FINAL DRAFT Chapter 12 IPCC WGII Sixth Assessment Report
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2 Chapter 12: Central and South America
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4 Coordinating Lead Authors: Edwin J. Castellanos (Guatemala), Maria Fernanda Lemos (Brazil)
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6 Lead Authors: Laura Astigarraga (Uruguay), Noemí Chacón (Venezuela), Nicolás Cuvi (Ecuador),
7 Christian Huggel (Switzerland), Liliana Miranda (Peru), Mariana Moncassim Vale (Brazil), Jean Pierre
8 Ometto (Brazil), Pablo L. Peri, (Argentina), Julio C. Postigo (USA/Peru), Laura Ramajo (Chile/Spain),
9 Lisandro Roco (Chile), Matilde Rusticucci (Argentina).
10
11 Contributing Authors: Júlia Alves Menezes (Brazil), Pedro Borges (Venezuela), Jhonattan Bueno
12 (Venezuela), Francisco Cuesta (Ecuador), Fabian Drenkhan (Peru), Alex Guerra (Guatemala), Valeria
13 Guinder (Argentina), Isabel Hagen (Switzerland), Jorgelina Hardoy (Argentina), Stella Hartinger (Peru),
14 Gioconda Herrera (Ecuador), Cecilia Herzog (Brazil), Bárbara Jacob (Chile), Thais Kasecker (Brazil),
15 Andrea Lampis (Colombia/Brazil), Izabella Lentino (Brazil), Luis C. S. Madeira Domingues (Brazil), José
16 Marengo (Brazil), David Montenegro Lapola (Brazil), Ana Rosa Moreno (Mexico), Julia de Niemeyer
17 Caldas (Brazil), Eduardo Pacay (Costa Rica/Guatemala), Roberto Pasten (Chile), Matias Piaggio (Uruguay),
18 Osvaldo Rezende (Brazil), Alfonso J. Rodriguez-Morales (Colombia), Marina Romanello (Argentina/United
19 Kingdom), Sadie J. Ryan (USA/ United Kingdom), Anna Stewart-Ibarra (USA/Ecuador), María Valladares
20 (Chile/Spain)
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22 Review Editors: Carlos Méndez (Venezuela), Avelino Suarez (Cuba)
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24 Chapter Scientist: María Valladares (Chile/Spain)
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26 Date of Draft: 1 October 2021
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28 Notes: TSU Compiled Version
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30
31 Table of Contents
32
33 Executive Summary..........................................................................................................................................3
34 12.1 Introduction ..............................................................................................................................................8
35 12.1.1 The Central and South America Region .........................................................................................8
36 12.1.2 Approach and Storyline for the Chapter.......................................................................................10
37 12.2 Summary of the Fifth Assessment Report and Recent IPCC Special Reports.................................11
38 12.3 Hazards, Exposure, Vulnerabilities and Impacts ................................................................................12
39 12.3.1 Central America (CA) Sub-region ................................................................................................12
40 12.3.2 Northwest South America (NWS) Sub-region ...............................................................................16
41 12.3.3 Northern South America (NSA) Sub-region..................................................................................20
42 12.3.4 South America Monsoon (SAM) Sub-region.................................................................................23
43 12.3.5 Northeast South America (NES) Sub-region.................................................................................28
44 12.3.6 Southeast South America (SES) Sub-region..................................................................................30
45 12.3.7 Southwest South America (SWS) Sub-region ................................................................................34
46 12.3.8 Southern South America (SSA) Sub-region...................................................................................39
47 12.4 Key Impacts and Risks...........................................................................................................................44
48 12.5 Adaptation...............................................................................................................................................50
49 12.5.1 Terrestrial and Freshwater Ecosystems and their Services..........................................................50
50 12.5.2 Ocean and Coastal Ecosystems and their Services .....................................................................53
51 12.5.3 Water.............................................................................................................................................58
52 12.5.4 Food, Fibre and other Ecosystem Products..................................................................................63
53 12.5.5 Cities, Settlements and Infrastructure...........................................................................................69
54 12.5.6 Health and Wellbeing....................................................................................................................73
55 12.5.7 Poverty, Livelihood and Sustainable Development ......................................................................78
56 12.5.8 Cross-cutting Issues in the Human Dimension .............................................................................82
57 12.5.9 Adaptation Options to Address Key Risks in CSA ........................................................................88
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1 12.5.10 Feasibility Assessment of Adaptation Options.....................................................................91
2 12.6 Case Studies ............................................................................................................................................93
3 12.6.1 Nature-based Solutions in Quito, Ecuador ...................................................................................93
4 12.6.2 Anthropogenic Soils, an Option for Mitigation and Adaptation to Climate Change in Central
5 and South America. Learning from the "Terras Pretas de Índio" in the Amazon ...............95
6 12.6.3 Towards a Metropolitan Water-related Climate Proof Governance (re)configuration? The case
7 of Lima, Perú ........................................................................................................................96
8 12.6.4 Strengthening Water Governance for Adaptation to Climate Change: Managing Scarcity and
9 Excess of Water in the Pacific Coastal area of Guatemala..................................................97
10 12.7 Knowledge Gaps .....................................................................................................................................98
11 12.7.1 Knowledge Gaps in the Subregions ..............................................................................................99
12 12.7.2 Knowledge Gaps by Sector ...........................................................................................................99
13 12.8 Conclusion .............................................................................................................................................103
14 FAQ 12.1: How are inequality and poverty limiting options to adapt to climate change in Central and
15 South America? ....................................................................................................................................106
16 FAQ 12.2: How have urban areas in Central and South America adapted to climate change so far,
17 which further actions should be considered within the next decades and what are the limits of
18 adaptation and sustainability? ............................................................................................................107
19 FAQ 12.3: How do climatic events and conditions affect migration and displacement in Central and
20 South America, will this change due to climate change, and how can communities adapt? .........108
21 FAQ 12.4: How is climate change impacting and expected to impact food production in Central and
22 South America in the next 30 years and what effective adaptation strategies are and can be
23 adopted in the region?..........................................................................................................................109
24 FAQ 12.5: How can Indigenous knowledge and practices contribute to adaptation initiatives in
25 Central and South America? ...............................................................................................................111
26 References......................................................................................................................................................113
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1 Executive Summary
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3 Vulnerability and observed impacts:
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5 Central and South America are highly exposed, vulnerable and strongly impacted by climate change,
6 a situation amplified by inequality, poverty, population growth and high population density, land use
7 change particularly deforestation with the consequent biodiversity loss, soil degradation, and high
8 dependence of national and local economies on natural resources for production of commodities (high
9 confidence1). Profound economic, ethnic and social inequalities are exacerbated by climate change. High
10 levels of widespread poverty, weak water governance, unequal access to safe water and sanitation services
11 and lack of infrastructure and financing reduce adaptation capacity, increasing and creating new population
12 vulnerabilities (high confidence). {12.1.1, 12.2, 12.3, 12.5.5, 12.5.7, Figure 12.2}
13
14 The Amazon forest, one of the world's largest biodiversity and carbon repositories, is highly
15 vulnerable to drought (high confidence). The Amazon forest was highly impacted by the unprecedented
16 droughts and higher temperatures observed in 1998, 2005, 2010 and 2015/2016 attributed partly to climate
17 change. This resulted in high tree mortality rates and basin-wide reductions in forest productivity,
18 momentarily turning pristine forest areas from a carbon sink into a net source of carbon to the atmosphere
19 (high confidence). Other terrestrial ecosystems in Central and South America have been impacted by climate
20 change, through persistent drought or extreme climatic events. The combined effect of anthropogenic land
21 use change and climate change increases the vulnerabilities of terrestrial ecosystems to extreme climate
22 events and fires (medium confidence). {12.3, 12.4, Figure 12.7, Figure 12.9, Figure 12.10}
23
24 The distribution of terrestrial species has changed in the Andes due to increasing temperature (very
25 high confidence). Species have shifted upslope leading to range contractions for highland species, and range
26 contractions and expansions for lowland species, including crops and vectors of diseases (very high
27 confidence). {12.3.2.4}
28
29 Ocean and coastal ecosystems in the region such as coral reefs, estuaries, salt marshes, mangroves and
30 sandy beaches are highly sensitive and negatively impacted by climate change and derived-hazards
31 (high confidence). Observed impacts include the reduction in coral abundance, density and cover in Central
32 America, Northwest South America and Northeast South America and increasing number of coral bleaching
33 events in Central America and Northeast South America; changes in the plankton community and in ocean
34 and coastal food web structures, loss of vegetated wetlands and changes in macrobenthic communities in
35 Central America, Northwest, Northern, and Southeast South America. {12.3, 12.5.2, Figure 12.8, Figure
36 12.9, Table SM12.3}
37
38 Global warming has caused glacier loss in the Andes from 30% to more than 50% of their area since
39 the 1980s. Glacier retreat, temperature increase and precipitation variability, together with land-use
40 change, have affected ecosystems, water resources, and livelihoods through landslides and flood
41 disasters (very high confidence). In several areas of the Andes, flood and landslide disasters have increased,
42 and water availability and quality and soil erosion have been affected by both climatic and non-climatic
43 factors (high confidence). {12.3.2, 12.3.7, Figure 12.9, Figure 12.13, Table SM12.6}
44
45 The scientific evidence since the IPCC AR5 increased the confidence on the synergy among fire, land
46 use change, particularly deforestation, and climate change, directly impacting human health,
47 ecosystem functioning, forest structure, food security and the livelihoods of resource-dependent
48 communities (medium confidence). Regional increase in temperature, aridity and drought increased the
49 frequency and intensity of fire. On average, people in the region were more exposed to high fire danger
50 between 1 and 26 additional days depending on the subregion for the years 2017-2020 compared to 2001-
51 2004 (high confidence). {12.2, 12.3, Figure 12.9, Figure 12.10, Table 12.5}
1 In this Report, the following summary terms are used to describe the available evidence: limited, medium, or robust;
and for the degree of agreement: low, medium, or high. A level of confidence is expressed using five qualifiers: very
low, low, medium, high, and very high, and typeset in italics, e.g., medium confidence. For a given evidence and
agreement statement, different confidence levels can be assigned, but increasing levels of evidence and degrees of
agreement are correlated with increasing confidence.
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2 Changes in timing and magnitude of precipitation and extreme temperatures are impacting
3 agricultural production (high confidence). Since the mid-20th century, increasing mean precipitation has
4 positively impacted agricultural production in Southeast South America, although extremely long dry spells
5 have become more frequent affecting the economies of large cities in southeast Brazil. Inversely, reduced
6 precipitation and altered rainfall at the start and end of the rainy season and during the mid-summer drought
7 is impacting rainfed subsistence farming particularly in the Dry Corridor in Central America and in the
8 tropical Andes compromising food security (high confidence). The crop growth duration for maize for those
9 regions was reduced by at least 5% between 1981-2010 and 2015-2019. {12.3.1, 12.3.2, 12.3.6, Table 12.4}
10
11 Climate change affects the epidemiology of climate-sensitive infectious diseases in the region (high
12 confidence). Examples are the effects of warming temperatures on increasing the suitability of transmission
13 of vector-borne diseases, including endemic and emerging arboviral diseases such as dengue fever,
14 chikungunya, and Zika (medium confidence). The reproduction potential for the transmission of dengue
15 increased between 17% and 80% for the period 1950-54 to 2016-2021 depending on the subregion as a result
16 of changes in temperature and precipitation (high confidence). {12.3.1, 12.3.2, 12.3.3, 12.3.5, 12.3.6, Table
17 12.1}
18
19 The Andes, northeast Brazil and the northern countries in Central America are among the more
20 sensitive regions to climatic-related migrations and displacements, a phenomenon that has increased
21 since AR5 (high confidence). Climatic drivers interact with social, political, geopolitical and economical
22 drivers; the most common climatic drivers for migration and displacements are droughts, tropical storms and
23 hurricanes, heavy rains and floods (high confidence). {12.3.1.4, 12.3.2.4, 12.3.3.4, 12.3.5.4, 12.5.8.4}
24
25 The impacts of climate change are not of equal scope for men and women (high confidence). Women,
26 particularly the poorest, are more vulnerable and are impacted in greater proportion. Often they have less
27 capacity to adapt, further widening structural gender gaps (high confidence). {12.3.7.3, 12.5.2.4, 12.5.2.5,
28 12.5.7.3, 12.5.8.1, 12.5.8.3, 12.5.8.4}
29
30 Current adaptation responses:
31
32 Ecosystem-based adaptation is the most common adaptation strategy for terrestrial and freshwater
33 ecosystems (high confidence). There is a focus on the protection of native terrestrial vegetation through
34 implementation of protected areas and payment for ecosystem services, especially those related to water
35 provision. The adaptation measures in place, however, are insufficient to safeguard terrestrial and freshwater
36 ecosystems in the CSA from negative impacts of climate change (high confidence). {12.5.1, 12.5.3, 12.6}
37
38 Adaptation initiatives in ocean and coastal ecosystems mainly focus on conservation, protection and
39 restoration) (high confidence). The main adaptation measures are ocean zoning, the prohibition of
40 productive activities (e.g., fisheries, aquaculture, mining, tourism) on marine ecosystems, the improvement
41 of research and education programs, and the creation of specific national policies (high confidence). {12.5.2}
42
43 Adaptive water management has mainly centred on enhancing quantity and quality of water supply,
44 including large infrastructure projects, which, however, are often contested and can exacerbate water
45 related conflicts (high confidence). Inclusive water regimes that overcome social inequalities and
46 approaches including nature-based solutions, such as wetland restoration and water storage and infiltration
47 infrastructure, with synergies for ecosystem conservation and disaster risk reduction, have been found to be
48 more successful for adaptation and sustainable development (high confidence). {12.5.3, 12.6.1, 12.6.3}
49
50 Adaptation strategies for agricultural production are increasing in the region as a response to current
51 and projected changes in climate (high confidence). The main observed adaptation strategies in agriculture
52 and forestry are soil and water management conservation, crop diversification, climate-smart agriculture,
53 early warning systems, upward shifting for plantations to avoid warming habitat and pests and improved
54 management of pastures and livestock. Adaptation requires governance improvements and new strategies to
55 address changing climate; nevertheless, barriers limiting adaptive capacity persist such as lack of educational
56 programs for farmers, adequate knowledge of site-specific adaptation and institutional and financial
57 constraints (high confidence). {12.5.4}
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2 Urban adaptation in the region includes solutions on regulation, planning, urban waters management
3 and housing (high confidence). Regulation, planning and control systems are central tools on reducing risk
4 associated with the security of the buildings, their location, and the proper supply of basic urban services and
5 transport (high confidence). The adoption of nature-based solutions (e.g., urban agriculture and rivers
6 restoration) and hybrid (grey-green) infrastructure are still incipient with weak connections to poverty and
7 inequality reduction strategies (medium confidence). Focusing on risk reduction encompasses upgrading
8 informal and precarious settlements, built-environments, and improving housing conditions, which offer an
9 important but still limited contribution to urban adaptation (high confidence). {12.5.5, 12.5.7, 12.6.1}
10
11 Adaptation initiatives for the health sector are mainly focused on the development of climate services
12 such as integrated climate-health surveillance and observatories, forecasting climate-related disasters
13 and vulnerability maps (high confidence). Climate services for the health sector are largely focused on
14 epidemic forecast tools and associated early warning systems for vector-borne diseases and heat and cold
15 waves. Political, institutional and financial barriers reduce the feasibility of implementing these tools (high
16 confidence). {12.5.6, Table 12.9, Table 12.11}
17
18 Indigenous knowledge and local knowledge are crucial for the adaptation and resilience of social-
19 ecological systems (high confidence). Indigenous knowledge and local knowledge can contribute to
20 reducing the vulnerability of local communities to climate change (medium confidence). {12.5.1, 12.5.8,
21 12.6.2}
22
23 What are the projected impacts and key risks?
24
25 Climate change is projected to convert existing risks in the region into severe key risks (medium
26 confidence). Key risks are assessed as follows: 1. Risk of food insecurity due to droughts; 2. Risk to people
27 and infrastructure due to floods and landslides; 3. Risk of water insecurity due to declining snow cover,
28 shrinking glaciers and rainfall variability; 4. Risk of increasing epidemics particularly of vector-borne
29 diseases; 5. Cascading risks surpassing public service systems; 6. Risk of large-scale changes and biome
30 shifts in the Amazon; 7. Risks to coral reef ecosystems; and 8. Risks to coastal socio-ecological systems due
31 to sea level rise, storm surges and coastal erosion. {12.3, 12.4, Figure 12.9, Figure 12.11, Table 12.6, Table
32 SM12.5}
33
34 Impacts on rural livelihoods and food security, particularly for small and medium-sized farmers and
35 Indigenous Peoples in the mountains, are projected to worsen, including the overall reduction of
36 agricultural production, suitable farming area and water availability (high confidence). Projected yield
37 reductions by 2050 under A2 scenario are: bean 19%, maize 421%, rice 23% in Central America with
38 seasonal droughts projected to lengthen, intensify and increase in frequency. Small fisheries and farming of
39 seafood will be negatively affected as ENSO events become more frequent and intense and ocean warming
40 and acidification continues (medium confidence). {12.2, 12.3, 12.4, Figure 12.9, Figure 12.11, Table 12.4}
41
42 Extreme precipitation events, which result in floods, landslides and droughts, are projected to
43 intensify in magnitude and frequency due to climate change (medium confidence). Floods and landslides
44 pose a risk to life and infrastructure; a 1.5ºC increase would result in an increase of 100200% in the
45 population affected by floods in Colombia, Brazil and Argentina, 300% in Ecuador and 400% in Peru
46 (medium confidence). {12.3, Figure 12.7, Figure 12.9, Table SM12.5}
47
48 Increasing water scarcity and competition over water are projected (high confidence). Disruption in
49 water flows will significantly degrade ecosystems such as high-elevation wetlands and affect farming
50 communities, public health and energy production (high confidence). {12.3, Figure 12.3, Figure 12.9, Figure
51 12.11}
52
53 In the next decades, endemic and emerging climate-sensitive infectious diseases are projected to
54 increase (medium confidence). This can happen through expanded distribution of vectors, especially viral
55 infectious diseases from zoonotic origin in transition areas between urban and suburban, or rural settings,
56 and upslope in the mountains (medium confidence). {12.3.2, 12.3.5, 12.3.7, Figure 12.5, Figure 12.9, Figure
57 12.11, Table 12.6, Table SM12.5}
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2 The positive feedback between climate change and land use change, particularly deforestation, is
3 projected to increase the threat to the Amazon forest, resulting in the increase of fire occurrence,
4 forest degradation (high confidence) and long-term loss of forest structure (medium confidence). The
5 combined effect of both impacts will lead to a long-term decrease in carbon stocks in forest biomass,
6 compromising Amazonia´s role as a carbon sink, largely conditional on the forest's responses to elevated
7 atmospheric CO2 (medium confidence). The southern portion of the Amazon has become a net carbon source
8 to the atmosphere in the past decade (high confidence). {12.3.3, 12.3.4, Figure 12.9, Figure 12.11, Table
9 12.6, Table SM12.5}
10
11 Up to 85% of natural systems (plant and animal species, habitats and communities) evaluated in the
12 literature for biodiversity-rich spots in the region are projected to be negatively impacted by climate
13 change (medium confidence). Available studies focus mainly on vertebrates and plants of the Atlantic
14 Forest and Cerrado in Brazil and in Central America, with a large knowledge gap on freshwater ecosystems
15 {12.3, 12.5.1, CCP1}
16
17 Ocean and coastal ecosystems in the region will continue to be highly impacted by climate change
18 (high confidence). Coral reefs are projected to lose their habitat, change their distribution range and suffer
19 more bleaching events driven by ocean warming. In the RCP4.5 and RCP8.5 scenarios by 2050, virtually
20 every coral reef will experience at least one severe bleaching event per year (high confidence). Under all
21 RCP scenarios of climate change, there will be changes in the geographical distribution of marine species
22 and ocean and coastal ecosystems such as mangroves, estuaries, rocky shores, as well as those species
23 subjected to fisheries (medium confidence). {Figure 12.9, Table SM12.3, Table SM12.4}
24
25 Contribution of adaptation to solutions and barriers to adaptation
26
27 Policies and actions at multiple scales and the participation of actors from all social groups, including
28 the most exposed and vulnerable populations, are critical elements for effective adaptation (high
29 confidence). Engaging social movements and local actors in policy-making and planning for adaptation
30 generates positive synergies and better results. Adaptation policies and programs that consider age,
31 socioeconomic status, race, and ethnicity are more efficient, as these factors determine vulnerability and
32 potential benefits of adaptation. Socio-economic and political factors that provide some level of safety and
33 continuity of policies and actions are critical enablers of adaptation (high confidence). {12.5.1, 12.5.2,
34 12.5.7, 12.5.8, 12.6.4}
35
36 The knowledge and awareness of climate change as a threat has been increasing since AR5 due to the
37 increasing frequency and magnitude of extreme weather events in the region, information available
38 and climate justice activism (high confidence). Conflicts in which direct biophysical impacts of climate
39 change play a major role can unleash protests and strengthen social movements (medium confidence).
40 {12.5.8, 12.6.4}
41
42 Research approaches that integrate Indigenous knowledge and local knowledge systems, with natural
43 and social sciences, have increased since AR5 (high confidence), and are helping to improve decision-
44 making processes in the region, reduce maladaptation, and foster transformational adaptation through the
45 integration with ecosystem-based adaptation and community-based adaptation (high confidence). {12.5.1,
46 12.5.8, 12.6.2}
47
48 The most reported obstacle for adaptation in terrestrial, freshwater, ocean and coastal ecosystems is
49 financing (high confidence). There is also a significant gap in identifying limits to adaptation and weak
50 institutional capacity for implementation. This hinders the development of comprehensive adaptation
51 programs, even under adequate funding. {12.5.1, 12.5.2}
52
53 Climate Smart Agriculture technologies strengthening synergies among productivity and mitigation is
54 growing as an important adaptation strategy in the region (high confidence). Pertinent information for
55 farmers provided by Climate Information Services are helping them to understand the role of climate vs.
56 other drivers in perceived productivity changes. Index insurance builds resilience and contributes to
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1 adaptation both by protecting farmers' assets in the face of major climate shocks, by promoting access to
2 credit, and by the adoption of improved farm technologies and practices. {12.5.4}
3
4 Institutional instability, fragmented services and poor water management, inadequate governance
5 structures, insufficient data and analysis of adaptation experience are barriers to address the water
6 challenges in the region (high confidence). {12.5.3}
7
8 Inequality, poverty and informality shaping cities in the region increase vulnerability to climate
9 change while policies, plans or interventions addressing these social challenges with inclusive
10 approaches are opportunities for adaptation (high confidence). Initiatives to improve informal and
11 precarious settlement, guaranteeing access to land and decent housing, are aligned with comprehensive
12 adaptation policies that include development and reduction of poverty, inequality and disaster risk (medium
13 confidence). {12.5.5, 12.5.7}
14
15 Adaptation policies often address climate impact drivers, but seldom include the social and economic
16 underpinnings of vulnerability. This narrow scope limits adaptation results and compromises their
17 continuity in the region (high confidence). In a context of unaddressed underdevelopment, adaptation
18 policies tackling poverty and inequality are marginal, underfunded, and not clearly included at national,
19 regional or urban levels. Dialogue and agreement including multiple actors are mechanisms to acknowledge
20 trade-offs and promote dynamic, site-specific adaptation options (medium confidence). {12.5.7}
21
22
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1 12.1 Introduction
2
3 12.1.1 The Central and South America Region
4
5 Central and South America (CSA) is a highly diverse region, both culturally and biologically. It harbours one
6 of the highest biodiversity on the planet (Hoorn et al., 2010; Zador et al., 2015; IPBES, 2018a) (Cross-
7 Chapter Paper 1: Biodiversity Hotspots) and a wealth of cultural diversity resulting from more than 800
8 Indigenous Peoples who share the territory with European and African descendants and more recent Asian
9 migrants (CEPAL, 2014). Moreover, it is one of the most urbanized regions in the world, with some of the
10 most populated metropolitan areas (UNDESA, 2019). Several countries in the region have experienced
11 sustained economic growth in the last decades, making important advances in reducing poverty in the area.
12 Yet, it is a region of substantial social inequality including the highest inequality in land tenure, where there
13 still remains a large percentage of the population below the poverty line, unequally distributed between rural
14 and urban areas and along aspects like gender and race; these groups are highly vulnerable to climate change
15 and natural extreme events that frequently affect the region (high confidence) (ECLAC, 2019b; Busso and
16 Messina, 2020; Poveda et al., 2020).
17
18 Land use changes in the region, particularly deforestation, are large, mostly due to agricultural production for
19 export purposes, one of the main sources of income for the area (Salazar et al., 2016) (Figure 12.2c).
20 Additional pressure on the land comes from illegal activities, pollution and induced fires. These changes
21 exacerbate the impacts of climate change and make the region play a key role in the future of the world
22 economy and food production (IPBES, 2018a). The region boasts the largest tropical forest on the planet and
23 other important biomes of high biodiversity on mountains, lowlands and coastal areas. It can potentially
24 continue its agricultural expansion and development at the expense of substantially reducing the areas of
25 natural biomes. Indigenous Peoples and smallholder families are lacking adequate climate policies combined
26 with institutions to protect their property rights; this could result in a more sustainable process of agricultural
27 expansion, without substantially increasing greenhouse gas emissions and the vulnerability of those
28 populations (high confidence) (Sá et al., 2017).
29
30 Central and South America (CSA) is divided into eight climatic sub-regions by WGI (Figure 12.1). Though
31 the southern part of Mexico is included in the climatic sub-region SCA for WGI, Mexico is assessed in
32 Chapter 14 (North America). In this chapter, we refer to this sub-region as Central America (CA) as it
33 excludes southern Mexico. The climate change literature for the region occasionally includes Mexico and in
34 those cases, our assessment makes reference to Latin America but when only southern Mexico is included,
35 the term Mesoamerica is used. Figure 12.2 and Table SM12.1 summarize relevant characteristics of the sub-
36 regions included in this chapter.
37
38
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2 Figure 12.1: Sub-regions included in the Central and South America region. Note that the WGI climatic sub-region
3 South Central America SCA corresponds to Central America CA in this chapter, as southern Mexico is included in
4 Chapter 14. Small islands in the region are approached in Chapter 15 in more detail.
5
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2 Figure 12.2: Characterization of the region. Population data from ISIMIP (2021) after Klein Goldewijk et al. (2017).
3 Biodiversity expressed as marine and terrestrial species richness adapted from Gagné et al. (2020). Land cover data
4 from ESA (2018). Human Development Index and its components from UNDP (2020). HDI and components for
5 French Guiana from Global Data Lab (2020).
6
7
8 12.1.2 Approach and Storyline for the Chapter
9
10 The chapter is divided in two main sections. The first section follows an integrative approach in which
11 hazards, exposure, vulnerability, impacts and risks are discussed following the eight climatically
12 homogeneous sub-regions described in WGI AR6 (see Figure 12.1). The second section assesses the
13 implemented and proposed adaptation practices by sector; in doing so, it connects to the WGII AR6 cross-
14 chapters themes. The storyline is then a description of the hazards, exposure, vulnerability and impacts
15 providing as much detail as available in the literature at the sub-regional level, followed by the identification
16 of risks as a result of the interaction of those aspects. This integrated sub-regional approach ensures a
17 balance in the text, particularly for countries that are usually underrepresented in the literature but that show
18 a high level of vulnerability and impacts, such as those observed in CA. The sectoral assessment of
19 adaptation that follows is useful for policy makers and implementers, usually focused and organized by
20 sectors, governments' ministries or secretaries that can easily locate the relevant adaptation information for
21 their particular sector. To ensure coherence in the chapter, a summary of the assessed adaptation options by
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1 key risks is presented, followed by a feasibility assessment for some relevant adaptation options. The chapter
2 closes with case studies and a discussion of the knowledge gaps evidenced in the process of the assessment.
3
4
5 12.2 Summary of the Fifth Assessment Report and Recent IPCC Special Reports
6
7 Central and South America shows increasing trends of climatic change and variability and extreme events
8 severely impacting the region, exacerbating problems of rampant and persistent poverty, precarious health
9 systems and water and sanitation services, malnutrition and pollution. Inadequate governance and lack of
10 participation escalates the vulnerability and risk to climate variability and change in the region (high
11 confidence) (WGII AR5 Chapter 27) (Magrin et al., 2014).
12
13 Increasing trends in precipitation had been observed in Southeast South America (SES in Figure 12.1) in
14 contrast with decreasing trends in CA and central-southern Chile (high confidence) (WGII AR5 Chapter 27)
15 (Magrin et al., 2014). Frequency and intensity of droughts have increased in many parts of SA (IPCC,
16 2019c). Warming has been detected throughout CSA except for a cooling trend reported for the ocean off the
17 Chilean coast.
18
19 Climate projections indicate increases in temperature for the entire region by 2100 for RCP4.5 and RCP8.5,
20 but rainfall changes will vary geographically, with a notable reduction of 22% in Northeast Brazil and an
21 increase of +25% in SES. Significant dependency on rainfed agriculture (>30% in Guatemala, Honduras, and
22 Nicaragua) indicates high sensitivity to climatic variability and change, and challenge food security (high
23 confidence) (SRCCL Chapter 5, Mbow et al., 2019). Undernutrition has worsened since 2014 in CSA
24 (SRCCL Chapter 5, Mbow et al., 2019). Evidence of climate change impacts on food security is emerging
25 from Indigenous knowledge and local knowledge studies in SA. Municipalities in CA with high proportion
26 of subsistence crops tend to have less resources for adaptation and more vulnerable to climate change
27 (SRCCL Chapter 5, Mbow et al., 2019). Rising temperature and decreased rainfall could reduce agricultural
28 productivity by 2030, threatening food security of the poorest populations (WGII AR5 Chapter 27, Magrin
29 et al., 2014). Though reduced suitability and yield for beans, coffee, maize, plantain, and rice is expected in
30 CA (SRCCL Chapter 5, Mbow et al., 2019), limiting the warming to 1.5ºC, compared with 2ºC, is projected
31 to result in smaller net reductions in yields of maize, rice, wheat and other cereal crops for CSA (high
32 confidence) (SR15 Chapter 3, Hoegh-Guldberg et al., 2018). The heat stress is expected to reduce the
33 suitability of Arabica coffee in Mesoamerica but it can improve in high latitude areas in SA (SRCCL
34 Chapter 4, Olsson et al., 2019). There is limited evidence that these declines in crop yields may result in
35 significant population displacement from the tropics to the subtropics (SR15 Chapter 3, Hoegh-Guldberg et
36 al., 2018).
