Editing IPCC:AR6/WGII/Chapter-16 (section)

== 16.3 Synthesis of Observed Adaptation-Related Responses ==

<div id="h1-4-siblings" class="h1-siblings"></div>

'''''A new development since AR5 is that there is now growing evidence assessing progress on adaptation''''' across sectors, geographies and spatial scales. Uncertainty persists around what defines adaptation and how to measure it (Cross-Chapter Box FEASIB in Chapter 18, [[#UNEP--2021|UNEP, 2021]] ). As a result, most literature synthesising responses is based on documented or reported adaptations only, and is thus subject to substantial reporting bias.

'''''We document implemented adaptation-related responses that could directly reduce risk.''''' Adaptation ''as a process'' is more broadly covered in [[IPCC:Wg2:Chapter:Chapter-17|Chapter 17]] ( [[IPCC:Wg2:Chapter:Chapter-17#17.4.2|Section 17.4.2]] ), including risk management, decision making, planning, feasibility (see Cross-Chapter Box FEASIB in Chapter 18), legislation and learning. Here, we focus on a subset of adaptation activities: adaptation-related responses of species, ecosystems, and human societies that have been implemented, observed, and could directly reduce risk. We consider all adaptation-related responses to assumed, perceived or expected climate risk, regardless of whether or not impacts or risks have been formally attributed to climate change.

'''''We use the term ‘adaptation-related responses’, recognising that not all responses reduce risk.''''' While ‘adaptation’ implies risk reduction, we use the broader term ‘responses’ to reflect that responses may decrease risk, but in some cases may increase risk.

It is not currently possible to conduct a comprehensive global assessment of effectiveness, adequacy or the contribution of adaptation-related responses to changing risk owing to an absence of robust empirical literature. This constrains assessment of adaptation progress and gaps in the context of over-shoot scenarios. Given ''limited evidence'' to inform comprehensive global assessment of effectiveness and adequacy, we assess evidence that adaptation responses in human systems indicate transformational change. [[IPCC:Wg2:Chapter:Chapter-17|Chapter 17]] considers adaptation planning and governance, including adaptation solutions, success, and feasibility assessment (Cross-Chapter Box FEASIB in Chapter 18), discussed further in Box 16.2 (also see Cross-Chapter Box PROGRESS in Chapter 17).

'''''In natural ecosystems or species, detectable changes can be considered as ‘impact’ or ‘response’.''''' The distinction between ‘observed impacts’ ( [[#16.2|Section 16.2]] ) and ‘observed responses’ ( [[#16.3|Section 16.3]] ) is not always clear. For example, autonomous distributional shifts in wild species induced by increasing temperatures (an observed impact) may reduce risk to the species (an autonomous adaptation response), but this process can be enhanced or supported by human intervention such as intentional changes in land use. Observed autonomous changes in natural ecosystems or species unsupported by human intervention are treated as impacts (see [[#16.2|Section 16.2]] ).

Adaptation-related responses are frequently motivated by a combination of climatic and non-climatic drivers, and interact with other transitions to affect risk. For societal responses, it is difficult to say whether they are triggered by observed or anticipated changes in climate, by non-climatic drivers, or by a combination of all three. In the case of observed impacts, assessment typically focuses on detection and attribution ''vis à vis'' a counterfactual of no climate change. While there has been some effort to attribute reduced climate risk to adaptation-related responses ( [[#Toloo--2013a|Toloo et al., 2013a]] ; [[#Toloo--2013b|Toloo et al., 2013b]] ; [[#Hess--2018|Hess et al., 2018]] ; [[#Weinberger--2018|Weinberger et al., 2018]] ), in many cases this has not been feasible given difficulties in defining adaptation and empirically disentangling the contribution of intersecting social transitions and changing risks. Literature on adaptation-related response frequently draws on theories of change to assess the likely contribution of adaptations to changes in risk, including maladaptation and co-benefits.

<div id="box-16.1:-case-study-on-climate-change-and-the-outbreak-of-the-syrian-civil-war" class="h2-container box-container"></div>

'''Box 16.1: Case Study on Climate Change and the Outbreak of the Syrian Civil War'''
<div id="h2-22-siblings" class="h2-siblings"></div>

Separating between climatic and non-climatic factors in impact attribution is often challenging, as highlighted by the debate surrounding the causes of the Syrian civil war. During the years 2006–2010, the Fertile Crescent region in Eastern Mediterranean and Western Asia was hit by the worst drought on meteorological record, compounding a consistent drying of the region over the past half century ( [[#Trigo--2010|Trigo et al., 2010]] ; [[#Hoerling--2012|Hoerling et al., 2012]] ; [[#Mathbout--2018|Mathbout et al., 2018]] , SR15 BOX 3.2 ( [[#Hoegh-Guldberg--2018a|Hoegh-Guldberg et al., 2018a]] )). The magnitude of the multi-year drought is estimated to have become two to three times more likely as a result of increased CO 2 forcing ( [[#Kelley--2015|Kelley et al., 2015]] ). The drought had a devastating impact on agricultural production in the northeast of Syria. In 2007–2008 alone, average crop yields dropped by 32% in irrigated areas and as much as 79% in rain-fed areas ( [[#De%20Châtel--2014|De Châtel, 2014]] ), and herders in the northeast lost around 85% of their livestock ( [[#Werrell--2015|Werrell et al., 2015]] ). Successive years with little or no income eventually forced people to leave their farms in great numbers and seek employment in less affected parts of the country, adding to existing pressures on housing, labour market and public goods provision ( [[#Gleick--2014|Gleick, 2014]] ; [[#Kelley--2015|Kelley et al., 2015]] ). In March 2011, by which time the ‘Arab Spring’ uprisings had gained momentum and spread across much of the region, anti-regime protests broke out in Syria, first in the southern city of Dara’a and then in Damascus and throughout the country.

Yet, the attribution of the Syrian civil war to climate change has triggered a heated debate. A number of studies argue that the principal drivers of the drought-induced economic collapse were political rather than environmental in nature, shaped by adverse economic reforms and unsustainable agricultural policies, promoting water-intensive irrigation schemes for cotton cultivation and implementing abrupt subsidy cuts at the peak of the drought, implying that many poor farmers no longer could afford fertilis ers or fuel to power irrigation pumps ( [[#Barnes--2009|Barnes, 2009]] ; [[#De%20Châtel--2014|De Châtel, 2014]] ; [[#Eklund--2017|Eklund and Thompson, 2017]] ; [[#Selby--2017|Selby et al., 2017]] ). Thus, the 2006–2010 drought did not precipitate similar devastating socioeconomic impacts on agrarian communities across the borders in Turkey, Iraq or Jordan, although environmental conditions were comparable ( [[#Trigo--2010|Trigo et al., 2010]] ; [[#Eklund--2017|Eklund and Thompson, 2017]] ; [[#Feitelson--2017|Feitelson and Tubi, 2017]] ).

However, the relevant attribution question is not whether the same drought would produce the same consequences under different political and socioeconomic conditions, but rather, given the same political and socioeconomic context, how would the outcomes have differed in the absence of climate change? Research still provides very limited insights into whether and how the escalation process would have evolved differently in a counterfactual no-climate-change world.

Thus, the role of the drought in augmenting pre-existing internal migration, and the role of the distress migration in accentuating demographic, economic and social pressures in receiving areas, remain contested. Estimates of the number of people who abandoned their farms in response to the drought range from less than 40,000–60,000 families ( [[#Selby--2017|Selby et al., 2017]] ) to more than 1.5 million displaced ( [[#Gleick--2014|Gleick, 2014]] ). However, the numbers have to be seen in the context of prevailing population growth, significant rural–urban migration, and the preceding inflow of around 1.5 million refugees from neighbouring Iraq ( [[#De%20Châtel--2014|De Châtel, 2014]] ; [[#Hoffmann--2016|Hoffmann, 2016]] ). In addition, research suggests that the migrants played a peripheral role in the initial social mobilisation in March 2011 ( [[#Fröhlich--2016|Fröhlich, 2016]] ).

While it is undisputed that the drought caused direct economic losses, its overall additional impact on the Syrian economy, relative to other prevalent drivers of economic misery, including rampant unemployment, increasing inequalities, declining rural productivity, and loss of oil revenues ( [[#Aïta--2009|Aïta, 2009]] ; [[#Landis--2012|Landis, 2012]] ; [[#De%20Châtel--2014|De Châtel, 2014]] ; [[#Selby--2019|Selby, 2019]] ), has not been quantified.

In addition, the protesters’ demands centred around contentious political rather than economic issues, including release of political prisoners, ending of torture and indiscriminate violence by security forces, and abolishment of the near 50-year-old state of emergency ( [[#Selby--2017|Selby et al., 2017]] ; [[#Ash--2020|Ash and Obradovich, 2020]] ). The mobilisation in Syria in the spring of 2011 also made explicit references to events across the Middle East and North African region. Analyses of regional and social media and networks show a high level of interaction across the Arab world, and the initial Syrian uprising adopted a mobilisation model and rhetorical frames similar to those developed in Tunisia and Egypt ( [[#Leenders--2013|Leenders, 2013]] ; 2014). However, the Syrian uprising stands out in how it was met with overwhelming violent force by the police and security forces, which changed the character of the resistance and opened up for militarisation of non-state actors that further escalated the conflict ( [[#Heydemann--2013|Heydemann, 2013]] ; [[#Leenders--2013|Leenders, 2013]] ; [[#Bramsen--2020|Bramsen, 2020]] ).

In summary, the drought itself is shown to be attributable to GHG emissions. The agricultural losses and internal migration from rural to urban areas can be directly linked to the drought and in this way are partly attributable to GHG emissions, although there are no studies comparing the observed losses and number of people displaced with a counterfactual situation of a weaker drought in a ‘no climate change’ situation. Current research does not provide enough evidence to attribute the civil war to climate change. In contrast, it is likely that social uprisings would have occurred even without the drought.

<div id="16.3.1" class="h2-container"></div>

<span id="adaptation-related-responses-by-natural-systems"></span>
=== 16.3.1 Adaptation-Related Responses by Natural Systems ===

<div id="h2-8-siblings" class="h2-siblings"></div>

There is growing evidence of shifts in species distributions and ecosystem structure and functioning in response to climate change (Chapter 2). While many species are increasingly responding to climate change, there is ''limited evidence'' that these responses will be fully adaptive, and for many species the rate of response appears insufficient to keep pace with the rate of climate change under mid- and high-range emissions scenarios ( ''medium confidence'' ). There is relatively limited, but growing, empirical data to document adaptation of natural systems in the absence of human interventions. For example, [[#Scheffers--2016|Scheffers et al. (2016)]] reviewed climate responses across diverse species, reporting widespread and extensive observed changes in organisms (genetics, physiology, morphology), populations (phenology, abundance and dynamics), species (distributions) and ecosystems. A systematic review by Franks et al. (2014) synthesised evidence from 38 empirical studies of changes in terrestrial plant populations, finding evidence to support a mix of plastic and evolutionary responses. [[#Boutin--2014|Boutin and Lane (2014)]] similarly reviewed adaptive responses in mammals, finding most species’ responses to be due to phenotypic plasticity. [[#Charmantier--2014|Charmantier and Gienapp (2014)]] reviewed responses to climate change among birds, finding emerging evidence that birds from a range of taxa show advancement in their timing of migration and breeding in response to warming. [[#Aragão--2018|Aragão et al. (2018)]] reviewed adaptation responses in marine systems, including 12 studies of live marine mammals. They observed widespread evidence of shifting distributions and timing of biological events (Chapter 2, Chapter 3, and Cross-Chapter Paper 1).

