Editing IPCC:AR6/WGII/Chapter-9 (section)

== 9.1 Introduction ==

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=== 9.1.1 Point of Departure ===

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This chapter assesses the scientific evidence on observed and projected climate change impacts, vulnerability and adaptation options in Africa. The assessment refers to five African sub-regions—north, west, central, east and southern—closely following the African Union (AU), but including Mauritania in west Africa and Sudan in north Africa because much of the literature assessed places these countries in these regions (Figure 9.1). Madagascar and other island states are addressed in Chapter 15.

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[[File:e420a7f86dddcb25cd88f179d2ed853b IPCC_AR6_WGII_Figure_9_001.png]]

'''Figure 9.1 |''' '''The''' '''five regions of Africa used in this chapter, also showing estimated population density in 2019.''' The population of Africa was estimated at 1.312 billion for 2020, which is about 17% of the world’s population but this is projected to grow to around 40% of the world’s population by 2100 ( [[#UNDESA--2019a|UNDESA, 2019a]] ). Although 57% of the African population currently live in rural areas (43% urban), Africa is the most rapidly urbanising region globally and is projected to transition to a majority urban population in the 2030s, with a 60% urban population by 2050 ( [[#UNDESA--2019b|UNDESA, 2019b]] ). The 2019 gross domestic product (GDP) per capita in constant 2010 USD averaged USD 2250 across the 43 countries reporting data, ranging from USD 202 (Burundi) to USD 8840 (Gabon), with 40% of the population of sub-Saharan Africa living below the international poverty line of USD 1.90 per day in 2018 ( [[#World%20Bank--2019|World Bank, 2019]] ). The highest life expectancy at birth is 67 (Botswana and Senegal) and the lowest is 52 (Central African Republic) [[#World%20Bank--2019|World Bank (2019)]] . Grid-cell population density data for mapping are from [[#Tatem--2017|Tatem (2017)]] ; [[#WorldPop--2021|WorldPop (2021)]] .

The contribution of Africa is among the lowest of historical greenhouse gas (GHG) emissions responsible for human-induced climate change and it has the lowest per capita GHG emissions of all regions currently ( ''high confidence'' ) (Figure 9.2). Yet Africa has already experienced widespread impacts from human-induced climate change ( ''high confidence'' ) (Figure 9.2; see Table 9.1).

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[[File:98f0b7bdf883e42d0fe77c1af99f8e16 IPCC_AR6_WGII_Figure_9_002.png]]

'''Figure 9.2 |''' '''Historical greenhouse gas (GHG) emission trends for Africa compared to other world regions:'''

'''(a)''' Per person GHG emissions by region and their change from 1990 to 2019 (circles represent countries, diamonds represent the region average).

'''(b)''' Total GHG emissions by region since 1990.

'''(c)''' The total GHG emissions in 1990 and 2019 for the 15 highest emitting countries within Africa.

'''(d)''' Total emissions in Africa since 1990, broken down by GHG (left) and sector (right). Methane and CO 2 emissions comprise an almost equal share of GHG emissions in Africa, with the largest emissions sectors being energy and agriculture ( [[#Crippa--2021|Crippa et al., 2021]] ). Agriculture emissions in panel (d) do not include land use, land use change and forestry (LULUCF CO 2 ). One-hundred-year global warming potentials consistent with WGI estimates are used. Emissions data are from [[#Crippa--2021|Crippa et al. (2021)]] , compiled in Working Group III (WGIII) Chapter 2.

Since AR5 (Assessment Report 5), there have been notable policy changes in Africa and globally. The Paris Agreement, 2030 Sustainable Development Goals (SDGs), the Sendai Framework and Agenda 2063 emphasise interlinked aims to protect the planet, reduce disaster risk, end poverty and ensure all people enjoy peace and prosperity ( [[#AU--2015|AU, 2015]] ; [[#UNFCCC%20Paris%20Agreement--2015|UNFCCC Paris Agreement, 2015]] ; [[#UNISDR%20Sendai%20Framework--2015|UNISDR Sendai Framework, 2015]] ; [[#United%20Nations%20General%20Assembly--2015|United Nations General Assembly, 2015]] ). To match these interlinked ambitions, this chapter assesses risks and response options both for individual sectors and cross-sectorally to assess how risks can compound and cascade across sectors, as well as the potential feasibility and effectiveness, co-benefits and trade-offs and potential for maladaptation from response options ( [[#Simpson--2021b|Simpson et al., 2021b]] ; [[#Williams--2021|Williams et al., 2021]] ).