37
38 There is a high confidence that heat waves will increase in frequency, intensity and duration, becoming,
39 under high emission scenarios, extremely long, over 60 days in duration in SA; the risk of wildfires will also
40 increase significantly in SA (SRCCL Chapter 2, Jia et al., 2019). These processes are and will lead to
41 increased desertification that cost between 8 and 14% of gross agricultural product in many CSA countries
42 (SRCCL Chapter 3, Mirzabaev et al., 2019). Distinguishing climate induced changes from land use changes
43 is challenging, but 56% of biomes in SA are expected to change by 2100 due to climate change (SRCCL
44 Chapter 4, Olsson et al., 2019).
45
46 Changes in weather and climatic patterns are negatively affecting human health in CSA, in part through the
47 emergence of diseases in previously non-endemic areas (WGII AR5 Chapter 27, Magrin et al., 2014).
48 Projections of potential impacts of climate change on malaria confirm that weather and climate are among
49 the drivers of geographic range, intensity of transmission, and seasonality; the changes of risk become more
50 complex with additional warming (very high confidence) (SR15 Chapter 3, Hoegh-Guldberg et al., 2018).
51 There is high confidence that constraining the warming to 1.5°C would reduce risks for unique and
52 threatened ecosystems safeguarding the services they provide for livelihoods and sustainable development
53 (food, water) in CA and Amazon (SR15 Chapter 5, Roy et al., 2018).
54
55 Observed changes in streamflow and water availability affect vulnerable regions (WGII AR5 Chapter 27,
56 Magrin et al., 2014). Glacier mass changes in the Andes over the past decades are among the most negative
57 ones worldwide (SROCC Chapter 2, Hock et al., 2019). This reduction has modified the frequency,
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1 magnitude and location of related natural hazards, while the exposure of people and infrastructure has
2 increased because in relation with growing population, tourism and economic development (high confidence)
3 (SROCC Chapter 2, Hock et al., 2019).
4
5 Negative impacts of climate change in the region are exacerbated by deforestation and land degradation
6 attributed mainly to expansion and intensification of agriculture and cattle ranching, usually under insecure-
7 tenure land. This conversion of natural ecosystems is the main cause of biodiversity and ecosystem loss and
8 is an important source of greenhouse gas (GHG) emissions (high confidence) (WGII AR5 Chapter 27,
9 Magrin et al., 2014).
10
11 The combination of continued anthropogenic disturbance, particularly deforestation, with global warming
12 may result in dieback of forest in the region (medium confidence) (SR15 Chapter 3, Hoegh-Guldberg et al.,
13 2018). Loses as high as 40% of biomass are projected in CA with a warming of 3°C4°C and the Amazon
14 may experience a significant dieback at similar warming levels (SR15 Chapter 3, Hoegh-Guldberg et al.,
15 2018). Advances in second-generation bioethanol from sugarcane and other feedstock will be important for
16 mitigation. However, agricultural expansion results in large conversions in tropical dry woodlands and
17 savannas in SA (Brazilian Cerrado, Caatinga and Chaco) (high confidence) (SRCCL Chapter 1, Arneth et al.,
18 2019). The expansion of soybean plantations in the Amazonian state of Mato Grosso in Brazil reached
19 16.8% yr-1 from 2000 to 2005; and oil palm, a significant biofuel crop, is also linked to recent deforestation
20 in tropical CA (Costa Rica and Honduras) and SA (Colombia and Ecuador), although lower in magnitude
21 compared to deforestation from soybean and cattle ranching (WGII AR5 Chapter 27, Magrin et al., 2014).
22
23 Ocean and coastal ecosystems in the region already show important changes due to climate change and
24 global warming (SROCC Chapter 5, Bindoff et al., 2019).
25
26 Adaptation to future climate changes starts by reducing the vulnerability to present climate considering the
27 deficient welfare of people in the region. Generalizing to the region cases of synergies among development,
28 adaptation and mitigation planning requires a governance model where development needs, vulnerability
29 reduction, and adaptation strategies are intertwined (WGII AR5 Chapter 27, Magrin et al., 2014).
30
31
32 12.3 Hazards, Exposure, Vulnerabilities and Impacts
33
34 12.3.1 Central America (CA) Sub-region
35
36 12.3.1.1 Hazards
37
38 Since the mid-20th century, extreme warm temperatures have increased and extreme cold temperatures have
39 decreased in the region (medium confidence). The magnitude and frequency of extreme precipitation events
40 have increased, but droughts have mixed signals (low confidence) (WGI AR6 Table 11.13, Table 11.14,
41 Table 11.15, Seneviratne et al., 2021). There are spatially variable trends detected for the mid-summer
42 drought (MSD) timing, the amount of rainy season precipitation, the number of consecutive and total dry
43 days, and extreme wet events at the local scale since the 1980s. At the regional scale, a positive trend in the
44 duration, but not the magnitude of the MSD was found (Anderson et al., 2019).
45
46 Significant increases in tropical cyclone (TC) intensification rates in the Atlantic basin, highly unusual
47 compared to model-based estimates of internal climate variations has been observed (Bhatia et al., 2019). TC
48 contributed approximately 10% of the annual precipitation (Khouakhi et al., 2017). During the TC season
49 more TC-driven events of extreme sea level exceed a 10-year return period (Muis et al., 2019).
50
51 Massive heat wave events and increase in the frequency of warm extremes are projected at the end of the
52 21st century (high confidence). When comparing 2.0 with 1.5 degrees of warming, the longest annual warm
53 wave is projected to increase more than 60 days (Taylor et al., 2018).
54
55 General decrease in the magnitude of heavy precipitation extremes (Chou et al., 2014; Giorgi et al., 2014) (in
56 1.5ºC projection) but increase in the frequency of extreme precipitation (R50mm) (Imbach et al., 2018) are
57 projected for both 2ºC and 4ºC GWL. Strong declines in mean daily rainfall are projected for July in Belize
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1 (Stennett-Brown et al., 2017; WGI AR6 Table 11.14, Seneviratne et al., 2021) and decreased rainfall through
2 the year for all capital cities except Panama City (medium confidence: limited evidence, high agreement)
3 (Pinzón et al., 2017).
4
5 The main climate impact drivers like extreme heat, drought, relative sea level rise, coastal flooding, erosion,
6 marine heatwaves, ocean aridity, (high confidence) and aridity, drought and wildfires will increase by mid-
7 century (medium confidence) (Figure 12.6, WGI AR6 Table 12.6, Ranasinghe et al., 2021).
8
9 The rainy season in CA will likely experience more pronounced MSD by the end of this century, with a
10 signal for reduced minimum precipitation by the mid-century for the JJA and SON quarters, and a broader
11 second peak is projected consistent with the future south displacement of the ITCZ (high confidence)
12 (Fuentes-Franco et al., 2015; Hidalgo et al., 2017; Maurer et al., 2017; Imbach et al., 2018; Naumann et al.,
13 2018; Ribalaygua et al., 2018; Corrales-Suastegui et al., 2020).
14
15 Climate projections indicate a decrease in frequency of tropical cyclones in CA accompanied with an
16 increased frequency of intense cyclones (WGI AR6 Section 12.4.4.3, Ranasinghe et al., 2021).
17
18 12.3.1.2 Exposure
19
20 Of the 47 million Central Americans in 2015, 40% lived in rural areas with Belize being the least urbanized
21 (54% rural) and Costa Rica the most (21% rural) (CELADE, 2019); 10.5 million lived in the Dry Corridor
22 region, an area recently exposed to severe droughts that have resulted in 3.5 million people in need of
23 humanitarian assistance (FAO, 2016a). Except in Belize and Panama, the majority of the countries'
24 population --ranging from 56% in Honduras to 95% in El Salvador-- is exposed to 2 or more risks derived
25 from natural extreme events, affecting between 57% to 96% of the GDP of the countries (UNISDR and
26 CEPREDENAC, 2014). Central America is one of the regions most exposed to climatic phenomena; with
27 long coastlines and lowland areas, the region is repeatedly affected by drought, intense rains, cyclones and
28 ENSO events (high confidence) (ECLAC et al., 2015).
29
30 Large urban centres are located on mountains or away from the shore, with the notable exceptions of Panama
31 City, Belmopan and Managua, capital cities housing around 3 million people. Urban development in the
32 capital cities and suburbs has almost tripled in the last forty years reaching population densities as high as
33 11,000 inhabitants per km2 in Guatemala City and Tegucigalpa, with the spread of poor neighbourhoods in
34 steep ravines and other marginal high risk areas (Programa Estado de la Nación - Estado de la Región, 2016).
35
36 12.3.1.3 Vulnerability
37
38 Climate change is exacerbating socioeconomic vulnerability in CA, a region with high levels of
39 socioeconomic, ethnic and gender inequality, high rates of child and maternal mortality and morbidity, high
40 levels of malnutrition and inadequate access to food and drinking water (ECLAC et al., 2015). Disasters
41 from adverse natural events exacerbate CA's economic vulnerability, accounting for substantial human and
42 economic losses (UNISDR and CEPREDENAC, 2014). Vulnerability in most sectors is considered high or
43 very high (high confidence) (Figure 12.7).
44
45 Approximately 40% of the CA population are living in poverty. Guatemala (62%), Honduras (60%),
46 Nicaragua (46%) and Belize (42%, 2009) had the highest poverty rates in CSA in 2018 (ECLAC, 2019b;
47 BCIE, 2020). Rural poverty rates are higher, 82% in Honduras and 77% in Guatemala in 2014, and so is
48 poverty among Indigenous Peoples, up to 79% in Guatemala. Rural poor are the most sensitive to climate
49 extremes as their main economic activity is based on agriculture in vulnerable terrains (NU CEPAL, 2018).
50 In 2014, all CA countries, except for El Salvador (excluding Belize), had higher GINI coefficients (more
51 inequality) than the average for Latin America (0.473), which in itself is the most unequal region in the
52 world (ECLAC, 2019b); in 2018 the situation remained similar with El Salvador showing the lowest GINI
53 coefficient (40) and the rest of the countries showing values higher than the Latin-American average (BCIE,
54 2020).
55
56 12.3.1.4 Impacts
57
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1 The countries in the region are consistently ranked with the highest risk in the world of being impacted by
2 extreme events (high confidence). Economic cost of climate change impacts in 2010 was estimated from
3 2.9% of GDP for Guatemala to 7.7% for Belize (ECLAC et al., 2015). For the period 19922011, Honduras,
4 Nicaragua and Guatemala were among the 10 most impacted countries in the world by extreme weather
5 events (UNISDR and CEPREDENAC, 2014). The number of these events has increased 3% annually in the
6 last 30 years (Bárcena et al., 2020a).
7
8 Human and economic losses, changing water availability and increasing food insecurity are the most studied
9 impacts of climate change in CA (Figure 12.9; Harvey et al., 2018; Hoegh-Guldberg et al., 2019). Hydro-
10 meteorological events, such as storm surges and tropical cyclones, are the most frequent extreme events and
11 have the highest impact (high confidence) (Reyer et al., 2017). From 2005 to 2014, the cumulative impacts
12 were over 3410 people dead, hundreds of thousands displaced, and damages estimated around USD 5.8
13 billion (Ishizawa and Miranda, 2016). One standard deviation in the intensity of a hurricane windstorm leads
14 to a decrease in both the growth of total GDP per capita (0.9% to 1.6%) and total income and labour income
15 by 3%, whereas it increases moderate and extreme poverty by 1.5% in CA (Ishizawa and Miranda, 2016).
16
17 Food insecurity is a serious impact of climate change in a region where 10% of the GDP depends on
18 agriculture, livestock and fisheries (very high confidence) (ECLAC et al., 2015; CEPAL et al., 2018; Harvey
19 et al., 2018; BCIE, 2020). Crop losses largely result from highly variable rainfall and seasonal droughts
20 which have increased significantly in the last decades (Table 12.3; CEPAL and CAC-SICA, 2020),
21 particularly the observed changes in the MSD that reduces rainfall at the onset of the rainy season (May-
22 June) (Anderson et al., 2019). Small and subsistence farmers receive the highest impact as they practice
23 rainfed agriculture (Imbach et al., 2017), and poor neighbourhoods, which face socioeconomic and physical
24 barriers for adapting to climate change (Kongsager, 2017). In 2015, precipitation diminished between 50% to
25 70% of its historic average causing the loss of up to 80% of beans and 60% of maize, leaving 2.5 million
26 people food insecure, 1.6 million of which were in the Dry Corridor of CA (ECLAC et al., 2015; FAO,
27 2016a). In 2019, the region entered its fifth consecutive drought year with 1.4 million people in need of food
28 aid. Seasonal-scale droughts are projected to lengthen by 1230%, intensify by 1742% and increase in
29 frequency by 2142% in RCP4.5 and RCP8.5 scenarios by the end of the century (Depsky and Pons, 2021).
30
31 Studies have shown that the incidence of some vector-borne and zoonotic diseases in CA is correlated to
32 climatic variables, particularly temperature and rainfall (high confidence) (Figure 12.4; Table 12.1). In
33 Honduras, rainfall and relative humidity were positively correlated with the occurrence of hemorrhagic
34 dengue cases (Zambrano et al., 2012). In Costa Rica, temperature and rainfall was correlated to cattle rabies
35 outbreaks and mortality during 19852016 (Hutter et al., 2018); Incidence of leishmaniasis showed cycles of
36 three years related to temperature changes (Chaves and Pascual, 2006); and snakebites were more likely to
37 occur at high temperatures and was significantly reduced after the rainy season for the period 20052013
38 (Chaves et al., 2015). In Panama, rainfall was associated with the increased number of malaria cases among
39 the Gunas, an Indigenous People with high vulnerability living in poverty conditions on small islands
40 affected by sea-level rise (Hurtado et al., 2018). These correlations point to a possible change in disease
41 incidence with climate change; evidence of that change is yet to be reported in the literature as longitudinal
42 studies are lacking in the region.
43
44 Heat stress is another health concern in this already warm and humid part of the world (high confidence)
45 (Table 12.2); it is an increasing occupational health hazard with potential impacts on kidney disease
46 (Sheffield et al., 2013; Dally et al., 2018; Johnson et al., 2019). Sea-level rise exacerbating wave-driven
47 flooding is expected to impact infrastructure and freshwater availability in small islands and atolls off the
48 coast of Belize (Storlazzi et al., 2018). Observed and expected impacts in the coastal and ocean ecosystems
49 of the sub-region are described in Figure 12.9.
50
51 Decreasing water availability is another impact of climate change (high confidence). Under a climate change
52 scenario of 3.5°C warming and a 30% reduction of rainfall, a reduction in production and export of crops and
53 livestock is projected affecting the wages and decreasing the GDP of Guatemala by 1.2%, thereby increasing
54 food insecurity (Vargas et al., 2018b). By 2100, water availability per capita is projected to decrease 82%
55 and 90% on average for the region under B2 (low emissions) and A2 (high emissions) scenarios respectively
56 (CEPAL, 2010) (Figure 12.3).
57
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1
2 Figure 12.3: Reduction of water availability per capita projected to 2100 without climate change (baseline scenario)
3 and with two climate change scenarios (CEPAL, 2010).
4
5
6 Impacts on rural livelihoods, particularly for small and medium-sized farmers and Indigenous Peoples on the
7 mountains, include the overall reduction of the production, yield (Table 12.4), suitable farming area, and
8 water availability (high confidence) (Walshe and Argumedo, 2016; Bouroncle et al., 2017; Hannah et al.,
9 2017; Imbach et al., 2017; Harvey et al., 2018; Batzín, 2019; Donatti et al., 2019). Bean production in El
10 Salvador, Nicaragua, Honduras, and Guatemala, is projected to decrease, using the Decision Support for
11 Agro-Technology Transfer (DSSAT) under A2 scenario, by 19% for 2050, whereas maize production,
12 depending on water retention capacity of soils, will drop between 4% and 21% by 2050 (CEPAL et al.,
13 2018). In Guatemala, the yield of rainfed maize is expected to decrease by 16% by 2050 under RCP8.5 using
14 the Global Gridded Crop Model Intercomparison GGCMI; yields for rainfed sugarcane are expected to drop
15 by 44% and irrigated sugarcane by 36% under the same modelling conditions (Castellanos et al., 2018). Rice
16 production is expected to decrease by 23% under scenario A2 by 2050 (CEPAL and CAC/SICA, 2013).
17
18 The extent and quality of suitable areas for basic grains are expected to contract (high confidence). The
19 suitable area for maize will experience a 35% reduction of cultivated area expected by 2100 under A2
20 scenario. The area suitable for beans is expected to reduce by 2050. Projections show that suitable areas with
21 excellent aptitude under current conditions will decrease by 14%, mainly in Panama (41%) Costa Rica (21%)
22 and El Salvador (20%). Species Distribution Model, using the IPSL GCM, projects that the suitable zones
23 for cacao and coffee will shrink between 25% to 75% under RCP6.0 (Fernandez-Manjarrés, 2018; Fernández
24 Kolb et al., 2019). Warmer and dryer lower areas will become unsuitable for coffee and will drive its
25 production to higher land (Läderach et al., 2013; Bunn et al., 2015). Under A2 climate change scenario, areas
26 with excellent aptitude for Arabica coffee will decrease by 12% in Central America; coffee yield will
27 decrease in suitable zones whereby the extent of high yield (> 0.8 T ha-1) zones is project to shrink from 34%
28 to 12% whereas low yield (< 0.3 T ha-1) zone will expand from 14% to 36% by 2100 under A2 scenario
29 (CEPAL and CAC/SICA, 2014).
30
31 The Mesoamerica, biodiversity-rich spot spanning through CA and southern Mexico is a global priority for
32 terrestrial biodiversity conservation, and it is projected to be negatively impacted by climate change,
33 especially through the contraction of distribution of native species at the area becomes increasingly dryer
34 (high confidence) (Cross-Chapter Paper 1.2.2; Feeley et al., 2013; Manes et al., 2021) . A significant
35 reduction in net primary productivity in tropical forests is expected under both RCP4.5 and RCP8.5 as a
36 result of temperature increase, precipitation reduction, and droughts (Lyra et al., 2017; Castro et al., 2018;
37 Stan et al., 2020). Models of aridity index show that the dry, sub humid vegetation of the dry corridor will
38 expand to neighbouring areas and replace the humid forests in the Pacific lowlands and the northern parts of
39 Guatemala by 2050 under RCP4.5 and RCP8.5 scenarios (Pons et al., 2018; CEPAL and CAC-SICA, 2020).
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1 3°C warming would shrink the tropical rainforest and replace it with savannah grassland. Wetlands are also
2 expected to be highly affected by climate change in the region (Hoegh-Guldberg et al., 2019).
3
4 12.3.2 Northwest South America (NWS) Sub-region
5
6 12.3.2.1 Hazards
7
8 Significant increases in the intensity and frequency of hot extremes and significant decreases in the intensity
9 and frequency of cold extremes (Dereczynski et al., 2020; Dunn et al., 2020) was likely2 observed (Figure
10 12.6; WGI AR6 Table 11.13, Seneviratne et al., 2021).
11
12 Insufficient data coverage and trends in available data are generally not significant for heavy precipitation
13 (low confidence) (Dereczynski et al., 2020; Dunn et al., 2020; Sun et al., 2021) (Figure 12.6; WGI AR6
14 Table 11.14) (Seneviratne et al., 2021).
15
16 ENSO is the dominant phenomenon affecting weather conditions in all CSA, and along the Pacific Coast of
17 NWS with effects of heavy rains, storms, floods, landslides, heat and cold waves and extreme sea level rise
18 (Ashok et al., 2007; Reguero et al., 2015; Wang et al., 2017b; Muis et al., 2018; Rodríguez-Morata et al.,
19 2018; Rodríguez-Morata et al., 2019; Cai et al., 2020). There is a medium confidence that extreme ENSO
20 will increase long after 1.5°C warming stabilization according to CMIP5 (Cai et al., 2015; Wang et al.,
21 2017b; Cai et al., 2018). It is very likely that ENSO rainfall variability, used for defining extreme El Niño
22 and La Niña, will increase significantly, regardless of amplitude changes in ENSO SST variability, by the
23 second half of the 21st century in scenarios SSP2-4.5, SSP3-7.0, and SSP5-8.5 (WGI AR6 Chapter 4; Lee et
24 al., 2021).
25
26 Warming and drier conditions are projected through the reduction of total annual precipitation, extreme
27 precipitation and consecutive wet days, and increase in consecutive dry days (Chou et al., 2014). Heat waves
28 will increase in frequency and severity in places close to the equator as Colombia (Guo et al., 2018; Feron et
29 al., 2019), with decrease but strong wetting in coastal areas, pluvial and river flood, and mean wind increase
30 (Mora et al., 2014). Models project for a 2ºC GWL very likely increase in the intensity and frequency of hot
31 extremes and decrease in the intensity and frequency of cold extremes. Nevertheless, models project
32 inconsistent changes in the region for extreme precipitation (low confidence) (Figure 12.6; WGI AR6 Table
33 12.14; Ranasinghe et al., 2021). The main climate impact drivers in the region, like extreme heat, mean
34 precipitation and coastal and oceanic will increase and snow, ice and permafrost will decrease with high
35 confidence (WGI AR6 Table 12.6, Ranasinghe et al., 2021).
36
37 12.3.2.2 Exposure
38
39 There is high confidence that coastal lowlands are exposed to sea level rise in the form of coastal flooding
40 and erosion, subsidence and saltwater intrusion (Hoyos et al., 2013). Those hazards can affect settlements,
41 ports, industries and other infrastructures. Mangrove and aquaculture areas are among the most exposed
42 systems (Gorman, 2018). The Eastern Tropical Pacific, particularly Sector Niño 3.4, will see the worst
43 increase in sea surface temperature, affecting industrial and small-scale fisheries (very high confidence)
44 (Castrejón and Defeo, 2015; Reguero et al., 2015; Eddy et al., 2019; Bertrand et al., 2020; Castrejón and
45 Charles, 2020; Escobar-Camacho et al., 2021).
46
47 Settlements and agriculture of different scales, and hydroelectric infrastructures, especially near big rivers or
48 in plains, are exposed to floods. Exposure and vulnerabilities to precipitation, overflows and related
49 landslides, are increasing (Briones-Estébanez and Ebecken, 2017).
50
2 In this Report, the following terms have been used to indicate the assessed likelihood of an outcome or a result:
Virtually certain 99100% probability, Very likely 90100%, Likely 66100%, About as likely as not 3366%,
Unlikely 033%, Very unlikely 010%, and Exceptionally unlikely 01%. Additional terms (Extremely likely: 95
100%, More likely than not >50100%, and Extremely unlikely 05%) may also be used when appropriate. Assessed
likelihood is typeset in italics, e.g., very likely). This Report also uses the term `likely range' to indicate that the assessed
likelihood of an outcome lies within the 17-83% probability range.
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1 The Andean piedmont (5001200 m.a.s.l.) ecosystems and crops and elevation ranges above the treeline are
2 more exposed to thermal anomalies (very high confidence) (Urrutia and Vuille, 2009; Vuille et al., 2015;
3 Aguilar-Lome et al., 2019; Pabón-Caicedo et al., 2020). Temperature rise, combined with precipitation and
4 floods, leave people more exposed to epidemics (very high confidence) (Stewart-Ibarra and Lowe, 2013;
5 Sippy et al., 2019; Petrova et al., 2020). A bigger exposure is related to lower socioeconomic conditions,
6 poor health and marginalisation (Oliver-Smith, 2014).
7
8 12.3.2.3 Vulnerability
9
10 Local economies reliant on limited and specialized resources, highly dependent on ecosystem services such
11 as water and soil fertility, as the alpaca and llama herders or small-scale fishers, are amongst the more
12 vulnerable (very high confidence) (Hollowed et al., 2013; Postigo, 2013; Glynn et al., 2017; Duchicela et al.,
13 2019). Also the agricultural sector in the face of extreme events (Coayla and Culqui, 2020). Their
14 vulnerabilities increase as a result of unequal chains of value, incomplete transfers of technology and other
15 socioeconomic and environmental drivers (high confidence) (Ariza-Montobbio and Cuvi, 2020; Gutierrez et
16 al., 2020).
17
18 Informal housing and settlements, usually located in the highest risk land, exacerbates vulnerability (very
19 high confidence) (Miranda Sara and Baud, 2014; Cuvi, 2015; Miranda Sara et al., 2016). The absence of
20 proper drainage systems in urban areas increases the vulnerability, especially to floods. Most of the cities and
21 infrastructure are considered highly vulnerable to climate change (high confidence) (Figure 12.7).
22
23 Regions dependent on glacier runoff are particularly vulnerable (Jiménez Cisneros et al., 2014; Mark et al.,
24 2017; Polk et al., 2017). Also biodiversity and water dependent activities where seasonality and rainfall
25 patterns are changing, and where other non-climatic sources of change, such as land use, affect the capacity
26 of ecosystems to provide hydrological services (very high confidence) (Cerrón et al., 2019; Molina et al.,
27 2020). The three countries are amongst the most vulnerable in terms of wellbeing and health Figure 12.7;
28 Nagy et al., 2018).
29
30 12.3.2.4 Impacts
31
32 An increase in the frequency of climate related disasters has been reported (high confidence) (Huggel et al.,
33 2015a; Stäubli et al., 2018) (WGI AR6 Chapter 12) (Ranasinghe et al., 2021). Scale studies indicate an
34 increase of flood risk during the 21st century, consistent with more frequent floods, being worse in higher
35 emission scenarios (high confidence) (Arnell and Gosling, 2013; Hirabayashi et al., 2013; Alfieri et al., 2017;
36 WGI AR6 Chapter 12, Ranasinghe et al., 2021). Those living on riverbanks and slums built on steep slopes
37 are among the most affected by floods of all kinds (high confidence) (Emmer et al., 2016; Emmer, 2017).
38 There is still uncertainty in relation to future drought intensity and frequency (Pabón-Caicedo et al., 2020).
39
40 Increased sea surface temperature, coupled with stronger ENSO events, will affect marine life and fisheries
41 by loss of productive habitat, disruption of nutrient structure, productivity, and altering the migration of
42 species, leading to changes in fishing rates, impacting coastal livelihoods (high confidence) (Bayer et al.,
43 2014; Cai et al., 2015; Ding et al., 2017; Mariano Gutiérrez et al., 2017; Bertrand et al., 2020). Figure 12.8
44 shows other observed sensitivities in several ecosystems and in places as the Galapagos and Malpelo islands,
45 and the coastal Economic Exclusion Zone (EEZ).
46
47 ENSO events coupled with climate change, lead to warmer ocean temperatures, heavy rains, floods and
48 heavy river discharges that have and will impact several activities, including small-scale fisheries
49 infrastructure (very high confidence). In Peru alone, wet extremes are estimated to be at least 1.5 times more
50 likely to happen compared to preindustrial times. The extremely wet ENSO event of 2017 left 69 billion
51 USD in monetary losses in that country, 1.7 million inhabitants affected, and crops, roads, bridges, homes,
52 schools, and health posts damaged or destroyed. Distinct types of ENSO events can have differentiated
53 impacts (French and Mechler, 2017; Christidis et al., 2019; Takahashi and Martínez, 2019; Bertrand et al.,
54 2020; Coayla and Culqui, 2020).
55
56 Irrigation, potable water, health and education infrastructures, as well as roads, bridges, cities, and housing
57 buildings are frequently damaged or destroyed by extreme precipitations, having also impacts on sediment
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1 transport, river erosion and annual discharge (very high confidence) (Martínez et al., 2017; Morera et al.,
2 2017; Isla, 2018; Rosales-Rueda, 2018; Salazar et al., 2018; Puente-Sotomayor et al., 2021). The increasing
3 variability of precipitation has compromised rain-fed agriculture and power generation, particularly in the
4 dry season (high confidence) (Bradley et al., 2006; Bury et al., 2013; Buytaert et al., 2017; Carey et al., 2017;
5 Vuille et al., 2018; Orlove et al., 2019). For the Amazon-Andes transition zone, impacts of hydrological
6 variability and transport of sediments have been noticed in riparian agriculture and biodiversity (high
7 confidence) (Maeda et al., 2015; Espinoza et al., 2016; Vauchel et al., 2017; Ronchail et al., 2018; Ayes
8 Rivera et al., 2019; Armijos et al., 2020; Figueroa et al., 2020; Pabón-Caicedo et al., 2020). Changes in
9 seasonality and rain patterns are affecting coffee producers (Lambert and Eise, 2020).
10
11 Increases in vector-borne diseases can be related with the increase of rainfall and minimum temperatures
12 during ENSO events (Stewart-Ibarra and Lowe, 2013) and the expansion of the diseases' altitudinal
13 distribution (high confidence) (Lowe et al., 2017; Lippi et al., 2019; Portilla Cabrera and Selvaraj, 2020).
14 ENSO events have been related with diseases such as dengue or leptospirosis (Quintero-Herrera et al., 2015;
15 Sánchez et al., 2017; Arias-Monsalve and Builes-Jaramillo, 2019); they can also increase the incidence of
16 Chikungunya (Section 7.2.2.1; Section 7.3.1.3). Precipitation, relative humidity and temperature have
17 influenced dengue incidence over the last years (Mattar et al., 2013) (Table 12.1). Dengue cases are
18 predicted to increase in the 1.5°C and the 3.7°C warming scenarios by 2050 and 2100, with increases
19 ranging from 28,900 to 88,800 in Peru, 34,600 to 110,000 in Ecuador, and 97,400 to 317,000 in Colombia,
20 although these scenarios do not consider the potential of vaccines or socioeconomic trajectories (Colón-
21 González et al., 2018). Other studies found that Aedes aegypti (arbovirus vector) will shift into higher
22 elevations, increasing the populations at risk (Lippi et al., 2019) (Figure 12.5). Climate change will
23 contribute to increased malaria vectorial capacity (high confidence) (Laporta et al., 2015) (Section 7.2.2.1).
24 Increases in minimum temperature were associated with historical malaria transmission when taking into
25 consideration disease control interventions and climate factors (Fletcher et al., 2020). Figure 12.4 shows
26 mixed changes in the number of months suitable for malaria transmission with low-lying areas in coastal
27 regions becoming more suitable. Zoonotic tick-borne diseases and the epidemiology of tuberculosis are also
28 influenced (Garcia-Solorzano et al., 2019; Rodriguez-Morales et al., 2019).
29
30
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1 Figure 12.4: Change in the average number of months in a given year suitable for malaria transmission by Plasmodium
2 falciparum, from 1950-1959 to 2010-2019. The threshold-based model used incorporates precipitation accumulation,
3 average temperature, and relative humidity (Grover-Kopec et al., 2006; Romanello et al., 2021).
4
5
6 Accelerated warming is reducing tropical glaciers. Glacier volume loss and permafrost thawing will continue
7 in all scenarios (high confidence) (Ranasinghe et al., 2021). On average, the tropical Andes have lost about
8 30% and more of their area since the 1980s (Basantes-Serrano et al., 2016; Mark et al., 2017; Thompson et
9 al., 2017; Rabatel et al., 2018; Vuille et al., 2018; Reinthaler et al., 2019a; Seehaus et al., 2019; Masiokas et
10 al., 2020). In a low emissions scenario, by the end of the 21st century, Peru will lose about 50% of the
11 present glacier surface, while in a high-emission scenario there will remain very small areas of only about 3
12 5% on the highest peaks (Schauwecker et al., 2017).
