate change and the urgency of actions, as well as other motivational factors such as descriptive norms and perceived self-efficacy ( [[#van%20Valkengoed--2019|van Valkengoed and Steg, 2019]] ) and the underlying approaches taken to valuing human well-being (e.g., see work from Bhutan on Gross National Happiness and climate change actions ( [[#Kamei--2021|Kamei et al., 2021]] )).

An increase in finance mobilised, however, does not automatically equate to adaptation interventions on the ground, nor does it guarantee the effectiveness of those adaptations deployed ( [[#Berrang-Ford--2021|Berrang-Ford et al., 2021]] ). Unintended negative consequences may arise due to lack of understanding of the drivers of vulnerability (such as gender inequality or inequitable access to natural resources), non-involvement of marginalised local groups, retrofitting adaptation into existing development agendas, and insufficiently defining adaptation success ( [[#Eriksen--2021|Eriksen et al., 2021]] ). A 2017 study estimated that less than 10% of climate finance committed from international, regional and national climate funds to developing countries between 2003 and 2016 went to locally focused projects, suggesting a need to rethink approaches if the most affected groups are to build sufficient resilience to the impacts of climate change ( [[#Soanes--2017|Soanes et al., 2017]] ).

The literature shows with ''high confidence'' that the poorest groups in society often lose out, and require greater planned adaptation support, having less capacity to adapt than better off groups with easy access to assets ( [[#Barbier--2018|Barbier and Hochard, 2018]] ; [[#Ziervogel--2019b|Ziervogel, 2019b]] ; Box 8.5). Developing countries such as Burkina Faso, Mali and Zambia are not only among the most vulnerable to climate change, they are also the least able to mobilise the finance needed to adapt to its impacts (ND-GAIN, 2019). Women and girls are often most heavily burdened. When building adaptive capacity, these groups can require different support such that their knowledge, capacities and skills can be harnessed, in such a way that does not feminise responsibility and add to their burdens ( [[#Clissold--2020|Clissold et al., 2020]] ; [[#McNamara--2021a|McNamara et al., 2021a]] ).

There is broad support for the notion, enshrined in the Paris Agreement, that adaptation finance flowing to developing countries of the Global South should primarily benefit the most climate-vulnerable among them due to their limited technical capacity and financial capabilities, yet such countries are often insufficiently considered in funding decisions. There are nevertheless concerns regarding institutional fit: that foreign funding regimes may not map onto more recently developed administrative traditions, leading to dominance of governance models emanating from donors ( [[#Vink--2018|Vink and Schouten, 2018]] ). Research has found multilateral donors do not prioritise vulnerable developing countries at the project selection stage and they have received smaller allocations of adaptation finance from bilateral donors than less vulnerable countries ( [[#Saunders--2019|Saunders, 2019]] ), leaving the poor vulnerable to climate impacts. The lack of climate finance flowing to LDCs and SIDs (currently 14% and 2% of the total, respectively) is compounded by access issues due to the inability of domestic institutions to meet specific fiduciary standards and other access requirements, insufficient human resource support and the inflexibility of current approaches, which are biased in favour of governments and against non-traditional actors, such as local enterprise and grassroots organisations ( [[#Shakya--2021|Shakya et al., 2021]] ). Further, vulnerable developing countries shoulder additional financial burden, embodied in higher interest payments to service public and private debt, due to the increased cost of capital brought about by greater exposure to climate risks ( [[#Buhr--2018|Buhr et al., 2018]] ). This has been further exacerbated by the recession and debt distress accompanying the COVID-19 pandemic ( [[#Kose--2021|Kose et al., 2021]] ). A range of reforms, including comprehensive debt relief by public creditors, green recovery bonds, debt-for-climate swaps and new SDG-aligned debt instruments may address unsustainable debt burdens, freeing up investment in climate adaptation and a green economic recovery ( [[#Volz--2020|Volz et al., 2020]] ; see [[#8.6.3.1|Section 8.6.3.1]] ).

Greater investment is also needed in the developed countries of the Global North. For example, the 2018 forest fires in Sweden, the 2019–2020 Australian bushfire season and the 2020 forest fire season along the US West Coast were unusually long and severe, resulting in unprecedented damage to natural habitats and human livelihoods and, relatedly, significant economic cost, particularly given interlinkages with other stressors such as COVID-19. While a range of drivers underpin annual fire seasons, including greater water withdrawal and years of fire suppression, early research indicates that climate change increases their likelihood due to long-term warming trends ( [[#van%20Oldenborgh--2021a|van Oldenborgh et al., 2021a]] ).

However, investing in poverty reduction does not necessarily lead to climate change adaptation and where adaptation does result, it does not always reduce vulnerability of the most marginalised, as documented in case studies from northeast Brazil ( [[#Nelson--2016|Nelson et al., 2016]] ). Poverty also affects private adaptation options. For example, research from Portugal highlights the importance of private financial assets in helping older adults to adapt to extreme temperatures ( [[#Nunes--2018|Nunes, 2018]] ).