'''''Some ecosystems and species’ responses may be insufficient to keep pace with rates of climate change.''''' It is difficult to distinguish whether adaptations are due to genotypic change or to phenotypic plasticity. Long-term natural adaptations will require the former, but the latter may provide short-term coping mechanisms to ‘buy time’ to respond to climate changes or lay foundations for evolutionary adaptation. There is mixed evidence regarding evolutionary versus plastic responses, with relatively limited evidence of longer-term evolutionary responses of species that can be associated with climate change. Similarly, it is difficult to assess whether responses are indeed potentially adaptive (e.g., coping, shifting, migrating) or simply reflective of impacts (e.g., stress, damage). Among mammal responses reviewed by [[#Boutin--2014|Boutin and Lane (2014)]] , for example, only 4 of 12 studies found some evidence that responses were adaptive. Even where adaptive responses are occurring, they may not be sufficient to keep pace with the rate of climate change. found, for example, that, among the 12 studies in their review that directly assessed the sufficiency of responses to keep pace with the rate of climate change, 8 concluded that responses would be insufficient to avert extinction.

<div id="16.3.2" class="h2-container"></div>

<span id="adaptation-related-responses-by-human-systems"></span>
=== 16.3.2 Adaptation-Related Responses by Human Systems ===

<div id="h2-9-siblings" class="h2-siblings"></div>

The literature that seeks to assess adaptation progress is growing at the global ( [[#Berrang-Ford--2021a|Berrang-Ford et al., 2021a]] ), regional ( [[#Bowen--2015|Bowen and Ebi, 2015]] ; [[#England--2018|England et al., 2018]] ; [[#Robinson--2018a|Robinson, 2018a]] ; [[#Wirehn--2018|Wirehn, 2018]] ; [[#Olazabal--2019|Olazabal et al., 2019]] ; [[#Thomas--2019a|Thomas et al., 2019a]] ; [[#Biesbroek--2020|Biesbroek et al., 2020]] ; [[#Canosa--2020|Canosa et al., 2020]] ; [[#Robinson--2020b|Robinson, 2020b]] ), national ( [[#Hegger--2017|Hegger et al., 2017]] ; [[#Lesnikowski--2019a|Lesnikowski et al., 2019a]] ; [[#Lesnikowski--2019b|Lesnikowski et al., 2019b]] ) and municipal ( [[#Araos--2016|Araos et al., 2016]] ; [[#Reckien--2018|Reckien et al., 2018]] ; [[#Reckien--2019|Reckien et al., 2019]] ; [[#Lesnikowski--2020|Lesnikowski et al., 2020]] ; [[#Singh--2021|Singh et al., 2021]] ) levels, using National Communications ( [[#Gagnon-Lebrun--2007|Gagnon-Lebrun and Agrawala, 2007]] ; [[#Lesnikowski--2015|Lesnikowski et al., 2015]] ; [[#Muchuru--2017|Muchuru and Nhamo, 2017]] ), local climate change action plans ( [[#Regmi--2016b|Regmi et al., 2016b]] ; [[#Regmi--2016a|Regmi et al., 2016a]] ; [[#Reckien--2018|Reckien et al., 2018]] ; [[#Reckien--2019|Reckien et al., 2019]] ), adaptation project proposals, and reported adaptations in the peer-reviewed literature. There remains persistent publication bias in the evidence base on adaptation given the difficulty of integrating diverse knowledge sources (see [[#16.3.3|Section 16.3.3]] ). To better assess how adaptation is occurring in human systems, we draw on this literature base and characterise evidence of adaptation across regions and sectors in terms of five key questions (Table 16.4, [[#Ford--2013|Ford et al., 2013]] ; [[#Biagini--2014|Biagini et al., 2014]] ; [[#Ford--2015a|Ford et al., 2015a]] ; [[#Bednar--2018|Bednar and Henstra, 2018]] ; [[#Reckien--2018|Reckien et al., 2018]] ; [[#Tompkins--2018|Tompkins et al., 2018]] ): What types of hazards are motivating adaptation-related responses? Who is responding? What types of responses are being documented? What evidence is available on adaptation effectiveness, adequacy and risk reduction? To characterise evidence that adaptation responses indicate transformation, we use a typology based on four dimensions of climate adaptation: scope, depth, speed, and consideration of limits to adaptation ( [[#16.4|Section 16.4]] , [[#Termeer--2017|Termeer et al., 2017]] ; [[#Berrang-Ford--2021a|Berrang-Ford et al., 2021a]] ).

'''Table 16.4 |''' Key constraints associated with limits to adaptation for regions

{| class="wikitable"
|-
! Region

! Key constraints associated with limits to adaptation

|-
| Africa

| Financial constraints inhibit implementation of a variety of adaptation strategies including ecosystem-based adaptation ( [[IPCC:Wg2:Chapter:Chapter-9#9.11.4|Section 9.11.4.2]] ) and adoption of drought-tolerant crops by farmers ( [[IPCC:Wg2:Chapter:Chapter-9#9.12.3|Section 9.12.3]] ).

Information constraints (including limited climate science information), governance constraints (such as communication disconnects between national, district and community levels) and human capacity constraints (limited capacities to analyse threats and impacts) are identified as negatively affecting the implementation of adaptation policies ( [[IPCC:Wg2:Chapter:Chapter-9#9.1|Section 9.1]] 3.1).

Social/cultural constraints (social status, caste and gender) also affect adaptation in contexts with deep-rooted traditions ( [[IPCC:Wg2:Chapter:Chapter-9#9.12|Section 9.12.4]] ).

|-
| Asia

| Governance, human capacity, financial and informational constraints commonly present barriers to urban adaptation ( [[IPCC:Wg2:Chapter:Chapter-10#10.4.6.5|Section 10.4.6.5]] ).

Economic, governance, financial and informational constraints are related to both soft and hard limits to adaptation against a range of hazards in South Asia (Box 10.7), while in West Asia, physical constraints to heatwaves and drought have been associated with limits to adaptation (Box 10.7).

|-
| Australasia

| A range of constraints, including governance, information and awareness, social/cultural, human capacity and financial, have been identified as impeding adaptation action in the region ( [[IPCC:Wg2:Chapter:Chapter-11#11.7.2|Section 11.7.2]] , Box 11.1).

Evidence of limits to adaptation are primarily for ecosystems (Sections 11.7.2, 11.6), although individuals and communities are also approaching soft limits owing to social constraints ( [[IPCC:Wg2:Chapter:Chapter-11#11.7.2|Section 11.7.2]] ).

|-
| Central and South America

| Financial, governance, knowledge, biophysical and social/cultural constraints identified as most significant for adaptation ( [[IPCC:Wg2:Chapter:Chapter-12#12.5|Section 12.5]] , Table 12.3).

Soft limits are largely related to governance constraints, while evidence of hard limits is related to biophysical constraints, such as glacier shrinking leading to loss of livelihoods and cultural values ( [[IPCC:Wg2:Chapter:Chapter-12#12.5.3.4|Section 12.5.3.4]] ).

|-
| Europe

| Key constraints are identified as technical, biophysical, economic and social ( [[IPCC:Wg2:Chapter:Chapter-13#13.6.2.4|Section 13.6.2.4]] ).

For cities, settlements and key infrastructure, technical socioeconomic and environmental and regulatory constraints may lead to limits at a range of spatial scales (Figure 13.12).

Biophysical constraints may lead to limits to the ability of water saving and water efficiency measures to prevent water insecurity under high warming scenarios ( [[IPCC:Wg2:Chapter:Chapter-13#13.2.2.2|Section 13.2.2.2]] ).

|-
| North America

| Social/cultural, governance, financial, knowledge and biophysical constraints are identified as most significant for adaptation and leading to both soft and hard limits (Sections 14.5.2.1, 14.6, 14.6.2.1, Table 14.8).

|-
| Small islands

| Financial, governance, information/awareness, technological, cultural and human capacity constraints are identified as affecting adaptation and leading to soft limits (Sections 15.5.3, 15.5.4, 15.6.1, 15.6.3, 15.6.4).

Differences between constraints and soft limits in the small island context is marginal, with policymakers in the Caribbean and Indian Oceans seeing these as synonymous ( [[IPCC:Wg2:Chapter:Chapter-15#15.6.1|Section 15.6.1]] ).

|}

<div id="_idContainer009" class="Figure"></div>

[[File:f3c8985143059df6085c28fbf653c24f IPCC_AR6_WGII_Figure_16_003.png]]

'''Figure 16.3 |''' '''Salience of different types of hazards in the scientific literature on adaptation-related responses (''' '''i.''' '''e., responses that people undertake to reduce risk from climate change and associated hazards).''' Updated from a systematic review of 1682 scientific publications (2013–2019) reporting on adaptation-related responses in human systems ( [[#Berrang-Ford--2021a|Berrang-Ford et al., 2021a]] ). Numbers in table reflect the number of publications reporting. Darker colours denote more extensive reporting on a hazard as a motivating factor for the response. Publications are counted in all relevant regions or sectors.

<div id="16.3.2.1" class="h3-container"></div>

<span id="what-hazards-are-motivating-adaptation-related-responses"></span>
==== 16.3.2.1 What Hazards Are Motivating Adaptation-Related Responses? ====

<div id="h3-18-siblings" class="h3-siblings"></div>

Drought and precipitation variability are the most prevalent hazards in the adaptation literature, particularly in the context of food and livelihood security. Adaptation frequently occurs in response to specific rapid or slow-onset physical events that can have adverse impacts on people. In some cases, people adapt in anticipation of climate change in general or to take advantage of new opportunities created by hazards (e.g., increased navigability due to melting sea ice). There is evidence that prior experience with hazards increases adaptation response ( [[#Barreca--2015|Barreca et al., 2015]] ). Following drought and precipitation variability, the next specific hazards that are most frequently documented in the global adaptation literature are heat and flooding. Heat, while less salient, appears to be a driver of adaptation across all regions and sectors (Stone Jr et al., 2014; [[#Hintz--2018|Hintz et al., 2018]] ; [[#Nunfam--2018|Nunfam et al., 2018]] ). Drought, extreme precipitation, and inland flooding are commonly reported in the context of water and sanitation ( [[#Bauer--2015|Bauer and Steurer, 2015]] ; [[#Lindsay--2018|Lindsay, 2018]] ; [[#Kirchhoff--2019|Kirchhoff and Watson, 2019]] ; [[#Hunter--2020|Hunter et al., 2020]] ; [[#Simpson--2020|Simpson et al., 2020]] ). Flooding is frequently reported as a key hazard for adaptation in cities, followed by drought, precipitation variability, heat, and SLR ( [[#Broto--2013|Broto and Bulkeley, 2013]] ; [[#Araos--2016|Araos et al., 2016]] ; [[#Georgeson--2016|Georgeson et al., 2016]] ; [[#Mees--2017|Mees, 2017]] ; [[#Reckien--2018|Reckien et al., 2018]] ; [[#Hunter--2020|Hunter et al., 2020]] ).