13
14 Changing glaciers, snow and permafrost (Figure 12.13), in synergy with land use change, have implications
15 for the occurrence, frequency and magnitude of derived floods and landslides (high confidence) (Huggel et
16 al., 2007; Iribarren Anacona et al., 2015; Emmer, 2017; Mark et al., 2017). Also to landscape transformation
17 through lakes' formation or drying, and to alteration of hydrological dynamics, with impacts on water for
18 human consumption, agriculture, industry, hydroelectric generation, carbon sequestration and biodiversity
19 (high confidence) (Michelutti et al., 2015; Carrivick and Tweed, 2016; Kronenberg et al., 2016; Emmer,
20 2017; Mark et al., 2017; Milner et al., 2017; Polk et al., 2017; Reyer et al., 2017; Young et al., 2017; Vuille
21 et al., 2018; Cuesta et al., 2019; Drenkhan et al., 2019; Hock et al., 2019; Motschmann et al., 2020a).
22
23 Water flow has decreased in several basins as the Shullcas River in the Cordillera Huaytapallana in Peru and
24 is expected to decrease in the near future in in places such as the Cordillera Blanca in Peru (very high
25 confidence) (Baraer et al., 2012; Vuille et al., 2018; Somers et al., 2019; Molina et al., 2020). Disruptions in
26 water flows will significantly degrade or disappear high-elevation wetlands (high confidence) (Bury et al.,
27 2013; Dangles et al., 2017; Mark et al., 2017; Polk et al., 2017; Cuesta et al., 2019). Impacts on wetlands are
28 affecting the wild vicuña and the domesticated alpaca (Duchicela et al., 2019). New lakes represent a source
29 of future hazards and water scarcity, as well as an opportunity as water reservoirs (Colonia et al., 2017;
30 Drenkhan et al., 2019). The timing and extent of peak water due to glacier shrinkage is spatially highly
31 variable, and has passed for a large number of tropical Andes glaciers (Hock et al., 2019). Cities dependent
32 on glacier melt have experienced high variability in domestic water supply (Chevallier et al., 2011; Soruco et
33 al., 2015; Mark et al., 2017) as shown in Case Study 2.7.3, but the increase of the demand may also be
34 determinant (Buytaert and De Bièvre, 2012). Water provision is related to socio economic issues (Drenkhan
35 et al., 2015). Glacier retreat impacts Andean pastoralists (high confidence), as shown in Case Study 2.6.5.4.
36
37 NWS houses several global priority areas for biodiversity conservation, including the Tropical Andes and
38 Tumbes-Chocó-Magdalena terrestrial biodiversity-rich spots (Cross-Chapter Paper 1.2.2; Manes et al., 2021)
39 . Biodiversity in Tropical Andes and Tumbes-Chocó-Magdalena is projected to suffer negative impacts
40 (medium confidence: medium evidence, high agreement) (Figure 12.9). Invasive plant species might benefit
41 from climate change in these hotspots (Wang et al., 2017a). Species distribution is changing upslope due to
42 increasing air temperature, leading to range contraction and local extinctions for highland species. Whereas,
43 lowland species are experiencing range contractions at the rear end and expansions in the frontend, including
44 vectors of diseases (high confidence) (Crespo-Pérez et al., 2015; Duque et al., 2015; Morueta-Holme et al.,
45 2015; Moret et al., 2016; Aguirre et al., 2017; Cuesta et al., 2017a; Seimon et al., 2017; Fadrique et al., 2018;
46 Tito et al., 2018; Zimmer et al., 2018; Cauvy-Fraunié and Dangles, 2019; Cuesta et al., 2019; Moret et al.,
47 2020; Rosero et al., 2021). Vegetation in summits of the northern Andes is particularly vulnerable because of
48 a high abundance of endemic species with narrow thermal niches, and lowland dispersal capacity in
49 comparison to the Central Andes (Cuesta et al., 2020).
50
51 The upper limit of alpine vegetation (paramo) shifted upslope 500 m in the Chimborazo (Morueta-Holme et
52 al., 2015). Yet, the upper forest limit (the ecotone between forest and alpine vegetation), is migrating at
53 slower rates, or not migrating at all (Harsch et al., 2009; Rehm and Feeley, 2015b), so it is expected to be a
54 major barrier to migration to several montane species, leading to population reductions and biodiversity
55 losses (Lutz et al., 2013; Rehm and Feeley, 2015a). Shifts in tree species distribution may result in decreased
56 above ground carbon stocks and productivity in tropical mountain forests (high confidence) (Feeley et al.,
57 2011; Duque et al., 2015; Fadrique et al., 2018; Duque et al., 2021), a biomass loss that will only be partially
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1 offset through increased recruitment and growth of lowland species migrating upslope. Water scarcity can
2 enhance tree mortality and decrease above ground carbon stocks (Álvarez-Dávila et al., 2017; McDowell et
3 al., 2020). Agricultural frontier of crops, as potatoes or maize, is going upwards (high confidence), following
4 the freezing level height upward displacement (Morueta-Holme et al., 2015; Skarbø and VanderMolen,
5 2016; Schauwecker et al., 2017; Vuille et al., 2018). Modelling exercises agree with the observed impacts in
6 species, ecosystem processes, crop impacts and related pests and diseases (high confidence) (Cernusak et al.,
7 2013; Tovar et al., 2013; Ramirez-Villegas et al., 2014; Ovalle-Rivera et al., 2015; van der Sleen et al., 2015;
8 Lowe et al., 2017). Agricultural options are changing as a result of intra seasonal temperature variation
9 (Ponce, 2020). Changes in timing and amount of precipitation are also impacting agriculture (Table 12.4;
10 Heikkinen, 2017; Altea, 2020) .
11
12 Species distribution is changing in dry lowland forests, where deforestation is the more intense driver and
13 climate change is intensely acting (Aguirre et al., 2017; Manchego et al., 2017). Extinctions in amphibians
14 have been related with temperature raises acting in synergy with diseases (Catenazzi et al., 2014). The
15 fungus Batrachochytrium dendrobatidis successfully accompanied and caused disease in high-elevation
16 Andean frogs as they expanded their ranges to reach 52005400 m (Seimon et al., 2017). Several groups of
17 freshwater species of the tropical Andes represent 35% of threatened freshwater species in the world
18 (Gardner and Finlayson, 2018). Potential impacts of species turnover in key areas for biodiversity
19 conservation have been identified (Cuesta et al., 2017b).
20
21 Climate change related hazards could foster rural poverty, and its impacts have led to the modification of
22 agriculture calendars and irrigation adjustments (Postigo, 2014). Livestock is reducing due to rising
23 temperatures, changing water flows and diminishing of pastures, particularly cattle and pig production
24 (Bayer et al., 2014; Tapasco et al., 2015; Bergmann et al., 2021). In some cases farmers respond to extreme
25 temperatures by increasing use of land and crop intensity (Aragón et al., 2021). Climate change has and will
26 prompt internal and international migrations (Løken, 2019; Bergmann et al., 2021). A change in fire regimes
27 and fire risk is expected in highland ecosystems, although it is difficult to determine the influence of human
28 activities and climate change influence on fire patterns (Oliveras et al., 2014; Oliveras et al., 2018;
29 Armenteras et al., 2020).
30
31 12.3.3 Northern South America (NSA) Sub-region
32
33 12.3.3.1 Hazards
34
35 A significant increase in the intensity and frequency of warm extremes and length of heat waves, and
36 decrease in the frequency of cold extremes (Skansi et al., 2013) was likely observed (Figure 12.6; Donat et
37 al., 2013; Almeida et al., 2017; WGI AR6 Table 11.13, Seneviratne et al., 2021). Precipitation showed
38 increasing trends in annual and wet season totals over the eastern part and decreasing trends of the dry
39 season (Almeida et al., 2017). Increase in the frequency of anomalous severe floods (Gloor et al., 2015) was
40 observed but insufficient data coverage for extreme precipitation and trends in available data result in low
41 confidence (Avila-Diaz et al., 2020; Dereczynski et al., 2020; Dunn et al., 2020; Sun et al., 2021) (WGI AR6
42 Table 11.14) (Seneviratne et al., 2021). Droughts presented mixed trends between subregions, but evidences
43 indicate increasing length of dry periods (low confidence) (Skansi et al., 2013; Marengo and Espinoza, 2016;
44 Spinoni et al., 2019; Avila-Diaz et al., 2020; Dereczynski et al., 2020; Dunn et al., 2020) (WGI AR6 Table
45 11.15) (Seneviratne et al., 2021) (WGI AR6 Table 12.3) (Ranasinghe et al., 2021).
46
47 An overall increase in temperature by the end of century is projected for all the seasons, from 2 to 6°C
48 depending on the scenario (Chou et al., 2014). Projections also suggest increases in the intensity and
49 frequency of hot extremes and decreases in the intensity and frequency of cold extremes (very likely for a
50 2ºC GWL) (López-Franca et al., 2016) (WGI AR6 Table 11.13) (Seneviratne et al., 2021). In all the region,
51 extreme maximum temperature estimates under the RCP4.5 scenario are projected to increase. Tropical
52 major cities are expected to be strongly affected by heat waves and daily record temperatures (Feron et al.,
53 2019).
54
55 A decrease in precipitation over the tropical region but regional changes, such as increases in rainfall
56 amounts in western NSA of up to 40 mm, are expected by mid-century under RCP8.5 (Teichmann et al.,
57 2013; Sánchez et al., 2015). Changes in the dry season in the central part of South America due to the late
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1 onset and late retreat of monsoon, decreases in precipitation over the Amazon and central Brazil are expected
2 (Coppola et al., 2014; Giorgi et al., 2014; Llopart et al., 2014). And with medium confidence: increase in the
3 frequency and geographic extent of meteorological drought in the eastern Amazon, and the opposite in the
4 west (Duffy et al., 2015). A decreasing of total annual precipitation, but increase in heavy precipitation
5 (Seiler et al., 2013; Chou et al., 2014) are projected for a 2ºC GWL (Figure 12.6; WGI AR6 Table 11.15;
6 Seneviratne et al., 2021).
7
8 Mean precipitation will decrease and heavy precipitation, aridity and drought will increase with medium
9 confidence, mean temperature, extreme heat, fire weather, coastal and oceanic climate impact drivers all of
10 them will increase with high confidence (Sun et al., 2019) (WGI AR6 Table 12.6; WGI AR6 Figure 12.8)
11 (Ranasinghe et al., 2021).
12
13 12.3.3.2 Exposure
14
15 In NSA the percentage of the national population living in Low Elevation Coastal Zones (LECZ) and
16 exposed to Sea Level Rise (SLR) is 68% for Suriname, 56% for Guyana and 6% Venezuela (Nagy et al.,
17 2019). In these countries, exposure of populations, land areas and built capital to coastal floods is projected
18 to continue and increase (Neumann et al., 2015; Reguero et al., 2015).
19
20 In the Amazon basin, approximately 80% of the population is concentrated in cities due to migrations in
21 search of improvements in education, job opportunities, health and goods and services (Eloy et al., 2015;
22 Pinho et al., 2015). These populations settle in areas prone to flooding combined with various levels of
23 sanitation due to limited economic access to areas of lower risk (Pinho et al., 2015; Mansur et al., 2016;
24 Andrade and Szlafsztein, 2018; Parry et al., 2018). In these areas, poor urban planning and high population
25 densities increase exposure levels (Mansur et al., 2016). In this context, 41% of the total population of urban
26 centres, of the Amazon Delta and Estuaries (ADE) are exposed to flooding (Mansur et al., 2016), while in
27 Santarem, population and infrastructure are highly exposed to floods and flash floods (Andrade and
28 Szlafsztein, 2018).
29
30 Exposure of the Brazilian Amazon to severe to extreme drought has increased from 8% in 2004/2005, to
31 16% in 2009/2010 and 16% in 2015/2016 (Anderson et al., 2018b); a similar trend is reported in other
32 regions (Table 12.3). During the extreme drought of 2015/2016 in the Amazonian forests 10% or more of the
33 area showed negative anomalies of the Minimum Cumulative Water Deficit (Anderson et al., 2018b). This
34 extreme drought also caused an increase in the occurrence and spread of fires in the basin (medium
35 confidence: medium evidence, high agreement) (Aragão et al., 2018; Lima et al., 2018; Silva Junior et al.,
36 2019; Bilbao et al., 2020).The exposure to anomalous fires in ecosystems such as savannas, more fire-prone,
37 increases the exposure and vulnerability of adjacent forest ecosystems not adapted to fire, such as seasonally
38 flooded forests (Bilbao et al., 2020; Flores and Holmgren, 2021).
39
40 12.3.3.3 Vulnerability
41
42 NSA is one of the most vulnerable subregions in the region, after CA, as evidenced by its very high
43 vulnerability in four of the six sectors assessed (Figure 12.7). LECZ of Venezuela, Guyana and Suriname are
44 highly vulnerable to climate change due to SLR (high confidence) (CAF, 2014; Mycoo, 2014; Reguero et al.,
45 2015; Villamizar et al., 2017; Nagy et al., 2019). In Guyana, the combined effect of increased rainfall
46 intensity and SLR has caused flooding over the past two decades, increasing the vulnerability of the
47 agriculture sector (Tomby and Zhang, 2019).
48
49 The unprecedented extreme events of floods (2009, 2012 and 2014) and drought (2010) in the Amazon basin
50 led to increased societies vulnerability (medium confidence: medium evidence, high agreement) (Mansur et
51 al., 2016; Debortoli et al., 2017; Marengo et al., 2018; Menezes et al., 2018). The disruption of the region
52 natural hydrology dynamics, as a consequence of extreme events increases the sensitivity of the food and
53 transport systems of the Indigenous Peoples and rural resource-dependent communities (Pinho et al., 2015).
54
55 Migration by Indigenous Peoples and rural resource-dependent communities to cities have increased due to
56 urbanization, development of extractive activities, agroindustry and infrastructure. Upon migrating, they are
57 forced to abandon their livelihoods in order to acquire temporary jobs and to live in poverty and exclusion
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1 conditions on the periphery of the city (Cardoso et al., 2018). Between 6090% of the population in the
2 urban centres of ADE live in conditions of moderate to high degree of vulnerability (Mansur et al., 2016)
3 (Figure 12.7). Amazon populations located in remote urban centres with limited or non-existing roads are
4 more vulnerable to extreme events in relation to more connected urban centres (Parry et al., 2018). These
5 highly vulnerable circumstances reduce the adaptive capacity of these populations (Cardoso et al., 2018).
6 Nevertheless, the dynamics of the adaptive capacity of the Indigenous Peoples and rural resource-dependent
7 communities is a complex issue. There is robust and growing literature showing that resource-dependent
8 communities located in remote areas, address climate anomalies by reducing the vulnerability of socio-
9 ecological systems through Indigenous knowledge and local knowledge (high confidence) (Mistry et al.,
10 2016; Vogt et al., 2016; Bilbao et al., 2019; Bilbao et al., 2020; Camico et al., 2021).
11
12 Amazonian forests constitute one of the major carbon (C) sinks on Earth (Pan et al., 2011), playing a pivotal
13 role in the climate system and regional balance of C and water (Marengo et al., 2018; Molina et al., 2019).
14 Deforestation, temperature increase and any factor affecting the forests ecosystem dynamics will have an
15 impact on the atmospheric CO2 concentration and hence on the global climate (Ruiz-Vásquez et al., 2020;
16 Sullivan et al., 2020).There is robust scientific evidence of the high vulnerability of the Amazonian forests
17 to increasing temperature and repeated extreme drought events (high confidence) (Figure 12.7; Brienen et al.,
18 2015; Olivares et al., 2015; Feldpausch et al., 2016; Zhao et al., 2017; Anderson et al., 2018b; Anjos and De
19 Toledo, 2018; Yang et al., 2018; Barkhordarian et al., 2019; Sampaio et al., 2019; Rammig, 2020; Sullivan et
20 al., 2020) .
21
22 12.3.3.4 Impacts
23
24 Suriname has experienced coastal erosion and flooding, causing damage to infrastructure, agriculture and
25 ecosystems while Georgetown has suffered a significant number of floods (CAF, 2014). In Guyana, coastal
26 flooding has negatively impacted agricultural activity (Tomby and Zhang, 2018) (Figure 12.9). Sugarcane
27 production has been one of the most impacted cash-crops. The impact on sugar production has affected
28 Guyana's sugar industry (Tomby and Zhang, 2019). Among the main impacts observed in the sugar industry
29 are an increase in production costs, greater use of pesticides and fertilizers, and a reduction in workers'
30 income (Tomby and Zhang, 2018).
31
32 Indigenous Peoples and resource-dependent rural communities in the Amazon have been impacted over the
33 last decade by extreme drought and flood events in various dimensions of their livelihoods (Pinho et al.,
34 2015). Food security has been strongly impacted since it is based on fishing and small-scale agriculture, two
35 sectors highly vulnerable to climate change. During extreme events, fishing decreases due to limited access
36 to fishing grounds (medium confidence: low evidence, high agreement) (Figure 12.9; Pinho et al., 2015;
37 Camacho Guerreiro et al., 2016. Overfishing, deforestation and dam construction are a threat to fishing in the
38 subregion (Lopes et al., 2019) and therefore contribute to exacerbating the impacts of climate change. Small
39 scale agriculture practices (e.g., floodplain agriculture and slash and burn), are highly coupled with natural
40 hydrological cycles and therefore severely affected by extreme events (Figure 12.9; Cochran et al., 2016.
41 Livelihoods are also impacted by disruptions in land and river transport, restrictions in drinking water access,
42 increased incidence of forest fires and disease outbreaks (medium confidence: medium evidence, high
43 agreement) (Figure 12.9; Marengo et al., 2013; Pinho et al., 2015; Marengo and Espinoza, 2016; Marengo et
44 al., 2018). In addition, flood events have caused losses of homes and disruption of public and commercial
45 services (Figure 12.9; Parry et al., 2018).
46
47 Several vector-driven diseases such as malaria and leishmaniasis are endemic of Amazon region, however
48 socio-environmental changes are altering their natural dynamics (Confalonieri et al., 2014b). An important
49 relationship between the outbreak of infectious diseases and changes in climatic events (e.g., droughts,
50 floods, heat waves, ENSO) or environmental events (e.g., deforestation, dam construction and habitat
51 fragmentation) have been found for the Brazilian Amazon (medium confidence: medium evidence, high
52 agreement) (Pan et al., 2014; Filho et al., 2016; Nava et al., 2017; Ellwanger et al., 2020). These impacts are
53 more severe in poor populations with limited access to health services (Pan et al., 2014; WHO and
54 UNFCCC, 2020). In the case of Venezuela, the impact of climate change on the epidemiology of malaria has
55 been studied, showing significant influence on transmission in the Amazonia area of the country (Figure
56 12.4; Laguna et al., 2017) . Other studies from Venezuela have documented the role of ENSO in dengue
57 outbreaks (Vincenti-Gonzalez et al., 2018). Table 12.1 shows the changes observed in reproduction potential
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1 for dengue in the different subregions due to changes in rainfall and temperature. Forest fires are a major
2 concern to public health in the region as they relate to an increase in hospital admissions due to respiratory
3 problems, mainly among children and the elderly (Figure 12.5). The amount of air pollutants detected is
4 sometimes higher than that observed in large urban areas, especially during dry seasons when biomass
5 burning increases (Aragão et al., 2016; de Oliveira Alves et al., 2017; Paralovo et al., 2019).
6
7
8 Table 12.1: Environmental suitability for the transmission of dengue by Aedes aegypti as modelled by the influence of
9 temperature and rainfall on vectorial capacity and vector abundance; this is overlaid with human population density data
10 to estimate the reproduction potential for these diseases (R0, the expected number of secondary infections resulting from
11 one infected person). The Southwest South America (SWS) and Southern South America (SSA) subregions are not
12 presented, as the vector is not abundant in these areas and the estimated R0 is lower than 0.01. Data derived from
13 Romanello et al. (2021).
Subregion Average R0 Average R0 Absolute change in % change in R0
1950-1954 2016-2020 R0 from 1950-54 to from 1950-54 to
2016-20 2016-21
Central America (CA) 3.00 3.53 0.53 18%
Northwest South America (NWS) 1.85 2.40 0.55 30%
Northern South America (NSA) 1.31 2.05 0.74 56%
South America Monsoon (SAM) 0.93 1.67 0.74 80%
Northeast South America (NES) 2.11 2.47 0.36 17%
Southeast South America (SES) 0.64 0.81 0.17 26%
14
15
16 Climate change impacts have also been observed in ocean, coastal ecosystems (coral reefs and mangroves),
17 Exclusive Economic Zones (EEZ) and saltmarshes in NSA; further impacts are expected in coral reefs,
18 estuaries, mangroves and EEZs in the sub-region (Figure 12.9). Species in freshwater ecoregions (e.g., the
19 Orinoco and Amazon Rivers and their flooded forests) are predicted to suffer a decrease in range and
20 climatic suitability (medium confidence: low evidence, high agreement) (Cross-Chapter Paper 1.2.3; Manes
21 et al., 2021) . A significant decrease in climate refugia (90%) for multiple vertebrate and plant species in the
22 region has been projected for a 4ºC scenario, with considerable benefits of mitigation and reducing risks to
23 40% for a 2oC scenario (Warren et al., 2018).
24
25 Droughts in 2009/2010 and 2015/2016 increased tree mortality rate in Amazon forests (Doughty et al., 2015;
26 Feldpausch et al., 2016; Anderson et al., 2018b), while productivity didn't show a consistent change; some
27 authors report a drop in productivity (Feldpausch et al., 2016) and others found no significant changes
28 (Brienen et al., 2015; Doughty et al., 2015). Nevertheless the combined effect of increasing tree mortality
29 with variations in growth, results in a long-term decrease in C stocks in forest biomass compromising their
30 role of these forests as C sink (high confidence) (Brienen et al., 2015; Rammig, 2020; Sullivan et al., 2020)
31 (Figure 12.9). Under the RCP8.5 scenario for 2070, drought will increase the conversion of rainforest to
32 savannahs (medium confidence: medium evidence, high agreement) (Anadón et al., 2014; Olivares et al.,
33 2015; Sampaio et al., 2019). The transformation of rainforest into savannahs brings forth biodiversity loss
34 and alterations in ecosystem functions and services (medium confidence: medium evidence, high agreement)
35 (Anadón et al., 2014; Olivares et al., 2015; Sampaio et al., 2019). In the Amazon basin, the synergic effects
36 of deforestation, fire, expansion of the agricultural frontier, infrastructure development, extractive activities,
37 climate change and extreme events may exacerbate the risk of savannisation (medium confidence: medium
38 evidence, high agreement) (Nobre et al., 2016b; Bebbington et al., 2019; Sampaio et al., 2019; Rammig,
39 2020).
40
41 12.3.4 South America Monsoon (SAM) Sub-region
42
43 12.3.4.1 Hazards
44
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1 Temperature extremes have likely increased in the intensity and frequency of hot extremes and decrease in
2 the intensity and frequency of cold extremes (Donat et al., 2013; Bitencourt et al., 2016) (WGI AR6 Table
3 11.13) (Seneviratne et al., 2021). In a vast transition zone between the Amazon and the Cerrado Biomes
4 within the region, analysis of seasonal precipitation trends suggested that almost 90% of the observational
5 sites showed reduced in the length of the rainy season in the region (Debortoli et al., 2015), on a period from
6 1971 to 2014 (Marengo et al., 2018), confirming the growth in length of the dry season. Changes in the
7 hydrological and precipitation regimes, characterized by reduction in rainfall in Southern Amazonia,
8 contrasting to an increase in the northwest Amazonia, and overall increases in extreme precipitation and in
9 the frequency of Consecutive Dry Days, is being reported by several authors (Fu et al., 2013; Almeida et al.,
10 2017; Marengo et al., 2018; Espinoza et al., 2019a) with low confidence (WGI AR6 Table 11.14;
11 Seneviratne et al., 2021) due to insufficient data coverage and trends in available data generally not
12 significant.
13
14 The Amazon has been identified as one of the areas of persistent and emergent regional climate change
15 hotspots in response to various representative concentration pathways (Diffenbaugh and Giorgi, 2012). In
16 Bolivia, CMIP3/5 models projected an increase in temperature (2.5ºC5.9ºC), with seasonal and regional
17 differences. In the lowlands, both ensembles agreed on less rainfall (19%) during drier months (June
18 August and SeptemberNovember), with significant changes in inter-annual rainfall variability, but
19 disagreed on changes during wetter months (JanuaryMarch) (Seiler et al., 2013). As a consequence of
20 higher temperatures and reduced rainfall, an increased water deficit would be expected in the Brazilian
21 Pantanal (Marengo et al., 2016; Bergier et al., 2018; Llopart et al., 2020) with high confidence. The largest
22 increases in warmer days and nights, and aridity, drought and significant increases in fire occurrence are
23 calculated over the Amazon area (Huang et al., 2016). Over all the region, by mid-century (RCP4.5) there is
24 medium confidence of increase of river and pluvial floods, aridity and mean wind speed, and extreme heat,
25 fire weather and drought are projected to increase with high confidence (WGI AR6 Table 12.6; Ranasinghe
26 et al., 2021).
27
28 12.3.4.2 Exposure
29
30 A large expansion in cropland area (soybean, corn and sugarcane) was observed in the past two decades in
31 SAM, in response to an increased local and global demand for biofuels and agricultural commodities (high
32 confidence) (Lapola et al., 2014; Cohn et al., 2016). Feedbacks to the climate system resulting from such
33 land-use changes are intricate. The clear-cutting of Amazon forest and Cerrado savannah in the region lead
34 to a local warming due to an increase in the energy balance and evapotranspiration (Malhado et al., 2010),
35 contrastingly the replacement of pasture by agriculture leads to local cooling effect, due to changes in the
36 surface albedo (medium confidence: medium evidence, medium agreement). Deforestation of the Amazon for
37 pastures and soybean have decreased evapotranspiration during drought months and caused a localized
38 lengthening of the dry season in Northwest SAM by 6.5 (± 2.5) days since 1979 (medium confidence:
39 medium evidence, medium agreement) (Fu et al., 2013).
40
41 It is not surprising therefore that while SAM is the region in CSA that experienced the highest temperature
42 increase in the last century, it is where most of the fire spots in the sub-continent are located, owing also to
43 the prevalent use of fires in pasture lands (medium confidence: medium evidence, high agreement) (Bowman
44 et al., 2009). Recently, da Silva Junior et al. (2020) reported 6,708,350 and 6,188,606 fire foci in Cerrado
45 and Amazonia, between 1999 and 2018, corresponding to 80% of the total observed in Brazil. The
46 occurrence of extreme droughts has affected the carbon and water cycles in large areas of the Amazon Forest
47 (high confidence) (Lapola et al., 2014; Agudelo et al., 2019), in particular in its southern and eastern
48 portions, where deforestation rates are higher. The loss of carbon in the Amazon region considering the
49 combined effect of land use change in the southern portion of the region, bordering Cerrado and Pantanal,
50 and global carbon emission scenarios, can be up to 38% at 4ºC of warming, but limited to 8% if the Paris
51 agreed limit of 1.5°C is achieved (medium confidence, medium evidence, high agreement) (Burton et al.,
52 2021), driving the region to be a net carbon source to the atmosphere (Gatti et al., 2021). A recent extreme
53 drought was estimated to affect the photosynthetic capacity of 400,000 km2 of the forest (Anderson et al.,
54 2018b), nevertheless there are considerable uncertainties regarding the effects of CO2 fertilization in tropical
55 forests and ecosystems (medium confidence: medium evidence, high agreement) (Sampaio et al., 2021).
56 Extreme drought events increase forest vulnerability to fire, directly affecting the biodiversity, the forest
57 structure and its plant species distribution (high agreement) (Brando et al., 2014). Production sectors are also
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1 exposed. SAM is pointed out as a region where agricultural production will be especially impacted by
2 climate change, affecting production of annual crops, fruits and livestock (medium confidence: medium
3 evidence, high agreement) (Lapola et al., 2014; Zilli et al., 2020).
4
5 12.3.4.3 Vulnerability
6
7 The largest expanses of remaining vegetation in the Cerrado biome are located in SAM, but the region shows
8 low number of protected areas (only 7.5% inside protected areas), which will leave fauna and flora with little
9 room for moving across the landscape in the face of climate change. Protected areas --Indigenous lands
10 included-- have markedly detained forest clear-cutting in the Amazon deforestation arc (most of which is
11 inside SAM) (high confidence) (Nolte et al., 2013). However nearly one hundred protected areas in the
12 Amazon, Cerrado and Pantanal biomes inside SAM have been identified as highly or moderately vulnerable
13 to future climate change and demand deep adaptation interventions (medium confidence: medium evidence,
14 high agreement) (Feeley and Silman, 2016; Lapola et al., 2019b). Yet, the maintenance of these protected
15 areas or even the halting of deforestation may do little to impede a large-scale ecosystem shift, persistently,
16 to an alternative state (crossing a tipping point) of the Amazon forest or even more subtle changes caused by
17 climate change in the region (medium confidence: medium evidence, high agreement) (Aguiar et al., 2016a;
18 Boers et al., 2017; Lapola et al., 2018; Lovejoy and Nobre, 2018).
19
20 The agriculture in the region is highly dependent on the climate (high confidence), responsible for ¾ of the
21 variability in agricultural yields in the region (Table 12.4). Irrigation is an important strategy for agriculture
22 production in part of the region, nevertheless not accounting to more than 8% of the total agricultural area in
23 South America and 7% in Central America (OECD and FAO, 2019). This practice faces potential impacts
24 from reduction in surface water availability in future climate scenarios (Ribeiro Neto et al., 2016; Zilli et al.,
25 2020), enhanced by non-climate drivers such as land use changes (medium confidence: medium evidence,
26 high agreement) (Spera et al., 2020). The remaining fluctuation on yields relates to issues of infrastructure,
27 market, economy, policy and social aspects. Good infrastructure, transport logistics, quality of roads and
28 storage, strongly influences the vulnerability of the agriculture sector (Figure 12.7).
29
30 The combined effect of extreme climate events and ecosystem fragmentation, e.g., by deforestation or fire,
31 lead to changes in forest structure, with the death of taller trees and reduction in diversity of plant species,
32 loss of productivity and carbon storage (high agreement) (Brando et al., 2014; Reis et al., 2018). The rise of
33 the large-scale soybean agroindustry in the early 2000's led to a faster increase in human development
34 indicators in some regions, tightly linked to the agricultural production chain (high confidence) (Richards et
35 al., 2015). Such a development also came at a considerable cost for the environment (e.g., Neill et al. (2013))
36 and the regional climate, even though a moratorium implemented in 2006 to refrain new soy plantations on
37 deforested areas reduced deforestation by a factor of five (high confidence) (Macedo et al., 2012; Kastens et
38 al., 2017). The same sort of supply chain interventions along with incentive-based public policies applied to
39 the beef supply chain could minimize the need for agricultural expansion in the SAM deforestation frontier
40 (medium confidence: medium evidence, high agreement) (Nepstad et al., 2014; Pompeu et al., 2021).