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=== 9.1.2 Major Conclusions from Previous Assessments ===

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Based on an analysis of 1022 mentions of Africa or African countries across the three AR6 Special Reports, the following main conclusions emerged.

* Hot days, hot nights and heatwaves have become more frequent; heatwaves have also become longer ( ''high confidence'' ). Drying is projected particularly for west and southwestern Africa ( ''high confidence'' ) ( [[#IPCC--2018c|IPCC, 2018c]] ; [[#Shukla--2019|Shukla et al., 2019]] ).
* Climate change is contributing to land degradation, loss of biodiversity, bush encroachment and spread of pests and invasive species ( [[#IPCC--2018b|IPCC, 2018b]] ; [[#IPCC--2019a|IPCC, 2019a]] ; [[#IPCC--2019b|IPCC, 2019b]] ).
* Climate change has already reduced food security through losses in crop yields, rangelands, livestock and fisheries, deterioration in food nutritional quality, access and distribution, and price spikes. Risks to crop yields are substantially less at 1.5°C compared with 2°C of global warming, with a large reduction in maize cropping areas projected even for 1.5°C, as well as reduced fisheries catch potential ( [[#IPCC--2018b|IPCC, 2018b]] ; [[#IPCC--2019b|IPCC, 2019b]] ; [[#IPCC--2019a|IPCC, 2019a]] ).
* Increased deaths from undernutrition, malaria, diarrhoea, heat stress and diseases related to exposure to dust, fire smoke and other air pollutants are projected from further warming ( [[#IPCC--2018c|IPCC, 2018c]] ; [[#Shukla--2019|Shukla et al., 2019]] ).
* The largest reductions in economic growth for an increase from 1.5°C to 2°C of global warming are projected for low- and middle-income countries, including in Africa ( [[#IPCC--2018c|IPCC, 2018c]] ).
* Climate change interacts with multi-dimensional poverty, among other vulnerabilities. Africa is projected to bear an increasing proportion of the global exposed and vulnerable population at 2°C and 3°C of global warming ( [[#IPCC--2018c|IPCC, 2018c]] ).
* Poverty and limited financing continue to undermine adaptive capacity, particularly in rapidly growing African cities ( [[#Shukla--2019|Shukla et al., 2019]] ).
* Large-scale afforestation and bioenergy can reduce food availability and ecosystem health ( [[#IPCC--2018c|IPCC, 2018c]] ; [[#IPCC--2019a|IPCC, 2019a]] ).
* Transitioning to renewable energy would reduce reliance on wood fuel and charcoal, especially in urban areas, with co-benefits including reduced deforestation, desertification, fire risk and improved indoor air quality, local development and agricultural yield ( [[#Shukla--2019|Shukla et al., 2019]] ).
* Sustainable use of biodiversity, conservation agriculture, reduced deforestation, land and watershed restoration, rainwater harvesting and well-planned reforestation can have multiple benefits for adaptation and mitigation, including water security, food security, biodiversity, soil conservation and local surface cooling ( [[#IPBES--2018|IPBES, 2018]] ; [[#Shukla--2019|Shukla et al., 2019]] ).
* Climate resilience can be enhanced through improvements to early warning systems, insurance, investment in safety nets, secure land tenure, transport infrastructure, communication, access to information and investments in education and strengthened local governance ( [[#Shukla--2019|Shukla et al., 2019]] ).
* Scenarios of socio-environmental change are under-used in decision making in Africa ( [[#IPBES--2018|IPBES, 2018]] ).
* Africa’s rich biodiversity together with a wealth of Indigenous Knowledge and Local Knowledge (IKLK) is a key strategic asset for sustainable development ( [[#IPBES--2018|IPBES, 2018]] ).

