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

=== 8.3.5 Economic and Non-economic Losses and Damages Due to Climate Change and their Implications for Livelihoods and Livelihood Shifts ===

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This section examines the intersections between L&amp;Ds and livelihood shifts. This requires an examination of the differentiated aspects of livelihoods. Understanding economic (e.g., loss of food crops, infrastructure, assets etc.) and non-economic losses (e.g., health, well-being, loss of place, agency) and their consequences for livelihoods is important that the intangible aspects become clearly visible and receive greater attention in loss assessments and in designing adaptation strategies and programmes. Figure 8.10 provides a summary of examples of observed impacts of climate hazards on economic and non-economic capital and the section assesses livelihood implications across regions. It shows examples of climate hazards attributed to climate change in studies since AR5, across a range of geographical sites for heatwaves, drought, hurricanes, and floods and non-economic L&amp;Ds. Figure 8.10 reveals examples of climate hazards attributed to climate change in studies since AR5 across a range of geographical sites for extreme and slow-onset events, such as heatwaves, drought, hurricanes and sea level rise. These are associated with non-economic L&amp;Ds. The figure underscores that non-economic L&amp;Ds lead to significant livelihood threats and livelihood changes. In addition, the limits of adaptation become evident (Chapter 16).

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'''Figure 8.10 |''' '''Examples of non-economic loss and damage associated with climate hazards attributed to climate change against a background of global vulnerability.''' Symbols with corresponding detail in the table show examples where non-economic losses have been documented. The figure is not exhaustive in terms of examples of extreme or slow-onset events or losses. It does not capture undocumented cases. It is an illustration of the relationship between unequivocal human-induced climate change and intangible losses (Adapted from Boyd et al., 2021).

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==== 8.3.5.1 Livelihood Shifts Resulting from L&amp;D from Climate Change ====

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While there are limited studies that view economic and NELD from climate change at a global scale of livelihood transformations there is ''robust evidence'' on the granular linkages, at community, national and regional levels, between losses, coping strategies and livelihood shifts. Across Africa, climate change is impacting crop yields and destroying homes, resulting in loss of infrastructure and leading to non-economic losses associated with involuntary migration and displacement ( [[#Olsson--2014|Olsson et al., 2014]] ), and loss of livestock and assets (see IPCC SR 1.5°C, Chapter 3, ( [[#Hoegh-Guldberg--2018|Hoegh-Guldberg et al., 2018]] ), resulting in long-term reduction in the capacity for agriculture and land management. For example, in March 2019 Tropical Cyclone Idai in Mozambique, Zimbabwe and Malawi led to substantial losses of agriculture, infrastructure, and access to aid and support, all of which contributed to significant displacement in each country ( [[#Fischel%20de%20Andrade--2021|Fischel de Andrade and de Lima Madureira, 2021]] ). Examples of livelihood impacts include livelihood shifts among Kenyan pastoralists to camel husbandry, resulting from household inequalities in assets and changes in relation to weakening of social norms of reciprocity and social cohesion ( [[#Volpato--2019|Volpato and King, 2019]] ).