41
42 SAM has a low population density, and the majority of population is located in cities. The population of
43 some of these cities are indicated as highly vulnerable considering the enormous social inequalities
44 embedded in these cities (high confidence) (Filho et al., 2016). Inequalities and uneven access to
45 infrastructure, housing and health support, increase population vulnerability to atmospheric pollution and
46 drier conditions (high confidence) (Rodrigues et al., 2019; IPAM, 2020; Machado-Silva et al., 2020).
47
48 12.3.4.4 Impacts
49
50 The Amazon and the Cerrado are amongst the largest and unique phytogeographical domains in South
51 America. The Brazilian Cerrado is amongst the richest biodiversity in the world, with more than 12,600 plant
52 species, being 35% endemic (high confidence) (Forzza et al., 2012). Historic land cover change and
53 concurrent climate change in the region strongly impacted the biodiversity and led to the extinction of 657
54 plant species for the Cerrado, which is more than four-fold the global recorded plant extinctions (high
55 confidence) (Strassburg et al., 2017; Green et al., 2019). Effects of climate change, expressed by drought and
56 heat waves, lead to plant stress, compromising growth and increasing mortality (Yu et al., 2019). The fauna
57 dependent on dew water was strongly impacted due to a temperature rise of 1.6ºC from 1961 to 2019
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1 (medium confidence: medium evidence, medium agreement) (Hofmann et al., 2021). Modelling outcomes
2 project impacts in forest ecosystems in the region, with persistent warming and significant moisture
3 reduction (Anjos et al., 2021), leading to a potential change in the ecosystem structure and distribution in the
4 region (medium confidence: medium evidence, medium agreement) (Government of Brazil, 2020).
5
6 The observed impact on plant species in SAM is projected to worsen in a warmer world (Warszawski et al.,
7 2013). An increasing dominance of drought-affiliated genera of tree species has been reported in the
8 southern part of the Amazon forest in the last 30 years (medium confidence: medium evidence, medium
9 agreement) (Esquivel-Muelbert et al., 2019). Due to the tight relation of drought and fire occurrence, an
10 increase of 39 to 95% of burned area is modelled to impact the Cerrado region under RCP4.5 and RCP8.5,
11 while under RCP2.6, a 22% overshoot in temperature is estimated to impact the area in 2050 decreasing to
12 11% overshoot by 2100 (Silva et al., 2019d), leading to high impact on agriculture production (high
13 confidence).
14
15 SAM hosts the headwaters of important SA rivers such as the Paraguay, Madeira, Tocantins-Araguaia and
16 Xingu. The impact from climate change is expressed differently among several sub-regions. Extreme floods
17 in Southern Amazon and Bolivian Amazon floodplains were described and related to exceptionally warm
18 subtropical South Atlantic ocean (high confidence) (Espinoza et al., 2014), causing high economic impact
19 (losses in crop and livestock production and infrastructure) and number of fatalities (very high confidence)
20 (Ovando et al., 2016). Contrastingly, decline in stream flow, particularly in the dry season, expressed by the
21 ratio between runoff and rainfall, is observed for the southern part of the Amazon basin (high evidence)
22 (Molina-Carpio et al., 2017; Espinoza et al., 2019b; Heerspink et al., 2020). Observed precipitation reduction
23 in the Cerrado region impacted main water supply reservoir for important cities in the Brazilian central
24 region, leading to a water crisis in 2016/2017 (Government of Brazil, 2020) and affecting energy
25 hydropower generation (Ribeiro Neto et al., 2016). Modelling studies project decreases in river discharge
26 rate in the order of 27% for the Tapajós basin and 53% for the Tocantins-Araguaia basin for the end of the
27 century, which may affect freshwater biodiversity, navigation and generation of hydroelectric power
28 (medium confidence: medium evidence, high agreement) (Marcovitch et al., 2010; Mohor et al., 2015). This
29 region also holds one of the largest floodplains in the globe, the Pantanal. The climatic connection of
30 Pantanal regions to the Amazon, and the influence of deforestation in local precipitation (Marengo et al.,
31 2018) has implications for conservation of ecosystem services and water security in Pantanal (high
32 confidence) (Bergier et al., 2018). Impacts of extreme drought, with increasing numbers of dry days, and
33 peak of fire foci was recently reported (robust evidence) (Lázaro et al., 2020; Garcia et al., 2021). Projected
34 impacts of climate change shall lead to profound changes in the annual flood dynamics for the Pantanal
35 wetland, altering ecosystem functioning and severely affecting biodiversity (high confidence) (Thielen et al.,
36 2020; Marengo et al., 2021)
37
38 Soybean and corn yields, in the Cerrado region, will suffer one of the strongest negative impacts under
39 RCP4.5 and RCP8.5 scenarios estimate and will demand high investments for adaptation should it continue
40 to be cultivated in the same localities as today (high confidence) (Oliveira et al., 2013; Camilo et al., 2018).
41 Changes in precipitation patterns were related to reduction of agriculture productivity and revenues in the
42 southern portion of the Amazon region (medium confidence: medium evidence, high agreement) (Costa et
43 al., 2019; Leite-Filho et al., 2021). As such, the future socio-economic vigour of the region will be, to a large
44 extent, connected to an unlikely stability of the regional climate and eventual fluctuations of global markets
45 potentially affecting the agricultural supply chain (high confidence) (Nepstad et al., 2014).
46
47 Observations from recent past droughts in SAM indicates how the incidence of respiratory diseases may
48 worsen under a drier and warmer climate. Northwest SAM had a ~54% increase in the incidence of
49 respiratory diseases associated with forest fires during the 2005 drought compared to a no-drought 10-year
50 mean (high confidence) (Ignotti et al., 2010; Pereira et al., 2011; Smith et al., 2014). It is estimated that more
51 than 10 million people are exposed to forest fires in the deforestation arc, a region comprising several
52 Brazilian states in the southern and western parts of the Amazon forest, with several impacts on human
53 health including potential exacerbation the COVID-19 crisis in Amazonia (medium confidence: medium
54 evidence, high agreement) (de Oliveira et al., 2020) (Table 12.5). Increases in hospital admissions, asthma,
55 DNA damage and lung cell death due to inhalation of fine particulate matter, represents an increase in public
56 health system costs (high confidence) (Ignotti et al., 2010; Silva et al., 2013; de Oliveira Alves et al., 2017;
57 Machin et al., 2019).The patchy landscape created by forest clearing contribute to a rising risk of zoonotic
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1 disease emergence by increasing interactions between wildlife, livestock and humans (medium confidence:
2 low evidence, medium agreement) (Dobson et al., 2020; Tollefson, 2020). Recent studies also suggested the
3 influence of climate change in zoonotic diseases, such as Orthohantavirus and Chapare virus infections,
4 rodent-borne diseases, in some areas of Bolivia (Escalera-Antezana et al., 2020a; Escalera-Antezana et al.,
5 2020b). Extreme fluctuation in the river level in the amazon was associated to a significant increase in the
6 incidence of diarrhoea, leptospirosis and dermatitis (de Souza Hacon et al., 2019; Government of Brazil,
7 2020). A comprehensive characterization of future heatwaves, and alternative RCPs scenarios, Brazilian
8 urban areas at SAM region are projected to face increasing related mortality from 400 to 500% in the period
9 from 2031 to 2080 compared to the period of 19712020, under the highest emission scenario and high-
10 variant population scenario (medium confidence: low evidence, medium agreement) (Guo et al., 2018). Table
11 12.2 shows the increase in days of exposure to heatwaves already observed in the region.
12
13
14 Table 12.2: Average change in the mean number of days exposed to heatwaves (defined as a period of at least two days
15 where both the daily minimum and maximum temperatures are above the 95th percentile of their respective climatologies)
16 in the population over 65 years of age in 2016-2020 relative to 1986-2005. Temperature data taken from the European
17 Centre for Medium-Range Weather Forecasts (ECMWF) ERA5 dataset; calculations derived from Romanello et al.
18 (2021).
Country Number of additional days of
heatwave exposure in 2016-
2020 relative to 1986-2005
Argentina 4.9
Belize 8.8
Bolivia 2.2
Brazil 3.1
Chile 3.3
Colombia 9.3
Costa Rica 0.8
Ecuador 7.6
El Salvador 2.2
Guatemala 8.4
Guyana 8.2
Honduras 11.2
Nicaragua 2.2
Panama 2.6
Paraguay 2.6
Peru 3.6
Suriname 15.2
Uruguay 2.7
Venezuela 8.5
19
20
21 The high risk of floods (high-frequency and high-incurred damage) is centred in the Brazilian states of Acre,
22 Rondônia, Southern Amazonas and Pará (Andrade et al., 2017). Global-scale studies indicate an increase of
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1 flood risk for the SAM region during the 21st century (consistent with floods that are more frequent) (high
2 confidence) (Hirabayashi et al., 2013; Arnell et al., 2016; Alfieri et al., 2017). Higher emission scenarios
3 result in substantially higher flood risks than low emission scenarios (Alfieri et al., 2017).
4
5 12.3.5 Northeast South America (NES) Sub-region
6
7 12.3.5.1 Hazards
8
9 The region has likely experienced an increase in temperature, with significant increases in the intensity and
10 frequency of hot extremes and significant decreases in the intensity and frequency of cold extremes (Donat et
11 al., 2013) (WGI AR6 Table 11.13, Seneviratne et al., 2021).
12
13 A decrease in the frequency and magnitude of extreme precipitation was observed but with low confidence,
14 due to insufficient data coverage and trends in available data generally not significant. An increase in
15 drought duration was observed with high confidence but medium confidence on the increase of drought
16 intensity (WGI AR6 Table 11.14, Seneviratne et al., 2021). Table 12.3 shows the estimates of changes in
17 land area per subregion affected by drought events, being this subregion which presented the highest changes
18 in CSA.
19
20
21 Table 12.3: Change in the percentage of land area affected by extreme drought in 2010-19, with respect to 1950-59
22 using the Standardised Precipitation-Evapotranspiration Index (SPEI); extreme drought is defined as SPEI -1.6
23 (Federal Office of Meteorology and Climatology MeteoSwiss, 2021). Data derived from Romanello et al. (2021).
Average change in the percentage of land area in drought in 2010-19
with respect to 1950-59
Subregion At least 1 month in At least 3 months in At least 6 months in
drought
drought drought
Central America (CA) 38.8% 17.6% 6.1%
Northwest South America (NWS) 51.8% 25.3% 7.0%
Northern South America (NSA) 52.5% 18.3% 2.5%
South America Monsoon (SAM) 48.0% 34.4% 12.2%
Northeast South America (NES) 64.5% 38.4% 12.0%
Southeast SouthAmerica (SES) 16.4% 6.7% 0.4%
Southwest South America (SWS) 20.5% 13.9% 7.5%
Southern South America (SSA) -23.5% -8.8% --
24
25
26 The projected warming for the extreme annual maximum temperatures over NES is TXx: +2°C for the 1.5°C
27 scenario and about +2.5°C for 2°C scenario (Hoegh-Guldberg et al., 2018). An increased number of tropical
28 nights with minimum temperatures exceeding the 20°C threshold is projected (Orlowsky and Seneviratne,
29 2012). In general, extreme heat will increase and cold spells decrease with high confidence. A decrease in
30 total precipitation is projected with high confidence with an increase in heavy precipitation events and an
31 increase in dryness (medium confidence). Increase in drought severity due to the combination of increased
32 temperatures, less rainfall, and lower atmospheric humidity (5 to 15% relative humidity reduction) create
33 water deficits, projected for the entire region after 2041 (34 mm day-1 reduction), particularly over western
34 NES and over the semiarid region (Marengo and Bernasconi, 2015; Marengo et al., 2017). Fire will
35 significantly increase (high confidence) (Figure 12.6).
36
37 12.3.5.2 Exposure
38
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1 NES is home to about 60 million people (estimate from IBGE (2019)), with >70% living in urban areas (data
2 from IBGE (2010); Silva et al. (2017)), and high poverty levels (> 50%, data from IBGE (2003)). People are
3 exposed to intense drought and famine (high confidence), and about 94% of the region has moderate to high
4 susceptibility to desertification (Marengo and Bernasconi, 2015; Spinoni et al., 2015; Vieira et al., 2015;
5 Mariano et al., 2018; Tomasella et al., 2018; Marengo et al., 2020c). The most severe dry spell of 2012
6 2013 affected about 9 million people, which were exposed to water, food and energy scarcity (Marengo and
7 Bernasconi, 2015).
8
9 People, infrastructure and economic activities are exposed to sea level rise in the 3800 km of coastline
10 (medium confidence). The high concentration of cities on the coast is a concern (Martins et al., 2017), with
11 all state capital cities but one on the coast, totalling almost 12 million exposed people (estimate from IBGE
12 (2019)). The ports of São Luís, Recife and Salvador are important exporters of Brazilian commodities, and
13 the beaches in the subregion are an international touristic destination, producing considerable revenues
14 (Pegas et al., 2015; Ribeiro et al., 2017).
15
16 Natural systems in NES are also exposed to climate change. In terrestrial ecosystems, 913,000 km2 of NES'
17 dry forest Caatinga vegetation (Silva et al., 2017) is exposed to predicted increase in dryness. Despite what
18 has been previously suggested, the Caatinga has high biodiversity and endemism (Silva et al., 2017), which
19 is exposed to habitat reduction due to climate change and agriculture expansion (Silva et al., 2019b). Fifty-
20 two percent of the freshwater fish (203 species) are endemic (Lima et al., 2017) and are exposed to predicted
21 reduction in river flow due to climate change (Marengo et al., 2017; de Jong et al., 2018). The coastal waters
22 contain a separate marine ecoregion due to its uniqueness (Spalding et al., 2007). The region is responsible
23 for 99% of the Brazilian shrimp production, exposed to sea level rise and increases in ocean temperature and
24 acidification (Gasalla et al., 2017). Most coral reefs in the Southern Atlantic Ocean are along NES's coast
25 (Leão et al., 2016), increasing its conservation and touristic value. The 685 km2 of coral reefs along NES's
26 coast (likely underestimated - Moura et al. (2013); UNEP-WCMC et al. (2018)) are exposed to increased
27 sea temperatures.
28
29 12.3.5.3 Vulnerability
30
31 NES is the world's most densely populated semi-arid land and its population is highly vulnerable to droughts
32 (high confidence), which have well-documented impacts on water and food security, human health and well-
33 being in the region (e.g., Confalonieri et al. (2014a); Marengo et al. (2017); Bedran-Martins et al. (2018))
34 (Figure 12.7). The region's relative low economic development and poor social and health indicators
35 increase vulnerability, especially of poor farmers and traditional communities (Confalonieri et al., 2014a;
36 Bech Gaivizzo et al., 2019). In state capital cities, about 45% of the population live in poverty (data from
37 IBGE (2003)), often in slums with already deficient water supply and sewage systems and poor access to
38 health and education. Climate change will increase pressures on water availability, threatening water, energy
39 and food security (Marengo et al., 2017).
40
41 Natural systems in NES are also vulnerable (Figure 12.7). The Caatinga vegetation is particularly sensitive to
42 variations in water availability and climate change (Seddon et al., 2016; Rito et al., 2017; Dantas et al.,
43 2020). It has already lost about 50% of its original vegetation cover (Souza et al., 2020), with only about 2%
44 of the remaining vegetation within fully protected areas (CNUC and MMA, 2020). Caatinga's high
45 vulnerability to climate change is further increased by the extensive conversion of native vegetation (high
46 confidence) (Rito et al., 2017; Silva et al., 2019b; Silva et al., 2019c).
47
48 Studies with terrestrial animals show that habitat loss increases the vulnerability of species to climate change
49 (high confidence) (de Oliveira et al., 2012; Arnan et al., 2018; da Silva et al., 2018b). NES' coral reefs have
50 shown some resilience to bleaching, but vulnerability is intensified by the synergism between chronic heat
51 stress caused by increased sea surface temperature (Teixeira et al., 2019) and other well-documented
52 stressors, such as coastal runoff, urban development, marine tourism, overexploitation of reef organisms and
53 oil extraction (high confidence) (Figure 12.8; Leão et al., 2016).
54
55 12.3.5.4 Impacts
56
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1 Impacts of intense drought have been reported in NES since 1780, with severe losses in agricultural
2 production, livestock death, increase in agricultural prices, and human death (Figure 12.9; Marengo et al.,
3 2017; Martins et al., 2019; Government of Brazil, 2020; Marengo et al., 2020c; Silva et al., 2020) (). The
4 rural population already suffers from natural water scarcity in the countryside. In 2012, the drought was
5 responsible for reducing up to 99% of the corn production in Pernambuco state (Government of Brazil,
6 2020). A predicted increase in drought, coupled with inadequate soil management practices by small farmers
7 and agribusiness, increases the region's susceptibility to desertification (Spinoni et al., 2015; Vieira et al.,
8 2015; Mariano et al., 2018; Tomasella et al., 2018; Marengo et al., 2020c). In NES, 70,000 km2 have reached
9 a point at which agriculture is no longer possible (Government of Brazil, 2020). Intense droughts has
10 triggered migration to urban centres in and outside NES (Confalonieri et al., 2014a; Government of Brazil,
11 2020). More than 10 million people have been impacted by the drought of 2012/14 in the region, which was
12 responsible for water shortage and contamination, increasing death by diarrhoea (Marengo and Bernasconi,
13 2015; Government of Brazil, 2020).
14
15 There is growing evidence on the impacts of climate change on human health in NES, mostly linked to food
16 and water insecurity caused by recurrent long droughts (e.g., gastroenteritis and hepatitis) (high confidence)
17 (Figure 12.9; Sena et al., 2014; de Souza Hacon et al., 2019; Marengo et al., 2019; Government of Brazil,
18 2020; Salvador et al., 2020) . From 2071 to 2099, thermal conditions in NES might improve for vectors of
19 dengue, chikungunya and Zika (de Souza Hacon et al., 2019). Additionally, a high risk of mortality
20 associated with climatic stress in the period 20712099 is expected in São Francisco river basin (de Oliveira
21 et al., 2019; de Souza Hacon et al., 2019).
22
23 Recent studies predict strong negative impact of climate change on NES' agriculture (high confidence)
24 (Ferreira Filho and Moraes, 2015; Nabout et al., 2016; Gateau-Rey et al., 2018) (Figure 12.9; Table 12.4).
25 NES concentrates the bulk of the predicted loss of regional gross domestic product associated with
26 agriculture in Brazil (Ferreira Filho and Moraes, 2015; Forcella et al., 2015). Although agriculture gives a
27 modest contribution to the regions' economy, its drop could have a severe impact on the poorest rural
28 household, by shrinking the agricultural labour market and increasing food prices (Ferreira Filho and
29 Moraes, 2015; Government of Brazil, 2020). Expected increase in dryness is also predicted to impact the
30 region's hydroelectric power generation (Marengo et al., 2017; de Jong et al., 2018). Sea level rise has also
31 been reported to impact coastal cities such as Salvador, destroying urban constructions (Government of
32 Brazil, 2020). Sea level rise, increased ocean temperature and acidification may also negatively impact
33 NES's shrimp aquaculture production (Figure 12.8; Gasalla et al., 2017) . Along with climate change,
34 overfishing has driven exploited marine fish species to collapse (Verba et al., 2020).
35
36 Biodiversity in NES is highly threatened by climate change in terrestrial (medium confidence: medium
37 evidence, high agreement) and freshwater (low confidence: low evidence, high agreement) ecosystems
38 (Figure 12.9). There are few studies projecting the likely impact of climate change on NES' biodiversity,
39 especially on its endemic freshwater fish. Recent studies have already reported the reduction in several
40 endemic plant species affecting pollination and seed dispersal (Bech Gaivizzo et al., 2019; Cavalcante and
41 Duarte, 2019; Silva et al., 2019b). Studies with terrestrial animals predict that most groups would be
42 negatively impacted by climate change (de Oliveira et al., 2012; Arnan et al., 2018; da Silva et al., 2018b;
43 Montero et al., 2018). Changes in the abundance of coral reef community and extreme reduction in coral
44 cover have been observed in NES (de Moraes et al., 2019; Duarte et al., 2020). A number of observed coral
45 bleaching events associated with abnormal increase in sea temperatures have occurred in NES (Krug et al.,
46 2013; Leão et al., 2016; de Oliveira Soares et al., 2019) (Figure 12.8), but thus far mortality remained low
47 and corals have been able return to normal values or remain stable after sea water temperature rise (medium
48 confidence: medium evidence, high agreement) (Leão et al., 2016). Mangroves in the region have shown
49 increased mortality, but have also expanded their range inland (Figure 12.6; Godoy and Lacerda, 2015;
50 Cohen et al., 2018) . Future projections include mangrove landward expansion and lower migration rates by
51 2100 (Cohen et al., 2018).
52
53 12.3.6 Southeast South America (SES) Sub-region
54
55 12.3.6.1 Hazards
56
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1 The increase in the intensity and frequency of hot extremes and decrease in the intensity and frequency of
2 cold extremes was observed with high confidence (Rusticucci et al., 2017; Wu and Polvani, 2017) (WGI
3 AR6 Table 11.13) (Seneviratne et al., 2021). There is low confidence that the decrease in hot extremes over
4 SES is related with an increase of extreme precipitation (Wu and Polvani, 2017).
5
6 Over SES most of the stations have registered an increase in annual rainfall, largely attributable to changes in
7 the warm season; this is one of few sub-regions where a robust positive trend in precipitation and significant
8 intensification of heavy precipitation has been detected since the beginning of the 20th century (high
9 confidence) but with medium confidence in a reduction of hydrological droughts (Vera and Díaz, 2015;
10 Saurral et al., 2017; Lovino et al., 2018; Avila-Diaz et al., 2020; Carvalho, 2020; Dereczynski et al., 2020;
11 Dunn et al., 2020; Marengo et al., 2020a; Olmo et al., 2020) (WGI AR6 Table 11.14) (Seneviratne et al.,
12 2021). A higher observed frequency of extratropical cyclones in the region has been detected (Parise et al.,
13 2009; Reboita et al., 2018) with three cyclogenetic foci: South-southeast Brazil, extreme south of Brazil and
14 Uruguay, and southeast of Argentina.
15
16 In Montevideo, mean sea-levels increased over the past 20 years, reaching 11 cm from 1902 to 2016, and a
17 recent accelerating trend has been observed (Gutiérrez et al., 2016b). A value of water-level rise and its
18 acceleration for Buenos Aires was calculated from a record of annual mean water levels obtained from
19 hourly levels (19052003). Annual mean water level showed a trend of +1.7 ± 0.05 mm yr-1, and an
20 acceleration of +0.019 ± 0.005 mm yr-2 (D'Onofrio et al., 2008).
21
22 Increasing trends in mean air temperature and extreme heat, and decreasing cold spells are projected (high
23 confidence) (WGI AR6 Table 12.6Ranasinghe et al., 2021). The increase in the frequency of warm nights is
24 larger than that projected for warm days consistent with observed past changes that have been related with
25 changes in cloud cover that affect differently daytime temperatures as compared to night time temperatures
26 (López-Franca et al., 2016; Menéndez et al., 2016; Feron et al., 2019).
27
28 Increases in mean precipitation (high confidence), pluvial floods and river floods are projected (medium
29 confidence) (Nunes et al., 2018) (WGI AR6 Table 12.6) (Ranasinghe et al., 2021). Droughts in the La Plata
30 Basin will be more frequent in the medium-term (2011-2040) and the distant future (2071-2100) (with
31 respect to the 1979-2008 period), but also shorter and more severe, for the more extreme emission scenario
32 (RCP8.5) (low confidence) (Carril et al., 2016).
33
34 Negative trend in the annual number of cyclone events in the long-term future of 3.6 to 6.5% (2070-2098)
35 are projected, that showed an increase of 3 to 11% (2080-2100 for the A1B scenario) (Grieger et al., 2014;
36 Reboita et al., 2018). All coastal and oceanic climate impact drivers (relative sea level, coastal flood and
37 erosion, marine heatwaves and ocean aridity) are expected to increase by mid-century in the RCP8.5
38 scenario (high confidence) (WGI AR6 Table 12.6, Ranasinghe et al., 2021).
39
40 12.3.6.2 Exposure
41
42 Higher temperatures and rising sea levels, changes in rainfall patterns, increased frequency and intensity of
43 extreme weather events, could generate risks to the energy and the infrastructure sectors, and to the mining
44 and metals network. In the Plata basin, urban floods have become more frequent, causing infrastructure
45 damage and sometimes substantial mortality (high confidence) (Barros et al., 2015; Zambrano et al., 2017;
46 Nagy et al., 2019; Mettler-Grove, 2020; Morales-Yokobori, 2021; Oyedotun and Ally, 2021). A large
47 increase in landslides and flash floods is also predicted for the Brazilian portion of SES, where they are
48 responsible for the majority of the deaths related to natural disasters in the country (high confidence)
49 (Debortoli et al., 2017; Haque et al., 2019; Saito et al., 2019; Marengo et al., 2020d; da Fonseca Aguiar and
50 Cataldi, 2021). Due to uncontrolled urban growth, 21.5 million people living in the large Brazilian cities of
51 São Paulo, Rio de Janeiro and Belo Horizonte (estimate from IBGE (2019)) are expected to be exposed to
52 water scarcity, despite great water availability in the region (medium evidence, medium agreement)
53 (Marengo et al., 2017; Lima and Magaña Rueda, 2018; Marengo et al., 2020b).
54
55 The expected increase in temperature also exposes the population in large cities to extreme heat. Urban heat
56 islands are already a reality in large cities in the region, such as Buenos Aires (high confidence) (Wong et al.,
57 2013; Sarricolea and Meseguer-Ruiz, 2019; Wu et al., 2019; Mettler-Grove, 2020), Rio de Janeiro (high
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1 confidence) (Ceccherini et al., 2016; Neiva et al., 2017; Geirinhas et al., 2018; Peres et al., 2018; Sarricolea
2 and Meseguer-Ruiz, 2019; Wu et al., 2019; de Farias et al., 2021) and São Paulo (high confidence) (Mishra
3 et al., 2015; Barros and Lombardo, 2016; Ceccherini et al., 2016; Vemado and Pereira Filho, 2016; de
4 Azevedo et al., 2018; Lima and Magaña Rueda, 2018; Ferreira and Duarte, 2019; Lapola et al., 2019a;
5 Sarricolea and Meseguer-Ruiz, 2019; Wu et al., 2019), with reported impact on human health in the latter
6 (medium confidence: medium evidence, medium agreement) (e.g., Araujo et al. (2015); Son et al. (2016);
7 Diniz et al. (2020)). These cities alone represent 22 million people exposed to increased heat (estimate from
8 IBGE (2019) and from INDEC (2010)).
9
10 The sub-region presents a high frequency of occurrence of intense severe convection events (Section
11 12.3.6.1). Because of this situation, strong winds from the south or southeast and high water levels affect the
12 whole Argentine coast, as well as the Rio de la Plata shores, Uruguay, and southern Brazil (Isla and Schnack,
13 2009). The coast of the Plata River is subject to flooding when there are strong winds from the southeast
14 (sudestadas). As sea level rises as a result of global climate change, storm surge floods will become more
15 frequent in this densely populated area, particularly in low-lying areas (high confidence) (Figure 12.8;
16 D'Onofrio et al., 2008; Nagy et al., 2014a; Santamaria-Aguilar et al., 2017; Nagy et al., 2019 impacts and
17 adaptation in Central and South America coastal areas; Cerón et al., 2021) .
18
19 The region's natural systems are also exposed to climate change. SES region houses two important
20 biodiversity hotspots, with high levels of species endemism: the Cerrado and the Atlantic Forest, where
21 about 72% of Brazil's threatened species can be found (PBMC, 2014).
22
23 12.3.6.3 Vulnerability
24
25 The Rio de la Plata basing and the city of Buenos Aires are highly vulnerable to recurring floods, and the
26 increasing number of newcomers to the area reduce the collective cultural adaptation developed by older
27 neighbours (high confidence) (Barros, 2006; Nagy et al., 2019; Mettler-Grove, 2020; Morales-Yokobori,
28 2021; Oyedotun and Ally, 2021). Extreme events, including storm surges and coastal inundation/flooding
29 caused injuries and economic/environmental losses on the urbanized coastline of Southern Brazil (States of
30 Sao Paulo and Santa Catarina) (high confidence) (Muehe, 2010; Khalid et al., 2020; Ohz et al., 2020; de
31 Souza and Ramos da Silva, 2021; Quadrado et al., 2021; Silva de Souza et al., 2021).
32
33 Cities like Rio de Janeiro and São Paulo are overpopulated, where most people live in poor conditions of
34 inadequate housing and sanitation, such as slums, with little and no trees and high temperatures. These
35 people have low access to sanitation, public health and residential cooling and are vulnerable to the effects of
36 heat islands on human comfort and health (Figure 12.7). These include cardiopulmonary and vector-borne
37 diseases, and even death (medium confidence: medium evidence, medium agreement) (Araujo et al., 2015;
38 Mishra et al., 2015; Geirinhas et al., 2018; Peres et al., 2018). Heat stress is known to worsen cardiovascular,
39 diabetic and respiratory conditions (Lapola et al., 2019a). As an effect of Heat islands, these people are also
40 vulnerable to injuries and casualties due to increased thunderstorms, causing economic losses and other
41 social problems (Vemado and Pereira Filho, 2016).
42
43 12.3.6.4 Impacts
44
45 Despite the observed increase in rainfall amount in the region, between 2014 and 2016 Brazil endured a
46 water crisis that affected the population and economy of major capital cities in the SES region Brazil
47 (Blunden and Arndt, 2014; Nobre et al., 2016a). Extremely long dry spells have become more frequent in
48 southeast of Brazil, affecting 40 million people and the economies in cities such as Rio de Janeiro, São Paulo
49 and Belo Horizonte, which are the industrial pole of the country (medium confidence: medium evidence,
50 medium agreement) (PBMC, 2014; Nobre et al., 2016a; Cunningham et al., 2017; Marengo et al., 2017;
51 Lima and Magaña Rueda, 2018; Marengo et al., 2020b). It also impacted agriculture, affecting food supply
52 and rural livelihoods, especially in Minas Gerais (Nehren et al., 2019). Agricultural prices increased by 30%
53 in some cases and harvest yields of sugar cane, coffee and fruits suffered a reduction of 1540% in the
54 region. The number of fires increased by 150%, and energy prices increased by 2025%, as most electricity
55 from hydroelectric power (Nobre et al., 2016a). In Argentina, projected changes in hydrology of Andean
56 rivers associated to glacier retreat are predicted to have negative impacts on the region's fruit production
57 (low evidence, medium agreement) (Barros et al., 2015).