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=== 9.1.3 What’s New on Africa in AR6? ===

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# Increased confidence in observed and projected changes in climate hazards, including heat and precipitation
# Increased regional, national and sub-national observed impacts and projected risks
# Loss and damage assessment
# Increased quantification of projected risks at 1.5°C, 2°C, 3°C and 4°C of global warming (see [[#9.2|Section 9.2]] ; Figure 9.6)
# Improved assessment of sea level rise risk (Sections 9.9; 9.12)
# Increased quantification of risk across all sectors assessed
# Expanded assessment of adaptation feasibility and effectiveness and limits to adaptation (see Figure 9.7)
# Assessment of adaptation finance ( [[#9.4.1|Section 9.4.1]] )
# Increased assessment of how climate risk and adaptation and mitigation response options are interlinked across multiple key development sectors ( [[#9.4.3|Section 9.4.3]] ; Boxes 9.4; 9.5).

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=== 9.1.4 Climate Change Impacts Across Africa ===

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In many parts of southern, east and west Africa, temperature or precipitation trends since the 1950s are attributable to human-caused climate change and several studies document the impacts of these climate trends on human and natural systems ( ''high confidence'' ) (Figure 9.5; Sections 9.5.6; 9.5.7). Nevertheless, research into attribution of trends to human-caused climate change or climate impacts remains scarce for multiple regions, especially in north and central Africa. This illustrates an ‘attribution gap’ where robust evidence for attributable impacts is twice as prevalent in high- compared to low-income countries globally ( [[#Callaghan--2021|Callaghan et al., 2021]] ). Most studies on climate impacts in Africa have focused on terrestrial ecosystems or water, with fewer on marine ecosystems, agriculture, migration, and health and well-being ( [[#Callaghan--2021|Callaghan et al., 2021]] ). Specific factors driving these knowledge gaps include limited data collection, data access and research funding for African researchers (see next section).

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=== 9.1.5 Climate Data and Research Gaps Across Africa ===

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Since AR5, there have been rapid advances in climate impact research due to increased computing power, data access and new developments in statistical analysis ( [[#Carleton--2016|Carleton and Hsiang, 2016]] ). However, sparse and intermittent weather station data limit attribution of climate trends to human-caused climate change for large areas of Africa, especially for precipitation and extreme events, and hinder more accurate climate change projections ( [[#9.5.2|Section 9.5.2]] ; Figure 9.5; [[#Otto--2020|Otto et al., 2020]] ). Outside of South Africa and Kenya, digitally accessible data on biodiversity is limited ( [[#Meyer--2015|Meyer et al., 2015]] ). Lack of comprehensive socioeconomic data also limits researchers’ ability to predict climate change impacts. Ideally, multiple surveys over time are needed to identify effects of a location’s changing climate on changing socioeconomic conditions. Twenty-five African countries conducted only one nationally representative survey that could be used to construct measures of poverty during 2000–2010 and 14 conducted none over this period ( [[#Jean--2016|Jean et al., 2016]] ). Because of these challenges, much of what is known about climate impacts and risks in Africa relies on evidence from global studies that use data largely from outside Africa (e.g., [[#Zhao--2021|Zhao et al., 2021]] ). These studies generate estimates of average impacts across the globe, but may not have the statistical power to distinguish whether African nations display differential vulnerability, exposure or adaptive capacity. In sections of this chapter, we have relied, when necessary, on such studies, as they often provide best available evidence for Africa. Increasing data coverage and availability would increase the ability to discern important differences in risk both among and within African countries.