Extreme climatic events pose serious disruptions to local livelihoods and asset bases, requiring people to reconstruct, transform and diversify livelihoods ( [[#Uddin--2021|Uddin et al., 2021]] ). Examples of livelihood shifts across Asia and Southeast Asia (e.g., Bangladesh, India, Philippines, Vietnam) include rural communities in coastal areas, urban settlements that are experiencing economic losses ( ''high confidence'' ) from, for example, crop failure and reduced access to fish, which contribute to non-economic losses associated with involuntary migration ( [[#Ghosh--2018|Ghosh, 2018]] ) and the malnutrition of children ( [[#Siddiqi--2011|Siddiqi et al., 2011]] ). For Bangladesh, Chiba et al. (2017) show a connection between mental stress and impacts to the fundamental capacity to sustain livelihoods, such as food and a place to live, due to severe damage to houses, homesteads, properties, livestock and crops, loss of family members and relatives, and anxiousness about securing employment and income in the future. In Bangladesh coastal communities experienced losses in livelihood assets due to Cyclones Sidr and Aila ( [[#Uddin--2021|Uddin et al., 2021]] ) and a significant number of cyclone victims were displaced from their homes by severe cyclones. People have had to change their occupations—both intra- and intersectorally—and are confronted by increased consumption and social costs. The study uncovered differences in impacts between occupations, such as farming and fishing; fishers changed their occupation post-disaster. The study also showed evidence that local people are learning to live with change and uncertainty by nurturing and combining various types of knowledge and social memory, generating diversified livelihood options and self-organising to enhance their resilience to future extreme weather events. In Bangladesh, [[#Ahmed--2019|Ahmed et al. (2019)]] found cyclones, riverbank erosion, salinity intrusion and floods negatively impacted people’s lives by reducing their livelihood options. Their study found that when there are limited adaptation strategies, many people turn to ‘illegal livelihoods’ included using fine mesh nets to collect shrimp fry in the rivers, as well as logging in the Sundarbans. These people include the poorest and vulnerable, and law enforcement only exacerbates their vulnerability. [[#Escarcha--2020|Escarcha et al. (2020)]] , studied impacts of typhoons, floods and droughts on crop production and effects on livelihoods of cash crop focused on rural villages in the Philippines. Their preliminary observations show a shift from crop to livestock production as a buffer activity to recover from crop losses. Farmers changed their farming activities as a multi-adaptive response driven by past experiences of climatic changes, farmers’ social relations, household capacity and resources available.

In Central Asia, the Sahel and South Asia, three global poverty hotspots, change impacts were shown to undermine traditional knowledge about livelihoods in ways that jeopardise future culture cohesion and sense of place ( [[#Tucker--2015|Tucker et al., 2015]] ). [[#Acosta--2016|Acosta et al. (2016)]] identified loss to productive sites in the Philippines with landslides destroying agriculture, leaving many farmers without livelihoods. Similarly, Beckman and Nguyen (2016) in Vietnam identified an example where communal dams had been destroyed in floods leading to lack of irrigation for communal sites and local loss of farmland for farming communities. [[#Chandra--2017|Chandra et al. (2017)]] identified the vicious cycle between declining agricultural production and conditions of soil erosion due to floods and droughts resulting in decreased crop fertility to productive sites with implications for decline in crop yields, loss of crops and of livelihood assets. Climate change-related extreme weather events, such as typhoons, floods, and droughts, can have detrimental impacts on crop production ( ''high confidence'' ) and in the Philippines and Pakistan have significantly affected the livelihoods of cash crop-focused rural villages ( [[#Escarcha--2020|Escarcha et al., 2020]] ; [[#Jamshed--2020b|Jamshed et al., 2020b]] ). There is an emerging shift from crop to livestock production as a buffer activity to recover from crop losses ( [[IPCC:Wg2:Chapter:Chapter-5#5.10.4|Section 5.10.4]] ; [[#Jamshed--2017|Jamshed et al., 2017]] ; [[#Escarcha--2020|Escarcha et al., 2020]] ). As with many examples of livelihood shifts, the viability of the shifts in the long term under climate change have yet to be assessed.

In Africa, many communities already experience drought- and flood-related disasters ( ''high confidence'' ) such as those that negatively impact livelihoods and assets in the Muzarabani district of Zimbabwe ( [[#Mavhura--2017|Mavhura, 2017]] ). In Muzarabani community has revived and developed new livelihood strategies to manage risks, including local informal safety nets, local farming practices and the traditional flood-proofing structures. Food security and agriculture productivity are examples of livelihood resources most at risk to climate hazards (see Figure 8.2) ( ''high confidence'' ). An illustration of such risks to cocoa farmers in Ghana includes increased incidences of crop pests and diseases, wilting of cocoa leaves, high mortality of cocoa seedlings which affected expansion and farm rehabilitation, and wilting of cherelles resulting in losses of crop yield. An illustration of livelihood shifts resulting from losses is of farmers shifting to cereals due to the unpredictable climatic patterns and the shortened duration of rainfall. Yet, insecurity with storage, supply chains and low returns from cereal production, coupled with land scarcity in the Western region, have resulted in a return to cocoa production ( [[#Asante--2017|Asante et al., 2017]] ).