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1
2 Heat islands affect ecosystems by increasing the energy consumption for cooling, the concentration of
3 pollutants and the incidence of fires (high confidence) (Wong et al., 2013; Akbari and Kolokotsa, 2016;
4 Singh et al., 2020b; Ulpiani, 2021). It also affects human health, as well increasing the incidence of
5 respiratory, cardiovascular diseases (medium confidence: medium evidence, medium agreement) (Araujo et
6 al., 2015; Barros and Lombardo, 2016; de Azevedo et al., 2018; Geirinhas et al., 2018).
7
8 Warming temperatures have been implicated in the emergence of dengue in temperate latitudes increasing
9 populations of Aedes aegypti (high confidence) (Natiello et al., 2008; Robert et al., 2019; Estallo et al., 2020;
10 Robert et al., 2020; López et al., 2021) (Table 12.1), and field studies have shown the role of local climate in
11 vector activity (Benitez et al., 2021). Figure 12.5 shows the modelled transmission suitability for dengue for
12 two climate change scenarios. Future increase in the number of months suited for transmission of dengue is
13 highest in SES (see SM12.8 for additional information). There is additional evidence of the spread of
14 arbovirus transmission into southern temperate latitudes (Basso et al., 2017), however a longer historical
15 time series is needed to understand climate-disease interactions, given the relatively recent emergence in this
16 region.
17
18
19
20 Figure 12.5: Predicted thermal suitability for transmission of dengue by Aedes aegypti mosquitoes, mapped as the
21 number of months of the year suitable under baseline or current conditions (2015), and in 2030, 2050, 2080 under two
22 representative concentration pathways, RCP4.5 and RCP8.5. Adapted from Ryan et al. (2019). See SM12.8 for
23 additional data on population at risk for dengue and Zika in the subregions and methodological details.
24
25
26 Sea-level rise impacted the port complex in Santa Catarina, which during the last six years interrupted its
27 activities 76 times due to strong winds or big waves with estimated losses varying between USD 25,000 and
28 USD 50,000 for each 24 idle hours (Ohz et al., 2020). Historically, extratropical cyclones associated with
29 frontal systems cause storm surges in Santos city. Although there are no fatality records, these events cause
30 several socio-economic losses, especially in vulnerable regions including the Port of Santos, the largest port
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1 in Latin America (São Paulo). According to 88-year time span (1928-2016), the frequency of storm surge
2 events were three times more frequent in the last 17 years (2000-2016), than in the previous period of 71
3 years (1928-1999) (Souza et al., 2019).
4
5 There are many projected impacts of climate change on natural systems. The impacts of sea-level rise are
6 habitat destruction and the invasion of exotic species, affecting biodiversity and the provision of ecosystem
7 services (Figure 12.8; Nagy et al., 2019) ().
8
9 SES is a global priority for terrestrial biodiversity conservation, housing two important biodiversity
10 hotspots--the Atlantic Forest and Cerrado--which are among the World's most studied biodiversity-rich
11 spots in terms of climate change impact on biodiversity, especially for terrestrial vertebrates (Cross-Chapter
12 Paper 1.2.2; Manes et al., 2021) . An increasing number of studies show that the Atlantic Forest and Cerrado
13 are at risk of biodiversity loss, largely due to projected reduction of species' geographic distributions in
14 many different taxa (e.g., Loyola et al. (2012); Ferro et al. (2014); Loyola et al. (2014); Hoffmann et al.
15 (2015); Martins et al. (2015); Aguiar et al. (2016b); Vale et al. (2018); Borges et al. (2019); Braz et al.
16 (2019); Vale et al. (2021)). Cerrado savannas are projected to be the hotspot most negatively impacted by
17 climate change within South America, mostly though range contraction of plant species (very high
18 confidence), while the Atlantic Forest is projected to be highly impacted especially though the contraction of
19 the distribution of endemic species (very likely) (Cross-Chapter Paper 1.2.2; Figure 12.10; Manes et al.,
20 2021) . Reductions in species' distribution are also projected in the La Plata Basin for subtropical
21 amphibians (Schivo et al., 2019) and the river tiger (Salminus brasiliensis), a keystone fish of economic
22 value (Ruaro et al., 2019). Farming of mussels and oysters in the region is predicted to be negatively
23 impacted by climate change, particularly sea-level rise, and ocean warming and acidification (Gasalla et al.,
24 2017). Some more localized habitats are also at risk of losing area due to climate change, such as the
25 meadows of northwest Patagonia (Crego et al., 2014) and mangroves of southern Brazil (Godoy and
26 Lacerda, 2015). Predicted changes in global climate along with agricultural expansion will strongly affect
27 South American wetlands, which comprise around 20% of the continent and bring many benefits, such as
28 biodiversity conservation and water availability (Junk, 2013).
29
30 12.3.7 Southwest South America (SWS) Sub-region
31
32 12.3.7.1 Hazards
33
34 Significant increases in the intensity and frequency of hot extremes and significant decreases in the intensity
35 and frequency of cold extremes have likely been observed for the region (Skansi et al., 2013; Ceccherini et
36 al., 2016; Meseguer-Ruiz et al., 2018; Vicente-Serrano et al., 2018; Dereczynski et al., 2020; Dunn et al.,
37 2020; Olmo et al., 2020) (WGI AR6 Table 11.13) (Seneviratne et al., 2021). In particular, a significant
38 increment in the duration and frequency of heatwaves mainly in central Chile from 1961 to 2016 has been
39 observed (Piticar, 2018).
40
41 A robust drying trend for Chile (30ºS48°S) has been recorded (medium confidence) (Saurral et al., 2017;
42 Boisier et al., 2018). However, inconsistent trends over the region in the magnitude of precipitation extremes
43 with both decreases and increases (Chou et al., 2014; Giorgi et al., 2014; Heidinger et al., 2018; Meseguer-
44 Ruiz et al., 2018) (WGI AR6 Table 11.14) (Seneviratne et al., 2021) have been observed (low confidence).
45 The glacier equilibrium line altitude has presented an overall increase over central Chilean Andes (Barria et
46 al., 2019).
47
48 For central Chile, a significant increase (5% to 20% in the last 60 years) in wave heights in the sea has been
49 observed (Martínez et al., 2018). From 1982 to 2016, sea level at central Chile have increased 5 mm yr-1,
50 where El Niño events of 1982-1983 and 1997-1998 caused an extreme increase of 15 to 20 cm in the mean
51 sea level (Campos-Caba, 2016; Martínez et al., 2018).
52
53 From 1946 to 2017, the number of fires and areas burned have increased significantly in Chile (high
54 confidence) (González et al., 2011; Jolly et al., 2015; Úbeda and Sarricolea, 2016; de la Barrera et al., 2018;
55 Urrutia-Jalabert et al., 2018). Fires are attributed to changes in the temperatures regimes (González et al.,
56 2011; de la Barrera et al., 2018; Gómez-González et al., 2018) and precipitation regimes (medium
57 confidence) (Gómez-González et al., 2018; Urrutia-Jalabert et al., 2018).
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1
2 The glaciers of the Southern Andes (including the SWS and SSA regions) show the highest glacier mass loss
3 rates worldwide (high confidence) contributing to sea level rise (Jacob et al., 2012; Gardner et al., 2013;
4 Dussaillant et al., 2018; Braun et al., 2019; Zemp et al., 2019). Since 1985, the glacier area loss in the sub-
5 region is in a range of 20 up to 60% (Braun et al., 2019; Reinthaler et al., 2019b).
6
7 Four sets of downscaling simulations based on the Eta Regional Climate Model forced by two global climate
8 models (Chou et al., 2014) projected warmer conditions (more than 1°C) for all the sub-region by 2050
9 under the RCP4.5 scenario (medium confidence). Extremely warm December-January-February days as well
10 as the number of heatwaves per season are expected to increase by 510 times in the northern Chile (Feron et
11 al., 2019), likely increasing in the intensity and frequency of hot extremes over all the region (WGI AR6
12 Table 11.13) (Seneviratne et al., 2021). Drier conditions (medium confidence), by mean of the decrease of
13 total annual and extreme precipitations, are expected to increase for Southern Chile but inconsistent changes
14 in the sub-region (low confidence) (Chou et al., 2014) (WGI AR6 Table 11.14) (Seneviratne et al., 2021)
15 with high confidence on increase of fire weather and decrease of permafrost and snow extent (WGI AR6
16 Table 12.6, Ranasinghe et al., 2021).
17
18 Regional sea-level change for the region predicted by 2100 show that total mean SLR along the coast will lie
19 between 34 cm and 52 cm for the RCP4.5 scenario, and between 46 cm and 74 cm for the RCP8.5 scenario
20 with high confidence (Albrecht and Shaffer, 2016; WGI AR6 Table 12.6, Ranasinghe et al., 2021).
21
22 12.3.7.2 Exposure
23
24 There is high confidence that age and socio-economic status are key factors determining health exposure and
25 quality of life in SWS where low-income areas show an insufficient number of public spaces to provide
26 acceptable environmental quality in comparison with the high-income areas (Romero-Lankao et al., 2013;
27 Fernández and Wu, 2016; Paz et al., 2016; Hystad et al., 2019; Smith and Henríquez, 2019; Jaime et al.,
28 2020; Pino-Cortés et al., 2020).
29
30 Profound social inequalities, urban expansion and the inadequate city planning (e.g., drainage network)
31 increase exposure to flooding events and landslides (high confidence) (Müller and Höfer, 2014; Rojas et al.,
32 2017; Lara et al., 2018), heat hazards such as heatwaves (high confidence) (Welz et al., 2014; Qin et al.,
33 2015; Inostroza et al., 2016; Welz and Krellenberg, 2016; Krellenberg and Welz, 2017), and the loss and
34 fragmentation of green infrastructure (Hernández-Moreno and Reyes-Paecke, 2018). SWS cities show the
35 highest levels of air pollution of CSA (medium confidence: medium evidence, high agreement) (Pino et al.,
36 2015; Huneeus et al., 2020; González-Rojas et al., 2021), where the state air quality alerts have limited effect
37 on protective health behaviours, being the public perception about air pollution highly dissimilar among the
38 population (Boso et al., 2019). In particular, human communities living in coastal cities show a negative
39 safety perception about the performance of the infrastructure and coastal defences to flood events (low
40 confidence) (González and Holtmann-Ahumada, 2017; Igualt et al., 2019).
41
42 Although climate change is critically important for the current and future status of mining activity in SWS
43 (Odell et al., 2018), and SWS areas subjected to mining activities are highly exposed to water risk (Northey
44 et al., 2017), to date, there is low evidence of climate change impacting mining activities (Corzo and
45 Gamboa, 2018; Odell et al., 2018).
46
47 12.3.7.3 Vulnerability
48
49 Rapid changes in temperature and precipitation regimes make terrestrial ecosystems highly vulnerable to
50 climate change (high confidence) (Salas et al., 2016; Fuentes-Castillo et al., 2020) (Figure 12.7). Terrestrial
51 ecosystems dominated by exotic species (e.g., pine) with lower landscape heterogeneity, degraded soils and
52 close to settlements and roads are highly vulnerable to wildfires in comparison to forests dominated by
53 native trees (high confidence) (Altamirano et al., 2013; Castillo-Soto et al., 2013; Cóbar-Carranza et al.,
54 2014; Salas et al., 2016; Bañales-Seguel et al., 2018; Gómez-González et al., 2018; Sarricolea et al., 2020).
55 Changes in the land use, artificial forestation, deforestation, agricultural abandonment and urbanization have
56 provoked a permanent degradation of old-growth forest putting at risk the biodiversity, recreation and
57 ecotourism (medium confidence: medium evidence, high agreement) (Rojas et al., 2013; Nahuelhual et al.,
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1 2014). Marine coastal ecosystems such as dunes, sandy beaches and wetlands show a high deterioration
2 decreasing the ability to mitigate extreme events (medium confidence: low evidence, high agreement)
3 (González and Holtmann-Ahumada, 2017; Ministerio de Medio Ambiente de Chile, 2019).
4
5 Water sector shows a very high vulnerability (high confidence) (Figure 12.7) mainly due the weak water
6 governance focused on market aspects (e.g., inter-sectoral water transactions, setting rates, granting
7 concessions, waiving the water right) (high confidence) (Hurlbert and Diaz, 2013; Valdés-Pineda et al.,
8 2014; Barría et al., 2019; Hurlbert and Gupta, 2019; Muñoz et al., 2020a; Urquiza and Billi, 2020b). Potable
9 water and adequate sanitization is available in SWS; however, water availability along Chile is unevenly
10 distributed in rural communities (high confidence) (Valdés-Pineda et al., 2014; Nelson-Nuñez et al., 2019).
11 Spatial differences on water availability are enhanced by the strong population growth, economic
12 development, mining activities, and the high dependence of agriculture to irrigation (high confidence)
13 (Stathatou et al., 2016; Northey et al., 2017; Fercovic et al., 2019). Droughts in SWS are a major threat to
14 water security (high confidence) (Aitken et al., 2016; Núñez et al., 2017) as river streamflow are highly
15 dependent on the inter-annual to decadal climate conditions, snow melting processes, rainfall events (Boisier
16 et al., 2016), and impacted by land uses and changes in irrigated agriculture (medium confidence: medium
17 evidence, high agreement) (Vicuña et al., 2013; Fuentes et al., 2021).
18
19 Energy and water needs of large-scale mining activities make this socio economic sector particularly
20 vulnerable to climate change; additionally, the relative lack of power of resource-poor communities living in
21 areas where such mining is making claims on water and energy resources renders these communities even
22 more vulnerable (Odell et al., 2018). Given new conditions generated by changes in a growing demand and
23 climate change, mining industries will need to increase resilience to extreme events; additionally, the
24 declining concentrations of mineral of interest in the raw material require greater energy input for extraction
25 and processing and new methods to avoid associated emissions are required (Hodgkinson and Smith, 2018).
26
27 Urban and agriculture sectors are vulnerable to climate change (medium confidence: medium evidence, high
28 agreement) (Figure 12.7) increasing problems and demand for water (high confidence) (Monsalves-Gavilán
29 et al., 2013; Meza et al., 2014; Fercovic et al., 2019). Important health problems (e.g., pathogenic infections,
30 changes in vector-borne diseases, mortality by heat, lower neurobehavioral performance, among others) have
31 been associated with agriculture, mining and thermal power production activities along SWS (high
32 confidence) (Muñoz-Zanzi et al., 2014; Valdés-Pineda et al., 2014; Pino et al., 2015; Cortés, 2016;
33 Berasaluce et al., 2019; Muñoz et al., 2019a; Ramírez-Santana et al., 2020).
34
35 The large-scale agricultural growth has increased the vulnerability to climate change by favouring the
36 detriment of traditional agriculture, the homogenization of the biophysical landscape and the replacement of
37 traditional crops and native forests with exotic species like pines and eucalyptus (high confidence) (Torres et
38 al., 2015) where farmers' climate change perception is highly dependent on the education level and the
39 access to meteorological information (low confidence) (Roco et al., 2015). Agricultural systems owned by
40 Indigenous Peoples (i.e., Mapuche, Quechua and Aymara farmers) seem to present lower vulnerability to
41 drought and higher response capacity than non-indigenous farmers thanks to the use of the traditional
42 knowledge of specific management techniques and the tendency to conserve species or varieties of crops
43 tolerant to water scarcity (low confidence) (Montalba et al., 2015; Saylor et al., 2017; Meldrum et al., 2018).
44 Fishery and aquaculture-related livelihoods are vulnerable to climate and non-climate drivers (medium
45 confidence: medium evidence, high agreement) such as sea surface warming and precipitation reduction
46 (Handisyde et al., 2017; Soto et al., 2019; González et al., 2021), changes in upwelling intensity (low
47 confidence) (Oyarzún and Brierley, 2019; Ramajo et al., 2020), eutrophication and harmful algal bloom
48 (HAB) events (Almanza et al., 2019), the lack of observational elements and data management (Garçon et
49 al., 2019), and events such as earthquakes and tsunamis (Marín, 2019).
50
51 Chile has experienced an accelerated economic growth which has reduced poverty, however important
52 geographical, economic and educational inequalities are still present (Repetto, 2016). Chilean healthcare
53 system has become more equitable and responsive to the population necessities (e.g., Health reform AUGE
54 program); however, the high relative inequalities in terms of income (OECD, 2018), education level, and the
55 ruralurban factor are determinants of the quality of care, the health system barriers, and the health
56 differential access (high confidence) (Frenz et al., 2014). Exposure and vulnerability to psychosocial risks in
57 SWS shows significant inequalities to natural disasters such as earthquakes according to socio-economic,
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1 geographic and gender factors (high confidence) (Labra, 2002; Vitriol et al., 2014; Quijada et al., 2018)
2 which are increased by the absence of local planning and drills and the lack of coordination (Vitriol et al.,
3 2014). Indigenous Peoples have the highest levels of vulnerability in Chile in terms of income, basic needs,
4 and access to services to climate change (low confidence) (Parraguez-Vergara et al., 2016).
5
6 12.3.7.4 Impacts
7
8 Increasing temperatures in SWS have impacted temperate forests (high confidence) (Peña et al., 2014;
9 Urrutia-Jalabert et al., 2015; Camarero and Fajardo, 2017; Fontúrbel et al., 2018; Venegas-González et al.,
10 2018b; Peña-Guerrero et al., 2020). Increasing temperatures and decreasing precipitations have increased the
11 impacts of wildfires on terrestrial ecosystems (high confidence) (Boisier et al., 2016; Díaz-Hormazábal and
12 González, 2016; Martinez-Harms et al., 2017; de la Barrera et al., 2018; Gómez-González et al., 2018;
13 Urrutia et al., 2018; Bowman et al., 2019), creating conditions for future landslides and floods (de la Barrera
14 et al., 2018).
15
16 Future projections show important changes in the productivity, structure and biogeochemical cycles in SWS
17 temperate and rainforests (medium confidence: medium evidence, high agreement) (Gutiérrez et al., 2014;
18 Correa-Araneda et al., 2020), and their fauna (low confidence) (Glade et al., 2016; Bourke et al., 2018). The
19 "Chilean Winter Rainfall-Valdivian Forests'' is a biodiversity-rich spot (Manes et al., 2021) (Cross-Chapter
20 Paper 1.2.2) projected to suffer habitat change, with loss of vegetation cover in the future due to climate
21 change (medium confidence: medium evidence, high agreement) (Jantz et al., 2015; Mantyka-Pringle et al.,
22 2015). Species are projected to suffer changes in their distribution, including decrease in climatic refugia for
23 vertebrates (low confidence) (Cuyckens et al., 2015; Warren et al., 2018).
24
25 Increasing temperatures have enlarged the number and area extent of glacier lakes in Central Andes,
26 Northern Patagonia and Southern Patagonia (high confidence) (Wilson et al., 2018), while decreased rainfall
27 and rapid glacier melting have provoked changes in the environmental, biogeochemical and biological
28 properties of the central-southern and Andes Chilean lakes (low confidence) (Pizarro et al., 2016).
29
30 Increasing glacier lake outburst floods (GLOF), ice and rock avalanches, debris flows, and lahars from ice-
31 capped volcanoes have been observed in SWS (Iribarren Anacona et al., 2015; Jacquet et al., 2017;
32 Reinthaler et al., 2019b). There is low evidence about the effects of warming and degrading permafrost on
33 slope instability and landslides in these regions (Iribarren Anacona et al., 2015).
34
35 Increasing temperatures, decreasing precipitation regimes, and an unprecedented long-term drought have
36 decreased the annual average rivers streamflow that supply SWS megacities such as Santiago (high
37 confidence) (Meza et al., 2014; Muñoz et al., 2020a), with important and negative effects over the water
38 quality (Bocchiola et al., 2018; Yevenes et al., 2018) threatening irrigated agriculture activities (medium
39 confidence: medium evidence, high agreement) (Yevenes et al., 2018; Oertel et al., 2020; Peña-Guerrero et
40 al., 2020). Large reductions in the groundwater availability of the SWS region (Meza et al., 2014) and a
41 sustained decreasing of the mean annual flows (Ragettli et al., 2016; Bocchiola et al., 2018), especially
42 during the snowmelt season (Vargas et al., 2013) have been observed in SWS. Drought has affected wetlands
43 (low confidence) (Zhao et al., 2016; Domic et al., 2018), and desert ecosystems (medium confidence: medium
44 evidence, high agreement) (Acosta-Jamett et al., 2016; Neilson et al., 2017; Díaz et al., 2019).
45
46 There is low evidence about shoreline retreat attributed to climate change (Martínez et al., 2018; Ministerio
47 de Medio Ambiente de Chile, 2019) although increasing wind intensity along the central Chilean coast has
48 caused important damages in the coastal infrastructure and buildings (Winckler et al., 2017) and changes of
49 seawater properties and processes (low confidence) (Schneider et al., 2017; Aguirre et al., 2018). Ocean and
50 coastal ecosystems in SWS are sensitive to upwelling intensity which affect the abundance, diversity,
51 physiology and survivorship of coastal species (high confidence) (Anabalón et al., 2016; Jacob et al., 2018;
52 Ramajo et al., 2020) (Figure 12.8). Increasing radiation and temperatures, and reduced precipitations in
53 conjunction with increased nutrient load have increased HAB events producing massive fauna mortalities
54 (high confidence) (León-Muñoz et al., 2018; IPCC, 2019b, SPM A8.2 and B8.3; Quiñones et al., 2019; Soto
55 et al., 2019; Armijo et al., 2020). Multiple resources subjected to fisheries and aquaculture are highly
56 vulnerable to storms, alluvial disasters, ocean warming, ocean acidification, increasing ENSO extreme
57 events, and lower oxygen availability (high confidence) (Figure 12.8; García-Reyes et al., 2015; Silva et al.,
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FINAL DRAFT Chapter 12 IPCC WGII Sixth Assessment Report
1 2015; Duarte et al., 2016; Lagos et al., 2016; Navarro et al., 2016; Lardies et al., 2017; Duarte et al., 2018;
2 IPCC, 2019b; Mellado et al., 2019; Ramajo et al., 2019; Silva et al., 2019a; Bertrand et al., 2020). Ocean and
3 coastal ecosystems, especially the EEZ will be highly impacted by climate change in the near and long-term
4 (high confidence) (Figure 12.8; Table SM12.3; Silva et al., 2015; Silva et al., 2019a).
5
6 Changes in the temperature and drought have impacted crops significantly (medium confidence: medium
7 evidence, high agreement) (Ray et al., 2015; Zambrano et al., 2016; Lesjak and Calderini, 2017; Ferrero et
8 al., 2018; Piticar, 2018; Haddad et al., 2019; Zúñiga et al., 2021). Table 12.4 shows the changes in crop
9 growth duration, which affect the yields. Higher negative numbers then indicate yield reduction for the crop.
10 Increasing temperatures and decreasing precipitation are expected to impact the agriculture sector (i.e., fruits
11 crops, and forests) across the entire sub-region with the largest impacts in the northern and central zone (high
12 confidence) (Mera et al., 2015; Zhang et al., 2015; Silva et al., 2016; Lizana et al., 2017; Reyer et al., 2017;
13 Toro-Mujica et al., 2017; Beyá-Marshall et al., 2018; Lobos et al., 2018; O'Leary et al., 2018; Aggarwal et
14 al., 2019; Ávila-Valdés et al., 2020; Fernandez et al., 2020; Melo and Foster, 2021). Observed impacts and
15 future projections warn that increasing temperatures and decreasing precipitation will largely impact on
16 water demand by agricultural sectors (high confidence) (Novoa et al., 2019; Peña-Guerrero et al., 2020;
17 Webb et al., 2020). Extreme climate events have provoked that Indigenous Peoples (e.g., Mapuche, Uru and
18 Aymara) suffer scarcity of water, reduction of agricultural production, and a displacement of their traditional
19 knowledge and practices (medium confidence: low evidence, high agreement) (Parraguez-Vergara et al.,
20 2016; Meldrum et al., 2018; Perreault, 2020).
21
22
23 Table 12.4: Average percentage change in crop growth duration for the period 2015-19. Crop growth duration refers to
24 the time taken in a year for crops to accumulate the reference period (1981-2010) average growing season Accumulated
25 Temperature Total (ATT). As temperatures rise, the ATT is reached earlier (higher negative changes), the crop matures
26 too quickly, and thus yields are lower. "No data" means no data is available for the growth of that crop, in the specified
27 region. NP means that the crop is not present in significant areas in that region. Data derived from Romanello et al.
28 (2021).
Region Winter wheat Spring Rice Maize Soybean
wheat
Central America (CA) -4.8% No data -1.9% -5.0% -4.7%
Northwest South America (NWS) -3.8% -5.2% -5.2% -5.6% -3.1%
Northern South America (NSA) NP NP -0.7% -3.1% 0.0%
South America Monsoon (SAM) -5.3% -0.7% -1.4% -2.9% -1.5%
Northeast South America (NES) -1.0% -1.3% -0.7% -3.5% -2.6%
Southeast South America (SES) -2.3% -3.5% -2.3% -2.4% -2.7%
Southwest South America (SWS) -2.3% -5.2% -10.0% -5.2% No data
Southern South America (SSA) -0.8% -6.5% No data -1.6% No data
29
30
31 SWS cities have been largely impacted by wildfires, water scarcity and landslides affecting highways and
32 local roads, as well as, potable water supply (Sepúlveda et al., 2015; Araya-Muñoz et al., 2016). Increasing
33 temperature and heat extreme events in cities have increased the demand for water, the damage of urban
34 infrastructure (Monsalves-Gavilán et al., 2013), and accelerated the ageing and the death of trees (high
35 confidence) (Moser-Reischl et al., 2019). Increasing temperature will modify the energy demand in cities in
36 northern and central Chile (Rouault et al., 2019).
37
38 Increasing temperature, heat extreme events and air pollution in SWS have significantly impacted the
39 population health (cardiac complications, heat stroke, and respiratory diseases) (high confidence) (Table
40 12.2; Leiva G et al., 2013; Monsalves-Gavilán et al., 2013; Pino et al., 2015; Herrera et al., 2016; Henríquez
41 and Urrea, 2017; Ugarte-Avilés et al., 2017; de la Barrera et al., 2018; Johns et al., 2018; Bowman et al.,
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1 2019; González et al., 2019; Matus C and Oyarzún G, 2019; Sánchez et al., 2019; Terrazas et al., 2019;
2 Cakmak et al., 2021; Zenteno et al., 2021).There is low confidence about area changes of Chagas disease
3 (Tapia-Garay et al., 2018; Garrido et al., 2019), and transmission rates in the future (Ayala et al., 2019).
4
5 12.3.8 Southern South America (SSA) Sub-region
6
7 12.3.8.1 Hazards
8
9 There were inconsistent trends and insufficient data coverage about extreme temperatures and precipitation
10 (low confidence) but with medium confidence an increase in the frequency of meteorological droughts was
11 observed (Dereczynski et al., 2020; Dunn et al., 2020; WGI AR6 Tables 11.13, 11.14, 11.15, Seneviratne et
12 al., 2021; WGI AR6 Table 12.3, Ranasinghe et al., 2021). An increase in precipitation in Trelew, no change
13 for Comodoro Rivadavia, both stations located at Eastern Patagonia, and negative trends in austral summer
14 rainfall in southern Andes were observed (Vera and Díaz, 2015; Saurral et al., 2017). Chile's wildfires in
15 Patagonia (fire frequency and intensity) have grown at an alarming rate (Úbeda and Sarricolea, 2016).
16 Decreasing rainfall pattern in Punta Arenas is closely associated with the variability at inter-annual to inter-
17 decadal time scales of the main forcing system for climate in Patagonia. Snow Cover Extension (SCE) and
18 Snow Cover Duration decreased by an average of ~13 ± 2% and 43 ± 20 days respectively from 2000 to
19 2016, due to warming rather than drying (Rasmussen et al., 2007). In particular, the analysis of spatial
20 pattern of SCE indicates a slightly greater reduction on the eastern side (~14 ± 2%) of the Andes Cordillera
21 compared to the western side (~12 ± 3%). The longest time series of glacier mass balance data in the
22 Southern Hemisphere, the Echaurren Norte Glacier, lost 65% of its original area in the period 19552015
23 and disaggregated into two ice bodies in the late 1990s (Malmros et al., 2018; Pérez et al., 2018).
24
25 Mean temperatures in the SSA sub-region are projected to continue to rise up to +2.5°C in 2080 with respect
26 to the present climatology (Kreps et al., 2012). A rise in temperature means that the isotherm of 0°C will
27 move up the mountains leaving less surface for accumulation of snow (Barros et al., 2015).
28
29 An increase in the intensity and frequency of hot extremes and a decrease in the intensity and frequency of
30 cold extremes is likely projected (WGI AR6 Table 11.13, Seneviratne et al., 2021); CMIP6 models project an
31 increase in the intensity and frequency of heavy precipitation (medium confidence).
32
33 It is expected that an increase in the intensity of heavy precipitation, droughts and fire weather will intensify
34 through the 21st century in SSA but mean wind will decrease (medium confidence) (Kitoh et al., 2011; WGI
35 AR6 Tables 11.14 and Table 11.15, Seneviratne et al., 2021). The probability of having extended droughts,
36 such as the recently experienced mega-drought (2010-2015), increases to up to 5 events/100 yr (Bozkurt et
37 al., 2017). Snow, glaciers, permafrost and ice sheets will decrease with high confidence (WGI AR6 Table
38 12.6, Ranasinghe et al., 2021). The observed area and the elevation changes indicate that the Echaurren
39 Norte Glacier may disappear in the coming years if negative mass balance rates prevail (medium confidence)
40 (Farías-Barahona et al., 2019).
41
42 12.3.8.2 Exposure
43
44 Grasslands make a significant contribution to food security in Patagonia through providing part of the feed
45 requirements of ruminants used for meat, wool and milk production. There is a lack of information regarding
46 the combined effect of climate change and overgrazing and the consequences for pastoral livelihoods that
47 depend on rangelands. Temperature and the amount and seasonal distribution of precipitation were important
48 controls of vegetation structure in Patagonian rangelands (Gaitán et al., 2014). They found that over two-
49 thirds of the total effect of precipitation on above-ground net primary production (ANPP) was direct, and the
50 other third was indirect (via the effects of precipitation on vegetation structure). Thus, if evapotranspiration
51 and drought stress increase as temperature increases and rainfall decrease in water-limited ecosystems, it
52 would be expected a greater exposure of ranchers due to a reduction of stocking rate and therefore families'
53 income (medium confidence). The number of farmers (mainly family enterprises) exposed to climatic
54 hazards (drought) is approximately 7080 thousand that have 1415 million sheep in Argentina (Peri et al.,
55 2021).
56
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1 Argentinian Patagonia main cities have developed as the result of oil and gas extraction, which demand
2 massive quantities of water due to fracking and drilling techniques. Vaca Muerta is the major region in South
3 America where those techniques are used to extract oil and gas, and this will lead to an exacerbation of
4 current water scarcity and to competition with irrigated agriculture (Rosa and D'Odorico, 2019) which in the
5 context of drought may exacerbate socio-environmental conflicts (medium confidence).