Climate-related research in Africa faces severe funding constraints with unequal funding relationships between countries and with research partners in Europe and North America ( ''high confidence'' ). Based on analysis of over 4 million research grants from 521 funding organisations globally, it is estimated that, from 1990–2020, USD 1.26 billion funded Africa-related research on climate impacts, mitigation and adaptation. This represents only 3.8% of global funding for climate-related research—a figure incommensurate with Africa’s high vulnerability to climate change (see Figure 9.3; Box 9.1; [[IPCC:Wg2:Chapter:Chapter-8|Chapter 8]] Figure 8.6; [[#Overland--2021|Overland et al., 2021]] ). Almost all funding for Africa-related climate research originates outside Africa and goes to research institutions outside Africa ( [[#Blicharska--2017|Blicharska et al., 2017]] ; [[#Bendana--2019|Bendana, 2019]] ; [[#Siders--2019|Siders, 2019]] ; [[#Overland--2021|Overland et al., 2021]] ). From 1990–2020, 78% of funding for Africa-related climate research flowed to institutions in Europe and the USA—only 14.5% flowed to institutions in Africa (Figure 9.3; [[#Overland--2021|Overland et al., 2021]] ). Kenya (2.3% of total funding) and South Africa (2.2%) are the only African countries among the top 10 countries in the world in terms of hosting institutions receiving funding for climate-related research on Africa ( [[#Overland--2021|Overland et al., 2021]] ).

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[[File:a947084afe574b22a2fb01d06d073826 IPCC_AR6_WGII_Figure_9_003.png]]

'''Figure 9.3 |''' '''Climate-related research on Africa has received a very small percentage (around 4%) of global climate research funding (a).'''

'''(b)''' As a percentage of all research funding allocated to a region, climate research has, since 2010, made up 5% of Africa-related research funding compared to a 3% share for climate research in global research funding.

'''(c)''' Major funders are the UK, EU, USA, Germany and Sweden.

'''(d)''' Most funding for climate-related research on Africa flows to institutions based in Europe and the USA. Funding comes mainly from government organisations with private philanthropy providing only around 1% ( [[#Overland--2021|Overland et al., 2021]] ).

'''(e)''' Africa-related climate research funding focuses mostly on food systems, ecosystems and freshwater, while health, poverty, security and conflict, and urban areas have received the least.

'''(f)''' Research on climate mitigation received only 17% of funding while climate impacts and adaptation each received 40%. A greater proportion of Africa-focused climate funding has gone to social sciences and humanities (28%) than is the case globally (12%) ( [[#Overland--2021|Overland et al., 2021]] ). Data are from an analysis of 4,458,719 research grants in the Dimensions database with a combined value of USD 1.51 trillion awarded by 521 funding organisations globally (Overland et al. 2021). The Dimensions database is the world’s largest database on research funding flows (Overland et al. 2021). It draws on official data from all major funding organisations in the world, mainly government research councils or similar institutions. Note: The South African National Research Foundation is the only African research funding body that is sufficiently large to be included in Dimensions.

These unequal funding relations influence inequalities in climate-related research design, participation and dissemination between African researchers and researchers from high-income countries outside Africa, in ways that can reduce adaptive capacity in Africa ( ''very high confidence'' ). Those empowered to shape research agendas can shape research answers: climate research agendas, skills gaps and eligible researchers are frequently defined by funding agencies, often from a global north perspective ( [[#Vincent--2020a|Vincent et al., 2020a]] ). Larger funding allocations for research focused on Ghana, South Africa, Kenya, Tanzania and Ethiopia are reflected in higher concentrations of empirical research on impacts and adaptation options in these countries, and there is a general lack of adaptation research for multiple of the most vulnerable countries in Africa (Figure 9.4) ( [[#Callaghan--2021|Callaghan et al., 2021]] ; [[#Overland--2021|Overland et al., 2021]] ; [[#Sietsma--2021|Sietsma et al., 2021]] ; [[#Vincent--2021|Vincent and Cundill, 2021]] ). The combination of northern-led identification of both knowledge and skills gaps can result in projects where African partners are positioned primarily as recipients engaged to support research and/or have their ‘capacity built’ rather than also leading research projects on an equal basis ( [[#Vincent--2020a|Vincent et al., 2020a]] ; [[#Trisos--2021|Trisos et al., 2021]] ). Analysis of &gt;15,000 climate change publications found for over 75% of African countries 60–100% of climate change publications on these countries did not include a single local author, with authorship dominated by researchers from richer countries outside Africa ( [[#Pasgaard--2015|Pasgaard et al., 2015]] ). This can reduce adaptive capacity in Africa as researchers at global north institutions may shape research questions and outputs for a northern audience rather than providing actionable insights on priority issues for African partners ( [[#Pasgaard--2015|Pasgaard et al., 2015]] ; [[#Nago--2020|Nago and Krott, 2020]] ). Moreover, in order to access research publications in a timely manner, many researchers in Africa are forced to use shadow websites bypassing journal paywalls ( [[#Bohannon--2016|Bohannon, 2016]] ). Ways to enhance research partnerships to produce actionable insights on climate impacts and solutions in Africa include: increased funding from African and non-African sources, increasing direct control of resources for African partners, having African research and user priorities set research questions, identify skills gaps, and lead research, and having open access policies for research outputs ( [[#ESPA%20Directorate--2018|ESPA Directorate, 2018]] ; [[#Vogel--2019|Vogel et al., 2019]] ; [[#Vincent--2020a|Vincent et al., 2020a]] ; [[#IDRC--2021|IDRC, 2021]] ; [[#Trisos--2021|Trisos et al., 2021]] ).