Research from Australia shows complex linkages between the impacts of drought on livelihood income, health and cultural heritage, increasing risk of heat stroke, and possibly a link to suicide among male farmers ( [[#Alston--2012|Alston, 2012]] ; [[#Hanigan--2012|Hanigan et al., 2012]] ; [[#Marshall--2019|Marshall et al., 2019]] ). The link between agricultural losses and suicides has also been noted in South Asia, including India ( [[#Carleton--2017|Carleton, 2017]] ). Livelihoods are shifting with impacts to well-being, as noted by ( [[#Evans--2016|Evans et al., 2016]] ), who showed connections between loss of fishery productivity and impact on tourism sector livelihoods in the Great Barrier Reef region. In Europe, losses to Indigenous Peoples are associated with loss of well-being of Sami communities and has forced livelihood shifts from reindeer herding due to loss of ecosystems to support the animals ( [[#Persson--2017|Persson et al., 2017]] ; [[#Jaakkola--2018|Jaakkola et al., 2018]] ). Traditional pastoralist systems are also greatly impacted by cumulative dual challenges of encroachment of other land users and by climate change. Traditional Sami reindeer herding strategies are still practiced, but the rapidly changing environmental circumstances are forcing herders into uncharted territories where traditional strategies and the transmission of knowledge between generations may be of limited use. For example, rotational grazing is no longer possible as all pastures are being used, and changes in climate result in unpredictable weather patterns unknown to earlier generations ( [[#Axelsson-Linkowski--2020|Axelsson-Linkowski et al., 2020]] ). These examples show that there are complex factors underpinning the linking L&amp;D and shifting livelihoods. Moreover, there are significant challenges to undertaking a shift to secure alternative livelihoods.

Linkages between losses, coping strategies and livelihood shifts in small islands (e.g., in the Pacific region, Kiribati and Tuvalu, and in the Caribbean, the Bahamas) shed light on impacted low-income households. For example, farmers have experienced extensive damage to homes and loss of infrastructure, and experience lack of migration opportunities ( [[#Curtain--2019|Curtain and Dornan, 2019]] ). Evidence is growing that there is also significant loss of cultural heritage in resettlement ( [[#Barnett--2012|Barnett and O’neill, 2012]] ), evidence from small islands’ displaced communities suggests that resettlement can have impacts on sense of place, identity and social fabric, a theme highly relevant to loss, coping and adapting livelihoods, and not only restricted to small islands ( [[#McNamara--2021b|McNamara et al., 2021b]] ). Roberts (2015) identified loss of communal sites in Kiribati. It is predicted that, by 2050, up to 80% of the land on the island of Buariki and 50% of the land on Bikenibeu may be completely inundated and these effects will result in significant loss of livelihoods and displacement. Throughout the Caribbean, evidence indicates that there will be an overall reduction in the area of land suitable for crop cultivation, as the region’s climate gets progressively warmer and as rainfall becomes more variable ( [[#Rhiney--2016|Rhiney et al., 2016]] ).

The multiple shocks of extreme events reduce crop yields, destroy homes, and lead to loss of infrastructure and displacement ( ''high confidence'' ). These are experienced in South and North America. For example, in Peru, glacial outbursts have led to loss of livelihoods ( [[#Drenkhan--2019|Drenkhan et al., 2019]] ). People use a range of coping and adaptation strategies to deal with hazards where they live, such as shifting livelihood activities, inputs or production areas. However, traditional techniques are increasingly failing due to changing weather patterns. Across Peru, findings demonstrate that people use temporary and permanent migration among their many coping and adaptation strategies. Hazards related to water excess have been the key force in destroying homes and driving displacement in Peru. In contrast, studies demonstrate that water scarcity also threatens livelihoods and thereby influences migration in Peru. While non-climatic reasons for moving dominate migrants’ motivations in many areas of Peru, water-related climatic drivers of migration are becoming increasingly relevant ( [[#Wrathall--2014|Wrathall et al., 2014]] ). Peru’s smallholder farmers and urban poor are not responsible for the climate crisis, yet their lives and cultural heritage are being increasingly jeopardised by its effects, making improvements in governance an imperative for Peru ( [[#Bergmann--2021|Bergmann et al., 2021]] ). Another area of significance is coffee production in Brazil, where the majority of Brazilian coffee farms are operated by smallholders, producers with relatively small properties, who are mostly reliant on family labour ( [[#Koh--2020|Koh et al., 2020]] ). In the USA (e.g., New Orleans and Puerto Rico), people have lost livelihoods due to displaced households and destroyed homes, leading to loss of income, as well as loss of social networks and family networks and loss of cultural heritage. For example, impacts of Hurricane Katrina have led to people being displaced from their employment, many evacuees had to relocate to new areas, which disrupted their social networks and placed them in unfamiliar labour markets, resulting in mental health challenges ( [[#Palinkas--2020|Palinkas, 2020]] ). There has also been a ‘climate gentrification’ in parts of New Orleans ( [[#Aune--2020|Aune et al., 2020]] ). Many of those who returned to their pre-Katrina areas had to deal with extensive damage to their homes and to public infrastructure.