6
7 12.3.8.3 Vulnerability
8
9 There are reports related to a decrease in survival, growth and higher vulnerability to drought and fire-
10 severity for species of native forest due to climate change and wildfire (high confidence) (Mundo et al.,
11 2010; Landesmann et al., 2015; Whitlock et al., 2015; Jump et al., 2017; Camarero et al., 2018; Venegas-
12 González et al., 2018a). There is a reported coincidence between major changes in regional decline in the
13 growth of forests with severe droughts due to climatic variations over northern Patagonia (Rodríguez-Catón
14 et al., 2016). Once the forest decline begins, other contributing factors such as insects (e.g., defoliator
15 outbreaks) increase the forest vulnerability or accelerate the loss of forest health of previously stressed trees
16 (Piper et al., 2015). This region hosts unique temperate rainforests and it is particularly rich in endemic and
17 long-lived conifer species (e.g., Fitzroya cupressoides), which may be vulnerable to declines in soil moisture
18 availability (Camarero and Fajardo, 2017). Patagonia will probably be vulnerable by a decrease in
19 precipitation regimes due to climate change, and consequently many species that rely on meadows in an arid
20 environment will also be impacted (Crego et al., 2014). The floods triggered by strong ENSOs caused
21 significant changes in the crop production (Isla et al., 2018).
22
23 The development of various human activities and water infrastructure are decreasing water sources, changing
24 river basins from exoreic to endoreic and the disappearance of one lake in 2016 (Scordo et al., 2017).
25 Numerous dams for irrigation, some also used for hydropower, have been and are planned to be built despite
26 wind power generation potential (Silva, 2016). Oil and gas have played an important role in the rise of
27 Neuquén-Cipolletti as Patagonia's most populous urban area, and in the growth of Comodoro Rivadavia,
28 Punta Arenas, and Rio Grande, as well.
29
30 12.3.8.4 Impacts
31
32 The potential impact of climate change is of special concern in arid and semi-arid Patagonia, a >700,000 km2
33 region of steppe-like plains in Argentina. Thus, melting snow and ice in the glaciers of Patagonia and the
34 Andes will alter surface runoff into interior wetlands; sea level rise of between 20 and 60 cm will destroy
35 coastal marshes; and an increase in extreme events, such as storms, floods, and droughts, will affect
36 biodiversity in wet grasslands (medium confidence: low evidence, high agreement) (after Junk et al. 2013;
37 Joyce et al. 2016). Three species of lizard from Patagonia are at risk of extinction as a result of global
38 warming (Kubisch et al., 2016).
39
40 Patagonian ice fields in South America are the largest bodies of ice outside of Antarctica in the southern
41 hemisphere. They are losing volume due partly to rapid changes in their outlet glaciers which end up in lakes
42 or the oceans, becoming the largest contributors to eustatic sea level rise (SLR) in the world, per unit area
43 (Foresta et al., 2018; Moragues et al., 2019; Zemp et al., 2019). Most calving glaciers in the Southern
44 Patagonia ice field retreated during the last century (high confidence). Upsala Glacier retreat generated slope
45 instability and a landslide movement destroyed the western edge in 2013. The Upsala Argentina Lake has
46 become potentially unstable and may generate new landslides (Moragues et al., 2019). The climate effect on
47 the summer stratification of piedmont lakes is another issue in relation to glacier dynamics (Isla et al., 2010).
48
49 Between 41º and 56° South latitude, the absolute glacier area loss was 5450 km2 (19%) in the last 150
50 years, with an annual area reduction increase of 0.25% a-1 for the period 20052016 (Meier et al., 2018). The
51 small glaciers in the north of the Northern Patagonian Ice field had over all periods the highest rates of
52 0.92% a-1. In this sub-region, increased melting of ice is leading to changes in the structure and functioning
53 of river ecosystems and in freshwater inputs to coastal marine ecosystems (medium confidence: low
54 evidence, high agreement) (Aguayo et al., 2019). In addition, in the case of coastal areas, the importance of
55 tides and rising sea levels in the behaviour of river floods has been demonstrated (Jalón-Rojas et al., 2018).
56
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1 Suitable areas for meadows (very productive areas for livestock production) will decrease by 7.85% by 2050
2 given predicted changes in climate (low confidence) (Crego et al., 2014).
3
4 A major drought from 1998 to 1999 coincident with a very hot summer led to extensive dieback in a
5 Nothofagus species (Suarez et al., 2004). In another dominant Nothofagus species, several periodic droughts
6 have triggered forest decline as of the 1940s (Rodríguez-Catón et al., 2016).
7
8 Climate change impacted ocean ecosystems by reducing kelps coverage, increasing reproductive failure and
9 chick mortality of penguins, and poleward expansion of saltmarshes in the Atlantic Patagonia. SSA houses
10 the Patagonian Steppe Global-200 terrestrial ecoregion being a conservation priority at global scale, but with
11 a clear lack of studies on likely future climate change impacts (Cross-Chapter Paper 1.2.2.2; Manes et al.,
12 2021). The Patagonian Steppe may suffer pronounced expansion in invasive species' ranges under climate
13 change (low confidence) (Wang et al., 2017a).
14
15 Fire has been found to promote or halt biological invasions (medium confidence: medium evidence, high
16 agreement). For example, an analysis of Pinus spreading after wildfires in Patagonia reveals that there is a
17 high risk of pines becoming invasive if ignition frequency increases as a result of climate change (Raffaele et
18 al., 2016). According to Inostroza et al. (2016), the Magellan Region is one of the most fragile regions in
19 Patagonia and despite its low population densities, it is under a silent process of anthropogenic alteration
20 where between 53.1% and 68.1% of the area needs to be considered as influenced by human activity whom
21 are occupying pristine ecosystems even extensive conservation designations (Inostroza et al., 2016). Fire
22 exposure can result in several health problems for human populations; Table 12.5 shows that SSA is the
23 region with the highest exposure to wildfire danger.
24
25
26 Table 12.5: Change in population-weighted exposure to very high or extremely high wildfire risk. Data derived from
27 the Fire Danger Indices FDI produced by the Copernicus Emergency Management Service for the European Forest Fire
28 Information System EFFIS (available at Copernicus Emergency Management Service (2021)). High and very high
29 wildfire danger defined as FDI >= 5. Data derived from Romanello et al. (2021).
Population-weighted mean days of exposure to extremely high and
very high wildfire danger
Subregion In 2001-04 In 2017-20 Change from
2001-04 to 2017-20
Central America (CA) 30.4 26.9 -3.5
Northwest South America (NWS) 4.2 4.6 0.5
Northern South America (NSA) 19.7 21.2 1.5
South America Monsoon (SAM) 16.0 27.8 11.8
Northeast South America (NES) 47.9 53.3 5.4
Southeast SouthAmerica (SES) 4.2 8.2 4.0
Southwest SouthAmerica (SWS) 31.9 58.4 26.5
Southern South America (SSA) 88.7 104.9 16.2
30
31
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1
2 Figure 12.6: Observed trends (WGI AR6 Tables 11.13, 11.14, 11.15) (Seneviratne et al., 2021) and summary of
3 confidence in direction of projected change in climatic impact-drivers, representing their aggregate characteristic
4 changes for mid-century for scenarios RCP4.5, SSP3-44 4.5, SRES A1B, or above within each AR6 region,
5 approximately corresponding (for CIDs that are independent of sea-level rise) to global warming levels between 2°C
6 and 2.4°C (WGI AR6 Table 12.6) (Ranasinghe et al., 2021).
7
8
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1
2 Figure 12.7: Sectoral distribution of vulnerability levels to climate change for the subregions. The vulnerability levels
3 are based on studies that include: i) databases with climate change vulnerability indexes by country and sector, ii)
4 researches that implement climate change vulnerability indexes by sector at the local, national, regional or global scale,
5 and iii) studies that define some vulnerability level based on the authors' expert judgment. Panel (a) shows the
6 vulnerability and confidence levels for each subregion. Panel (b) indicates the references used and the level of
7 vulnerability attributed by subregion. The numbers within the table indicate the reference used for the assessment in the
8 following order: 1) Aitken et al. (2016); 2) Anderson et al. (2018b); 3) Bañales-Seguel et al. (2018); 4) Bouroncle et al.
9 (2017); 5) CAF (2014); 6) Carrão et al. (2016); 7) Donatti et al. (2019); 8) Eguiguren-Velepucha et al. (2016); 9) FAO
10 (2020a); 10) FAO (2020b); 11) FAO (2021a); 12) FAO (2021b); 13) FAO (2021c); 14) FAO et al. (2021); 15) FAO and
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FINAL DRAFT Chapter 12 IPCC WGII Sixth Assessment Report
1 ECLAC (2020); 16) Ferreira Filho and Moraes (2015); 17) Filho et al. (2016); 18) Fuentes-Castillo et al. (2020); 19)
2 FSIN and Global Network Against Food Crisis (2021); 20) Global Health Security Index (2019); 21) Godber and Wall
3 (2014); 22) Handisyde et al. (2017); 23) Hannah et al. (2017); 24) Immerzeel et al. (2020); 25) Inform Risk Index
4 (2021); 26) Koutroulis et al. (2019); 27) Krishnamurthy et al. (2014); 28) Lapola et al. (2019a); 29) Li et al. (2018); 30)
5 Lin et al. (2020); 31) Mansur et al. (2016); 32) Martins et al. (2017); 33) Menezes et al. (2018); 34) Nagy et al.
6 (2018);35) ND-Gain (2020); 36) Northey et al. (2017); 37) Olivares et al. (2015); 38) Pacifici et al. (2015); 39) Qin et
7 al. (2020); 40) Romeo et al. (2020); 41) Liu and Chen (2021); 42) Silva et al. (2019b); 43) Soto Winckler and Del
8 Castillo Pantoja (2019); 44) Soto et al. (2019); 45) Tomby and Zhang (2019); 46) Venegas-González et al. (2018b); 47)
9 Yeni and Alpas (2017); 48) Marengo et al. (2017); 49) Bedran-Martins et al. (2018); 50) Confalonieri et al. (2014a).
10 Detailed methodology can be found in SM12.2.
11
12
13
14 Figure 12.8: Climate and non-climate sensitivity drivers of ocean, coastal ecosystems and Exclusive Economic Zones
15 (EEZs) of Central and South America.
16
17
18 12.4 Key Impacts and Risks
19
20 This section synthesizes key risks across the Central and South America CSA region. It follows the
21 definition and concept of risk provided in AR5, distinguishing the risk components, climatic hazard,
22 exposure and vulnerability of people and assets (IPCC, 2014). This concept is further developed in AR6,
23 defining key risks as potentially severe risks (Section 16.5). Key risks may refer to present or future
24 conditions, with a focus on the 21st century. Both mitigation and adaptation can moderate the extent or
25 severity of risks. The identification and evaluation of risks imply socio-cultural values, which may vary
26 across individuals, communities or cultures.
27
28 In line with chapter 16 of this report, this chapter uses a risk outcome perspective, i.e., the focus is on the
29 consequences related to risks, which potentially can result from different combinations of hazards, exposure
30 and vulnerabilities. There is limited literature with a focus on severe risks in the CSA region, and scant
31 studies specifically and explicitly considering risk drivers such as level of warming, level of exposure,
32 vulnerability and adaptation.
33
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1 Criteria for identifying key risks for this chapter include the magnitude of the consequences, in particular the
2 number of people potentially affected; the severity of the negative effects of the risk (e.g., lives threatened,
3 major negative effect on livelihoods, well-being, or the economy); the importance of the affected system
4 (e.g., for vital ecosystem services, for large population groups); the irreversibility of either the process
5 leading to the risk or the consequences; and the potential to reduce the risk.
6
7 Several of the key risks identified for the CSA region align well with the overarching key risks assessed in
8 AR5 (Oppenheimer et al., 2014) and later in O'Neill et al. (2017), as well as with the representative key risks
9 assessed in Section 16.5 of this report. The identified key risks include KR1: risk of food insecurity due to
10 frequent and/or extreme droughts; KR2: risk to life and infrastructure due to floods and landslides; KR3: risk
11 of water insecurity; KR4: risk of severe health effects due to increasing epidemics (in particular vector-borne
12 diseases); KR5: systemic risks of surpassing infrastructure and public service systems KR6: risk of large-
13 scale changes and biome shifts in the Amazon; KR7: risk to coral reef ecosystems due to coral bleaching;
14 KR8: risks to coastal socio-ecological systems due to sea level rise, storm surges and coastal erosion (Table
15 12.6; Figure 12.11; Table SM12.5).
16
17
18 Table 12.6: Synthesis of key risks identified and assessed for the Central and South America region
Consequence that would Associated changes in Associated changes in Associated changes in
make the risk severe hazards exposure vulnerability
1. Risk of food insecurity due to frequent/extreme droughts
Substantial decrease in yield More frequent and/or More people exposed to Reduced capacity of
for key crops, disruption of longer drought periods. food insecurity due to farmers (especially small-
food provision chains, Decrease in annual spatially more extensive scale) to adapt to
reduced capacity or rainfall, severe decrease drought; high population changing climatic
production of goods, reduced in rainfall at onset of growth rate (including conditions. Soil
food security and increased rainy season. rural areas) and more degradation. Insufficient
malnutrition. Desertification of population dependent on government support of
semiarid regions. agricultural goods. adaptation measures,
financial contributions,
infrastructure, insurance,
and research efforts.
Inefficient water
management.
2. Risk to life and infrastructure due to floods and landslides
Death and severe health More frequent and severe More people exposed to Low income and marginal
effects, disruption of critical storms and heavy floods and landslides due populations, low
infrastructure and service precipitation events. to changing hazards, land- resilience of
systems. Changing snow use and increased infrastructure and critical
conditions and thawing population; occupation of service systems. Limited
permafrost. Retreating more risk-prone areas such government support
glaciers, formation of as flood plains and steep through insurance,
glacier lakes, increased slopes. monitoring, early warning
glacier lake outburst flood systems and recovery.
hazard.
3. Risk of water insecurity
Seasonal water availability Glacier shrinkage, snow Increase in population Unequal water
change and decline due to cover change, more dependent on contribution consumption systems,
glacier shrinkage, snow cover pronounced dry periods, of glacier/snow melt, failed water management
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change, more pronounced dry precipitation and especially during drought and government
periods and poor or failed circulation changes. conditions. Increased capacities, low water
water management and demand from infrastructure efficiency,
governance. intensification of growing urban areas.
agriculture, mining,
hydropower and
urbanisation.
4. Risk of severe health effects due to increasing epidemics (in particular vector-borne diseases)
Increased rate of epidemics of Higher temperatures Increased population Poor sanitation
vector-borne diseases increase the geographical density and mobility conditions, particularly in
(malaria, dengue, Zika, range of vectors, leading through urbanization low-income communities
leishmaniasis) together with to expansion of climate results in high and for Indigenous
diarrheal diseases. Severe suitable areas. transmission rate. Peoples. Insufficient
health effects and damage to Increased population coverage of appropriate
health systems in countries exposed to arboviruses due water provision and
with low adaptive capacity to expansion of vectors, sewage systems. Low
and where original endemicity including higher altitudes structural or economic
is high and control status and latitudes. capacity to cope;
poor. underfunding of health
systems. Increase in
infections can increase
incidence of more severe
forms of dengue.
5. Systemic risks of surpassing infrastructure and public service systems
Breakdown of public service Higher frequency and More people and Increasing vulnerability
systems, including magnitude of climate- infrastructure exposed to of public service and
infrastructure and health related events (storms, climate/weather events. infrastructure systems.
services due to cascading floods, landslides) Increase in population Insufficient disaster
impacts of natural hazards and together with an increase exposed to arboviruses due management. Little
epidemics, affecting a large in spatial and temporal to spatial expansion of improvement,
part of the population. distribution of vectors. maintenance and
pathogens/vectors for expansion of public
malaria, dengue, Zika and health care systems. Low
leishmaniasis. system resilience.
6. Risk of large-scale changes and biome shifts in the Amazon
Transition from tropical forest More frequent, stronger Reduced availability of Strong dependence on
into other biomes such as and persistent drought natural sources for local non-climatic drivers, in
seasonal forest or savannah periods. Temperature people. Land use and land particular land-use
through forest degradation increase and reduction in cover change (mining, change, deforestation,
and deforestation. Risk of annual rainfall. deforestation). Loss of forest fire practices. Low
shifting from carbon sink to biodiversity and ecosystem capacity to monitor and
source. services. Health impacts control deforestation.
from increased forest fires
particularly for Indigenous
Peoples.
7. Risk to coral reef ecosystems due to coral bleaching
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Degradation and possible Ocean sea surface Continued exposure to Ecosystem highly
death of the Mesoamerican temperature increase, increased atmospheric CO2 sensitive to water
coral reef, the second largest lowered seawater pH and levels and sea surface temperature and pH
reef in the world. Severe carbonate levels due to temperatures together with fluctuations. High levels
damage to habitat for marine increased atmospheric destruction from coastal of negative human
species, degrading coastal CO2 levels, leading to development, fishing interference with reefs
protection and other ocean acidification and practices and tourism. including runoff and
ecosystem services, decreased coral bleaching. pollution..
food security from fisheries,
lack of income from tourism.
8. Risks to coastal socio-ecological systems due to sea level rise, storm surges and coastal erosion
Coastal flooding and erosion High continuing Coastal population growth. Poor planning in coastal
causing severe damage to trajectories of sea level Increased number of development and
coastal population and rise. More intense and people, infrastructure and infrastructure,
infrastructure. Loss of persistent coastal services (coastal tourism) disproportionate
fisheries, reef degradation and flooding, salt water exposed; need of vulnerability and limited
decline in coastal protection intrusion, coastal erosion. relocation of millions of adaptation options for
due to increased storm surges people. rural communities and
and waves. Salt water Indigenous Peoples,
intrusion and land subsidence. increasing urbanisation in
coastal cities. Large
economic losses and
unemployment from
declining tourism.
1
2
3 Identification and assessment of key risks are informed by observed and projected impacts in the different
4 sub-regions of CSA (Section 12.3). Figure 12.10 shows the summary of different levels of observed and
5 future impacts per sub-region for different sectors, based on a detailed assessment of climate change impacts
6 on various systems and components for the respective sector (Figure 12.9). This assessment is consistent
7 with and complementary to the assessment in Section 12.3. A synthesis of these impacts (Figure 12.10)
8 indicates the following: Climate change has a major impact on observed and future decline of Andean
9 glaciers and snow (high confidence), and leads to degradation of permafrost and destabilization of related
10 landscapes (medium evidence, high agreement). Water quality is a major concern across the region but there
11 is limited evidence of impacts of climate change on water quality as well as on groundwater. Climate change
12 has had a high impact on terrestrial and freshwater ecosystems in the NWS, SES and SWS sub-regions, and a
13 medium impact in the other subregions but the level of confidence is varying across sub-region. Projections
14 indicate a strong impact of climate change on these ecosystems for the future (medium confidence: medium
15 evidence, high agreement). Many aspects and assets of ocean and coastal ecosystems (e.g., mangroves, coral
16 reefs, saltmarshes) were identified to be strongly impacted by climate change, both for observed and future
17 periods (high confidence) (Section 12.5.2; Figure 12.9).
18
19
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1
2
3 Figure 12.9: Observed and projected impacts for the subregions of Central and South America. Impacts are
4 distinguished for main sectors and for their corresponding systems (or components). Observed impacts refer to a time-
5 period of the last several decades. Projected impacts represent a synthesis across several emission and warming
6 scenarios, indicative of a time-period from mid- to end of the 21st century. For each system (e.g., coral reefs) it is
7 distinguished whether the impact of climate change is low, medium or high. The references underlying this assessment
8 can be found in SM12.4.1.
9
10
11
12 Figure 12.10: Synthesis of observed and projected impacts, distinguished for different sectors and each subregion of
13 Central and South America. Observed impacts refer to a time-period of the last several decades. Projected impacts
14 represent a synthesis across several emission and warming scenarios, indicative of a time-period from mid- to end of the
15 21st century. For each sector (e.g., health) it is distinguished whether the impact of climate change is low, medium or
16 high. The references underlying this assessment can be found in SM12.4.1 and the methodology to complete the
17 synthesis is found in SM12.4.2.
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1
2
3
4 Figure 12.11: Synthesis of key risks for the Central and South America region. The base map indicates the mean
5 temperature change between the scenario SSP2 4.5 using CMIP6 model projections for 2081-2100, and a baseline
6 period of 1986-2005 (WGI AR6 Atlas, Gutiérrez et al., 2021).
7
8
9 In most sub-regions, crop, livestock, fisheries and food systems in general show medium to high impacts of
10 climate change over the observed period and similarly for the future of the 21st century (medium confidence:
11 medium evidence, high agreement). For some sub-regions, the available literature does not allow the
12 assessment of impacts on several human systems, including cities and infrastructure, health, poverty,
13 livelihoods, migration, conflict, Indigenous knowledge and local knowledge, especially for future time
14 periods. This points to important knowledge gaps about climate change impacts on human systems.
15 Indication of high impacts for several human systems and sub-regions points to the need to close these
16 knowledge gaps.
17
18 The assessment of key observed and projected impacts and risks shows that in the CSA region several
19 systems are already approaching critical thresholds under current warming levels, in particular glaciers in the
20 Andes and coral reefs in Central America (high confidence), and further ocean and coastal ecosystems in
21 virtually all sub-regions (medium confidence: medium evidence, high agreement). Some systems could cross
22 these thresholds with different levels of reversibility depending on the degrees of future warming, namely
23 glaciers in the Andes and coral reefs in Central America which will show partial but irreversible loss already
24 under low levels of warming (RCP2.6) (high confidence). The risk of large-scale ecological changes and
25 biome shifts of the Amazon forest, i.e., a transition from tropical forest into other biomes such as seasonal
26 forest or savannah, is now assessed with medium confidence, with the extent of the changes depending on the
27 level of future warming and non-climatic drivers (land-use change, deforestation, forest fire practices).
28
29 Systemic risks where critical infrastructure and public service system capacities are surpassed due to storms,
30 floods and epidemics, with cascading impacts through vulnerable systems and populations and economic
31 sectors, have the potential to affect large parts of the population and are therefore of major concern (medium
32 confidence: limited evidence, high agreement). The COVID-19 crisis has exposed the existing vulnerabilities
33 in important systems, in particular health systems and public service (Phillips et al., 2020). However, tipping
34 points in social systems are poorly understood (Bentley et al., 2014; Milkoreit et al., 2018), and there is
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1 limited evidence to inform understanding about which level of compound climatic, environmental and socio-
2 economic stressors social systems withstand in CSA.
3
4 Overall, most key risks and their severity and extent are strongly driven and determined by the system's
5 exposure, vulnerability and adaptive capacity. In particular, the high vulnerability of large populations,
6 infrastructure and service systems such as health, food and energy production and supply are important
7 factors, along with high inequalities and poor governance, for creating and increasing key risks (high
8 confidence). Prevailing low levels of available information and understanding exacerbate the uncertainties
9 surrounding key risks, and hence pose limitations to adaptation. An example is Central America with high
10 levels of vulnerability and exposure but there is limited evidence and understanding on impacts and risks,
11 making this region susceptible to inappropriate adaptation to expected future climate change impacts.
12
13
14 12.5 Adaptation
15
16 Adaptation initiatives across the region have increased since AR5. National Communications (NC),
17 Nationally Determined Contributions (NDC) and National Adaptation Plans (NAP) (https://unfccc.int)
18 recently published are providing guidance for adaptation in CSA. There is also a diversity of non-
19 governmental adaptation initiatives, both at the national and sub-national levels. In this context, this section
20 assesses, through a sectoral approach, the main challenges, opportunities, trends and initiatives to adapt to
21 climate change in the region.
22
23 12.5.1 Terrestrial and Freshwater Ecosystems and their Services
24
25 CSA is one of the most biodiverse regions in the World, hosting unique socio ecosystems that will be
26 strongly impacted by climate change (high confidence) (Section 12.3; Cross-Chapter Paper 1; CAF, 2014;
27 Camacho Guerreiro et al., 2016; IPBES, 2018a; Li et al., 2018; Retsa et al., 2020) . Warming has generated
28 extreme heat events in many parts of CSA (IPCC, 2019a) that, together with droughts and floods, will
29 seriously affect the integrity of terrestrial and freshwater ecosystems in the entire region (Section 12.3; CAF,
30 2014) . A reduction in net primary productivity in tropical forests and glacier retreat in the Andes, for
31 example, are expected to cause significant negative socioecological impacts (Feldpausch et al., 2016; Lyra et
32 al., 2017; Cuesta et al., 2019) (see Case Study, 12.7.1). Biodiversity-rich spots in the region are well assessed
33 in the literature as compared to other regions of the World, especially for the Atlantic Forest, Mesoamerica
34 and Cerrado (Cross-Chapter Paper 1.2.2; Manes et al., 2021) . Up to 85% of of evaluated natural systems
35 (species, habitats and communities) in the literature for biodiversity-rich spots since AR5 were projected to
36 be negative impacted by climate change (high confidence), with 26% of projections predicting species
37 extinctions (Cross-Chapter Paper 1.2.2; Manes et al., 2021) . Indigenous knowledge and local knowledge
38 play an important role in adaptation and are vital components of many socioecological systems, while also
39 being threatened by climate change (high confidence) (Box 7.1; Valdivia et al., 2010; Tengö et al., 2014;
40 Mistry et al., 2016; Harvey et al., 2017; Diamond and Ansharyani, 2018; Camico et al., 2021) .
41
42 12.5.1.1 Challenges and opportunities
43
44 The conversion of natural ecosystems to agriculture, pasture and other land uses in CSA has been identified
45 as a major challenge to climate change adaptation in the region (high confidence) (Scarano et al., 2018;
46 IPCC, 2019a). In the last three decades, South America has been a significant contributor of the growth of
47 agricultural production worldwide (OECD/Food and Agriculture Organization of the United Nations, 2015),
48 driven partly by increased international demand for commodities, especially soybeans and meat (IPCC,
49 2019a). Between 2001 and 2015 about 65% of all forest disturbance in the region was associated with
50 commodity-driven deforestation (Curtis et al., 2018). High rates of native vegetation conversion in
51 Argentina, Bolivia, Brazil, Colombia, Ecuador, Paraguay and Peru threaten important ecosystems (Amazon,
52 Cerrado, Chacos and Llanos savannas, Atlantic rainforest, Caatinga and Yungas) (Graesser et al., 2015;
53 FAO, 2016c). Almost 2/3 of soy consumed in EU+ comes from Brazil, Argentina and Paraguay (IDH, 2020),
54 increasing conversion risk in the Amazon, Cerrado, and Gran Chaco. Despite growing commodities
55 production traceability, in 2018 only 19% of the soybean meal consumed in EU+ was certified deforestation-
56 free, and 38% compliant with the FEFAC Soy Sourcing Guidelines (IDH, 2020), which is a great challenge
57 at the international level (Negra et al., 2014; Curtis et al., 2018; Lambin et al., 2018; IDH, 2020).
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1
2 Investing in actions aimed at protection, restoration and sustainable use of biodiversity and ecosystems is a
3 good approach for maintaining critical ecosystem services, and is part of a common strategy for adaptation,
4 mitigation and disaster risk reduction in the region (high confidence) (Kabisch et al., 2016; Scarano et al.,
5 2018). These strategies also meet the forest and water conservation international agendas, optimizing
6 resources and solutions (Strassburg et al., 2019). Global conservation and sustainable development
7 commitments, such as the Aichi Targets (CDB), Sustainable Development Goals (UN), the Nationally
8 Determined Contribution (NDC) under the Paris Agreement, and the New York Declaration on Forests
9 strongly rely on nature-based solutions (NbS) to achieve their objectives (Brancalion et al., 2019) (Figure
10 12.12). The COVID19 outbreak also brought attention to the need for preserving tropical forests as a mean
11 to prevent spill over of viruses from wildlife to humans, with concerns over that risk in the Amazon (Allen et
12 al., 2017b; Dobson et al., 2020; IPBES, 2020; Ferreira et al., 2021). These represent an important
13 opportunity for Ecosystem Based Adaptation (EbA) to be at the core of NbS for climate change, access
14 finance and promote climate resilient development pathways in CSA.
15
16 The Declaration on Protected Areas and Climate Change, presented by 18 CSA countries during the
17 UNFCCC COP21, highlights the fundamental role of protected areas in providing the "green infrastructure"
18 needed for implementing climate change mitigation and adaptation, and safeguard the provision of essential
19 ecosystem services and the livelihoods of Indigenous Peoples and local communities (Gross et al., 2016).
20 Protected Areas systems in CSA are underfunded (very high confidence). Latin American (including
21 Mexico) governments allocate just about 1% of national environmental budgets on protected areas (about
22 USD 1.18 ha-1 on average). This figure only covers 54% of their basic needs, resulting in insufficient
23 management. The financing gap to achieve optimal needs for protected areas in CSA is approximately USD
24 700 million yr-1 (Bovarnick et al., 2010). This seriously compromises the management and delivery capacity
25 of protected areas for climate change adaptation, and preparedness for ongoing ecological transformation
26 (van Kerkhoff et al., 2019). Furthermore, in order to become a relevant mechanism for resilience, protected
27 areas need to be managed for this purpose (Mansourian et al., 2009). About 40% of protected areas in Latin
28 America and Caribbean (including Mexico), have management effectiveness evaluations being undertaken
29 (UNEP-WCMC and IUCN, 2020a). This is hardly representative of Aichi's Goal 11, although far better than
30 the 11% global average. Collaborations with the Indigenous Peoples and local communities are also an
31 important issue to consolidate protected areas (Gross et al., 2016). In addition to protected areas as solutions
32 for climate change adaptation and mitigation, there is also a need to protect or restore ecosystems outside the
33 protected areas, as illustrated by the Mesoamerican Biological Corridor (Imbach et al., 2013).
34
35 Despite some local and specific assessments (e.g., Warner (2016)), there is a significant gap on identifying
36 barriers to adaptation or maladaptation in the region (Dow et al., 2013). In their National Communications
37 (NC), Nationally Determined Contributions (NDC) and/or National Adaptation Plans (NAP)
38 (https://unfccc.int), most countries identified inadequate financing and access to technology as barriers for
39 adaptation relevant to terrestrial and freshwater socio-ecosystems (high confidence). Insufficient institutional
40 coordination is also frequently mentioned (Rangecroft et al., 2013; Cameron et al., 2015). These limitations
41 could be partially addressed through multilateral cooperation, incorporation of synergies from the local to the
42 national scales, local empowerment, and poverty alleviation (Rangecroft et al., 2013; Harvey et al., 2017;
43 Murcia et al., 2017; Calispa, 2018; Chain-Guadarrama et al., 2018).
44
45 12.5.1.2 Governance and financing
46
47 All CSA countries have formulated policies that include measures relevant for socio-ecosystem adaptation in
48 their NCs, NDCs and NAPs (https://unfccc.int), with an emphasis on protection and restoration of water and
49 forests (high confidence). Existing proposed measures, instruments and programs, however, do not yet
50 reflect the vision needed to integrate the ecosystem and human dimensions of vulnerability. The
51 administration coordination and the progress in adaptive ecosystem management are incipient, due in part to
52 the lack of stable financial resources and scientific, Indigenous knowledge and local knowledge (IK and LK)
53 about adapting ecosystems to climate change (Bustamante et al., 2020). Brazil was an exception, showing
54 dramatic policy-driven reduction in deforestation in the Amazon between 20042012, with a concomitant
55 70% increase in soy production, the most profitable Amazon crop (Hansen et al., 2013; Nepstad et al., 2014).