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[[File:d590b08cfa2e5c42c0a2493b015de2db IPCC_AR6_WGII_Figure_9_004.png]]

'''Figure 9.4 |''' '''Major gaps in climate change research funding, participation and publication exist within Africa, and for Africa compared to the rest of the world.'''

'''(a)''' Funding: Amount of climate change research funding focused on African countries 1990–2020 ( [[#Overland--2021|Overland et al., 2021]] ). Considering population size, research on Egypt and Nigeria stands out as particularly underfinanced.

'''(b)''' Participation: Percentage of peer-reviewed climate change papers on impacts and adaptation published on a given country that also include at least one author based in that country (Pasgaard et al. 2015).

'''(c)''' Number of publications of climate change adaptation research focused on individual countries identified from a global sample of 62,191 adaptation-relevant peer-reviewed articles published from 1988–2020 ( [[#Sietsma--2021|Sietsma et al., 2021]] ). There is a general lack of adaptation-related research on many vulnerable countries in Africa. Topic biases in adaptation-relevant research also exist where research focuses more on disaster and development-related topics in global south countries (but published by authors from the global north), while research on global north countries focuses more on governance topics ( [[#Sietsma--2021|Sietsma et al., 2021]] ).

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[[File:b7fd765b3f563487ee35fc7c8b17a984 IPCC_AR6_WGII_Figure_9_005.png]]

'''Figure 9.5 |''' '''Observed''' '''climate change impacts on human and natural systems are widespread across Africa, as are climate trends attributable to human-induced climate change.''' This machine-learning-assisted evidence map shows the presence of historical trends in temperature and precipitation attributable to human-induced climate change (pinks compared to greys) and the amount of evidence (shown by intensity of colours) documenting the impacts of these climate trends on human and natural systems (e.g., ecosystems, agriculture, health) across Africa. ‘Robust’ indicates more than five studies documented impacts per grid cell. A ‘High’ amount of evidence indicates more than 20 studies documented impacts for a grid cell. Climate impact studies from the literature were identified and categorised using machine learning. A language representation model was trained on a set of 2373 climate impact studies coded by hand. This supervised machine learning model identified 102,160 published studies predicted to be relevant for climate impacts globally; references to places in Africa were found in 5081 studies (5% of global studies). Temperature trends were calculated from 1951–2018 and precipitation from 1951–2016. Attribution of climate trends to human induced climate change is limited in some regions of Africa due to insufficient data (see [[#9.5.1|Section 9.5.1]] , Figure 9.15). Hatching shows regions where trends in both temperature and precipitation are attributable to human-induced climate change. Data from [[#Callaghan--2021|Callaghan et al. (2021)]] .

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=== 9.1.6 Loss and Damage from Climate Change ===

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Assessment of impacts, vulnerability, and adaptation highlights climate change is leading to loss and damage across Africa, that breach current and projected adaptation limits (Table 9.1; Cross-Chapter Box LOSS in Chapter 17).