In summary, across regions there is an increasing number of examples of observed economic and NELD from climate change. Adaptation measures need to better incorporate actions to tackle the burgeoning negative social, psychological and well-being impacts of climate change ( [[#Barnett--2016|Barnett et al., 2016]] ; Box 8.5). At present, losses from climate change are potentially growing faster than adaptation measures across the globe. It is still uncertain how economic and non-economic losses trigger successful or viable new climate-related livelihood transitions for the poor and people or groups in vulnerable situations in the future (see Sections 8.4.4; 8.4.5). In all likelihoods, economic losses from climate hazards (e.g., drought) will be compounded by many factors including COVID-19 and other vulnerability drivers. For instance, globally, small-scale coffee producers have been destabilised by COVID-19, but also because of a history of recurrent (climate) shocks and structural inequalities, and may have to shift into alternative livelihoods ( [[#Guido--2020|Guido et al., 2020]] ). Coastal communities in Vanuatu have been impacted in the immediate period after COVID-19 showing changes in village populations, loss of cash income and difficulties in accessing food, and have experienced shifting pressures on particular resources and habitats ( [[#Steenbergen--2020|Steenbergen et al., 2020]] ). This trend poses real challenges to equity and sustainability.

In summary, this section has moved beyond the IPCC WGII AR5 in laying out structural elements of vulnerability and climate-related vulnerability hotspots globally, such as poverty, lack of access to basic services, gender inequality and undernourishment. The assessment provides new quantitative evidence about the global spatial distribution of systemic human vulnerability and therewith underscores that various hotspots of countries classified as having very high or high vulnerability emerge in regional clusters. In addition, the number of people living in very highly and highly vulnerable country contexts is significantly higher in some assessments, with even twice as many as the number of people living in countries classified as having low and very low vulnerability. The evidence suggests that statistically relevant differences in fatalities per hazard event are not just a product of the hazard event, but also strongly linked with the level of vulnerability of the region or community exposed. The assessment of non-economic losses has also received little attention in past IPCC Assessment Reports, therefore this section has provided new insights on how (next to measurable economic losses) non-economic losses and intangible losses emerge. These non-economic losses represent an important dimension of societal impacts of climate change that has not sufficiently captured so far within standard damage or post-disaster assessments. Finally, the section provides evidence about the existing adaptation gap in terms of differential vulnerabilities and various non-economic losses already experienced.