<div id="16.3.2.2" class="h3-container"></div>

<span id="who-is-responding"></span>
==== 16.3.2.2 Who Is Responding? ====

<div id="h3-19-siblings" class="h3-siblings"></div>

'''''Individuals and households play a central role in adaptation globally.''''' The most frequently reported actors engaged in adaptation-related responses in the scientific literature are individuals and households, particularly in the Global South (Figure 16.4). Regionally, household- and individual-level adaptation is documented most extensively in Africa and Asia, and to a lesser but still substantial extent in North America (Figure 16.4).

<div id="_idContainer011" class="Figure"></div>

[[File:3e95194749b90cfce1349af0f92eced4 IPCC_AR6_WGII_Figure_16_004.png]]

'''Figure 16.4 |''' '''Who is responding, by geographic region and sector? Cell contents indicate the number of publications reporting engagement of each actor in adaptation-related responses.''' Darker colours denote a high number of publications. Based on a systematic review of 1682 scientific publications (2013–2019) reporting on adaptation-related responses in human systems ( [[#Berrang-Ford--2021a|Berrang-Ford et al., 2021a]] ). SIS, Small Island States; Terr, terrestrial and freshwater ecosystems.

'''''National and local governments are also frequently engaged in reported adaptation across most regions.''''' In Africa and Asia, reported adaptations have been primarily associated with individuals, households, national governments, non-governmental organisations (NGOs), and international institutions, with more limited reporting of involvement from sub-national governments or the private sector ( [[#Ford--2015a|Ford et al., 2015a]] ; [[#Ford--2015|Ford and King, 2015]] ; [[#Hunter--2020|Hunter et al., 2020]] ). Engagement by sub-national governments in adaptation is more frequently documented in Europe and North America ( [[#Craft--2013|Craft and Howlett, 2013]] ; [[#Craft--2013|Craft et al., 2013]] ; [[#Bauer--2014|Bauer and Steurer, 2014]] ; [[#Lesnikowski--2015|Lesnikowski et al., 2015]] ; [[#Shi--2015|Shi et al., 2015]] ; [[#Austin--2016|Austin et al., 2016]] ). Reporting of private sector engagement is generally low. Civil society participation in adaptations is reported across all regions. Consistent with this, local governments are also widely reported in documented adaptation responses, particularly where municipal jurisdiction is high, including cities, infrastructure, water and sanitation.

<div id="16.3.2.3" class="h3-container"></div>

<span id="what-types-of-responses-are-documented"></span>
==== 16.3.2.3 What Types of Responses Are Documented? ====

<div id="h3-20-siblings" class="h3-siblings"></div>

'''''Behavioural change is the most common form of adaptation.''''' The scientific literature presents extensive evidence of behavioural adaptation—change in the strategies, practices and actions that people, particularly individuals and households, undertake to reduce risk (Figure 16.5). This includes, for example, household measures to protect homes from flooding, protect crops from drought, relocation out of hazard zones, and shifting livelihood strategies ( [[#Porter--2014|Porter et al., 2014]] ). This is followed by adaptation via technological innovation and infrastructural development, nature-based adaptation (enhancing, protecting or promoting ecosystem services) and institutional adaptation (enhancing multi-level governance or institutional capabilities). Behavioural adaptation is most frequently documented in Asia, Africa and Small Island States, and in the agriculture, health and development sectors. In the agricultural sector, households are adopting or changing to crops and livestock that are more adapted to drought, heat, moisture, pests and salinity ( [[#Arku--2013|Arku, 2013]] ; [[#Kattumuri--2017|Kattumuri et al., 2017]] ; [[#Wheeler--2019|Wheeler and Marning, 2019]] ). Studies in Africa and Asia have documented shifts in farming and animal husbandry practice ( [[#Arku--2013|Arku, 2013]] ; [[#Garcia%20de%20Jalon--2016|Garcia de Jalon et al., 2016]] ; [[#Gautier--2016|Gautier et al., 2016]] ; [[#Chengappa--2017|Chengappa et al., 2017]] ; [[#Epule--2017|Epule et al., 2017]] ; [[#Kattumuri--2017|Kattumuri et al., 2017]] ; [[#Abu--2018|Abu and Reed, 2018]] ; [[#Asadu--2018|Asadu et al., 2018]] ; [[#Haeffner--2018|Haeffner et al., 2018]] ; [[#Shaffril--2018|Shaffril et al., 2018]] ; [[#Wiederkehr--2018|Wiederkehr et al., 2018]] ; [[#Zinia--2018|Zinia and McShane, 2018]] ; [[#Currenti--2019|Currenti et al., 2019]] ; [[#Fischer--2019a|Fischer, 2019a]] ; [[#Fischer--2019b|Fischer, 2019b]] ; [[#Schofield--2019|Schofield and Gubbels, 2019]] ; [[#Sereenonchai--2019|Sereenonchai and Arunrat, 2019]] ; [[#Wheeler--2019|Wheeler and Marning, 2019]] ; [[#Mayanja--2020|Mayanja et al., 2020]] ). In Small Island Nations, studies have documented household flood protections measures such as raising elevation of homes and yards, creating flood barriers, improving drainage, moving belongings and, in some cases, relocating ( [[#Middelbeek--2014|Middelbeek et al., 2014]] ; [[#Currenti--2019|Currenti et al., 2019]] ; [[#Klock--2019|Klock and Nunn, 2019]] ).

<div id="_idContainer013" class="Figure"></div>

[[File:e27d2f40735a605dec7a2baab71aebce IPCC_AR6_WGII_Figure_16_005.png]]

'''Figure 16.5 |''' '''Type of adaptation responses by global region.''' Percentages reflect the number of articles mentioning each type of adaptation over the total number of articles for that region. Radar values do not total 100% per region since publications frequently report multiple types of adaptation; for example, construction of drainage systems (infrastructural), changing food storage practices by households (behavioural), and planting of tree cover in flood-prone areas (nature-based) in response to flood risk to agricultural crops. Data updated and adapted from [[#Berrang-Ford--2021a|Berrang-Ford et al. (2021a)]] , based on 1682 scientific publications reporting on adaptation-related responses in human systems.

'''''The mix of adaptation response types differs across regions and sectors.''''' Technological and infrastructural responses are widely reported in Europe, and globally in the context of cities and water and sanitation ( [[#Mees--2017|Mees, 2017]] ; [[#Hintz--2018|Hintz et al., 2018]] ). Responses to flood risk in Europe include the use of flood- and climate-resistant building materials, large-scale flood management, and water storage and irrigation systems ( [[#van%20Hooff--2015|van Hooff et al., 2015]] ; [[#Mees--2017|Mees, 2017]] ). Technological and infrastructural responses are also documented to some extent in agriculture, including, for example, breeding more climate-resilient crops, precision farming and other high-tech solutions such as genetic modification ( [[#Makhado--2014|Makhado et al., 2014]] ; [[#Fisher--2015|Fisher et al., 2015]] ; [[#Costantini--2020|Costantini et al., 2020]] ; [[#Fraga--2021|Fraga et al., 2021]] ; [[#Grusson--2021|Grusson et al., 2021]] ; [[#Naulleau--2021|Naulleau et al., 2021]] ). While less common, institutional responses are more prominent in North America and Australasia as compared with other regions, and include zoning regulations, new building codes, new insurance schemes, and coordination mechanisms ( [[#Craft--2013|Craft and Howlett, 2013]] ; [[#Craft--2013|Craft et al., 2013]] ; [[#Parry--2014|Parry, 2014]] ; [[#Ford--2015b|Ford et al., 2015b]] ; [[#Beiler--2016|Beiler et al., 2016]] ; [[#Lesnikowski--2016|Lesnikowski et al., 2016]] ; [[#Labbe--2017|Labbe et al., 2017]] ; [[#Sterle--2017|Sterle and Singletary, 2017]] ; [[#Hu--2018|Hu et al., 2018]] ; [[#Conevska--2019|Conevska et al., 2019]] ). Institutional adaptations are more frequently reported in cites than other sectors. Institutional adaptation may be particularly subject to reporting bias, however, with many institutional responses likely to be reported in the grey literature (see Chapter 17). Nature-based solutions are less frequently reported, except in Africa, where they are relatively well documented, and in the content of terrestrial systems where reports included species regeneration projects, wind breaks, erosion control, reforestation and riparian zone management ( [[#Munji--2014|Munji et al., 2014]] ; [[#Partey--2017|Partey et al., 2017]] ; [[#Muthee--2018|Muthee et al., 2018]] ).

'''''Some but not all adaptation-related responses are engaging vulnerable populations in planning or implementation''''' ( ''high confidence'' ) ( [[#Araos--2021|Araos et al., 2021]] ). Consideration of vulnerable populations is most frequently focused on low-income populations and women through the inclusion of informal or formal institutions or representatives in adaptation planning, or through targeted adaptations to reduce risk in these populations ( ''high confidence'' ). Consideration of vulnerable groups in adaptation responses is more frequently reported in the Global South ( ''medium confidence'' ). Engagement in adaptation planning of vulnerable elderly, migrants, and ethnic minorities remains low across all global regions ( ''medium confidence'' ). There is negligible literature on consideration of disabled peoples in planning and implementation of adaptation-related responses ( ''medium confidence'' ).