Policies and investments that are adopted are embedded within the relevant legal and regulatory frameworks, which extend beyond national jurisdictions upward to the regional scale (such as the Southern Africa Development Community’s Southern Africa Regional Framework of Climate Change Programmes, 2010) and international scale, for example, UNFCCC, the 2015 Paris Agreement, the Sendai Framework for Disaster Risk Reduction, the New Urban Agenda and the SDGs. Legal and regulatory concerns also extend downward to shape local- and city-scale adaptation efforts (e.g., Sao Paulo’s municipal policy and new master plan). Nevertheless, only a minority of countries have dedicated legal frameworks supporting adaptation ( [[#Lesnikowski--2017|Lesnikowski et al., 2017]] ) and these often lack in both precision and obligation—largely because adaptation is a contested global public good but also because adaptation is commonly bundled in with mitigation commitments ( [[#Hall--2018|Hall and Persson, 2018]] ). Coherence, horizontally and vertically in both policy and law is often lacking. At the same time, bottom-up, private, autonomous adaptation efforts are being better tracked, with different actors motivated by growing experiences of local climate change impacts ( [[#Berrang-Ford--2014|Berrang-Ford et al., 2014]] ). While the emergent polycentricity of adaptation governance is beginning to take shape, wherein both state and non-state actors share a common adaptation goal and interact coherently, yet often independently, to advance progress towards it ( [[#Morrison--2019|Morrison et al., 2019]] ), understandings of how various centres of decision making with different degrees of autonomy support an enabling environment for adaptation, remain at a nascent stage. Multiple scales and forms of adaptation occur, with attributes such as self-organisation, appreciation of site-specific conditions, and the need for learning and experimentation, alongside building of trust, increasingly shown to be vital ( [[#Dorsch--2017|Dorsch and Flachsland, 2017]] ). Literature indicates that professional and learning networks are important groups supporting adaptation in cities and can help harness resources ( [[#Woodruff--2018|Woodruff, 2018]] ); while the research of ( [[#Hauge--2019|Hauge et al., 2019]] ) in Norway underscores the importance of working across multiple disciplines and the inclusion of actors from different levels of authority in multi-level municipal networks. They found that these factors can help to identify specific adaptation actions as well support knowledge sharing within participating organisations, which in turn helps garner commitment to adaptation and its implementation. They also found that it is important to involve local leaders in polycentric adaptation networks.

Among the many institutions, actors and roles associated with successful adaptation, two play an increasingly important role: local governments and the private sector ( [[#Noble--2014|Noble et al., 2014]] ). These groups often define the flows of information and finance from the top down, as well as supporting the scaling up of community and household adaptation. In some countries, for example, in South America (Argentina, Brazil, Paraguay) vocational agricultural schools, often in remote rural locations, play a key part in knowledge-sharing activities that support adaptation. Similar valuable contributions are made by universities through their outreach activities, particularly those offering programmes in environmental and agricultural fields. Many actors face a lack of resources and capacity, particularly at the local level. Local institutions, including local governments, NGOs and civil society organisations, are hampered by ongoing challenges in gaining support from higher governance levels—from national government or the international community—particularly in developing countries. At the same time, private sector actors, from individual farmers and small/medium enterprises (SMEs) as well as large multinational businesses, will seek to protect and enhance their production systems, supply chains and markets by pursuing adaptation-related opportunities. Yet, while these goals will help expand adaptation activities, they may not align with government or community objectives and priorities without coordination and incentives, and in the process, can reinforce existing capacities, inequalities and power relations ( [[#Sovacool--2015|Sovacool et al., 2015]] ). Similarly, an enabling environment for businesses’ adaptation is highly differentiated and often requires structural deficits (such as limited market access, finance and transport and communications infrastructure) to be tackled ( [[#Gannon--2020|Gannon et al., 2020]] ).

The challenges of climate change have driven governments around the world to emphasise climate services as a route to enhance decision making and reduce climate-related risks, as well as inform adaptation, supporting calls for the right to information ( [[#Tall--2013|Tall and Njinga, 2013]] ). While there have been some efforts to evaluate the economic impact of climate services alongside other impacts (e.g, [[#Tall--2018|Tall et al., 2018]] ), little is known about the institutional contexts in which investments in climate services have taken place, nor those groups that are most vulnerable or marginalised in relation to specific climate risks. [[#Vincent--2017|Vincent et al. (2017)]] offer preliminary insights from Malawi, identifying that barriers to improved integration of climate services in national policy planning include factors relating to spatial and temporal scale, accessibility and timing of information provision, credibility and mismatches in time frames between planning cycles and climate projections. An understanding of the factors that enable climate service investment is important for the development of climate services at local, national and international levels ( [[#Vaughan--2017|Vaughan et al., 2017]] ) but this area of literature is not yet well developed.

Overall, adaptation entails financial (and non-financial) costs not just in implementing adaptation actions, but also in designing, facilitating and preparing for actions—costs to create and maintain an enabling environment (see also [[#8.2|Section 8.2.2.3]] ; Cross-Chapter Box LOSS in Chapter 17). Financial and economic investments target the whole range of other types of asset (natural capital, physical capital, human capital, social capital). AR5 reports that aggregate economic losses accelerate with increasing temperatures ( [[#IPCC--2014a|IPCC, 2014a]] ). Costs may be borne when gaining information (e.g., investments in climate services), while adjustment costs are incurred as adaptations take place. Nevertheless, to enable adaptation, investment is needed in various natural, human, physical and social assets, as considered below. The importance of investment in each of these different types of asset varies according to the scale and livelihood system in need of adaptation and the ways in which livelihood resilience is framed and power is distributed, within each specific setting ( [[#Carr--2020|Carr, 2020]] ).

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==== 8.5.2.2 Natural Capital ====

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It is well established that climate change compounds the impacts of pressures that humans place on the environment ( ''high confidence'' ) and that environmental degradation can undermine options for adaptation and an enabling environment, with poor and natural resource-dependent groups most acutely affected (see e.g., [https://www.ipcc.ch/chapter/cross-chapter-paper-3 Cross-Chapter Paper 3] for insights from deserts and semiarid areas). Sustainable management of natural capital contributes to building resilience and the natural ability of ecosystems to adapt to climate change ( [[#IPCC--2014a|IPCC, 2014a]] ; see also IPCC SROCC, [[IPCC:Wg2:Chapter:Chapter-5#5.3.2|Section 5.3.2]] , [[#Bindoff--2019|Bindoff et al., 2019]] ). Some systems like mangroves (found in 123 countries, many of which are in the Developing World) offer a broad range of vital ecosystem services ( [[#Hamza--2020|Hamza et al., 2020]] ). Mangroves provide regulating services by acting as a natural defence against sea level rise and storm surges; and by sequestering carbon in both the trees and sediments they capture. Provisioning services (e.g., fish, crabs, timber and fuelwood) from mangroves support livelihoods and livelihood adaptation options, especially for those with few other livelihood opportunities, while these systems also provide important habitat (breeding, spawning and nursery grounds for fish) and biodiversity, and offer cultural services in the forms of education, recreation and spiritual benefits ( [[#Quinn--2017|Quinn et al., 2017]] ). As the frequency of events such as hurricanes, storms and typhoons rises with climate change, natural capital assets like mangroves become increasingly important in protecting coastlines and supporting adaptation. While not reducing the hazard itself, the mangroves reduce exposure and, in some cases, also vulnerability. The literature shows with ''high confidence'' that environmental assets support both climate change mitigation (at a large scale) and adaptation (at a smaller scale), particularly for the poorest groups in society, who directly depend upon natural capital for their subsistence (e.g., [[#Angelsen--2014|Angelsen et al., 2014]] ). In turn, the legal and regulatory context and institutional set up determines who has access rights to different aspects of the natural resource base. This shows how different aspects of the enabling environment work in tandem to constitute one another.