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'''Box 8.5 | Western Cape Region in South Africa: drought challenges to equity and sustainability'''
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'''Nature of the drought'''
Between 2015 and 2017, the Western Cape region experienced an unprecedented three consecutive years of below average rainfall, leading to acute water shortages, most prominently in the city of Cape Town ( [[#Sousa--2018|Sousa et al., 2018]] ). Anthropogenic climate change made the drought five to six times more ''likely'' ( [[#Pascale--2020|Pascale et al., 2020]] ; see also AR6 WGI Chapter 10, [[IPCC:Wg2:Chapter:Chapter-10#10.6.2|Section 10.6.2]] ). The severity of the drought presented new challenges to the existing management and governance capacity to ensure equitable and sustainable water service delivery. The city’s water supply infrastructure and demand management practice were unprepared for the ‘rare and severe’ event of three consecutive years of below average rainfall ( [[#Wolski--2018|Wolski, 2018]] ; [[#Muller--2019|Muller, 2019]] ). Despite a potential total storage volume of about 900,000 Ml of water (enough water for around a year and a half of normal usage, after taking evaporation into account), Cape Town’s reservoirs fell from 97% full in 2014 to less than 20% in May 2018 ( [[#Ouweneel--2020|Ouweneel et al., 2020]] ; [[#Cole--2021|Cole et al., 2021]] ). The drought saw residents queue for water as restrictions were imposed together with threats of closure of water provision to households ( [[#Sorensen--2017|Sorensen, 2017]] ; [[#Scheba--2018|Scheba and Millington, 2018]] ). Poor communication in the early stages of the drought ( [[#Hellberg--2020|Hellberg, 2020]] ) and a lack of trust in the administration contributed to a near-panic situation at the threat of ‘Day Zero’ as dams almost ran dry in the first half of 2018 ( [[#Enqvist--2019|Enqvist and Ziervogel, 2019]] ; [[#Simpson--2020c|Simpson et al., 2020c]] ). ‘Day Zero’ was avoided largely through public response, water demand management and the 2018 winter rains ( [[#Sorensen--2017|Sorensen, 2017]] ; [[#Booysen--2019a|Booysen et al., 2019a]] ; [[#Muller--2019|Muller, 2019]] ; [[#Rodina--2019b|Rodina, 2019b]] ; [[#Matikinca--2020|Matikinca et al., 2020]] ). At a household level, responses to the drought showed everyday residents can display unprecedented degrees of resilience ( [[#Sorensen--2017|Sorensen, 2017]] ), including behavioural and attitudinal shifts and technological innovation across the full socioeconomic spectrum ( [[#Ouweneel--2020|Ouweneel et al., 2020]] ). But the private nature of some of these responses extended existing inequality in water access through privileged forms of ‘gated adaptation’ by elites which conventional water governance arrangements were unprepared for ( [[#Simpson--2019b|Simpson et al., 2019b]] ; [[#Simpson--2020a|Simpson et al., 2020a]] ).

These ‘climate gating’ actions, such as drilling boreholes, secured water access for high-income households and companies, but excluded a large proportion of Cape Town’s population who could not afford such private technologies ( [[#Simpson--2019a|Simpson et al., 2019a]] ; [[#Simpson--2020b|Simpson et al., 2020b]] ). These responses were unanticipated by the city administration and compounded fiscal challenges faced by the municipality which could no longer use revenues from high-consumption households to cross-subsidise water for low-income households ( [[#Simpson--2020a|Simpson et al., 2020a]] ). This shift threatened to undermine the sustainability of the municipal fiscus and general water access ( Box 9.8; [[#Simpson--2019a|Simpson et al., 2019a]] ; [[#Simpson--2020a|Simpson et al., 2020a]] ). In order to recover losses, municipal water tariffs for consumers were raised by 26% in 2018 ( [[#Muller--2018|Muller, 2018]] ; [[#Simpson--2019a|Simpson et al., 2019a]] ). In addition to a decline in tourism, median estimations of the overall economic impact of the drought indicate loss of 27.6 billion South African Rand (USD 1.7 billion) translating into 64,810 job losses in the Western Cape, with Cape Town accounting for approximately half of those job losses ( [[#DEDAT--2018|DEDAT, 2018]] ). This had a disproportionate impact on unskilled and semi-skilled workers, particularly for those from low- and middle-income households ( [[#DEDAT--2018|DEDAT, 2018]] ). The drought also exacerbated the potential for sanitation health risks of the urban poor where tens of thousands of people lack access to safely managed sanitation facilities ( [[#Enqvist--2019|Enqvist and Ziervogel, 2019]] ).