<div id="16.3.2.4" class="h3-container"></div>

<span id="adaptation-effectiveness-adequacy-and-risk-reduction"></span>
==== 16.3.2.4 Adaptation Effectiveness, Adequacy and Risk Reduction ====

<div id="h3-21-siblings" class="h3-siblings"></div>

Despite a lack of systematic methods for assessing general adaptation effectiveness, there is some evidence of risk reduction for particular places and hazards, especially flood and heat vulnerability. There is some evidence of a reduction in global vulnerability, particularly for flood risk ( [[#Jongman--2015|Jongman et al., 2015]] ; [[#Tanoue--2016|Tanoue et al., 2016]] ; [[#Miao--2019|Miao, 2019]] ) and extreme heat ( [[#Bobb--2014|Bobb et al., 2014]] ; [[#Boeckmann--2014|Boeckmann and Rohn, 2014]] ; [[#Gasparrini--2015|Gasparrini et al., 2015]] ; [[#Arbuthnott--2016|Arbuthnott et al., 2016]] ; [[#Chung--2017|Chung et al., 2017]] ; [[#Sheridan--2018|Sheridan and Allen, 2018]] ; [[#Folkerts--2020|Folkerts et al., 2020]] ). Investment in flood protection, including building design and monitoring and forecasting, have reduced flood-related mortality over time and are cost-effective (Bouwer and Jonkman 2018; Ward et al. 2017). Declining heat sensitivity, primarily reported in developed nations, has also been observed, and has been linked to air conditioning, reduced social vulnerability and improved population health ( [[#Boeckmann--2014|Boeckmann and Rohn, 2014]] ; [[#Chung--2017|Chung et al., 2017]] ; [[#Kinney--2018|Kinney, 2018]] ; [[#Sheridan--2018|Sheridan and Allen, 2018]] ). [[#Formetta--2019|Formetta and Feyen (2019)]] demonstrate declining global all-cause mortality and economic loss due to extreme weather events over the past four decades, with the greatest reductions in low-income countries, and with reductions correlated with wealth. Studies that correlate changes in mortality or economic losses with wealth indicators, to infer changes in vulnerability or exposure, lack direct empirical measures of vulnerability or exposure and are limited in their ability to assess how indirect effects of extreme events (e.g., morbidity, relocation, social disruption) may have changed or how changes may redistribute risk across populations.

There remain persistent difficulties in defining and measuring adaptation effectiveness and adequacy for many climate risks. No studies have systematically assessed the adequacy and effectiveness of adaptation at a global scale, across nations or sectors, or for different levels of warming. There has, however, been progress in operationalising assessment of adaptation feasibility (Cross-Chapter Box FEASIB in Chapter 18). Effectiveness of adaptation-related responses reflects whether a particular response actually reduces climate risk, typically through reductions in vulnerability and exposure (Figure 1.7 in [[IPCC:Wg2:Chapter:Chapter-1#1.4|Section 1.4]] ). Some adaptation-related responses may increase risk or create new risks (maladaptation) or have no or negligible impact on risk. Adequacy of adaptation-related responses refers to the extent to which responses are collectively sufficient to reduce the risks or impacts of climate change (Figure 1.7 in [[IPCC:Wg2:Chapter:Chapter-1#1.4|Section 1.4]] ). A set of adaptation-related responses may, for example, result in reduced climate risk (effectiveness), but these reductions may be insufficient to offset the level of risk and avoid loss and damages. Feasibility reflects the degree to which climate responses are possible or desirable, and integrates consideration of potential effectiveness. A feasibility assessment drawing on these methods is presented in Cross-Chapter Box FEASIB in Chapter 18.

Global adaptation is predominantly slow, siloed and incremental with little evidence of transformative adaptation ( ''high confidence'' ). In the absence of a general method to assess the adequacy of adaptation actions, we assessed evidence for transformational adaptation documented in peer-reviewed publications identified by a global stock-taking initiative ( [[#Berrang-Ford--2021b|Berrang-Ford et al., 2021b]] ) and in other AR6 chapters (2–15) (see Supplemental Material, SM16.1 for details). ‘Transformational adaptation’ refers to the degree to which adaptations have been implemented widely (scope), reflect major shifts (depth), occur rapidly (speed) and challenge limits to adaptation (limits, [[#Pelling--2015|Pelling et al., 2015]] ; [[#Few--2017|Few et al., 2017]] ; [[#Termeer--2017|Termeer et al., 2017]] , Table 16.1).

Based on the literature, the overall transformative nature of adaptation across most global regions and sectors is low ( ''high confidence)'' (Figure 16.6). Documented adaptations tend to involve minor modifications to usual practices taken to address extreme weather conditions ( ''high confidence'' ). For example, changing crop variety or timing of crop planting to address floods or droughts, new types of irrigation, pursuing supplementary livelihoods, and home elevations are widely reported but typically do not reflect radical or novel shifts in practice or values and are therefore considered low depth ( ''high confidence'' ) (see SM16.1 for more examples). Adaptations documented in the literature are also frequently focused on a single sector or small geographic area ( ''high confidence'' ). Actions taken by individuals or households are generally small in scope ( [[#Hintz--2018|Hintz et al., 2018]] ; [[#Hlahla--2018|Hlahla and Hill, 2018]] ) unless they are widely adopted (e.g., by farmers across a region) or address numerous aspects of life. National policies are more likely to be broad in scope ( [[#Puthucherril--2014|Puthucherril et al., 2014]] ), although they frequently focus on a single sector and are therefore still limited. The speed of adaptation is rarely noted explicitly, but the average speed documented in the literature is slow ( ''medium confidence'' ) (Cross-Chapter Box FEASIB in Chapter 18). Adaptation efforts frequently encounter either soft or hard limits (see [[#16.4|Section 16.4]] ), but there is ''limited evidence'' to suggest these limits are being challenged or overcome ( ''medium confidence'' ).

<div id="_idContainer016" class="Figure"></div>

[[File:4de6feb70ecd06157c4fd3613f5c1b54 IPCC_AR6_WGII_Figure_16_006.png]]

'''Figure 16.6 |''' '''Evidence of transformative adaptation by sector and region.''' Evidence of transformational adaptation does not imply effectiveness, equity or adequacy. Evidence of transformative adaptation is assessed based on the scope, speed, depth and ability to challenge limits of responses reported in the scientific literature (see Supplementary Material for methods). Studies relevant to multiple regions or sectors are included in assessment for each relevant sector/region.

Few documented responses are simultaneously widespread, rapid and novel ( ''high confidence'' ). Some examples exist, such as village relocations or creation of new multi-stakeholder resource governance systems ( [[#Schwan--2018|Schwan and Yu, 2018]] ; [[#McMichael--2020|McMichael and Katonivualiku, 2020]] ), but these are rare. In general, adaptations that are broad in scope tend to be slow ( ''medium confidence'' ), suggesting that achieving high transformation in all four categories (depth, scope, speed and limits) may be particularly challenging or even involve trade-offs.

'''Table 16.1 |''' Evidence of transformational adaptation assessed across four components (depth, scope, speed and limits). Transformational adaptation does not imply adequacy or effectiveness of adaptation (low transformation may be sufficient for some climate risks, and high transformation may be insufficient to offset others). Nevertheless, these components provide a systematic framework for tracking adaptation progress and assessing the state of adaptation-related responses. The ‘high’ categories across each component reflect more transformative scenarios. Methods are described in SM16.1.

{| class="wikitable"
|-
!
! colspan="3"| Transformative potential of adaptation

|-
| Dimensions

| '''Low'''

| '''Medium'''

| '''High'''

|-
| '''Overall'''

| ''Adaptation is largely sporadic and consists of small adjustments to Business-As-Usual. Coordination and mainstreaming are limited and fragmented.''

| ''Adaptation is expanding and increasingly coordinated, including wider implementation and multi-level coordination.''

| ''Adaptation is widespread and implemented at or very near its full potential across multiple dimensions.''

|-
| '''Depth'''

| Adaptations are largely expansions of existing practices, with minimal change in underlying values, assumptions or norms.

| Adaptations reflect a shift away from existing practices, norms or structures to some extent.

| Adaptations reflect entirely new practices involving deep structural reform, complete change in mindset, major shifts in perceptions or values, and changing institutional or behavioural norms.

|-
| '''Scope'''

| Adaptations are largely localised and fragmented, with ''limited evidence'' of coordination or mainstreaming across sectors, jurisdictions or levels of governance.

| Adaptations affect wider geographic areas, multiple areas and sectors, or are mainstreamed and coordinated across multiple dimensions.

| Adaptations are widespread and substantial, including most possible sectors, levels of governance, and actors.

|-
| '''Speed'''

| Adaptations are implemented slowly.

| Adaptations are implemented moderately quickly.

| Change is considered rapid for a given context.

|-
| '''Limits'''

| Adaptations may approach but do not exceed or substantively challenge soft limits.

| Adaptations may overcome some soft limits but do not challenge or approach hard limits.

| Adaptations exceed many soft limits and approach or challenge hard limits.

|}

<div id="16.3.2.5" class="h3-container"></div>

<span id="observed-maladaptation-and-co-benefits"></span>
==== 16.3.2.5 Observed Maladaptation and Co-benefits ====

<div id="h3-22-siblings" class="h3-siblings"></div>

'''There is increasing reporting of maladaptation globally (Table 16.2, [[IPCC:Wg2:Chapter:Chapter-17#17.5.1|Section 17.5.1]] ) (''' '''''high confidence''''' ''').''' Maladaptation has been particularly reported in the context of agricultural, forestry and fisheries practices, migration in the Global South, and some infrastructure-based interventions. Urban heat adaptations have been linked to maladaptation that increase health risks and/or energy consumption. Heat poses significant risks to the evolutionary tolerance levels of humans, animals and crops ( [[#Asseng--2021|Asseng et al., 2021]] ), and current adaptation interventions for reducing urban heat like cool or evaporation roofs and street trees may be insufficient to reduce heat-related vulnerabilities in some urban areas at higher levels of warming ( [[#Krayenhoff--2018|Krayenhoff et al., 2018]] ) (see also [[#16.4|Section 16.4]] on adaptation limits). There is evidence that autonomous adaptation by individuals and households can shift risk to others, with net increases in vulnerability. Intensification of pasture use as a coping response to climate-induced drought has been observed to increase risks to livestock reproduction and human life expectancy due to overgrazing, suggesting responses to pastoral vulnerability can cross tolerance limits for animals, humans and food available for foraging ( [[#Suvdantsetseg--2017|Suvdantsetseg et al., 2017]] ).

Evidence on ''realised'' co-benefits of implemented adaptation responses with other priorities in the SDGs is emerging among the areas of poverty reduction, food security, health and well-being, terrestrial and freshwater ecosystem services, sustainable cities and communities, energy security, work and economic growth, and mitigation (Table 16.2) ( ''high confidence'' ). Evidence on co-benefits of adaptation for mitigation is particularly strong, and is observed in various agricultural, forestry and land use management practices like agroforestry, climate-smart agriculture and afforestation ( [[#Kremen--2012|Kremen and Miles, 2012]] ; [[#Christen--2013|Christen and Dalgaard, 2013]] ; [[#Mbow--2014|Mbow et al., 2014]] ; [[#Locatelli--2015|Locatelli et al., 2015]] ; [[#Suckall--2015|Suckall et al., 2015]] ; [[#Wichelns--2016|Wichelns, 2016]] ; [[#Kongsager--2018|Kongsager, 2018]] ; [[#Debray--2019|Debray et al., 2019]] ; [[#Loboguerrero--2019|Loboguerrero et al., 2019]] ; [[#Morecroft--2019|Morecroft et al., 2019]] ; [[#Chausson--2020|Chausson et al., 2020]] ) as well as in the urban built environment ( [[#Perrotti--2020|Perrotti and Stremke, 2020]] ; [[#Sharifi--2020|Sharifi, 2020]] ). Evidence on co-benefits of implemented responses for other SDG priority areas is less developed, however, in the areas of education, gender inequality and reduced inequalities, clean water and sanitation, industry, innovation and infrastructure, consumption and production, marine and coastal ecosystem protection, and peace, justice, and strong institutions. This indicates a gap between some assumed likely co-benefits of adaptation and empirical evidence on the realisation of these co-benefits within the context of implemented adaptation responses ( [[#Berga--2016|Berga, 2016]] ; [[#Froehlich--2018|Froehlich et al., 2018]] ; [[#Gattuso--2018|Gattuso et al., 2018]] ; [[#Morris--2018|Morris et al., 2018]] ; [[#Chausson--2020|Chausson et al., 2020]] ; [[#Karlsson--2020|Karlsson et al., 2020]] ; [[#Krauss--2020|Krauss and Osland, 2020]] ).