In a market economy, human activities tend to exacerbate degradation of natural capital, despite its role in buffering climate change impacts, supporting mitigation and providing adaptation options. Economic agents base their decisions on market prices, even though market prices do not incorporate the costs of deteriorating natural capital because of externalities and other market failures, that is environmental degradation is not internalised ( [[#Bowen--2012|Bowen et al., 2012]] ). At the same time, expanding populations, capitalism and consumption choices affect the condition of natural capital, alongside short-termism stemming from poverty, linked to the need for survival. All these factors therefore interact, with the aggregate effect of worsening the impacts of climate change, while also undermining future adaptation options, particularly for the poor. Adaptation policies should, but do not always, compensate for the prevalent market failures. For example, in Melanesia, sea walls have been built out of coral by local people in an attempt to reduce the impacts of rising sea levels, leading to outright destruction of some of the world’s most productive and biodiverse coral reefs ( [[#Martin--2016|Martin and Watson, 2016]] ). Similarly, in the Congo Basin, farmers are adapting to increasingly variable rainfall by expanding their cropping activities into forested areas, releasing carbon into the atmosphere through forest clearance activities and threatening biodiversity. Agricultural land is also being degraded globally (see [[#IPCC--2019a|IPCC, 2019a]] ), and this too closes down adaptation and livelihood options for the poorest, natural resource-dependent populations, while jeopardising food security, biodiversity and human health at wider scales. An enabling environment for adaptation therefore demands investment in sustaining natural capital at multiple scales, internalising the costs of degradation, as well as establishing the necessary legal and regulatory frameworks (and associated enforcement) to reduce its degradation ( [[#IPBES--2018|IPBES, 2018]] ).

The literature increasingly shows that approaches such as nature-based solutions (NBS) and ecosystem-based adaptation (see Chapters 2; 6) can offer value for money in tackling climate change from both a mitigation and adaptation standpoint ( [[#Seddon--2020|Seddon et al., 2020]] ). According to the Global Commission on Adaptation, a global investment of USD 1.8 trillion between 2020 and 2030 into adaptation measures such as early warning systems, climate-resilient infrastructure, improved dryland agriculture, mangrove protection, and resilient water resources can yield USD 7.1 trillion in total net benefits ( [[#Global%20Commission%20on%20Adaptation--2019|Global Commission on Adaptation, 2019]] ). NBS operate by harnessing natural processes, sometimes in combination with technological or engineered solutions. Examples encompass green public spaces and parks ( [[#Sahakian--2020|Sahakian and Anantharaman, 2020]] ), green infrastructure, such as urban forests and street trees ( [[#Richards--2017|Richards and Edwards, 2017]] ), which create shade and reduce urban heat island effects whereby urban areas are warmer than their surroundings ( [[#Depietri--2013|Depietri et al., 2013]] ), and support human health and well-being by keeping people in cities more closely linked with nature ( [[#Gulsrud--2018|Gulsrud et al., 2018]] ). NBS also encompasses blue infrastructure including constructed wetlands, bioswales, rain gardens and so forth, which can reduce flood risks ( [[#Haase--2015|Haase, 2015]] ). While the literature is generally positive about the ability of NBS to support climate risk reduction and deliver multiple other benefits ( [[#Connop--2016|Connop et al., 2016]] ), such as green job opportunities, improved provision of recreational space, cleaner air, habitat provision and increased property values ( [[#Emmanuel--2015|Emmanuel and Loconsole, 2015]] ), more research is required to specifically assess and evaluate the conditions and contexts in which these kinds of potential benefits are realised and how they can be mainstreamed into policy ( [[#Frantzeskaki--2019|Frantzeskaki et al., 2019]] ). Similarly, there is ''limited evidence'' on unintended consequences (e.g., methane production, creation of habitat for disease vectors, increased human–wildlife conflict) and how these can be avoided ( [[#Wolch--2014|Wolch et al., 2014]] ).

<div id="8.5.2.3" class="h3-container"></div>

<span id="human-capital"></span>
==== 8.5.2.3 Human Capital ====

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Successful adaptation requires support to be directed towards human capital and socioeconomic capabilities and competences, in terms of education, knowledge, experience, health and well-being, and migration, enabling people to contribute meaningfully towards development ( [[#Bowen--2012|Bowen et al., 2012]] ). At the same time, strong human capital and investment in actions that build human capacities to deal with climate change, can further enhance adaptation activities linked to other capitals, and contribute positively to overall disaster risk reduction.