56 Policies included territorial planning (protected areas, Indigenous territories and land tenure), satellite
57 monitoring, market and credit restrictions on high-deforesting municipalities, plus some incentives to small
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1 farmers (Boucher et al., 2013; Hansen et al., 2013; Nepstad et al., 2014; Castelo, 2015; Cunha et al., 2016a).
2 It is important to highlight the important role of Indigenous territories, in addition to protected areas, in
3 forest conservation in the Amazon (high evidence, medium agreement) (Schwartzman et al., 2013; Barber et
4 al., 2014; Nepstad et al., 2014; Walker et al., 2014b). These policies were partially funded by results-based
5 compensation through the Amazon Fund. Since 2012, however, policies and institutions have weakened, and
6 Amazon deforestation rates started to rise (Carvalho et al., 2019), sharpening in recent years (Silva Junior et
7 al., 2021). Conservation incentives, a new complementary and allegedly cost-effective approach, is
8 increasingly being implemented in the region (Magrin et al., 2014). They include payment for ecosystem
9 services, REDD+, environmental certification and conservation easements, but remain controversial, and
10 more research is needed on their effectiveness, possible negative side effects, participatory management
11 systems and collective decision-making processes (Larson and Petkova, 2011; Locatelli et al., 2011; Pinho et
12 al., 2014; Strassburg et al., 2014; Mistry et al., 2016; Gebara and Agrawal, 2017; Scarano et al., 2018;
13 Ruggiero et al., 2019; To and Dressler, 2019; Vallet et al., 2019).
14
15 12.5.1.3 Adaptation options to avert and reduce key risks on terrestrial and freshwater ecosystems
16
17 Research, monitoring systems and other initiatives for knowledge management are promoted in the region on
18 terrestrial and freshwater socio-ecosystem adaptation (high confidence) (NCs, NDCs and NAPs,
19 https://unfccc.int). In Chile, for example, the Eco-social Observatory of Climate Change Effects for High
20 Altitude Wetlands of Tarapacá has been collecting information on physical, biological and social variables
21 since 2013 (Uribe Rivera et al., 2017). Other examples in the Andes are the GLORIA-Andes network
22 (Cuesta et al., 2017a), the Andean Forest Network (Malizia et al., 2020) and the Initiative of Hydrological
23 Monitoring in the Andes (IMHEA), with measures to optimize watershed management and protection, and
24 reduce the risk of water insecurity (Correa et al., 2020).
25
26 Poverty is a driver of climate change risk, while sustainable use of ecosystems fosters adaptation (Kasecker
27 et al., 2018) (high confidence). Most of 398 "Ecosystem-based Adaptation hotspots" identified in Brazil on
28 this premise are located in some of the most vulnerable ecosystems to climate change (Kasecker et al., 2018).
29 Although conservation and restoration is reported as effective to reduce risk (medium confidence: medium
30 evidence, high agreement) (Anderson et al., 2010; Borsdorf et al., 2013; Keenan, 2015; Pires et al., 2017;
31 Ramalho et al., 2021), their effectiveness depends on the integration of conservation actions with
32 enhancement of local socioeconomic conditions (medium confidence: medium evidence, high agreement)
33 (Scarano and Ceotto, 2015; Pires et al., 2017; Kasecker et al., 2018; de Siqueira et al., 2021; Vale et al.,
34 2021).
35
36 Since AR5, there has been an increase in the number of adaptation measures through natural resources and
37 ecosystem services management. The main approaches are EbA and Community-based Adaptation (CbA)
38 (high confidence) (NCs, NDCs and NAPs, https://unfccc.int). IK/LK can be very detailed and usually relates
39 to people's priorities identified by collective decision-making (Box 7.1; (Hurlbert et al., 2019, SRCCL
40 Section 7.6.4); SRCCL Cross-Chapter Box ILK in Chapter 13; (de Coninck et al., 2018, SR1.5 Section
41 4.3.5.5). In Manaus, central Amazon, fishermen perceive reductions on fish size, diversity and capture levels
42 caused by droughts; while recognizing that floods hinders access to fishing grounds (Keenan, 2015;
43 Camacho Guerreiro et al., 2016). In the Amazon floodplains, small-scale fisher and farmer's communities
44 incorporate their knowledge on natural hydrologic and ecological processes into management systems that
45 reduce climate change risk and impacts (Oviedo et al., 2016). Smallholder grain farmers in Guatemala and
46 Honduras implement EbA practices based on local knowledge (e.g., live fences, home gardens, shade trees in
47 coffee plantations, dispersed trees in corn fields and other food insecurity risk reduction practices) (Harvey et
48 al., 2017; Chain-Guadarrama et al., 2018). There is, therefore, a great potential for terrestrial and freshwater
49 ecosystem adaptation to climate change in CSA, provided that the right incentives and sociocultural
50 protective measures are in place (high confidence) (Section 12.5.10.4; Table SM12.7).
51
52 Disarticulation between policy and implementation is a common problem. Ecuadorian climate public policy
53 points towards a CbA approach, but it is often downsized in the implementation (Calispa, 2018). Important
54 adaptation actions have been undertaken in Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, El
55 Salvador, Paraguay, Peru and Uruguay; both in policymaking and institutional arrangements, but they tend to
56 be poorly coordinated with policies on development, land planning and other sectoral policies (Ryan, 2012).
57 Some type of community participation mechanisms is present in most country strategies, but their levels of
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1 implementation vary considerably (medium confidence: medium evidence, high agreement) (Ryan, 2012;
2 Pires et al., 2017; Calispa, 2018).
3
4 There is an ecosystem bias in adaptation priorities for research and implementation, hindering the
5 development of comprehensive adaptation programs. Most scientific research on adaptation in Peru focuses
6 on the highlands and coastal regions while mitigation research focuses on forests (Chazarin et al., 2014).
7 Combined adaptation and mitigation strategies can produce positive results, but they are often disconnected
8 (Locatelli et al., 2015). Most reviewed cases in agriculture and forestry in Latin America (84% of 274 cases)
9 reported positive synergies between adaptation and mitigation. Nevertheless, research on Latin American
10 forests tend to focus on mitigation, while studies on agriculture are usually oriented towards adaptation (high
11 confidence) (Locatelli et al., 2015; Locatelli et al., 2017).
12
13 Rural communities in the Cusco Region, Peru, ground their ability to adapt to climate change on four
14 cultural values, known in Quechua as ayni (reciprocity), ayllu (collectiveness), yanantin (equilibrium) and
15 chanincha (solidarity), but policies oriented towards "modernization" undermine these traditional
16 mechanisms. Adaptation strategies could benefit from integrating these and other insights from traditional
17 cultures, fostering risk reduction and transformational adaptation towards intrinsically sustainable systems
18 (medium confidence: medium evidence, high agreement) (Walshe and Argumedo, 2016).
19
20 Protected areas have become an important component as enablers of national climate change adaptation
21 strategies. They increase ecosystem's adaptive potential, reducing climate risk and delivering numerous
22 ecosystem services, sustainable development benefits while playing an important role in climate change
23 mitigation (high confidence) (Mackey et al., 2008; Dudley et al., 2010; Gross et al., 2016; Bebber and Butt,
24 2017; Dinerstein et al., 2019; IPCC, 2019a). CSA already has a greater percentage of land (24.1%) under
25 protected status than the world average (14.7%) (UNEP-WCMC and IUCN, 2020b). Some countries,
26 including Belize, Bolivia, Brazil, Guatemala, Nicaragua and Venezuela already met or surpassed the 30%
27 CDB and IUCN goal (Dinerstein et al., 2019), and others like Costa Rica and Honduras are very close to
28 doing so. In some cases, the establishment of protected areas not accompanied by collective decision-making
29 processes has displaced local people or denied them access to natural resources, increasing their vulnerability
30 to climate change (Brockington and Wilkie, 2015).
31
32 In addition to better managing and expanding protected areas networks, Other Effective Area-based
33 Conservation Measures (OECMs), recently defined by the Parties to the Convention on Biological Diversity
34 (Dudley et al., 2018), could also enhance ecosystem resilience (low confidence). Private Protected Areas in
35 the mountain regions of the Americas (e.g., Andes), play an important role in closing the gaps in fragmented
36 biomes and expanding protection in underrepresented areas (Hora et al., 2018). In Brazil, there is also a huge
37 potential for conservation and sustainable management in private areas, as roughly 53% of the country's
38 native vegetation is within private land (Lapola et al., 2014; Soares-Filho et al., 2014).
39
40 Large-scale restoration is also seen as pivotal to limiting both climate change (IPCC, 2019a) and species
41 extinction (IPBES, 2018a) (very high confidence). A new multi-criteria approach for optimizing multiple
42 restoration outcomes (for biodiversity, climate change mitigation, and cost), for example, indicate that South
43 America has the greatest extension of converted lands, evenly distributed in the top 50% of global priorities
44 (Strassburg et al., 2020).
45
46 12.5.2 Ocean and Coastal Ecosystems and their Services
47
48 Ocean and coastal ecosystems provide suitable habitats to a high number of species that support important
49 local fisheries, the tourism sector and the economy of the region (high confidence) (Section 3.5; Table 3.9;
50 González and Holtmann-Ahumada, 2017; Venerus and Cedrola, 2017; CEPAL, 2018; Carvache-Franco et
51 al., 2019; SROCC Section 5.4 Bindoff et al., 2019). There is high confidence that CSA ocean and coastal
52 ecosystems are already impacted by climate change (Figure 12.9, 12.10; Table SM12.3; Section 3.4; ,
53 Section 5.4 in SROCC, Bindoff et al., 2019), and highly sensitive to non-climate stressors (Figure 12.8;
54 Table SM12.3; Section 3.4). Projections for CSA ocean and coastal ecosystems alert about significant and
55 negative impacts (high confidence) which include major loss of ecosystem structure and functionality,
56 changes in the distributional range of several species and ecosystems, major mortality rates, and increasing
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1 number of coral bleaching events (Figure 12.9; Figure 12.10; Table SM12.3; Section 3.4; SROCC Sections
2 5.3, 5.4, Bindoff et al., 2019).
3
4 CSA subregions are highly dependent on ocean and coastal ecosystems, and thus vulnerable to climate
5 change (FAO, 2018). Fisheries and aquaculture contribute significantly to food security and livelihoods by
6 creating employment (more than two million people), income and economic growth for the region (Section
7 3.5; FAO, 2018) (). More than 45% of the total fisheries in CSA are based on marine products
8 (CEPALSTAT, 2019). Peru, Chile, Argentina and Ecuador are among the 15 countries with the largest
9 marine capture production worldwide (Gutiérrez et al., 2016a; FAO, 2018; Vannuccini et al., 2018), while
10 more than 90% of the hydrological resources produced by aquaculture in CSA have a marine origin
11 (CEPALSTAT, 2019). There is high confidence about important current and future impacts of climate
12 change hazards in marine resources subjected to fisheries, however there is low evidence about the impacts
13 on regional economies (Figure 12.9, 12.10; Table SM12.3).
14
15 12.5.2.1 Adaptation measures and strategies applied on oceans and coasts of CSA
16
17 Similar to those pointed by WGII AR5 Chapter 27 (Magrin et al., 2014) and Chapter 3 (Section 3.5; Section
18 3.6.2; Box SLR in Chapter 3), adaptation strategies in ocean and coastal ecosystems in CSA are still focused
19 on the ecosystem protection and restoration, and the sustainable use of marine resources (high confidence).
20 There is low evidence about how coastal urban areas and touristic settlements of CSA countries are adapting
21 to SLR and extreme events (Calil et al., 2017; Villamizar et al., 2017). Some of this strategies include
22 planned relocation (Dannenberg et al., 2019) and the use of grey infrastructures as seawalls and bulkheads
23 (Silva et al., 2014; Isla et al., 2018) .
24
25 There is medium confidence that Ecosystem-based Adaptation (EbA) is the main strategy used in CSA coral
26 reefs ecosystems. The set of strategies applied include the protection, restoration (e.g., coral gardening, larval
27 propagation), and conservation of coral reefs areas through the application of the spatial ocean zoning
28 schemes such as Marine Protected Areas (MPAs), marine managed areas (MMAs), National Parks, Wildlife
29 Refuges, Special Zones of Marine Protection, Special Management Zones, Responsible Fishing Areas, and
30 the establishment of management plans with some level of participatory processes. These strategies are
31 complemented with actions that promote the development of research and education programs, recreational
32 and cultural activities, the use of community-based approaches, and the creation of national specific laws
33 (Graham, 2017) and the adhesion of international treaties (e.g., Convention on International Trade in
34 Endangered Species of Wild Fauna and Flora (CITIES), AGENDA 21, United Nations Convention on the
35 Law of the Sea (UNCLOS), Ramsar Convention on Wetlands of International Importance Especially as
36 Waterfowl Habitat) (Cruz-Garcia and Peters, 2015; Gopal et al., 2015; Graham, 2017; Bayraktarov et al.,
37 2020).
38
39 Adaptation measures in mangroves ecosystems are mainly focused on the application of EbA strategies (high
40 confidence). This measures include the application of restoration programs, the creation of management
41 plans (which also have significant co-benefits with mitigation (Section 3.6.2.1), and the establishment of
42 coastal protected areas, followed by the development of research activities, the creation of specific mangrove
43 policies through new laws and resolutions (e.g., Colombia) (Cvitanovic et al., 2014; Krause, 2014; Blanco-
44 Libreros and Estrada-Urrea, 2015; Carter et al., 2015; Estrada et al., 2015; Ferreira and Lacerda, 2016;
45 Oliveira-Filho et al., 2016; Rodríguez-Rodríguez et al., 2016; Alvarado et al., 2017; Álvarez-León and
46 Álvarez Puerto, 2017; Baptiste et al., 2017; Borges et al., 2017; Jaramillo et al., 2018; Salazar et al., 2018;
47 Armenteras et al., 2019; Blanco-Libreros and Álvarez-León, 2019; Maretti et al., 2019; Ellison et al., 2020)
48
49 The use of territorial planning tools, the promotion of sustainable resource exploitation, the adherence to
50 certification schemes, and the implementation of management instruments such as Ecosystem-based
51 Management (EbM) followed by the use of an integrated coastal zone management, coastal marine spatial
52 planning, capacity building, ecological risk assessments have been the mains strategies used to ensure the
53 sustainability of marine resources subjected to fisheries across EEZs of CSA (high confidence) (Hellebrandt
54 et al., 2014; Gelcich et al., 2015; Singh-Renton and McIvor, 2015; Gutiérrez et al., 2016a; Karlsson and
55 Bryceson, 2016; Oyanedel et al., 2016; Debels et al., 2017; Isaac and Ferrari, 2017; Mariano Gutiérrez et al.,
56 2017; Barragán and Lazo, 2018; Bertrand et al., 2018; Lluch-Cota et al., 2018; Guerrero-Gatica et al., 2020).
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1 Other strategies include the application of local regulations (e.g., closed seasons) (Fontoura et al., 2016), and
2 the use of participative instances (Hellebrandt et al., 2014; Arroyo Mina et al., 2016; Matera, 2016).
3
4 12.5.2.2 Adaptation success in ocean and coastal ecosystems of CSA
5
6 There is low evidence about how the strategies and actions taken and implemented in ocean and coastal
7 systems of CSA have contributed to advance in the protection and conservation of ocean and coastal
8 ecosystems. However, some important advances are visible in Colombian Pacific areas with coral reefs (new
9 conservation plans, research monitoring and conservation practices) (low confidence) (Cruz-Garcia and
10 Peters, 2015; Alvarado et al., 2017; Bayraktarov et al., 2020). In Panama, actions taken have allowed the
11 protection of a high number of marine areas with coral reefs, as well as the incorporation of management
12 approaches that include several sectors such as fisheries, tourism, coral protection and coral conservation
13 (low confidence) (Alvarado et al., 2017). In the case of Costa Rica, 80% of coral habitats are located inside
14 of MPAs, multiple research coral-related activities have been performed, and several training activities have
15 favoured the engagement of the local community in their protection against climate and non-climate hazards
16 (low confidence) (Alvarado et al., 2017).
17
18 There is low evidence of how the incorporation of mangroves as Ramsar sites, the reforms of legislations
19 (e.g., fines and stronger regulations), and the creation of reserves and private protection initiatives (e.g.,
20 Belize Association of Private Protected Areas BAPPA), and capacity-building projects or new educational
21 programs have promoted the protection of mangroves in CSA countries such as Honduras, Guatemala and
22 Belize (Cvitanovic et al., 2014; Carter et al., 2015; Ellison et al., 2020). In Brazil, between 7584% of
23 mangroves are under some level of protection which has improved the forest structures, and multiple
24 research programs (e.g., Mangrove Dynamics and Management, MADAM, and `GEF-Mangle') have been
25 developed (medium confidence) (Krause, 2014; Medeiros et al., 2014; Estrada et al., 2015; Ferreira and
26 Lacerda, 2016; Oliveira-Filho et al., 2016; Borges et al., 2017; Maretti et al., 2019; Strassburg et al., 2019).
27 In Colombia, research projects (e.g., Mangroves of Colombia Projects, MCP), the installation of a
28 geographic information system for mangroves (e.g., SIGMA Sistema de Información para la Gestión de los
29 Manglares en Colombia), surveillance monitoring plans (e.g., EGRETTA Herramientas para el Control y
30 Vigilancia de los Manglares), and the establishment of protected areas have contributed to decrease loss of
31 the mangrove forest (high confidence) (Blanco-Libreros and Estrada-Urrea, 2015; Rodríguez-Rodríguez et
32 al., 2016; Álvarez-León and Álvarez Puerto, 2017; Baptiste et al., 2017; Jaramillo et al., 2018; Salazar et al.,
33 2018; Armenteras et al., 2019; Blanco-Libreros and Álvarez-León, 2019).
34
35 There is low evidence whether the establishment of MPAs and the creation of legal instruments have allowed
36 the development of new research activities have increased the environmental awareness, decreased the illegal
37 extraction, and improved the local coordination which have promoted the sustainable use of marine
38 resources, and improved the community-government cooperation in marine ecosystems (Alvarado et al.,
39 2017). The experience in countries like Chile demonstrates the importance of implementing robust
40 management plans that guarantee the protection objectives and the sustainability through the implementation
41 of EbA measures such as MPAs (Petit et al., 2018).
42
43 There is low confidence about how measures adopted are ensuring the sustainability of marine resources
44 subjected to fisheries. In Peru, the industrial fishery follows an adaptive management approach (i.e., stock
45 assessments, catch limits), while in Chile, the small-scale fishery of benthic-demersal resources is managed
46 through the granting of exclusive territorial use rights (called TURFS) with established quotas defined by the
47 central authority (Bertrand et al., 2018). In addition, MPAs in Chile are playing a key role in climate change
48 adaptation for fisheries (medium confidence) (Gelcich et al., 2015; Petit et al., 2018), and an increasing
49 amount of funds have been invested in initiatives to reduce the vulnerability of fishery and aquaculture
50 sectors to climate change (OECD, 2017). Since 2016, Argentina has been developing a strategy to implement
51 EbM on fisheries with support from the Global Environment Facility program (GEF). Also, Argentina and
52 Chile, are promoting the local consumption of seafood and the certification of its fishery products (OECD,
53 2017), while Brazil and Chile have advanced in their actions to climate change through the development of
54 new research studies and methodologies incorporating research institutions (Nagy et al., 2015). Uruguay is
55 incorporating stakeholders in their climate change adaptation strategies (low confidence) (Nagy et al., 2015),
56 while Colombia is supporting the capacity building of fishers promoting livelihood diversification to
57 increase the resilience of the sector (medium confidence: medium evidence, high agreement) (Hellebrandt et
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1 al., 2014; Arroyo Mina et al., 2016; Matera, 2016). Chile and Peru have showed certain advances in the
2 development of guidelines for the management of the coast line and the implementation of the EbM which
3 has favoured the collaboration of diverse and multiple stakeholders (fishers, academics, municipal
4 institutions), the development of outreach and educational activities, and the creation of networks, and the
5 interest of other fishery communities to implement EbM (medium confidence: medium evidence, high
6 agreement) (Hellebrandt et al., 2014; Gelcich et al., 2015; Gutiérrez et al., 2016a; Oyanedel et al., 2016;
7 Guerrero-Gatica et al., 2020). In countries like Peru and Chile, there is an increasing presence of
8 intergovernmental and international cooperation agencies, and new funding (e.g., GEF), and projects (Inter-
9 American Development, SPINCAM) related to change adaptation for the fishery sector (medium confidence:
10 medium evidence, high agreement) (Galarza and Kámiche, 2015; Barragán and Lazo, 2018).
11
12 12.5.2.3 National climate change commitments for ocean and coasts
13
14 Beyond the protection, conservation and climate change adaptation strategies implemented on CSA ocean
15 and coastal areas and their ecosystems, a high number of adaptation goals to face climate change impacts on
16 ocean and coastal ecosystems and their services are incorporated in most of the national climate change
17 adaptation commitments of CSA countries (Table 12.7).
18
19
20 Table 12.7: National plans with adaptation goals for ocean and coasts in CSA.
CSA country Adaptation Initiatives Year
Argentina Plan Nacional de Adaptación y Mitigación al Cambio Climático1 2019
Brazil National Adaptation Plan to Climate Change (Volume 1); General Strategies2 2016
National Adaptation Plan to Climate Change (Volume 2); Sectoral and thematic 2016
strategies3
Chile Plan Nacional de Adaptación al Cambio Climático4 2014
Plan Sectorial de Adaptación al Cambio Climático en Biodiversidad5 2014
Plan Sectorial de Adaptación al Cambio Climático en Pesca y Acuicultura6 2015
Plan de Adaptación y Mitigación de los Servicios de Infraestructura al Cambio 2017
Climático7
Plan de Adaptación al Cambio Climático Sector Salud8 2017
Colombia Plan Nacional de Adaptación al Cambio Climático9 2016
Costa Rica Política Nacional de Adaptación al Cambio Climático10 2018
Ecuador Plan Nacional de Cambio Climático11 2015
El Salvador Plan Nacional de Cambio Climático12 2015
Guatemala Plan de Acción Nacional de Cambio Climático13 2018
Guyana Política de Adaptación y Plan de Implementación14 2001
Honduras Plan Nacional de Adaptación al Cambio15 2018
Nicaragua Plan de Adaptación a la Variabilidad y el Cambio Climático en el Sector 2013
Agropecuario, Forestal y Pesca16
Peru Plan Nacional de Adaptación al Cambio Climático del Peru17 2021
Suriname Suriname National Adaptation Plan18 2019
Uruguay Plan Nacional de Respuesta al Cambio Climático19 2010
Belize Not Available 2019
Panamá Not Available
Venezuela Not Available
References: 1(Ministerio de Ambiente y Desarrollo Sostenible de la República de Argentina, 2019) 2(Ministry of
Environment of Brazil, 2016a) 3(Ministry of Environment of Brazil, 2016b) 4(Ministerio de Medio Ambiente de
Chile, 2014b) 5(Ministerio de Medio Ambiente de Chile, 2014a) 6(Ministerio de Economía Fomento y Turismo
de Chile, 2015) 7(Ministerio de Medio Ambiente de Chile, 2017) 8(Ministerio de Salud de Chile, 2017)
9(Ministerio de Ambiente y Desarrollo Sostenible de Colombia, 2016) 10(Ministerio de Ambiente y Energía de la
República de Costa Rica, 2018) 11(Gobierno Nacional de la República del Ecuador, 2015) 12(Ministerio de Medio
Ambiente y Recursos Naturales de El Salvador, 2015) 13(Consejo Nacional de Cambio Climático y la Secretaría
de Planificación y Programación de la Presidencia de Guatemala, 2018) 14(National Ozone Action Unit of
Guyana, 2016) 15(Secretaría de Recursos Naturales y Ambiente del Gobierno de la República de Honduras, 2018)
16(Ministerio Agropecuario y Forestal de Nicaragua, 2013) 17(Ministerio del Ambiente Gobierno del Perú, 2021)
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18(Government of Suriname, 2019) 19(Ministerio de Vivienda Ordenamiento Territorial y Medio Ambiente de la
República de Uruguay, 2010)
1
2
3 Current goals in national and sectoral adaptation plans attempt to promote research and monitoring (e.g., new
4 research actions, modelling, knowledge management), the development of new legislation tools and policies
5 (e.g., inter-institutional and territorial coordination, improvement of public policies), the conservation of
6 ocean and coastal ecosystems and their biodiversity (e.g., new MPAs establishment, protection tools), the
7 management of climate risks (e.g., alert systems), the management of productive activities (e.g.,
8 diversification of resources), the promotion of the construction of new infrastructure and technology (e.g.,
9 grey-green infrastructure - GGI), the creation of new financial tools (e.g., insurances), the improvement of
10 the capacity building (e.g., education, awareness), the management of water and residues (e.g., sewages and
11 freshwater availability), the social inclusion (e.g., strategies to support vulnerable sectors, gender inclusion),
12 and the incorporation of traditional practices (e.g., restoring traditional practices including Indigenous
13 knowledge). However, the amount and the type of adaptation goals per country differ enormously among
14 countries (Figure 12.12).
15
16
17
18
19 Figure 12.12: Type and amount of adaptation goals identified in National Adaptation Plans for ocean and coastal
20 systems of CSA countries.
21
22
23 12.5.2.4 Limits and barriers for adaptation in ocean and coastal ecosystems
24
25 Although current national adaptation plans and many other actions and strategies are focused on improving
26 the conservation and restoration of ocean and coastal ecosystems, as well as, the suitability of marine
27 resources along CSA, these measures are still not able to reduce the vulnerability and sensitivity of these
28 ecosystems to climate change hazards (high confidence) (Figure 12.6; Table SM12.3; Leal Filho, 2018; Nagy
29 et al., 2019) . There is high confidence that sandy beaches ecosystems of CSA countries show an important
30 loss of dunes as a consequence of the construction of infrastructures which have generate an interruption of
31 the natural dynamic of beaches decreasing the protection to tides, waves, extreme events or tsunamis (high
32 confidence) (Amaral et al., 2016; Bernardino et al., 2016; González and Holtmann-Ahumada, 2017;
33 Obraczka et al., 2017). Also, adaptation measures to cope with SLR and coastal extreme events sometimes
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1 fail as they exacerbate coastal erosion and damage (medium confidence: medium evidence, high agreement)
2 (Spalding et al., 2014; Lins-de-Barros and Parente-Ribeiro, 2018). There is medium evidence but high
3 agreement that the most barriers limiting the success of adaptation strategies in ocean and coastal systems in
4 CSA are due to the lack of coordination (e.g., absence of participatory processes, overlapping among fishing
5 and protection activities), the lack of knowledge (e.g., poor monitoring, poor control and surveillance, no
6 long-term studies), lack of adequate metrics for evaluating adaptation actions informing decision-makers
7 hinder the continuity and adjustment of measures, weak governance (e.g., perverse incentives, resource
8 overexploitation, conflicts), lack of financial resources and long-term commitments (e.g., crisis, lack of
9 budgets, market fluctuations), weak policies, cultural constraints, poverty, low flexibility, lack of awareness
10 of climate risks, and lack of engagement by stakeholders (Leal Filho, 2018; Nagy et al., 2019; Moreno et al.,
11 2020b; Aburto et al., 2021).
12
13 Some important limits and barriers have been detected for productive systems such as fisheries and tourism
14 in CSA (medium confidence: medium evidence, high agreement). Brazilian major fisheries management do
15 not follow an ecosystem approach, although some small-scale fisheries apply a precautionary approach
16 (Singh-Renton and McIvor, 2015). The management of Peruvian artisanal (medium and small-scale
17 fisheries) are minimal with an important lack of regulations, control, and management actions (Bertrand et
18 al., 2018). In Argentina, marine recreational fisheries have been largely unregulated with a lack of
19 monitoring programs which have contributed to the overexploitation of some key coastal stocks (Venerus
20 and Cedrola, 2017). Moreover, the participation of women fishers in CSA is not equally considered being
21 excluded from the decision-making processes (FAO, 2016b; Bruguere and Williams, 2017). Due to the lack
22 of monitoring programs, it is unknown how this tourism industry will respond to long-term changes driven
23 by climate change (Weatherdon et al., 2016).
24
25 12.5.2.5 Challenge and Opportunities
26
27 There is low evidence and high agreement that empower the local stakeholders (e.g., multilateral fisheries
28 agreements) improve the public awareness and simplify regulations and increase the flexibility and
29 sustainability of marine resources subjected to fisheries under future scenarios (Weatherdon et al., 2016;
30 Kalikoski et al., 2019). Ecosystem-Based Fishery Management (EBFM) arises as a suitable tool to minimize
31 the risk to climate change, avoid the degradation of the ecosystems and its services (Gullestad et al., 2017)
32 and maintain the long-term socioeconomic benefits when include climate complexity and the relationships
33 among species within the ecological systems (Long et al., 2015). There is high confidence that EbA is more
34 successful and feasible than hard coastal defences for the protection, management and restoration of ocean
35 and coastal ecosystems and their resources (Spalding et al., 2014; González and Holtmann-Ahumada, 2017;
36 Scarano, 2017).
37
38 There is high confidence that ecological and social resilience is improved by the presence of adequate
39 metrics evaluating adaptation measures that allow dynamic changes, increasing basic research and climate
40 data (Moreno et al., 2020b), the existence of early warning systems, improved local institutions, the
41 construction of adequate infrastructure, major funding for capacity building, and the enhanced engagement
42 and empowerment of women (FAO, 2016b; Harper et al., 2017; Frangoudes and Gerrard, 2018; Gallardo-
43 Fernández and Saunders, 2018; Leal Filho, 2018).
44
45 12.5.3 Water
46
47 CSA is one of the regions most affected by current and future hydrological risks to water security with an
48 increasing number of vulnerable people depending on water from mountain (high confidence) (Sections 4.3,
49 4.4, 4.5; Immerzeel et al., 2020; Viviroli et al., 2020; WWAP, 2020). Adaptation to changing water
50 availability is therefore a priority, but most efforts are documented only in the grey literature (e.g.,
51 governmental documents, project reports) with highly variable standards of quality and evidence. Most of the
52 documented adaptation initiatives are in an early planning or implementation stage and evidence on
53 successful outcomes is quite limited (Berrang-Ford et al., 2021). However, the growing number of adaptation
54 initiatives across the CSA region has contributed to improved understanding of complex interlinkages of
55 climate change, human vulnerabilities, local policies, and feasible adaptation approaches (McDowell et al.,
56 2019).