'''Table 16.2 |''' Observed examples of maladaptation and co-benefits from adaptation-related responses in human systems.

{| class="wikitable"
|-
! Implemented adaptations

! Observed maladaptation

! References

|-
| colspan="3"| Agricultural and forestry practices

|-
| Intensified cultivation of marginal lands: clearing of virgin forests for farmland; frequent weeding; poorly managed irrigation schemes; dependence on rainfed agriculture

| Increased competition for resources such as water and nutrients; reduced soil fertility; invasive species; degraded environment; increased greenhouse gas emissions; reduced crops diversity and reduced harvest, thus increasing food insecurity in rural areas; accelerated illegal logging practices; increased vulnerability of herders, translated into poor health and working conditions (Mongolia)

| Bele et al. (2014); D’haen et al. (2014); [[#Chapman--2016|Chapman et al. (2016)]] ; [[#Ifeanyi-obi--2017|Ifeanyi-obi et al. (2017)]] ; [[#Suvdantsetseg--2017|Suvdantsetseg et al. (2017)]] ; [[#Villamayor-Tomas--2017|Villamayor-Tomas and Garcia-Lopez (2017)]] ; Afriyie et al. (2018); [[#Ticehurst--2018|Ticehurst and Curtis (2018)]] ; [[#Tran--2018|Tran et al. (2018)]] ; [[#Neset--2019|Neset et al. (2019)]] ; [[#Work--2019|Work et al. (2019)]] ; Yamba et al. (2019); [[#Singh--2020|Singh and Basu (2020)]]

|-
| Agroforestry systems

| Higher water demand where trees were combined with crops and livestock; native trees replaced with non-indigenous trees; reduced resilience of certain plants (e.g., cocoa); degraded soil and water quality and accelerated environmental degradation in Africa and Asia (Pakistan, Nepal, India, China, Philippines)

| [[#Nordhagen--2013|Nordhagen and Pascual (2013)]] ; D’haen et al. (2014); [[#Hoang--2014|Hoang et al. (2014)]] ; [[#Ruiz-Mallen--2015|Ruiz-Mallen et al. (2015)]] ; [[#Kibet--2016|Kibet et al. (2016)]] ; Chengappa et al. (2017); [[#Haji--2017|Haji and Legesse (2017)]] ; [[#Abdulai--2018|Abdulai et al. (2018)]] ; [[#Antwi-Agyei--2018|Antwi-Agyei et al. (2018)]] ; [[#Mersha--2018|Mersha and van Laerhoven (2018)]] ; [[#Ullah--2018|Ullah et al. (2018)]] ; [[#Krishnamurthy--2019|Krishnamurthy et al. (2019)]]

|-
| Agricultural transitions: commercialisation of common property; market integration and sedentarisation of pastoralists; adoption and expansion of commercial crops

| Soil degradation and high dependency on external inputs in South and Central America (El Salvador, Guatemala, Honduras, Nicaragua and Peru); dependency on foreign corporation seed systems; land enclosures; adaptation that forced local farmers in Costa Rica to switch crops to commercially viable products (e.g., from rice to sugar cane) impoverished the land by removing nutrients and affecting food security for smallholder farmers

| [[#Nordhagen--2013|Nordhagen and Pascual (2013)]] ; D’haen et al. (2014); [[#Warner--2015|Warner et al. (2015)]] ; [[#Kibet--2016|Kibet et al. (2016)]] ; ( [[#Warner--2016|Warner and Kuzdas, 2016]] ); [[#Haji--2017|Haji and Legesse (2017)]] ; [[#Antwi-Agyei--2018|Antwi-Agyei et al. (2018)]] ; [[#Mersha--2018|Mersha and van Laerhoven (2018)]] ; [[#Krishnamurthy--2019|Krishnamurthy et al. (2019)]] ; [[#Neset--2019|Neset et al. (2019)]]

|-
| Proper, improper and increased use of agrochemicals, pesticides and fertilizers

| Fertilizer and agrochemicals negatively affected soil quality and accelerated environmental degradation in several parts of Africa (Ghana, Nigeria) and Asia (Pakistan, Nepal, India, China, Philippines). In Europe (Sweden and Finland), there are concerns about the risk of pests and weeds developing immunity to pesticides, and drainage systems and rain transferred chemicals to other fields, thereby affecting arable land. In South and Central America (El Salvador, Guatemala, Honduras, Nicaragua and Peru), agrochemicals led to soil degradation, and high dependency on external input was reported. Loss of soil nutrients, increased GHG emissions (Sweden, Finland); high nitrate and phosphate concentration (Great Britain)

| [[#Postigo--2014|Postigo (2014)]] ; [[#Rodriguez-Solorzano--2014|Rodriguez-Solorzano (2014)]] ; [[#Fezzi--2015|Fezzi et al. (2015)]] ; [[#Sujakhu--2016|Sujakhu et al. (2016)]] ; [[#Begum--2017|Begum and Mahanta (2017)]] ; [[#de%20Sousa--2018|de Sousa et al. (2018)]] ; [[#Tang--2018|Tang et al. (2018)]] ; Yamba et al. (2019)

|-
| Tree planting

| The lack of shaded trees increased vulnerability to landslides in areas where Robusta coffee was grown (Mexico); new tree species to cope with climate change increased sensitivity and displaced non-indigenous trees (India; Tanzania and Kenya); cocoa planted under shade trees had higher mortality rate and more stress (Ghana); eucalyptus trees planted to reduce soil erosion had high water demand (Pakistan); in certain urban areas, trees planted to provide shade damaged buildings during heavy storms

| [[#Benito-Garzon--2013|Benito-Garzon et al. (2013)]] ; [[#Hoang--2014|Hoang et al. (2014)]] ; [[#Ruiz%20Meza--2015|Ruiz Meza (2015)]] ; Chengappa et al. (2017); [[#Abdulai--2018|Abdulai et al. (2018)]] ; [[#Ullah--2018|Ullah et al. (2018)]]

|-
| colspan="3"| Fisheries and water management

|-
| Increased fishing activity

| Fishery depletion and exacerbated negative trends in the ecosystem that threatened fishermen’s subsistence

| [[#Goulden--2013|Goulden et al. (2013)]] ; Mazur et al. (2013); [[#Rodriguez-Solorzano--2014|Rodriguez-Solorzano (2014)]] ; [[#Pershing--2016|Pershing et al. (2016)]] ; Kanda et al. (2017); [[#Kihila--2018|Kihila (2018)]] ; [[#Pinsky--2018|Pinsky et al. (2018)]]

|-
| Shrimp farming

| A driver of deforestation of mangroves in Bangladesh; imposes external cost on paddy farmers; salinity levels are relatively higher in paddy plots closer to shrimp ponds; coral mining increased vulnerability to flooding (in small islands in the Philippines)

| [[#Johnson--2016|Johnson et al. (2016)]] ; [[#Jamero--2017|Jamero et al. (2017)]] ; [[#Paprocki--2018|Paprocki and Huq (2018)]] ; [[#Sovacool--2018|Sovacool (2018)]] ; [[#Morshed--2020|Morshed et al. (2020)]]

|-
| Water irrigation infrastructure for agriculture; water desalination in response to water shortages

| Increased land loss; redistributed risk among agrarian stakeholders; affected the rural poor (Cambodia; Costa Rica); uneven distribution of cost and benefits (USA–Mexico border); desalination plants to led disproportionately high cost for low-income water users

| [[#Barnett--2013|Barnett and O’Neill (2013)]] ; [[#Olmstead--2014|Olmstead (2014)]] ; [[#Warner--2016|Warner and Kuzdas (2016)]] ; [[#Work--2019|Work et al. (2019)]]

|-
| Storage of large quantities of water in the home

| Water rendered unsafe for drinking due contamination by faecal coliforms in Zimbabwe; drought-induced changes in water harvesting and storage increased breeding sites for mosquitoes (Australia); water storage facilities and tanks provided ideal breeding conditions for mosquitoes and flies, bringing both vectors and diseases closer to people (Ethiopia)

| [[#Boelee--2013|Boelee et al. (2013)]] ; [[#Trewin--2013|Trewin et al. (2013)]] ; Kanda et al. (2017)

|-
| Increased number of farm dams for water storage; groundwater extraction and interbasin water transfers

| Reduced river and ground water flow downstream; water grabs from shared surface or groundwater resources with poorly defined property rights shifted vulnerability to other groups and ecosystems (Cambodia; California): water extractions increased risks for the environment and food security, while transfers reduced hydropower generation and resulted in higher costs paid by electricity consumers and health impacts from air pollution caused by more electricity generation from natural gas (California); increase the concentration in the hands of the more powerful large farmers (Argentina)

| Mazur et al. (2013); Christian-Smith et al. (2015); ( [[#Hurlbert--2016|Hurlbert and Mussetta, 2016]] ); Work et al.)