Analyses of educational attainment distributions with datasets reaching back as far as 1970 show that improving educational attainment in people of working age has been the most consistent and significant driver of economic growth globally ( [[#Lutz--2008|Lutz et al., 2008]] ), showing the importance of the right to education. Education has further supported sustainable development by fostering empowerment, yielding access to information (including on climate change) and has clear links to other aspects of human capital, including health and mortality ( [[#Samir--2017|Samir and Lutz, 2017]] ). There is ''medium evidence'' and ''high agreement'' that education reduces vulnerability and enhances adaptive capacity ( [[#Frankenberg--2013|Frankenberg et al., 2013]] ; [[#Sharma--2013|Sharma et al., 2013]] ), with ''high agreement'' that climate change impacts can have negative effects on existing levels of human capital, with some development pathways affected more than others ( [[#Samir--2017|Samir and Lutz, 2017]] ). Education can help to shape people’s risk perception and assessment, as well as affecting knowledge sharing and the development of problem-solving abilities ( [[#Striessnig--2013|Striessnig et al., 2013]] ).

At the same time, IKLK can inform adaptation actions ( [[#Apgar--2018|Apgar et al., 2018]] ), but is poorly integrated into formal educational systems and, in some cases, is insufficient to adapt to new hazards that are emerging as a consequence of climate change. Education further feeds into livelihood options, with close relationships between people’s earning capacities, the livelihood choices they can make and their levels of financial capital. It also supports food security ( [[#Lutz--2004|Lutz et al., 2004]] ). There is ''medium evidence'' that climate change can undermine human capital and education. For example, studies have shown that higher temperatures reduce exam educational performance (Park, 2020), while extreme weather events such as snowstorms disrupt learning, yielding long-lasting and multidimensional effects ( [[#Maccini--2009|Maccini and Yang, 2009]] ; [[#Cho--2017|Cho, 2017]] ; [[#Graff%20Zivin--2018|Graff Zivin et al., 2018]] ).

As well as studies examining formal education, a large body of research has focused on social learning and its role in building adaptive capacity through joint knowledge production and reflexivity. Foregrounding the need for continuous changes in response to emerging conditions, this literature identifies the potential of shared learning for co-constructing policy and practice responses to complex, multi-stakeholder environmental problems, and highlights both the necessity and challenge of including non-dominant values, knowledge and expertise in adaptation decision making, considering the role of power dynamics therein ( [[#Collins--2009|Collins and Ison, 2009]] ; [[#Ensor--2015|Ensor and Harvey, 2015]] ; [[#Phuong--2017|Phuong et al., 2017]] ; [[#Apgar--2018|Apgar et al., 2018]] ; [[#Brymer--2018|Brymer et al., 2018]] ; [[#Fisher--2019|Fisher and Dodman, 2019]] ). A growing body of evidence also links to organisational learning and adaptation. Organisations’ adaptive behaviours, like those of households and individuals, do not operate in a vacuum, with organisations’ behaviours shaped by policy and market conditions amongst other factors. [[#Mudombi--2017|Mudombi et al. (2017)]] highlight further barriers in their study in South Africa, linked to inadequate resourcing, political interference, governance shortcomings and knowledge/expertise gaps within organisations, alongside short time frames for implementing projects.

Adaptations that support human health and well-being require investments in physical assets and infrastructure linked to water and sanitation (see Chapter 4), particularly in rapidly urbanising areas in the Global South, alongside specific pro-poor investment strategies given disproportionate climate change impacts on women (see Cross-Chapter Box GENDER in Chapter 18), other marginalised groups and low-income households who lack access to healthcare. Climate change facilitates the spread of vector-borne diseases such as malaria, as well as illnesses such as meningitis ( [[#Rocklöv--2020|Rocklöv and Dubrow, 2020]] ). Impacts on health are also experienced, through food insecurity resulting from climate change, including malnutrition, as well as through loss of livelihoods, making it more difficult to afford and to access health services. Health aspects are considered in-depth in Chapter 7, but we underscore the importance of a rights-based approach to adaptation in supporting the right to health and food in the context of inequality.

A key dimension of human capital is local understanding of climate risk, which includes knowledge systems outside Western scientific approaches. For millennia, local communities have relied heavily upon culturally accumulated Indigenous knowledge, participating in landscapes as stewards of their environment, engaged in profoundly detailed livelihood strategies that deal with natural hazards ( [[#Ajayi--2017|Ajayi and Mafongoya, 2017]] ). Indigenous knowledge systems are embedded in culture, and are passed from generation to generation in various ways: livelihoods, traditions, spiritual practices and oral tradition, cultural identity and historical memory. Indigenous knowledge is known or learnt from experience, or acquired through observation and practice, and handed down from generation to generation. It is acknowledged that Indigenous communities, particularly those in hazard-prone areas, have developed a profound understanding and knowledge of disaster prevention and mitigation, early warning, preparedness and response, and post-disaster recovery. Indigenous knowledge systems, themselves, are an indispensable dimension of capacity for adaptation, and where threatened represent a major risk to Indigenous communities. While still robust among Indigenous Peoples in many parts of Africa, Asia and Latin America, Indigenous knowledge is not well reflected or incorporated in assessments such as this, and stands in danger of being lost as its custodians are passing away.

Indigenous knowledge about natural hazards enables communities at risk to take steps to reduce climate risk. Indigenous knowledge systems are locally indispensable resources for adaptation to climate change, yet are often misunderstood and undervalued. Generally, Indigenous Peoples and other local groups hold relevant local-scale knowledge about environmental change, the impacts of those changes on ecosystems and livelihoods at local scales, and possible locally effective adaptive responses. However, it is important that IKLK is situated within knowledge from other scales in order to assess its broader relevance and applicability ( [[#Ahlborg--2012|Ahlborg and Nightingale, 2012]] ). Some authors suggest including Indigenous knowledge in the IPCC assessment process should be of high priority, as it is becoming increasingly relevant for climate services ( ''high confidence'' ) ( [[#Strauss--2003|Strauss and Orlove, 2003]] ; [[#Crate--2009|Crate and Nuttall, 2009]] ; [[#Crate--2011|Crate, 2011]] ). Their knowledge can draw attention to climate baselines and change, and identify adaptation priorities, such as plant and animal species that should be protected given local contextual environmental considerations. For example, using Indigenous knowledge in weather and climate prediction, local communities in different parts of Tanzania have been coping with, and adapting to, increased climate variability normally manifested in the form of increased frequency and magnitude of various exigencies, including droughts and floods, and outbreak of pests and diseases ( [[#Kijazi--2013|Kijazi et al., 2013]] ). Prediction of impending hazards has been an integral part of Indigenous Peoples’ adaptation strategies. Various environmental and astronomical indicators are used to predict rainfall, including plant phenology, behaviour and movement of birds, animal and insects, in many parts of Tanzania ( [[#Kijazi--2013|Kijazi et al., 2013]] ).