'''Table 9.1 |''' Loss and damage from climate change across sectors covered in this report. Loss and damage arise from adverse climate-related impacts and risks from both sudden-onset events, such as floods and cyclones, and slower-onset processes, including droughts, sea level rise, glacial retreat and desertification and include both include both economic (e.g., loss of assets and crops) and non-economic types (e.g., loss of biodiversity, heritage and health) ( [[#UNFCCC%20Paris%20Agreement--2015|UNFCCC Paris Agreement, 2015]] ; [[#IPCC--2018a|IPCC, 2018a]] ; [[#Mechler--2020|Mechler et al., 2020]] ). Sections marked with * and in bold highlight Loss and Damage attributed to human-induced climate change (16.1.3).

{| class="wikitable"
|-
! '''Sector'''

! '''Loss and damage from climate change'''

! '''Observed'''

! '''Projected'''

|-
| ''Ecosystems''

| Local, regional and global extinction

Reduced ecosystem goods and services

Declining natural coastal protection and habitats

Altered ecosystem structure and declining ecosystem functioning

Nature-based tourism

Biodiversity loss

| 9.6.2

9.6.1; 9.6.2

9.6.1; 9.6.2

9.6.1

9.6.3

'''9.6.2''' *

| 9.6.2

9.6.2

9.6.2

9.6.2

9.6.3

|-
| ''Water''

| Declining lake and river resources

Reduced hydroelectricity and irrigation

Disappearing glaciers

Reduced groundwater recharge and salinisation

Drought

| 9.7.1

9.7.2; 9.9.1

'''9.5.9''' *; 9.7.1

–

'''Box 9.4''' *

| 9.7.2

9.7.2; 9.9.3; Box 9.5

9.5.9

9.7.2

|-
| ''Food systems''

| Reduced crop productivity and revenues

Increased livestock mortality and price shocks

Decreased fodder and pasture availability

Reduced fisheries catch and fisher livelihoods

| '''9.7.2''' *, 9.8.1; 9.8.2; 9.11.1; Box 9.5

9.8.2

9.8.2

9.6.1; 9.8.5

| 9.8.2; 9.8.3; Box 9.5

9.8.2

9.8.2

9.8.5

|-
| ''Human settlements and infrastructure''

| Loss or damage to formal and informal dwellings

Damage to transport systems

Damage to energy systems

Water supply, sanitation, education and health infrastructure

Migration

| 9.9.2

9.9.2

9.9.2

9.9.2; 9.10; 9.11.1

9.9.1; Box 9.8

| 9.9.4

9.9.4

9.7.2; 9.9.4

9.7.3; 9.9.4; 9.10; 9.11.1

9.9.4; Box 9.8

|-
| ''Health''

| Loss of life

Loss of productivity

Reduced nutrition

| '''9.9.2*''' ; 9.10.2; Box 9.9

9.10.3; 9.11.1

9.8.1; 9.10.2

| 9.9.4; 9.10.2

9.10.2; 9.11.2

9.10.2

|-
| ''Economy, poverty and livelihoods''

| Loss of livelihoods, jobs and income

Reduced productive land

Reduced economic growth and increased inequality

Community and involuntary displacement

Reduced labour productivity and earning potential

Delayed and poorer education progress

Reduced tourism

Increased urban in-migration

| 9.9.2; 9.10.2; 9.11.1

9.8.2

'''9.11.1''' *; Box 9.5

9.9.3; Box 9.8

9.11.1

9.11.1

9.6.3

9.8.1; 9.9.1; Table Box 9.8

| 9.10.2; 9.11.2

9.8.2

9.11.2

9.9.4; Box 9.8

9.11.2

9.11.1

9.5.9, 9.6.3, 9.12.2

9.9.4; Table Box 9.8

|-
| ''Heritage''

| Loss of traditional cultures and ways of life

Loss of language and knowledge systems

Damage to heritage sites

| Box 9.2; 9.12.1

–

9.12.1

| 9.12.2

9.12.1

9.12.2

|}

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