|-
| colspan="3"| Built environment

|-
| Seawalls and infrastructural development along coastlines

| Coastal erosion, beach losses, changes in water current, and destruction of natural ecosystems in Asia, Australasia, Europe and North America; increased or shifted erosion from protected to unprotected areas in Fiji, Marshall Islands, Nuie, Kiribati and Norway; failed or sped up flood waters and worsened conditions for riparian habitat and downstream residents; harmed nearby reefs and impeded autonomous adaptation practise that could be effective (Bangladesh)

| [[#Macintosh--2013|Macintosh (2013)]] ; [[#Maldonado--2014|Maldonado et al. (2014)]] ; [[#Porio--2014|Porio (2014)]] ; [[#Betzold--2015|Betzold (2015)]] ; [[#Renaud--2015|Renaud et al. (2015)]] ; Gundersen et al. (2016); Sayers et al. (2018); [[#Craig--2019|Craig (2019)]] ; [[#Javeline--2019|Javeline and Kijewski-Correa (2019)]] ; [[#Loughran--2019|Loughran and Elliott (2019)]] ; [[#Rahman--2019|Rahman and Hickey (2019)]] ; [[#Piggott-McKellar--2020|Piggott-McKellar et al. (2020)]] ; Simon et al. (2020) [[#Dahl--2017|Dahl et al. (2017)]]

|-
| Smart or green luxury real estate development designed to reduce impacts from storm surges and erosion along coastal area; artificial islands

| Redistributed risk and vulnerability; displaced and diminished adaptive capacity of vulnerable groups, created new population of landless peasants; negatively affected neighbouring coastal areas and local ecology (Lagos, Miami, Hanoi, Jakarta, Manila; Maldives)

| Caprotti et al. (2015); [[#Magnan--2016|Magnan et al. (2016)]] ; [[#Atteridge--2018|Atteridge and Remling (2018)]] ; [[#Ajibade--2019|Ajibade (2019)]] ; Salim et al. (2019); [[#Thomas--2019|Thomas and Warner (2019)]]

|-
| Subsidised insurance premiums for properties located in flood-prone areas, levees, dykes

| Rebuilding in risky areas

| [[#Shearer--2014|Shearer et al. (2014)]] ; O’Hare et al. (2016); [[#Craig--2019|Craig (2019)]] ; [[#Loughran--2019|Loughran and Elliott (2019)]]

|-
| Autonomous flood strategies such as sandbags, digging channels and sand walls around homes

| Sandbags used to reduce coastal erosion released plastics into the sea and led to loss of recreational value of beaches; sand walls shifted the flood impacts across space and time and were more detrimental to poor informal urban settlers (Dakar); caused erosion and degraded coastal lands (South Africa)

| [[#Schaer--2015|Schaer (2015)]] ; [[#Wamsler--2015|Wamsler and Brink (2015)]] ; ( [[#Chapman--2016|Chapman et al., 2016]] ); [[#Magnan--2016|Magnan et al. (2016)]] ; [[#Mycoo--2018|Mycoo (2018)]] ; [[#Rahman--2019|Rahman and Hickey (2019)]]

|-
| Top-down technocratic adaptation with no consideration for ecosystem biodiversity, local adaptive capacity and gender issues

| Ignored the complexities of the landscapes and socio-ecological systems; constrained autonomous adaptation due to time and labour demands of public work; increased gender vulnerability; hamper women’s water rights (South Africa); altered local gender norms (Ethiopia); led to a mismatch that undermine local-level processes that are vital to local adaptive capacity (Rwanda)

| [[#Cartwright--2013|Cartwright et al. (2013)]] ; [[#Goulden--2013|Goulden et al. (2013)]] ; [[#Nordhagen--2013|Nordhagen and Pascual (2013)]] ; [[#Carr--2014|Carr and Thompson (2014)]] ; [[#Nyamadzawo--2015|Nyamadzawo et al. (2015)]] ; [[#Ruiz-Mallen--2015|Ruiz-Mallen et al. (2015)]] ; [[#Djoudi--2016|Djoudi et al. (2016)]] ; Gautier et al. (2016); Gundersen et al. (2016); [[#Barnett--2018|Barnett and McMichael (2018)]] ; [[#Kihila--2018|Kihila (2018)]] ; [[#Mersha--2018|Mersha and van Laerhoven (2018)]] ; [[#Clay--2019|Clay and King (2019)]] ; [[#Currenti--2019|Currenti et al. (2019)]] ; [[#Yang--2019|Yang et al. (2019)]]

|-
| colspan="3"| Migration and relocation

|-
| Out-migration or rural-to-urban migration in response to food insecurity and agricultural livelihood depreciation

| Migration mostly undertaken by poorer households weakened local subsistence production capacity; disrupted family structures; reduced labour available for agricultural work; increased burden of responsibilities on women; fostered loss of solidarity within communities; increased divorce rates; exacerbated conflicts among different groups; increased pressure on urban housing and social services; expanded slum settlements around riparian and coastal areas including flood plains and swamplands (Ethiopia, Namibia, Benin, Botswana, Nigeria, Ghana, Kenya, Niger, Mail, Tanzania, Zimbabwe, South Africa, Morocco, Nepal, Pakistan, Bangladesh China, India, Australia, Nicaragua); out-migration from small communities had devastating consequences on their fragile economies, thereby reducing community resilience in the long term (Australia)

| [[#Su--2017|Su et al. (2017)]] ; [[#Aziz--2015|Aziz and Sadok (2015)]] ; [[#Bhatta--2016|Bhatta and Aggarwal (2016)]] ; [[#Clay--2019|Clay and King (2019)]] ; Elagib et al. (2017); [[#Gao--2018|Gao and Mills (2018)]] ; Kattumuri et al. (2017); [[#Magnan--2016|Magnan et al. (2016)]] ; [[#Ofoegbu--2016|Ofoegbu et al. (2016)]] ; Rademacher-Schulz et al. (2014);Rademacher-Schulz et al. (2014);Wiederkehr et al. (2018); Yegbemey et al. (2017); [[#Yila--2013|Yila and Resurreccion (2013)]] ; Nizami et al. (2019); [[#Mersha--2016|Mersha and Van Laerhoven (2016)]] ; [[#Ojha--2014|Ojha et al. (2014)]] ; [[#Radel--2018|Radel et al. (2018)]] ; [[#Gioli--2014|Gioli et al. (2014)]] ; [[#Hooli--2016|Hooli (2016)]] ; [[#Koubi--2016|Koubi et al. (2016)]]

|-
| Certain autonomous, forced and planned relocation

Temporary resettlement (India)

| Expansion of informal settlements in cities (Solomon Islands); relocation to areas prone to landslide and soil erosion or insufficient housing (Fiji); disproportionate burden on vulnerable communities (China); temporary relocation created gender inequality associated with minimal privacy; poor access to private toilets; sexual harassment; reduced sleep; insufficient or food rationing; exploitation and abuse of children (India); inadequate funding and governance mechanism for community-based relocation caused loss of culture, economic decline and health concerns (Alaska); relocation of supply chain to reduce exposure to climate change resulted in adverse outcomes for communities along the supply chain

| [[#Monnereau--2013|Monnereau and Abraham (2013)]] ; [[#Maldonado--2014|Maldonado et al. (2014)]] ; [[#Pritchard--2014|Pritchard and Thielemans (2014)]] ; [[#Averchenkova--2016|Averchenkova et al. (2016)]] ; [[#Lei--2017|Lei et al. (2017)]] ; [[#Barnett--2018|Barnett and McMichael (2018)]] ; [[#Currenti--2019|Currenti et al. (2019)]]

|-
| colspan="3"| Agricultural practices

|-
| Integrated agricultural practices (e.g., climate-smart agriculture, urban and peri-urban agriculture and forestry; agro-ecology; silvopasture; soil desalinisation; drainage improvement; integrated soil–crop system management; no tillage farming; rainwater harvesting; check dams)

| Mitigation, especially carbon sequestration (but see [[#Sommer--2018|Sommer et al., 2018]] ); improved household equity regarding farming decisions, particularly inclusion of women; food security

| [[#Furman--2014|Furman et al. (2014)]] ; [[#Lwasa--2014|Lwasa et al. (2014)]] ; [[#Kibue--2015|Kibue et al. (2015)]] ; [[#Nyasimi--2017|Nyasimi et al. (2017)]] ; [[#Aryal--2018|Aryal et al. (2018)]] ; [[#Han--2018|Han et al. (2018)]] ; [[#Kakumanu--2018|Kakumanu et al. (2018)]] ; Sikka et al. (2018); [[#Debray--2019|Debray et al. (2019)]] ; [[#Kerr--2019|Kerr et al. (2019)]] ; ( [[#Teklewold--2019a|Teklewold et al., 2019a]] ); Teklewold et al. (2019b); [[#Wang--2020|Wang et al. (2020)]] [[#Sommer--2018|Sommer et al. (2018)]]

|-
| Improved irrigation systems

| Mitigation, especially avoided emissions; improved crop yields

| [[#Islam--2020|Islam et al. (2020)]]

|-
| Conservation agriculture (e.g., crop diversification; soil conservation; cover cropping)

| Mitigation, especially carbon sequestration; increased crop yields; food security; reduced heat and water stress; increased food security

| [[#Helling--2015|Helling et al. (2015)]] ; [[#Sapkota--2015|Sapkota et al. (2015)]] ; [[#Kimaro--2016|Kimaro et al. (2016)]] ; [[#Mainardi--2018|Mainardi (2018)]] ; Asmare et al. (2019); [[#Gonzalez-Sanchez--2019|Gonzalez-Sanchez et al. (2019)]]

|-
| Return to traditional farming practices

| Mitigation, especially carbon sequestration

| [[#Pienkowski--2019|Pienkowski and Zbaraszewski (2019)]]

|-
| Place-specific practices and innovations: animal cross-breeding; direct crop seeding; site-specific nutrient management; irrigation innovations; use of riparian buffer strips; use of green winter land; rice–rice system

| Mitigation, especially carbon sequestration; improved crop yields; food security

| [[#Sushant--2013|Sushant (2013)]] ; Balaji et al. (2015); [[#Helling--2015|Helling et al. (2015)]] ; [[#Jorgensen--2016|Jorgensen and Termansen (2016)]] ; [[#Sen--2017|Sen and Bond (2017)]] ; [[#Wilkes--2017|Wilkes et al. (2017)]] ; [[#Kakumanu--2018|Kakumanu et al. (2018)]] ; [[#Mainardi--2018|Mainardi (2018)]] ; Sikka et al. (2018) [[#Yadav--2020|Yadav et al. (2020)]]

|-
| colspan="3"| Land and water management

|-
| Agroforestry

| Mitigation, especially carbon sequestration; biodiversity and ecosystem conservation; improved food security; plant species diversification; diversification of household livelihoods; improved household incomes; improved access to forage material; energy access and reduced fuel wood gathering time and distance for women; soil and water conservation; aesthetic improvements in landscapes

| [[#Holler--2014|Holler (2014)]] ; Suckall et al. (2015); [[#Sharma--2016|Sharma et al. (2016)]] ; [[#Nyasimi--2017|Nyasimi et al. (2017)]] ; [[#Pandey--2017|Pandey et al. (2017)]] ; [[#Schembergue--2017|Schembergue et al. (2017)]] ; [[#Ticktin--2018|Ticktin et al. (2018)]] ; [[#Debray--2019|Debray et al. (2019)]] ; [[#Jezeer--2019|Jezeer et al. (2019)]] ; [[#Krishnamurthy--2019|Krishnamurthy et al. (2019)]] ; Nyantakyi-Frimpong et al. (2019); [[#Tschora--2020|Tschora and Cherubini (2020)]]

|-
| Afforestation and reforestation programs;

forest management practices (e.g., tree thinning)

| Mitigation, especially carbon sequestration; biodiversity and ecosystem conservation; new employment opportunities; diversification of household livelihoods; increased household incomes; improved access to fuel wood; harvesting opportunities from enclosures

| [[#Holler--2014|Holler (2014)]] ; [[#Etongo--2015|Etongo et al. (2015)]] ; [[#Diederichs--2016|Diederichs and Roberts (2016)]] ; [[#Acevedo-Osorio--2017|Acevedo-Osorio et al. (2017)]] ; [[#Nyasimi--2017|Nyasimi et al. (2017)]] ; [[#Krishnamurthy--2019|Krishnamurthy et al. (2019)]] ; [[#Rahman--2019|Rahman et al. (2019)]] [[#Wolde--2016|Wolde et al. (2016)]]

|-
| Ecosystem-based adaptations such as mangrove restoration and natural coastal defences

| Mitigation, especially carbon sequestration; habitat enhancement and protection for marine species; prevention of floor-related deaths, injuries and damage; improved nutrition and income generation for local communities, improved water quality

| [[#Fedele--2018|Fedele et al. (2018)]]