There are efforts in developing adaptation plans that utilise local knowledge. Local knowledge-based adaptation is focused primarily on the use of traditional knowledge to increase adaptive capacity at the community level and less on integration ( [[#Mimura--2014|Mimura et al., 2014]] ). Hence, there is need to increase effectiveness of policy processes that work towards integration of local and scientific knowledge ( [[#Nakashima--2013|Nakashima et al., 2013]] ; [[#IPCC--2014a|IPCC, 2014a]] ).

<div id="8.5.2.4" class="h3-container"></div>

<span id="physical-capital"></span>
==== 8.5.2.4 Physical Capital ====

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Ensuring sufficient investment in physical capital is vital to support development pathways at the national level, but for the poorest and most marginalised in society, physical capital represents an invaluable source of adaptation options ( [[#Hallegatte--2019|Hallegatte et al., 2019]] ). Physical capital constitutes assets such as land, roads and other infrastructure (e.g., water supplies, electricity, mobile phone connectivity), housing and other buildings, as well as the materials and tools needed to make a living (e.g., farming, forestry and fishing equipment, transportation vehicles, technology). It can also help to foster a sense of place, and can support well-being. Climate change impacts on physical capital are often widespread, as well as economically and emotionally costly, particularly when communities are afflicted by hardship (inadequate levels of sustainable human development through access to essential public goods and services and access to income opportunities) ( [[#Abbott--2004|Abbott and Pollard, 2004]] ).

Given the massive scale of investments required to build and sustain physical capital at the state level, it is imperative to ensure physical capital decisions consider climate resilience; not least because retrofitting and replacing are both highly costly. The World Bank estimates that adapting over the period 2010–2050 to a world that is 2°C warmer by 2050 will cost USD 70 billion to USD 100 billion per annum, with the infrastructure sector accounting for the largest share of costs ( [[#World%20Bank--2010|World Bank, 2010]] ). At the same time, every USD 1 invested in preventive measures can save USD 5 of repairs ( [[#PRIF--2013|PRIF, 2013]] ). While adequate financing and technical expertise are required, as well as foresight in planning and design and climate risk screening, successful adaptation relating to physical capital also demands legal and institutional enablers (e.g., development and enforcement of building codes and regulations; roll out of insurance options; planning restrictions to reduce construction in locations that are highly exposed to climate hazards, etc). In some situations, these are lacking. For example, low-lying LDCs, such as Bangladesh, as well as SIDS, regularly suffer from climate events such as floods, typhoons, cyclones, hurricanes and saline intrusion (see [[IPCC:Wg2:Chapter:Chapter-15|Chapter 15]] on small islands). Hazards such as typhoons cause substantial damage and destruction, impede mobility, reduce connectivity, disrupt communications, food, water and energy supplies, and render people homeless and without the assets they rely on to make a living. In the absence of adequate legal and institutional enablers, as well as livelihood assets, the maintenance of physical capital is far more challenging, as the case of Cyclone Aila in Box 8.8 demonstrates.

Physical capital in the form of technology is increasingly supporting climate change adaptation, despite that innovations can be rolled out under high uncertainty, opening up new risks (e.g., hacking). Moreover, deployment of technology is closely tied to other forms of capital, especially human capital, and innovations cannot just be rolled out in the absence of suitable institutional and technical support and training. Similarly, access to finance is vital. Some technological adaptations require a pre-existing level of infrastructure and literacy, raising important questions about inequality ( [[#Taylor--2018|Taylor, 2018]] ). [[#Rotz--2019|Rotz et al. (2019)]] warn of automation impacts on rural labour, especially in places with high youth unemployment, while [[#Taylor--2018|Taylor (2018)]] notes that social classes and gender are impacted differently by technological change, and failure to address underlying inequalities will shape who becomes vulnerable. Adequate testing of technologies in terms of their applicability to different contexts is also required, ensuring they do not become maladaptive when applied at scale.

Similarly, technology must always be grounded in an appreciation of the cultural context. Research in the European Arctic with the Indigenous Sami Peoples found that use of GPS technology on reindeer, together with supplementary feeding, offered useful adaptations for some herders. However, there are fears such technologies may, over time, reduce the skills, cultural knowledge and Indigenous adaptations of the Sami ( [[#Andersson--2017|Andersson and Keskitalo, 2017]] ), as, for example, reindeer become tamer through supplementary feeding, affecting their range selection. Overall, technology and other adaptations should seek not to erode Sami culture’s adaptive capacity ( [[#Vuojala-Magga--2011|Vuojala-Magga et al., 2011]] ; [[#Risvoll--2016|Risvoll and Hovelsrud, 2016]] ), particularly because reindeer grazing as a land management practice can play a useful climate change mitigation role too. Reindeer grazing protects tundra from tree line and bush encroachment, while summer grazing increases surface albedo by delaying snowmelt ( [[#Jaakkola--2018|Jaakkola et al., 2018]] ).