The Day Zero Disaster Plan included prioritising and protecting the poor and most vulnerable communities where critical infrastructure and facilities and vulnerable and informal residential areas would remain connected while higher-income residential areas would be cut off ( [[#Cole--2021|Cole et al., 2021]] ). Yet it is important to recognise that pre-existing deficiencies in service delivery meant water access for the urban poor did not change as significantly during the drought, particularly those in informal settlements who collect water from standpipes ( [[#Enqvist--2019|Enqvist and Ziervogel, 2019]] ; [[#Matikinca--2020|Matikinca et al., 2020]] ). For these communities, the negative economic impact of the drought was compounded by the unintended consequences of demand management regulation emanating from the drought response. South Africa ostensibly ensures a constitutional right to water, regardless of ability to pay ( [[#Rodina--2016|Rodina, 2016]] ), 58). Since 2018, however, as a consequence of new water tariffs instituted during the drought, Cape Town residents now have had to ‘prove their poverty’ in order to register as indigent households and access their water right ( [[#Scheba--2018|Scheba and Millington, 2018]] ). Further, since 2007 and with increasing effect during the drought, the municipality has installed approximately 250,000 water management devices as a credit control and, during the drought, also a consumption control measure. As these have been largely installed in low-income homes, this control measure disproportionately affected poor households ( [[#Scheba--2018|Scheba and Millington, 2018]] ; [[#Enqvist--2019|Enqvist and Ziervogel, 2019]] ).

'''Lessons from the drought'''
The effect of communication at different stages in the drought highlights how critical information needs to be provided in a format and language that empowers people to act appropriately and collaboratively ( [[#Muller--2019|Muller, 2019]] ; [[#Rodina--2019b|Rodina, 2019b]] ; [[#Rodina--2019a|Rodina, 2019a]] ). Getting political decisions made in a timely fashion and with public support is a long-standing challenge for managers of urban water supplies ( [[#Muller--2017|Muller, 2017]] ; [[#Muller--2019|Muller, 2019]] ). In Cape Town this was further challenged by dependence on a malfunctioning national department for water supply planning, poor coordination between the spheres of government—city, provincial and national governments—and poor collaboration between political representatives, technical experts and strategic managers ( [[#Madonsela--2019|Madonsela et al., 2019]] ; [[#Nhamo--2019|Nhamo and Agyepong, 2019]] ; [[#Rodina--2019a|Rodina, 2019a]] ; [[#Ziervogel--2019b|Ziervogel, 2019b]] ). This highlights the need to strengthen partnerships and collaboration across sectors and scales of governance ( [[#Ziervogel--2019a|Ziervogel, 2019a]] ), including the adoption of a ‘whole-of-society’ approach that recognises the contributions of non-state actors as adopted in the Cape Town Resilience Strategy ( [[#CoCT--2019|CoCT, 2019]] ; [[#Simpson--2020a|Simpson et al., 2020a]] ). Experienced yet inflexible water management initially operated at a distance from politicians and their citizens. There was limited knowledge and capacity in how various municipal departments thought about risk, exposure and vulnerability of Cape Town’s highly differentiated population ( [[#Mukheibir--2007|Mukheibir and Ziervogel, 2007]] ; [[#Pasquini--2015|Pasquini et al., 2015]] ; [[#Madonsela--2019|Madonsela et al., 2019]] ). In the later stages of the drought, Cape Town’s water management department was able to work collaboratively across different departments and with politicians to implement responses.

The Cape Town case highlights how disaster planning for slow-onset city-wide shocks will be become increasingly important to safeguard equity and sustainability across African cities ( [[#Cole--2021|Cole et al., 2021]] ). It demonstrates the importance of integrating state and non-state responses to climate change in municipal adaptation and disaster planning ( [[#Booysen--2019a|Booysen et al., 2019a]] ; [[#Booysen--2019b|Booysen et al., 2019b]] ; [[#Simpson--2020a|Simpson et al., 2020a]] ), particularly for responses with unintended consequences. Further, water tariff models need to be flexible enough and have built-in redundancies in order to prioritise the needs of the urban poor and ensure climate responses do not disproportionately affect low-income groups and deepen existing inequalities ( [[#Scheba--2018|Scheba and Millington, 2018]] ; [[#Enqvist--2019|Enqvist and Ziervogel, 2019]] ; [[#Simpson--2019b|Simpson et al., 2019b]] ). Systems and relationships of mutual accountability can also build more effective water management between spheres of government and enhance horizontal collaboration between municipal departments and non-state entities ( [[#Ziervogel--2019b|Ziervogel, 2019b]] ; [[#Ziervogel--2019a|Ziervogel, 2019a]] ).

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Box 8.5

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