[[#Roberts--2012|Roberts et al. (2012)]] ; [[#Morris--2019|Morris et al. (2019)]] ; ( [[#Jones--2020|Jones et al., 2020]] )

|-
| Sustainable water management

| Mitigation, especially avoided emissions; reduced water demand; increased awareness about impacts of water consumption; decreased incidence of faecal–oral disease transmission; decreased use of drinking water for irrigation; reduced soil loss; increased groundwater retention; increased vegetation cover; increased food security and health and well-being; increased forage for livestock and amount of cultivated area; enhanced recreational areas

| [[#Spencer--2017|Spencer et al. (2017)]] ; Siraw et al. (2018); [[#Stanczuk-Galwiaczek--2018|Stanczuk-Galwiaczek et al. (2018)]]

|-
| Return to traditional land management practices (e.g., the Ngitili system)

| Mitigation, especially carbon sequestration; increased water availability for household and livestock use; increase in presence of edible and medicinal plants; regional economic growth; reduced land management conflicts; increased household income and access to education for children; improved access to wood fuel and reduced collection time for women; improved wildlife habitat

| Duguma et al. (2014)

|-
| REDD+ participation to maintain intact forest ecosystems

| Mitigation, especially carbon sequestration; improved air quality; water and soil conservation; slowed rate of vector-borne disease; improved mental well-being associated with cultural continuity; clean water; nutritional and spiritual value of forest-derived foods; protection from violence related to natural resource extraction

| [[#McElwee--2017|McElwee et al. (2017)]] ; [[#Spencer--2017|Spencer et al. (2017)]]

|-
| colspan="3"| Urban planning and design

|-
| Spatial planning—walkable neighbourhood design; strategic densification

| Mitigation, particularly avoided emissions; public health—increases in physical activity, reductions in air pollution and urban heat island effect

| Beiler et al. (2016); [[#Belanger--2016|Belanger et al. (2016)]]

|-
| Urban greening (e.g., tree planting; construction of stormwater retention areas; construction of green roofs and cool roofs; provision of rainwater barrels; pervious pavement materials)

| Mitigation, particularly avoided emissions; public health improvements—increases in physical activity, reductions in air and noise pollution, reduced urban heat island effect, improved mental health; urban flood risk management; water savings; energy savings

| [[#Samora-Arvela--2017|Samora-Arvela et al. (2017)]] ; [[#Vahmani--2017|Vahmani and Jones (2017)]] ; Newell et al. (2018); [[#Alves--2019|Alves et al. (2019)]] ; [[#De%20la%20Sota--2019|De la Sota et al. (2019)]]

|-
| Improved building efficiency standards

| Mitigation, particularly avoided emissions; improved air quality; reduced urban heat island; improved natural indoor lighting

| Barbosa et al. (2015); [[#Koski--2016|Koski and Siulagi (2016)]] ; [[#Balaban--2017|Balaban and Puppim de Oliveira (2017)]] ; Landauer et al. (2019)

|-
| Use of local building materials

| Mitigation, particularly avoided emissions

| [[#Lundgren-Kownacki--2018|Lundgren-Kownacki et al. (2018)]]

|}

<div id="16.3.3" class="h2-container"></div>

<span id="knowledge-gaps-in-observed-responses"></span>
=== 16.3.3 Knowledge Gaps in Observed Responses ===

<div id="h2-10-siblings" class="h2-siblings"></div>

'''''Many adaptation responses are not documented''''' , and reporting bias is a key challenge for assessment of observed responses. Evidence of absence (i.e., where no adaptations are occurring) is different from absence of evidence (where responses are occurring but are not documented), with implications for understanding trends in global responses.

'''''Adaptation is being reported differently across different sources of knowledge''''' . The peer-reviewed literature, for example, has been primarily reporting reactive adaptation at the individual, household and community levels, while the grey literature has been more mixed, reporting adaptation across governmental levels and civil society, with less focus on individuals and households ( [[#Ford--2015a|Ford et al., 2015a]] ; [[#Ford--2015|Ford and King, 2015]] ). Synthesis of impacts and responses within the private sector is particularly limited ( [[#Averchenkova--2016|Averchenkova et al., 2016]] ; [[#Minx--2017|Minx et al., 2017]] ), further suggesting that knowledge accumulation on climate responses has been particularly slow, and that more ''robust evidence'' synthesis is required to fill key knowledge gaps.

'''''The potential for under-reporting is most acute in the context of minorities and remote and marginalised groups''''' , who are often also the most affected by the impacts of climate change and least able to respond to, or benefit from, the responses to climate change ( [[#Araos--2021|Araos et al., 2021]] ). Deficits in reporting on impacts and responses are well recognised in the Global South, among vulnerable populations (e.g., women, socioeconomically disadvantaged, Indigenous, people living with disabilities) and within civil society (ibid.).

'''''There is growing support for more comprehensive and systematic approaches to assess adaptation progress''''' ( [[#Berrang-Ford--2015|Berrang-Ford et al., 2015]] ; [[#Ford--2015a|Ford et al., 2015a]] ; [[#Ford--2015|Ford and King, 2015]] ; [[#Ford--2016|Ford and Berrang-Ford, 2016]] ; [[#Biesbroek--2018|Biesbroek et al., 2018]] ). Since the AR5, there is increased recognition of the value of integrating diverse knowledge sources to fill knowledge gaps in observation of impacts and responses (Chapter 17; Cross-Chapter Box PROGRESS in Chapter 17). Van Bavel, for example, found that the involvement of local and diverse knowledge can improve the detection ( ''medium confidence'' ) and attribution ( ''medium confidence'' ) of health impacts, and improve the action ( ''high confidence'' ) ( [[#Van%20Bavel--2020|Van Bavel et al., 2020]] ).

'''''A new development since AR5, there is now growing evidence assessing progress on adaptation''''' across sectors, geographies and spatial scales. Uncertainty persists around what defines adaptation and how to measure it (Cross-Chapter Box FEASIB in Chapter 18, [[#UNEP--2021|UNEP, 2021]] ). As a result, most literature synthesising responses is based on documented or reported adaptations only, and is thus subject to substantial reporting bias.

'''''We document implemented adaptation-related responses that could directly reduce risk.''''' Adaptation ''as a process'' is more broadly covered in [[IPCC:Wg2:Chapter:Chapter-17|Chapter 17]] ( [[IPCC:Wg2:Chapter:Chapter-17#17.4.2|Section 17.4.2]] ), including risk management, decision making, planning, feasibility (see Cross-Chapter Box FEASIB in Chapter 18), legislation and learning. Here, we focus on a subset of adaptation activities: adaptation-related responses of species, ecosystems, and human societies that have been implemented and observed, and could directly reduce risk. We consider all adaptation-related responses to assumed, perceived or expected climate risk, regardless of whether or not impacts or risks have been formally attributed to climate change.

'''''We use the term ‘adaptation-related responses’, recognising that not all responses reduce risk.''''' While ‘adaptation’ implies risk reduction, we use the broader term ‘responses’ to reflect that responses may decrease risk, but in some cases may increase risk.

Given ''limited evidence'' to inform comprehensive global assessment of effectiveness and adequacy, we assess evidence that adaptation responses in human systems indicate transformational change. [[IPCC:Wg2:Chapter:Chapter-17|Chapter 17]] considers adaptation planning and governance, including adaptation solutions, success, and feasibility assessment (Cross-Chapter Box FEASIB in Chapter 18). It is not currently possible to conduct a comprehensive global assessment of effectiveness, adequacy or the contribution of adaptation-related responses to changing risk due to an absence of robust empirical literature (discussed further in Cross-Chapter Box PROGRESS in Chapter 17).

'''''In natural ecosystems or species, detectable changes can be considered as ‘impact’ or ‘response’.''''' The distinction between ‘observed impacts’ ( [[#16.2|Section 16.2]] ) and ‘observed responses’ ( [[#16.3|Section 16.3]] ) is not always clear. For example, autonomous distributional shifts in wild species induced by increasing temperatures (an observed impact) may reduce risk to the species (an autonomous adaptation response), but this process can be enhanced or supported by human intervention such as intentional changes in land use. Observed autonomous changes in natural ecosystems or species unsupported by human intervention are treated as impacts (see [[#16.2|Section 16.2]] ).

Adaptation-related responses are frequently motivated by a combination of climatic and non-climatic drivers, and interact with other transitions to affect risk. For societal responses, it is difficult to say whether they are triggered by observed or anticipated changes in climate, by non-climatic drivers or, as is the case in many societal responses, by a combination of all three. In the case of impacts, assessment typically focuses on detection and attribution ''vis à vis'' a counterfactual of no climate change. While there has been some effort to attribute reduced climate risk to adaptation-related responses ( [[#Toloo--2013a|Toloo et al., 2013a]] ; [[#Toloo--2013b|Toloo et al., 2013b]] ; [[#Hess--2018|Hess et al., 2018]] ; [[#Weinberger--2018|Weinberger et al., 2018]] ), in many cases this has not been feasible given difficulties in defining adaptation and empirically disentangling the contribution of intersecting social transitions and changing risks. Literature on adaptation-related response frequently draws on theories of change to assess the likely contribution of adaptations to changes in risk, including maladaptation and co-benefits.

<div id="cross-chapter-box-intereg" class="h2-container box-container"></div>

'''Cross-Chapter Box INTEREG | Inter-regional Flows of Risks and Responses to Risk'''
<div id="h2-23-siblings" class="h2-siblings"></div>

Authors: Birgit Bednar-Friedl (Austria, Chapter 13), Christopher Trisos (South Africa, Chapter 9), Laura Astigarraga (Uruguay, Chapter 12), Magnus Benzie (Sweden/UK), Aditi Mukherji (India, Chapter 4), Maarten Van Aalst (the Netherlands, Chapter 16)

'''Introduction'''
Our world today is characterised by a high degree of interconnectedness and globalisation which establish pathways for the transmission of climate-related risks across sectors and borders ( ''high confidence'' ) ( [[#Challinor--2018|Challinor et al., 2018]] ; [[#Hedlund--2018|Hedlund et al., 2018]] ). While the IPCC 5th Assessment Report (AR5) has pointed to this connection of risks across regions as ‘cross-regional phenomena’ ( [[#Hewitson--2014|Hewitson et al., 2014]] ), only a few countries so far have integrated inter-regional aspects into their climate change risks assessments ( [[#Liverman--2016|Liverman, 2016]] ; [[#Surminski--2016|Surminski et al., 2016]] ; [[#Adams--2020|Adams et al., 2020]] ), and adaptation is still framed as a predominantly national or local issue ( [[#Dzebo--2015|Dzebo and Stripple, 2015]] ; [[#Benzie--2019|Benzie and]] [[#Persson--2019|Persson, 2019]] ).