<div id="8.5.2.4.1" class="h4-container"></div>

<span id="socio-cultural-factors"></span>
===== 8.5.2.4.1 Socio-cultural Factors =====

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Social and cultural factors are closely linked to values, beliefs and identities ( [[#Heimann--2016|Heimann and Mallick, 2016]] ) and mediate the ways in which people respond to climate variability and change ( [[#Adger--2013|Adger et al., 2013]] ). There is ''limited evidence'' but ''medium agreement'' about the importance and role of social and cultural factors in shaping adaptation, in terms of both the need to adapt and the way it is presented and communicated, although evidence is somewhat mixed in terms of how experiences of weather affect opinions and perceptions of climate change ( [[#Howe--2019|Howe et al., 2019]] ). Research also highlights the importance of context in understanding relations between perceptions of risks and behaviour, arguing that power relations and other obstacles and opportunities play a vital role in shaping actions ( [[#Rufat--2020|Rufat et al., 2020]] ). In general, nonetheless, adaptation is spurred when people perceive that there is an action they can take to make a difference ( [[#Kuruppu--2011|Kuruppu and Liverman, 2011]] ; [[#Mayer--2019|Mayer and Smith, 2019]] ), although it cannot be assumed that action will be taken if the socio-cultural setting is not amenable and it contravenes the values underlying people’s perceptions ( [[#Kwon--2019|Kwon et al., 2019]] ). Research testing for the effect of beliefs on behavioural change from 48 countries highlighted the need for policy leaders to present climate change as solvable yet challenging, if fatalistic beliefs that act as barriers to adaptation were to be reduced ( [[#Mayer--2019|Mayer and Smith, 2019]] ). This demonstrates how beliefs do not always reinforce actions, even when risks are perceived. Similarly, research from Burkina Faso working with the Fulbe ethnic group found that cultural norms restricted engagement in four of the most successful livelihood strategies that support adaptation to climate change (labour migration, working for development projects, gardening and female engagement in economic activities) ( [[#Nielsen--2010|Nielsen and Reenberg, 2010]] ). Cultural factors therefore play an important but under-researched role in adaptation.

Social factors in the context of adaptation, by contrast, are more widely studied. The literature on adaptation and the role of social capital as an enabler is diverse. There is ''high confidence'' that during disasters, social capital plays an important role in linking those who are affected to external supports and resources. On small islands, social networks can be dense and support adaptation ( [[#Petzold--2015|Petzold and Ratter, 2015]] ), with traditional knowledge and societal cohesion helping small island communities to have self-belief and build resilience even in the absence of external interventions ( [[#Nunn--2018|Nunn and Kumar, 2018]] ). Even the development of weak ties (e.g., one-way information transfer) can lead to the establishment of mutual collaboration relations that can be more easily drawn on in times of climate change-related shocks and stresses ( [[#Ingold--2017|Ingold, 2017]] ), while collective shared disaster experiences can cause new social groups to emerge and spur action, linked to a perceived common fate ( [[#Ntontis--2020|Ntontis et al., 2020]] ). However, this can exacerbate inequalities and create new ones, with those who are more connected having enhanced access to, for example, shelters following storm evacuations or earthquakes ( [[#Rahill--2014|Rahill et al., 2014]] ). In adapting to more incremental changes, social capital has been shown to increase shared local knowledge and awareness, support participatory processes and strengthen ties to corporate and political institutions, increasing their responsiveness to local concerns, as shown by examples from Aldrich et al. (2016). They describe how in Houma, Louisiana, located west of New Orleans, rising sea levels and hurricane risks have drawn on and built social capital at the community level. Having what was perceived locally as insufficient federal government support, residents, church groups and town council members collaborated to spur adaptation. Community mobilisation led to construction of self-funded levees and water projects to protect 200,000 residents from storm surges. Projects include marshland restoration, the elevation of existing housing, improved pumping systems and canal drainage, as well as buyouts and relocations of businesses and housing that has been repetitively damaged. Funds were raised from households through donations via a self-imposed sales tax. While this example paints a positive picture of the role of social capital and collective action in adaptation activities, it also raises questions about the coherence of actions across levels, again, highlighting a role for polycentric governance if risks of maladaptation are to be reduced. The danger in the example presented here is that should federal plans conflict with the community level work in the future, local efforts may have been in vain if installations have to be removed. This highlights the importance of careful evaluation of all adaptation options on an ongoing basis.

Further warnings about social capital as an adaptation enabler come from [[#Acosta--2016|Acosta et al. (2016)]] who recognise that it may be detrimental to private adaptation in some cases. Their research in rural Ethiopia found that qualitative measures of trust predict contributions to public goods, supporting theories about collective action, but that the effects of social capital are not homogenous: it can be helpful in some contexts, but unhelpful, or even detrimental in others. This led them to highlight the need for policymakers to consider these potentially different outcomes. Other research, also from Ethiopia, suggested that households with more social capital are more specialised in their livelihood strategies. This could leave them more vulnerable to climate change impacts (as per the Cyclone Aila example where shrimp farmers were specialised and hit hardest by the cyclone’s impacts), though social capital acts as a kind of informal insurance ( [[#Wuepper--2018|Wuepper et al., 2018]] ).

<div id="box-8.7" class="h2-container box-container"></div>

'''Box 8.7 | Addressing inequalities in national capabilities: common but differentiated responsibilities and respective capabilities relating to adaptation and the Paris Agreement'''
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Common but differentiated responsibilities and respective capabilities (CBDR-RC) is a key principle within the United Nations Framework Convention on Climate Change (UNFCCC), and attempts to acknowledge countries’ diverse development situations. The Convention and its Kyoto Protocol operationalised the principle by committing developed (Annex I) countries to absolute emission reduction or limitation targets and exempting developing countries from any binding reductions in emissions ( [[#Huggins--2016|Huggins and Karim, 2016]] ; [[#Pauw--2019|Pauw et al., 2019]] ). In contrast, the Paris Agreement distinguishes between ‘developed’ and ‘developing’ countries instead of Annex I and non-Annex I countries and acknowledges significant asymmetries and inequalities, not only between developed and developing countries, but also between developed and developing countries themselves, both in terms of vulnerability to climate change impacts and capacity to mitigate the problems. The literature contains extensive analyses of CBDR-RC in relation to equity in mitigation efforts in the post-2020 regime (e.g., [[#Michaelowa--2015|Michaelowa and Michaelowa, 2015]] ; [[#du%20Pont--2017|du Pont et al., 2017]] ; [[#Liu--2017|Liu et al., 2017]] ; [[#Holz--2018|Holz et al., 2018]] ; [[#Sælen--2019|Sælen et al., 2019]] ), but little in relation to adaptation, particularly relating to how it plays out in the Paris Agreement.

The somewhat static interpretation of CBDR-RC prior to the Paris Conference of the Parties was overcome through the introduction of a qualification to the CBDR-RC principle: the phrase ‘in the light of different national circumstances’. Without changing the original principle, the qualifier adds a dynamic element ( [[#Rajamani--2016|Rajamani, 2016]] ). Common but differentiated responsibilities and respective capabilities of parties are therefore recognised not to be ‘tied to the annexes’, but instead evolve alongside national circumstances ( [[#Maljean-Dubois--2016|Maljean-Dubois, 2016]] ; [[#Voigt--2016|Voigt and Ferreira, 2016]] p.301). The Paris Agreement also recognises context, considering differentiation in relation to each of the Durban pillars: mitigation, adaptation, finance, technology, capacity building and transparency ( [[#Rajamani--2017|Rajamani and Guérin, 2017]] ).

Article 7 of the Paris Agreement acknowledges adaptation as a ‘global challenge faced by all’, recognising, for the first time, a global aspiration of ‘enhancing adaptive capacity, strengthening resilience and reducing vulnerability to climate change’. It calls for a balance between mitigation and adaptation funding and emphasises the need to provide developing country parties, especially the most vulnerable, with ‘[c]ontinuous and enhanced international support’ for adaptation. The basis for differentiation under Article 7 therefore relies mostly on diverse national circumstances, capabilities and vulnerabilities. LDCs, as well as SIDS, are assumed by the literature, to be part of this category ( [[#Maljean-Dubois--2016|Maljean-Dubois, 2016]] ).

The literature offers two main perspectives when evaluating the effectiveness of these provisions on adaptation in the context of the post-Paris climate change regime. One argument follows that the Paris Agreement gives priority attention to the most vulnerable parties and, unlike previous international agreements in the climate change regime, places adaptation on equal footing to mitigation ( [[#Magnan--2016|Magnan and Ribera, 2016]] ; [[#Pérez--2017|Pérez and Kallhauge, 2017]] ; Morgan, 2018). Article 7 is interpreted here as a breakthrough, containing unprecedented provisions that give adaptation prominence and which elevate the importance of undertaking adequate action to cope with current and future climate change impacts. A second view argues that the Article 7 marks little departure from previous efforts to support adaptation efforts in developing countries ( [[#Doelle--2016|Doelle, 2016]] ) or that it could have included stronger provisions, such as a quantitative goal with respect to adaptation needs and costs ( [[#Bodansky--2016|Bodansky, 2016]] ).

The literature nevertheless shows ''high agreement'' that other parts of the Paris Agreement do contain consequential provisions on adaptation and the operationalisation of the CBDR-RC principle. Those provisions covering financial support are arguably the most pertinent, as they replace the dichotomy between developing countries and developed countries with a trichotomy which also includes ‘other Parties’ ( [[#Maljean-Dubois--2016|Maljean-Dubois, 2016]] ). While provision of support from developed parties continues to be mandatory, these ‘other parties’, apparently developing country parties, are ‘encouraged to provide or continue to provide such support voluntarily’ (Article 9.2). Parties themselves determine whether they belong to this category. So far, several developing countries have made contributions to the Green Climate Fund, ranging from Indonesia and Mexico to Mongolia and Panama (Green Climate Fund, 2017). Expanding the donor base to these ‘other parties’ and breaking down the wall between donor and recipient countries marks a departure from previous practice, under which developing countries had no formal role in climate finance and support ( [[#Bodansky--2016|Bodansky, 2016]] ; [[#Voigt--2016|Voigt and Ferreira, 2016]] ).

<div id="box-8.8" class="h2-container box-container"></div>

'''Box 8.8 | Cyclone Aila in Bangladesh: impact, adaptation and way forward'''
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Historically, southern coastal Bangladesh, where the 1970 Bhola Cyclone killed 500,000 people, has been considered among the most climate-vulnerable environments on Earth. However, in recent decades, extreme weather events, like Cyclone Aila, though still destructive and destabilising, have resulted in lower death tolls thanks to a concerted investment in flood mitigation infrastructure, a dense network of cyclone shelters and a robust early warning system ( [[#Chowdhury--1993|Chowdhury et al., 1993]] ; [[#Paul--2009|Paul, 2009]] ). Cyclone Aila struck the southwest coast of Bangladesh on 25 May 2009 with a wind speed of 120 km hour –1 ( [[#Islam--2016|Islam and Hasan, 2016]] ). With tidal surges of up to 6.5 m, occurring over dry pre-monsoon soils, 11 coastal districts and more than 3.9 million people were affected ( [[#United%20Nations--2010|United Nations, 2010]] ), 190 people died and 7100 people suffered injuries ( [[#Saha--2017|Saha, 2017]] ).