Inter-regional risks from climate change—also called cross-border, transboundary, transnational or indirect risks—are risks that are transmitted across borders (e.g., transboundary water use) and/or via teleconnections (e.g., supply chains, global food markets) ( [[#Moser--2015|Moser and Hart, 2015]] ). The risks can result from impacts, including compound or concurrent impacts, that cascade across several tiers, in ways that either diminish or escalate risk within international systems ( [[#Carter--2021|Carter et al., 2021]] ). Risk transmission may occur through trade and finance networks, flows of people (Cross-Chapter Box MIGRATE in Chapter 7), biophysical flows (natural resources such as water) and ecosystem connections. However, not only risks are transmitted across borders and systems; the adaptation response may also reduce risks at the origin of the risk, along the transmission channel or at the recipient of the risk ( [[#Carter--2021|Carter et al., 2021]] ). This cross-chapter box discusses four inter-regional risk channels (trade, finance, food and ecosystems) and how adaptation can govern these risks.

'''Trade'''
Most commodities are traded on global markets, and supply chains have become increasingly globalised. For instance, specialised industrial commodities such as semiconductors are geographically concentrated in a few countries ( [[#Challinor--2017|Challinor et al., 2017]] ; [[#Liverman--2016|Liverman, 2016]] ). When climatic events like flooding or heat affect the location of these extraction and production activities, economies are not only disrupted locally but also across borders and in distant countries ( ''high confidence'' ), as exemplified by the Thailand flood 2011 that led to a shortage of key inputs to the automotive and electronics industry not only in Thailand but also in Japan, Europe and the USA (Figure Cross-Chapter Box INTEREG.1). For many industrialised countries like the UK, Japan, the USA and the European Union, there is increasing evidence that the trade impacts of climate change are significant and can have substantial domestic impacts ( ''medium confidence'' ) ( [[#Nakano--2017|Nakano, 2017]] ; [[#Willner--2018|Willner et al., 2018]] , [[IPCC:Wg2:Chapter:Chapter-13#13.9.1|Section 13.9.1]] ; [[#Benzie--2019|Benzie and]] [[#Persson--2019|Persson, 2019]] ; [[#Knittel--2020|Knittel et al., 2020]] ). Enhanced trade can transmit risks across borders and thereby amplify damages ( [[#Wenz--2016|Wenz and Levermann, 2016]] ), but it can also increase resilience ( [[#Lim-Camacho--2017|Lim-Camacho et al., 2017]] ; [[#Willner--2018|Willner et al., 2018]] ).

[[File:47f8ef4f9654551d10cee3c0d177faf6 IPCC_AR6_WGII_Figure_16_Cross-Chapter_Box_INTEREG-1.png]]

'''Figure Cross-Chapter Box INTEREG.1 |''' '''Inter-regional climate risks: the example of the trade transmission channel, illustrated for the Thailand flood 2011 ( [[#Abe--2013|Abe and Ye, 2013]] ; [[#Haraguchi--2015|Haraguchi and Lall, 2015]] ; [[#Carter--2021|Carter et al., 2021]]''' '''.''' ''', 2021).'''

'''Finance'''
Climate risks can also spread through global financial markets ( [[#Mandel--2021|Mandel et al., 2021]] ). For the case of coastal and riverine flooding with low adaptation 2080 (RCP 8.5-SSP5), the financial system is projected to amplify direct losses by a factor of 2 (global average), but reach up to a factor of 10 for countries that are central financial hubs ( [[#Mandel--2021|Mandel et al., 2021]] , Figure 13.28). Indirect impacts may also arise through indirect effects on foreign direct investment, remittance flows and official development assistance ( [[#Hedlund--2018|Hedlund et al., 2018]] ).

'''Food'''
The global supply of agricultural products is concentrated to a few main breadbaskets ( [[#Bren%20d’Amour--2016|Bren d’Amour et al., 2016]] ; [[#Gaupp--2020|Gaupp et al., 2020]] , Chapter 5). For instance, Central and South America is one of the regions with the highest potential to increase food supplies to more densely populated regions in Asia, the Middle East and Europe (Chapter 12). The exports of agricultural commodities (coffee, bananas, sugar, soybean, corn, sugarcane, beef livestock) have gained importance in the past two decades as international trade and globalisation of markets have shaped the global agri-food system (Chapter 5).

The export of major food crops like wheat, maize and soybeans from many of the world’s water-scarce area—the Middle East, North Africa, parts of South Asia, North China Plains, southwest USA, Australia—to relatively water-abundant parts of the world carries a high virtual water content (the net volume of water embedded in trade) ( ''high confidence'' ) ( [[#Hoekstra--2012|Hoekstra and Mekonnen, 2012]] ; [[#Dalin--2017|Dalin et al., 2017]] ; [[#Zhao--2019|Zhao et al., 2019]] , Chapter 4). Both importing and exporting countries are exposed to transboundary risk transmission through climate change impacts on distant water resources ( [[#Sartori--2017|Sartori et al., 2017]] ; [[#Zhao--2019|Zhao et al., 2019]] ; [[#Ercin--2021|Ercin et al., 2021]] ). Climate change is projected to exacerbate risk and add new vulnerabilities for risk transmission ( ''medium confidence'' ). Rising atmospheric CO 2 concentration is projected to decrease water efficiency of growing maize and temperate cereal crops in parts of the USA, East and Mediterranean Europe, South Africa, Argentina, Australia and Southeast Asia, with important implications for future trade in food grains ( [[#Fader--2010|Fader et al., 2010]] ). By 2050 (SRES B2 scenario), virtual water importing countries in Africa and the Middle East may be exposed to imported water stress as they rely on imports of food grains from countries which have unsustainable water use ( [[#Sartori--2017|Sartori et al., 2017]] ). Until 2100, virtual trade in irrigation water is projected to almost triple (for SSP2-RCP6.5 scenarios) and the direction of virtual water flows is projected to reverse, with the currently exporting regions like South Asia becoming importers of virtual water ( [[#Graham--2020|Graham et al., 2020]] ). An additional 10–120% trade flow from water-abundant regions to water-scarce regions will be needed to sustain environmental flow requirements on a global scale by the end of the century ( [[#Pastor--2019|Pastor et al., 2019]] ). Exports of agricultural commodities contribute to deforestation, over-exploitation of natural resources and pollution, affecting the natural capital base and ecosystem services ( [[#Agarwala--2020|Agarwala and Coyle, 2020]] ; [[#Rabin--2020|Rabin et al., 2020]] , [[IPCC:Wg2:Chapter:Chapter-12#12.5.4|Section 12.5.4]] ).

'''Species and ecosystems'''
The spatial distributions of species on land and in the oceans are shifting due to climate change, with these changes projected to accelerate at higher levels of global warming ( [[#Pecl--2017|Pecl et al., 2017]] ). These ‘species on the move’ have large effects on ecosystems and human well-being, and present challenges for governance ( [[#Pecl--2017|Pecl et al., 2017]] ). For example, the number of transboundary fish stocks is projected to increase as key fisheries species are displaced by ocean warming ( [[#Pinsky--2018|Pinsky et al., 2018]] ). Conflict over shifting mackerel fisheries has already occurred between European countries ( [[#Spijkers--2017|Spijkers and Boonstra, 2017]] ), because few regulatory bodies have clear policies on shifting stocks; this leaves species open to unsustainable exploitation in new waters in the absence of regularly updated catch allocations to reflect changing stock distributions ( [[#Caddell--2018|Caddell, 2018]] ).

Human health will also be affected as vector-borne diseases such as malaria and dengue shift geographic distributions ( [[#Caminade--2014|Caminade et al., 2014]] ). There is also evidence that many warm-adapted invasive species, such as invasive freshwater cyanobacterium, have spread to higher latitudes because of climate change (Chapter 2).

'''Adaptation to inter-regional climate risks'''
Adaptation responses to reduce inter-regional risks can be implemented at a range of scales: at the point of the initial climate change impact (e.g., assistance for recovery after an extreme event, development of resilient infrastructure, climate-smart technologies for agriculture); at or along the pathway via which impacts are transmitted to the eventual recipient (e.g., trade diversification, re-routing of transport); in the recipient country (e.g., increasing storage to buffer supply disruptions), or by third parties (e.g., adaptation finance, technology transfer) ( [[#Bren%20d’Amour--2016|Bren d’Amour et al., 2016]] ; [[#Carter--2021|Carter et al., 2021]] ; [[#Talebian--2021|Talebian et al., 2021]] ). A knowledge gap exits on the need for, effectiveness of, and limits to adaptation under different socioeconomic and land use futures.

Due to regional and global interdependencies, climate resilience has a global, multi-level public good character ( [[#Banda--2018|Banda, 2018]] ). The benefits of adaptation are therefore shared beyond the places where adaptation is initially implemented. Conversely, adaptation may be successful at a local level while redistributing vulnerability elsewhere or even driving or exacerbating risks in other places ( [[#Atteridge--2018|Atteridge and Remling, 2018]] ). International cooperation is therefore needed to ensure that inter-regional effects are considered in adaptation and that adaptation efforts are coordinated to avoid maladaptation. However, regional- and global-scale governance of adaptation is only just beginning to emerge ( [[#Persson--2019|Persson, 2019]] ).

The United Nations Framework Convention on Climate Change (UNFCCC) Paris Agreement frames adaptation as a ‘global challenge’ (Article 7.2) and establishes the global goal on adaptation (Article 7.1), which provides space for dialogue between parties on the global-scale challenge of adaptation and the need for renewed political and financial investment in adaptation, including to address inter-regional effects ( [[#Benzie--2018|Benzie et al., 2018]] ).

National Adaptation Plans (NAPs) can evolve to consider inter-regional effects as well as domestic ones ( [[#Liverman--2016|Liverman, 2016]] ; [[#Surminski--2016|Surminski et al., 2016]] ; [[#European%20Environment--2020|European Environment, 2020]] ). Regional and international coordination of NAPs, coupled with building capacities and addressing existing knowledge gaps at the country level, can help to ensure that resources are oriented towards reducing inter-regional risks and building systemic resilience to climate change globally ( [[#Booth--2020|Booth et al., 2020]] ; [[#Wijenayake--2020|Wijenayake et al., 2020]] ).

Given the important role of private actors in managing inter-regional climate risks ( [[#Goldstein--2019|Goldstein et al., 2019]] ; [[#Tenggren--2019|Tenggren et al., 2019]] ), efforts will be needed to align public and private strategies for managing inter-regional climate risks to avoid maladaptation and ensure just and equitable adaptation at different scales ( [[#Talebian--2021|Talebian et al., 2021]] ).

Cross-Chapter Box INTEREG

Cross-Chapter Box INTEREG

Cross-Chapter Box INTEREG

<div id="16.4" class="h1-container"></div>

<span id="synthesis-of-limits-to-adaptation-across-natural-and-human-systems"></span>