Aila greatly damaged the region’s physical capital, including 6000 km of roads and 17,000 km of embankments. The cyclone polluted and damaged sources of drinking water and destroyed 243,000 houses and thousands of schools ( [[#Mallick--2017|Mallick et al., 2017]] ; [[#Paul--2019|Paul and Chatterjee, 2019]] ). In Satkhira and Khulna districts alone, 165,000 houses were destroyed and households were forced to live on damaged embankments in makeshift shanties ( [[#UNDP--2015|UNDP, 2015]] ). Many people had to live in these temporary shelters for years ( [[#Saha--2017|Saha, 2017]] ). Aila occurred during a high tide and the surge of saline water inundated not only the roads, embankments and houses but also vast areas of agricultural field and shrimp farms ( [[#Paul--2019|Paul and Chatterjee, 2019]] ) leaving many areas waterlogged for months ( [[#Abdullah--2016|Abdullah et al., 2016]] ; [[#Mallick--2017|Mallick et al., 2017]] ). The effect of saline water logging inside embankments caused further harm to houses, roads and culverts, adding more barriers to the post-disaster reconstruction activities ( [[#Roy--2020|Roy, 2020]] ). In the same area, tube-wells were damaged. Women had to travel up to 2 km every day to collect safe water, spending 30–90 minutes on this activity daily ( [[#Alam--2019|Alam and Rahman, 2019]] ). The distribution of costs across different socioeconomic groups was not always as expected. A study in Aila-affected Koyra sub-district of Khulna found that households with higher incomes were more vulnerable to Aila in both relative and absolute terms compared to middle- and low-income groups mainly due to damage to shrimp farming, which underpinned their livelihoods ( [[#Abdullah--2016|Abdullah et al., 2016]] ). This highlights how specialised livelihoods can leave people more vulnerable as they have fewer options. However, the same study found that the damage to physical capital such as fishing nets and boats was statistically significantly greater for middle- and low-income groups. Damage to houses was statistically significantly more among poorer households followed by middle- and higher-income groups.

A range of coping and adaptation actions were enacted in response to losses of and damage to physical capital (Table Box 8.8.1). Actions varied across the different affected areas and were taken by the households themselves, by the government and by NGOs.

'''Table Box 8.8.1 |''' '''Coping and adaptation actions enacted in the Cyclone Aila-affected area in response to losses of and damage to physical capital.'''

{| class="wikitable"
|-
! Coping and adaptation actions

! Action group

! References

|-
| Human migration—mostly forced due to loss of houses as well as other resources and livelihood activities

| Households

| ( [[#Abdullah--2016|Abdullah et al., 2016]] ; [[#Mallick--2017|Mallick et al., 2017]] ; [[#Paul--2019|Paul and Chatterjee, 2019]] )

|-
| Alternative livelihood activities such as crafts, and honey and wood collection from the Sundarbans, due to irreparable damage to fishing gear

| Households

| ( [[#Alam--2015|Alam et al., 2015]] )

|-
| Saving money for house repairs or construction

| Households

| ( [[#Alam--2015|Alam et al., 2015]] )

|-
| Underground storage of emergency items such as foods, matchbox, cooker and cooking fuel

| Households

| ( [[#Alam--2015|Alam et al., 2015]] )

|-
| Selection of high land to build shelter along both sides of the embankments

| Households

| ( [[#Alam--2015|Alam et al., 2015]] )

|-
| Tree plantation in the homestead periphery to protect the house from gusty winds and to use as a source of wood for house repair/construction

| Households

| ( [[#Alam--2015|Alam et al., 2015]] )

|-
| Increasing height of the house plinth

| Households

| ( [[#Alam--2015|Alam et al., 2015]] )

|-
| Changing of house roofing material from thatched to corrugated iron sheet or asbestos

| Households

| ( [[#Alam--2015|Alam et al., 2015]] )

|-
| Informally allowing people to harvest Sundarbans forest wood without any charge so they could make makeshift houses

| Forest Department

| ( [[#Abdullah--2016|Abdullah et al., 2016]] )

|-
| Rainwater harvesting using plastic or clay pots and artificial aquifer tube-wells for securing drinking water.

| NGOs and households

| ( [[#Sultana--2015|Sultana and Mallick, 2015]] )

|-
| Replacement of mud walls of houses with wood or bamboo sticks to enhance durability

| NGOs and households

| ( [[#Sultana--2015|Sultana and Mallick, 2015]] )

|-
| Making thick shelterbelts along coastal embankments

| NGOs and households

| ( [[#Rahman--2015|Rahman and Rahman, 2015]] )

|}

The impacts of some of these adaptations, particularly engagement in new livelihood activities after Aila, were varied, with income of the affected households increasing in some cases and decreasing in others. In Koyra, the income of the poorest and middle-income households increased by 16% and 4%, respectively, while the income of richer households (many of whom lost physical capital assets that they used to pursue their livelihoods) decreased by 50% ( [[#Abdullah--2016|Abdullah et al., 2016]] ).

Research into adaptation projects led by various actors has shown that adaptations taken by the households and community themselves are effective only to address typical challenges (such as seasonal shifts in temperature or rainfall) but are less effective in addressing extreme events that have long-lasting impacts. This is mainly due to lack of adequate resources and institutional support ( [[#Alam--2015|Alam et al., 2015]] ). At the same time, some coping mechanisms are harmful in the longer term, for example, harvesting Sundarbans forest wood after Aila for reconstruction could have negative impacts on the forest.

As of 2017, many of the affected areas had not yet been able to recover from the effects of Aila ( [[#Paul--2019|Paul and Chatterjee, 2019]] ). A transformative approach needs to be taken not only to help them recover in livelihood terms, but also to support people’s well-being. Suggestions of physical interventions that are needed include higher and stronger dykes, cyclone-resistant housing, active maintenance and strict policing of embankment use and good governance ( [[#Abdullah--2016|Abdullah et al., 2016]] ). Enabling formal institutions could help, for instance, by improving the climate resilience of physical capital (e.g., by developing and enforcing building codes for houses). Other institutional mechanisms could help to improve access to low interest credit, prevent maladaptation, improve enforcement of laws, and provide insurance. However, such institutional reforms need to be co-developed with local people and incorporate local cultural mechanisms ( [[#Islam--2017|Islam and Nursey-Bray, 2017]] ). Future adaptation strategies also need to consider the limits to autonomous adaptation (i.e. that without external intervention) and differential level of impacts and adaptive capacities among different groups of households in the Aila-affected areas. This example illustrates the importance of a more comprehensive approach to resilience building, and the need to better understand the interlinkages between the core components of an enabling environment for adaptation (see Figure 8.12).

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Box 8.8

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