57
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1 12.5.3.1 Challenges and opportunities
2
3 In several regions of CSA, water scarcity is a serious challenge to local livelihoods and economic activities.
4 Particularly (seasonally) dry regions, partly with large populations and increasing water demand, exhibit
5 major water stress. These include the dry corridor in CA, coastal areas of Peru (SWS) and Northern Chile
6 (SWS), the Bolivian-Peruvian Altiplano (NWS, SAM), the Dry Andes of Central Chile (SWS),Western
7 Argentina and Chaco in Northwest Paraguay (SES), and Sertão in Northeast Brazil (NES) (high confidence)
8 (Kummu et al., 2016; Mekonnen and Hoekstra, 2016; Schoolmeester et al., 2018). In NWS and SWS,
9 downstream areas are increasingly affected by decreasing and unreliable river runoff due to rapid glacier
10 shrinkage (high confidence) (Table SM12.6; Carey et al., 2014; Drenkhan et al., 2015; Buytaert et al., 2017).
11 Many regions in CSA rely heavily on hydroelectric energy, and as a result of rising energy demand,
12 hydropower capacity is constantly extended (Schoolmeester et al., 2018). Worldwide, SA features the
13 second-fastest growth with about 5.2 GW additional annual capacity installed in 2019 (IHA, 2020). This
14 development requires additional water storage options, which entail the construction of large dams and
15 reservoirs with important social-ecological implications. River fragmentation and corresponding loss of
16 habitat connectivity due to dam constructions have been described for e.g., the NSA, SAM, NES and SES
17 (high confidence) (Grill et al., 2015; Anderson et al., 2018a) with important implications for freshwater
18 biota, such as fish migration (medium confidence) (Pelicice et al., 2015; Herrera-R et al., 2020). Furthermore,
19 examples in e.g., the NWS (Carey et al., 2012; Duarte-Abadía et al., 2015; Hommes and Boelens, 2018) and
20 SWS (Muñoz et al., 2019b) showcase unresolved water-related conflicts between local villagers, peasant
21 communities, hydropower operators and governmental institutions in a context of distrust and lack of water
22 governance (high confidence).
23
24 Increasing water scarcity is also shaped by poor water quality, which has barely been assessed in CSA.
25 Declining water quality can be observed e.g., due to intense agricultural and industrial activities in SWS,
26 SES and SSA (medium confidence) (Mekonnen et al., 2015; Gomez et al., 2021), mining in Andean
27 headwaters (NWS, SWS and Western SAM) and tropical lowlands (Eastern SAM and NSA) (medium
28 confidence) (Bebbington et al., 2015 risk and climate resilience; Vuille et al., 2018), urban domestic use
29 (Desbureaux and Rodella, 2019), decreasing meltwater contribution (Milner et al., 2017) and acid rock
30 drainages from recently exposed glacial sediments (Santofimia et al., 2017; Vuille et al., 2018). The level of
31 water pollution is often exacerbated by missing water treatment infrastructure and low governance levels
32 (medium confidence) (Mekonnen et al., 2015) with considerable negative implications for human health
33 (Lizarralde Oliver and Ribeiro, 2016).
34
35 Water scarcity risks are projected to affect a growing number of people in the near and mid-term future in
36 view of growing water demand in most regions (medium confidence: medium evidence, high agreement)
37 (Veldkamp et al., 2017; Schoolmeester et al., 2018; Viviroli et al., 2020), expected precipitation reductions
38 in Western and Northern SAM and SWS (medium confidence: medium evidence, medium agreement)
39 (Neukom et al., 2015; Schoolmeester et al., 2018), substantial vanishing of glacier extent in NWS, SAM and
40 SWS (Table SM12.6; Rabatel et al., 2018; Vuille et al., 2018; Cuesta et al., 2019; Drenkhan et al., 2019), and
41 increasing evaporation rates in CA (medium confidence) (CEPAL, 2017). Furthermore, flood risk is a serious
42 concern (Arnell et al., 2016) and expected to increase especially in NWS, SAM, SES and SWS in the mid
43 and long-term future (high confidence) (Arnell and Gosling, 2016; Alfieri et al., 2017).
44 Risks of water scarcity and flood are threatening people unevenly across the region. In CSA, about 26% (130
45 million people) of the population have no access to safe drinking water and strong disparities prevail
46 regarding its spatial distribution, e.g., in Chile 99% of the population have access, compared to 50% in Peru,
47 73% in Colombia, 52% in Nicaragua or 56% in Guatemala (high confidence) (UNICEF and WHO, 2019).
48 Inequalities can be further exacerbated by unregulated or privately owned water rights and allocation
49 systems (e.g., in Chile) (Muñoz et al., 2020a). The most vulnerable people belong to low-income groups in
50 rural areas and informal settlements of large urban areas (high confidence) (WWAP, 2020).
51
52 Considerable uncertainties remain concerning future hydrological risks that strongly depend on the
53 respective pathways of human intervention, management, adaptation and socioeconomic development. The
54 combination of (seasonally) reduced water supply, growing water demand, declining water quality,
55 ecosystem deterioration and habitat loss, and low water governance could lead to increasing competition and
56 conflict associated with high economic losses (high confidence) (Vergara et al., 2007; Vuille et al., 2018;
57 Desbureaux and Rodella, 2019). This situation threatens human water security on the long term and poses an
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1 increasing risk to adaptation success in CSA (high confidence) (Drenkhan et al., 2015; Huggel et al., 2015b;
2 Urquiza and Billi, 2020a).
3
4 Important progress has been made on climate change and water management policies in combination with
5 more inclusive stakeholder processes. For instance, the implementation of NDCs in most countries of the
6 region provides an important baseline for improving water efficiency, quality and governance at multi-
7 sectoral level, and thus long-term adaptation planning (UNEP, 2015).
8
9 12.5.3.2 Main concepts and approaches
10
11 Adaptation in the water sector includes a broad set of responses to improve and transform, among others,
12 water infrastructure, ecosystem functions, institutions, capacity building and knowledge production, habits
13 and culture, and local-national policies (Section 4.6).
14
15 Most adaptive water management approaches in CSA centre around extending the water supply side
16 including large infrastructure projects. However, 'hard path' interventions are now strongly contested due to
17 negative effects exacerbating local water conflicts (Carey et al., 2012; Boelens et al., 2019; Drenkhan et al.,
18 2019), potentially leading to increasing water demand, vulnerabilities and water shortage risks (Di
19 Baldassarre et al., 2018), and, hence, limiting adaptive capacity (high confidence) (Ochoa-Tocachi et al.,
20 2019). More integrated approaches focus on multi-use of water storage with shared stakeholder vision,
21 responsibilities, rights and costs, as well as risks and benefits, and often integrating water and risk
22 management (Branche, 2017; Haeberli et al., 2017; Drenkhan et al., 2019). In this chapter, a feasibility
23 assessment was carried out for six major dimensions of multi-use water storage for the entire CSA (see Table
24 12.11). While geophysical and economic aspects allow for the implementation of water storage projects with
25 multi-use approach, the institutional, social and environmental dimensions pose a major barrier (see Section
26 12.5.3). Further demand-oriented approaches focus on incentives for the reduction of water use through
27 changes in people's habits, efficiency increase and smart water management (Gleick, 2002). These are
28 promoted in some regions, such as in CA and NWS (e.g., Colombia, Ecuador and Peru), to foster a
29 sustainable water culture (Bremer et al., 2016; Paerregaard et al., 2016).
30
31 Major attention has been put on nature-based solutions (NbS), i.e., catchment interventions that are inspired
32 and supported by nature and leverage natural processes and ecosystem services to contribute to the improved
33 management of water. NbS potentially enhances water infiltration, groundwater recharge and surface
34 storage, contributes to disaster risk reduction and can replace or complement grey (i.e., conventionally built)
35 infrastructure that is often socio-environmentally contested (WWAP, 2018). Some examples include the
36 reactivation of ancestral infiltration enhancement systems in the Peruvian Andes (NWS) (Ochoa-Tocachi et
37 al., 2019), the use of erosion control structures in the Bolivian Altiplano (SAM) (Hartman et al., 2016), and
38 the potential improvement of drinking water quality and flood risk reduction in urban areas of CSA (Tellman
39 et al., 2018, Section 12.5.5.3.2). Additionally, NbS in combination with ecosystem and community-based
40 adaptation potentially generate important co-benefits including increasing water security and the attenuation
41 of social conflicts in Chile (SWS) (Reid et al., 2018), water conservation in coastal Peru (NWS), and flood
42 protection in Guyana (NSA) (medium confidence: medium evidence, medium agreement) (Spencer et al.,
43 2017). However, evaluation of implementation success of NbS is often hampered by limited evidence on
44 actual benefits (WWAP, 2018).
45
46 In recent years, the inclusion of Indigenous knowledge (IK) and local knowledge (LK) into current
47 adaptation baselines has gained increasing attention, particularly in regions with a high share of Indigenous
48 Peoples (NWS, SAN, SWS, NSA) (high confidence) (Reyes-García et al., 2016; Schoolmeester et al., 2018;
49 McDowell et al., 2019). One example is the adapted use of agrobiodiversity when dealing with more
50 frequent and intense tidal floods in the Amazon delta (NSA) (Vogt et al., 2016). In another context, IK and
51 LK have been considered for the evaluation of water scarcity and glacier lake outburst flood risks in Peru
52 (NWS) (Motschmann et al., 2020b). Additionally, local citizen science based initiatives (Buytaert et al.,
53 2014; Tellman et al., 2016; Njue et al., 2019) can support the production of multiple knowledge with flexible
54 and extensive data collection. Important questions centre around how to integrate IK, LK and other types of
55 knowledge from the early planning stages on, to achieve enhanced or transformational adaptation building
56 on co-produced knowledge (Kates et al., 2012; Klenk et al., 2017). NbS combined with community
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1 engagement and integration of diverse knowledge can foster transformational adaptation of social-ecological
2 systems (Palomo et al., 2021).
3
4
5 Figure 12.13: Overview map of observed glacier changes, associated impacts, adaptation and policy efforts across the
6 Andes. (a) Selected impacts from glacier shrinkage. (b) Selected adaptation efforts (see upper-right map for the location
7 of each adaptation measure), (c) Policies and glacier inventory: NDC = submission year(s) of Nationally Determined
8 Contributions (u = update), CCL = climate change law, GLL = glacier law (i = initialized framework), INV = last
9 national glacier inventory. The explicit mention of glaciers, snow and mountain ecosystems within each law/inventory
10 is highlighted with the corresponding symbols (grey colour = not come into force). (d) Glacier area (km²) according to
11 last national inventory. (e) Glacier area change (%/year) according to the baseline of the last national inventory. (f)
12 Geodetic glacier mass balance (m w.e./year) and error estimate (±m w.e./year) retrieved from Dussaillant et al. (2019).
13 nd = no data available. Further details can be found in the Appendix in Table SM12.6.
14
15
16 12.5.3.3 Policies, governance and financing
17
18 National policies on climate change, water protection, regulation and management laws are important focal
19 areas of adaptation in the water sector (Section 4.7). Notable in the jurisdiction field is the Glacier Protection
20 Law in place in Argentina (2010-2019), and under construction in Chile (since 2005). This first glacier law
21 in the world represents a milestone for high-mountain conservation but is also criticized for hindering
22 effective disaster risk adaptation measures and excluding local socioeconomic needs (Anacona et al., 2018).
23 Furthermore, the first Framework Law on Climate Change was implemented in Peru (2018), and is
24 underway in Colombia, Chile and Venezuela (Figure 12.13; Table SM12.6). Overarching regional
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1 institutions (e.g., OAS (2016)) and most countries in CSA promote a move towards more integrative and
2 sustainable management of water resources through new legislations and financing mechanisms. For
3 instance, new water laws including principles of Integrated Water Resources Management (IWRM) have
4 entered into force, e.g., in Nicaragua (2007), Peru (2009), Ecuador (2014) and Costa Rica (2014) or are
5 underway, such as in Colombia (since 2009). However, current realities in all regions show major challenges
6 in implementing IWRM mechanisms and policies, related but not limited to political and institutional
7 instabilities, governance structures, fragmented service provision, lack of economies of scale and scope,
8 corruption and social conflicts (high confidence) (WWAP, 2020).
9
10 Many water-related conflicts in CSA are rooted in inequitable water governance that excludes water users
11 from decisions on water allocation (high confidence) (Drenkhan et al., 2015; Vuille et al., 2018). In turn,
12 inclusive water regimes leverage long-term adaptation planning. These have been addressed in some national
13 strategies, such as in Brazil (Ministry of Environment of Brazil, 2016a). At the local level, a decentralized
14 and participatory bottom-up water governance model was induced by civil society and research institutions
15 to foster rainwater harvesting technologies reducing drought risk in semi-arid Brazil (NES) (Lindoso et al.,
16 2018).
17
18 Water fund programs can generate important co-benefits for Sustainable Development contributing to
19 improved governance and conservation of watershed systems in CSA. Nevertheless, only a few experiences
20 have been evaluated as successful due to insufficient implementation, low decision-making of some
21 stakeholder groups and poor evidence-based approaches (medium confidence) (Bremer et al., 2016; Leisher
22 et al., 2019). Furthermore, financing mechanisms that produce incentives for sustainable water management
23 have been promoted, tested or implemented. Payments for Ecosystem Services (PES) for water provision
24 represent such an example and have been implemented across CSA since the 1990s (Grima et al., 2016).
25
26 Only about 5070% of required financial resources are currently allocated per year to meet the national
27 targets in the water, sanitation and hygiene (WASH) sector for the Sustainable Development Agenda (SDG
28 6) in several regions of CSA. This share drops down to less than 50% in NSA (Venezuela) and SES
29 (Argentina, Uruguay, Paraguay), except for Panama in CA allocating more than 75% of required financial
30 resources. For the implementation of NbS, evidence suggests that the overall expenditure remains well below
31 1% of total investment in water resources management infrastructure (WWAP, 2018). These funding deficits
32 pose important limitations for future water provision, adaptation to changing water resources, and the
33 achievement of the SDGs by 2030 (high confidence) (WHO, 2017).
34
35 12.5.3.4 Successful adaptation and limitations
36
37 Although a growing body of adaptation initiatives exists for CSA, evidence on effectiveness is scarce. In
38 many parts of CSA the level of success of respective adaptation measures depends much on the governance
39 of projects and stakeholder-based processes and is closely related to their effectiveness, efficiency, social
40 equity and socio-political legitimacy (high confidence) (Adger et al., 2005; Rasmussen, 2016b; Moulton et
41 al., 2021). Several Payments for Ecosystem Services experiences across CSA have been described as
42 successful measures for watershed conservation and adaptation (high confidence). An example of success
43 represents the Quito water fund in Ecuador which aims at improving the city's water quality by integrating
44 public and private stakeholder interests with ecosystem conservation and local community development
45 since the 2000's (Bremer et al., 2016; Grima et al., 2016) (case study 12.6.1). At the same time, in
46 Moyobamba in Peru the development of a watershed protection program was leveraged by a multi-
47 stakeholder platform process that enabled deep social learning (Lindsay, 2018). In turn, initiatives that do not
48 consider the entire set of social-ecological dimensions and dynamics of adaptation or unintentionally
49 increase vulnerabilities of human or natural systems, are at risk to lead to reduced outcomes (McDowell et
50 al., 2021) or maladaptation (Reid et al., 2018; McDowell et al., 2019; Eriksen et al., 2021). However,
51 systematic assessments of maladaptation in the water sector have barely been provided for CSA.
52
53 In CSA, only limited information on limits of adaptation in relation to water is available, for instance on
54 possible path dependency of institutions and associated resistance to change (Barnett et al., 2015). Examples
55 of soft adaptation limits (i.e., options to avoid intolerable risks currently not available) include the lack of
56 trust and stakeholder flexibility, associated with unequal power relations that lead to reduced social learning,
57 and poor outcomes for improved water management, as reported in e.g., NWS (Lindsay, 2018). An example
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1 for hard adaptation limits (i.e., intolerable risks cannot be avoided) in the region is the loss of livelihoods and
2 cultural values associated with glacier shrinkage in NWS (Jurt et al., 2015).
3
4 Most barriers to advance adaptation in CSA correspond to soft limits associated with missing links of
5 science-society-policy processes, institutional fragilities, pronounced hierarchies, unequal power relations
6 and top-down water governance regimes (high confidence). One example is the abandonment of hydrological
7 long-term monitoring sites within tropical Andean ecosystems (paramo) in Venezuela (Rodríguez-Morales et
8 al., 2019) due to the lack of governmental support within a political crisis. In that regard, the collection and
9 availability of consistent hydroclimatic and socioeconomic data at adequate scales represent an important
10 challenge in CSA. Major adaptation barriers are furthermore reported from Central Chile in the context of a
11 mega-drought since 2010, related to socioeconomic characteristics and a deficient bottom-up approach to
12 public policy informing and development (Aldunce et al., 2017). These gaps could be bridged by
13 strengthening transdisciplinary approaches at the science-policy interface (Lillo-Ortega et al., 2019) with
14 blended bottom-up and top-down adaptation to include scientific knowledge with impact and scenario
15 assessments into local adaptation agendas (Huggel et al., 2015b). For instance, a new allocation rule for the
16 Laja reservoir in Southern Chile (SWS), based on consistent water balance modelling results, could inform
17 policy and water management and potentially improve local water management and reduce water conflicts
18 on the long term (Muñoz et al., 2019b).
19
20 12.5.4 Food, Fibre and other Ecosystem Products
21
22 The CSA region globally has the greatest agricultural land and water availability per capita. With 15% of the
23 world's land area, it receives 29% of global precipitation and has 33% of globally available renewable
24 resources (Flachsbarth et al., 2015). Agricultural commodities (coffee, bananas, sugar, soybean, corn,
25 sugarcane, beef livestock) are some of the highest users of ecosystem resources such as land, water, nutrients
26 and technology. These exports have gained importance in the past two decades as international trade and
27 globalization of markets have shaped the global agri-food system. However continuous overuse on the
28 environment might account for resource depletion (deforestation, land degradation, nutrient depletion,
29 pollution), affecting the natural capital base. The effects of climate change on humans, via ecological
30 systems, exacerbate the impact related to depletion of ecosystem services (Scholes, 2016; IPBES, 2018b;
31 Castaneda Sanchez et al., 2019; Clerici et al., 2019; Tellman et al., 2020; Pacheco et al., 2021).
32
33 12.5.4.1 Challenges and opportunities
34
35 Even though there are large improvements in food availability in several regions, there is also a tendency of
36 a decline in food self-sufficiency in many countries (Porkka et al., 2013; Rolando et al., 2017). Drought
37 conditions in Central America and the Caribbean increased in line with climate model predictions (Herrera et
38 al., 2018a). The direct social and economic consequences for the sector are evident in Central America's so-
39 called Dry Corridor with a growing dependence on food imports (Porkka et al., 2013) and these degrees of
40 dependency make the region more vulnerable to price variability, climatic conditions (Bren d'Amour et al.,
41 2016; ECLAC, 2018) and therefore, to food insecurity if adaptation actions are not taken (high confidence)
42 (Porkka et al., 2013; Bren d'Amour et al., 2016; López Feldman and Hernández Cortés, 2016; Eitzinger et
43 al., 2017; Imbach et al., 2017; Lachaud et al., 2017; Harvey et al., 2018; Niles and Salerno, 2018; del Pozo et
44 al., 2019; Alpízar et al., 2020; Anaya et al., 2020).
45
46 Given these circumstances, some regions in CSA (Andes region and Central America) will just meet, or fall
47 below, the critical food supply/demand ratio for their population (Bacon et al., 2014; Barbier and Hochard,
48 2018b). Meanwhile, the more temperate part of South America in the south is projected to have agricultural
49 production surplus (low confidence) (Webb et al., 2016; Prager et al., 2020). The challenge for this region
50 will be to retain the ability to feed and adequately nourish its internal population as well as making an
51 important contribution to the food supplies available to the rest of the world.
52
53 The access of agricultural products from the region to other markets might be conditioned on the adoption of
54 low-carbon agriculture measures. Achieving net-zero emissions while improving standards of living is
55 possible but requires developing transition policy frameworks to attain the target (Frank et al., 2019;
56 Mahlknecht et al., 2020; Cárdenas et al., 2021).
57
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1 12.5.4.2 Governance and barriers for adaptation
2
3 The governance of adaptation for CSA implies modifying agricultural, socio-economic and institutional
4 systems in response to and in preparation for actual or expected impacts of climate variability and change, to
5 reduce harmful effects and exploit beneficial opportunities (high confidence). CSA agriculture has a diversity
6 of systems and segments of producers. While small-scale farmers have a big contribution to food production
7 and food security, especially in developing economies, they face global policies oriented towards global
8 commodity markets (Knapp, 2017; Fernández et al., 2019). Climate action initiatives that consider CSA's
9 high levels of poverty and inequality to reduce these pervasive problems are central for adapting the region
10 (Crumpler et al., 2020; Locatelli et al., 2020).
11
12 Since AR5, important advances at institutional level are observed based on the development and
13 implementation of national adaptation plans for the agriculture and forestry sector among countries.
14 Adapting to climate change entails the interaction of decision-makers, stakeholders, and institutions at
15 different scales of government from the local to the national. The Climate-Adapted Sustainable Agriculture
16 Strategy for the region of the Central American Integration System (EASAC) of the Central American
17 Agricultural Council of Ministers of Agriculture, constitutes a valuable example of how undertake climate
18 action in the agricultural sector, as a block of countries and in an intersectoral manner, to enhance results and
19 make better use of resources (IICA, 2019).
20
21 In Brazil, the Low Carbon Agriculture program (Programa ABC) funds practices for reducing GHG
22 emission in the sector (Government of Brazil, 2012), allocating about 15% of the total agriculture official
23 finance portfolio, although it faces challenges to advance (Souza Piao et al., 2021). Costa Rica offers an
24 example on how reforestation can help achieve Paris Agreement objectives. Reforestation through natural
25 regeneration on abandoned pastures boosted forest cover from 48% in 2005 to 53.4% in 2010 (Reid et al.,
26 2019; Cárdenas et al., 2021). Some key success factors included a strong institutional context, fiscal and
27 financial incentives for reforestation, conservation measures such as payment for environmental services,
28 cattle ranch subsidy reform, and a historically strong enforcement and focus on land titles that favoured the
29 restoration of lands. Uruguay offers another example, with the farm sector contribution of 32.8% of all
30 exports and 73.8% of the country's emissions, so decarbonisation is not just an environmental issue but an
31 economic competitiveness one as well. In the INDCs submitted to the UNFCCC in 2015, Uruguay set a
32 specific target for the agriculture sector to reduce enteric methane emissions intensity per kilogram of beef
33 (live-weight) by 33% to 46% in 2030 through improving efficiency of beef production by controlling the
34 grazing intensity to increase animal intake, reproductive efficiency, and daily weight gain (Picasso et al.,
35 2014).
36
37 It is relevant to generate conditions for the development of sustainable agricultural practices in a frame
38 where factors associated with climate have become important for producers, given recent experiences of
39 drought and lack of water (high confidence) (Clarvis and Allan, 2014; Roco et al., 2016; Hurlbert and Gupta,
40 2017; Pérez-Escamilla et al., 2017; Cruz et al., 2018; Zúñiga et al., 2021). Solutions that consider relevant
41 drivers that have demonstrated positive effect in diffusion of adaptation strategies are more efficient (Table
42 12.8). Some conditions such as the promotion of education programs; participation in cooperatives; credit
43 access; land tenure security can help in this task. In the same line, in CSA some elements such as technology
44 and information access, and local knowledge, reinforce climate change adaptation (Khatri-Chhetri et al.,
45 2019; Piggott-McKellar et al., 2019). As is stated in Table 12.8 barriers of different origin persist for climate
46 change adaptation in the region increasing vulnerability of farming systems and rural livelihoods.
47
48 Limited information regarding cost-benefit analyses of adaptation is available in the region as well as
49 avoiding maladaptation effects and promoting site-specific and dynamic adaptation options considering
50 available technologies (medium confidence) (Roco et al., 2017; Zavaleta et al., 2018; Ponce, 2020; Shapiro-
51 Garza et al., 2020).
52
53 Climate Information Services has an important role in climate change adaptation and there is a recognized
54 gap between climate science and farmers (high confidence) (Vaughan et al., 2017; Loboguerrero et al., 2018;
55 Tall et al., 2018; Thornton et al., 2018; Ewbank et al., 2019). Such services should address the challenges of
56 ensuring that climate information and advisory services are relevant to the decisions of small-holder and
57 family farmers, providing timely climate services access to remote rural communities with marginal
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1 infrastructure and ensuring that farmers own climate services and shape their design and delivery. An
2 interesting case facing this gap is the implementation of local technical agro-climatic committees in
3 Colombia which allow to share and to validate climatic and weather forecasts; and crop model results to
4 seasonal drought events (Loboguerrero et al., 2018). Another example is the web service, AdaptaBrasil-
5 MCTI, forecasting the risk of climate change impact on strategic sectors (e.g., food, energy, water) in Brazil
6 (Government of Brazil and Ministry of Science Technology and Innovation Secretariat of Policies and
7 Programs, 2021).
8
9 Barriers to financial access are present in the region restricting effective adaptation to extreme weather
10 events (high confidence) (Chen et al., 2018; Fisher et al., 2019; Piggott-McKellar et al., 2019; Vidal Merino
11 et al., 2019; de Souza Filho et al., 2021). In 2014, the penetration rate of this type of insurance in the region
12 averaged 0.03% of GDP, and a few countries dominate the market (Brazil, Argentina). Beyond these three
13 countries, some initiatives also exist in Uruguay, Paraguay, Chile and Ecuador. In most Latin American and
14 Caribbean countries, the public sector plays an important role in providing insurance or reinsurance and
15 coexists with private sector companies (Cárdenas et al., 2021). Insurance protections represent a strategy to
16 transfer climate risk to protect the wellbeing of vulnerable small farmers and accelerate uptake (recovery)
17 after a climate-related extreme weather event. Lack of finance and proper infrastructure is compounded by
18 limited knowledge of sustainable farming practices and high rates of financial illiteracy (high confidence)
19 (Hurlbert and Gupta, 2017; Piggott-McKellar et al., 2019).
20
21 Insufficient access to digital services and technologies further widens the gap between the rural poor and
22 more urban populations of Latin America and the Caribbean (medium confidence: insufficient evidence, high
23 agreement). In turn, these factors compromise productivity and competitiveness. Support for this group can
24 be focused on both economic competitiveness and social development. Finally, to align identified adaptation
25 options as a priority for achieving future food security in the NDCs of CSA countries to mitigation
26 commitments, it will be essential to highlight synergies by generating evidence (national research) in relation
27 to progress towards increasing productivity, resilience and reducing GHG; and also demonstrating its added
28 value as a development initiative (Rudel et al., 2015 sustainable; Loboguerrero et al., 2019).
29
30 12.5.4.3 Adaptation options
31
32 In order to contextualize the adaptation options at the regional level, the majority of the NDC of the CSA
33 countries reported the observed and/or projected climate-related hazards: occurrence of droughts and floods
34 (80% of countries each), followed by storms (45%) and landslides (30%), as well as extreme heat, wildfire
35 and invasion by pests and non-native species in agriculture (25% each) (Crumpler et al., 2020).
36
37 Main adaptation options for climate change in the region include preventive measures against soil erosion;
38 climate-smart agriculture which provide a framework for synergies between adaptation, mitigation and
39 improved food security; climate information systems; land use planning; shifting plantations in high altitude
40 to avoid temperature increases and plagues; improved varieties of pastures and cattle (Lee et al., 2014; Jat et
41 al., 2016; Crumpler et al., 2020; Moreno et al., 2020a; Aragón et al., 2021). Agricultural technologies are not
42 necessarily changing, but the economic activity is shifting to accommodate increasing climate variation and
43 adapt to changes in water availability and ideal growing conditions (high confidence) as is observed in
44 Argentina, Colombia and Brazil (McMartin et al., 2018; Rolla et al., 2018; Sloat et al., 2020; Gori Maia et
45 al., 2021). Coffee plantations are moving further up mountain regions with the land at lower elevations
46 converted for other uses. In Brazil, crop modelling suggests the need for the development of new cultivars,
47 with a longer crop cycle and with higher tolerance to high temperatures, a necessary technological advance
48 for maize, an essential staple crop, to be produced in the future. Additionally, irrigation becomes essential for
49 sustaining productivity in adverse climate change scenarios in several regions of CSA (McMartin et al.,
50 2018; Lyons, 2019; Reay, 2019).
51
52 Livestock production is for small farmers one of the main sources of protein and contributes to food security
53 (Rodríguez et al., 2016). The importance of this sub-sector in CSA, will continue to increase as the demand
54 for meat products does as well in the coming years, driven by growing incomes in the region (OECD and
55 FAO, 2019). However, the increase in animal production has been associated with land degradation,
56 triggered by the conversion of native vegetation to pastureland and aggravated by overgrazing and
57 abandoning of the degraded pastures (Baumann et al., 2017; ECLAC, 2018; Müller-Hansen et al., 2019). Sá
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1 et al. (2017) simulated the adoption of agricultural systems based on Low-Carbon Agriculture (LCA)
2 strategies towards 2050. According to the simulation, the adoption of LCA strategies in the SA region can
3 alter the growing trend of Land Use and Land Use Change emissions and at the same time, it can increase
4 meat production by 55Mt for the entire period (20162050). The restoration of degraded pasture and
5 livestock intensification account for 71.2%, and integrated crop-livestock-forestry system contributes 28.8%
6 of total meat production for the entire period. These results indicate that combined actions in agricultural
7 management systems in SA, can result in synergistic responses that can be used to make agriculture and
8 livestock production an important part of the solution of global climate change and advance food security
9 (medium confidence: insufficient evidence and high agreement) (Zu Ermgassen et al., 2018; Pompeu et al.,
10 2021). Crop-Livestock-Forestry-Systems are also important for climate change adaptation as they provide
11 multiple benefits, including the coproduction of food, animal feed, organic fertilizers and soil organic carbon
12 sequestration (Sharma et al., 2016; Rodríguez et al., 2021), achieving mitigation and adaptation goals (high
13 confidence) (Picasso et al., 2014; Modernel et al., 2016; Modernel et al., 2019; Rolla et al., 2019; Locatelli et
14 al., 2020). A recent analysis of agroforestry in Brazil, has shown positive and relevant impacts on the
15 heads/pasture area rate in livestock production and that the system may have also stimulated a shift toward
16 other production activities with higher gross added value (Gori Maia et al., 2021). Agroforestry has also
17 proven to have protective benefits to obtain more stable, less fluctuating yields due to climate damages in
18 coffee production (high confidence) (Bacon et al., 2017; Durand-Bessart et al., 2020; Ovalle-Rivera et al.,
19 2020). In the same way, the production of plant-based fibre can be less vulnerable to economic and climatic
20 variability through farming systems diversification. Textile fibre crops for the case of cotton include crop
21 rotation, agroecological intercropping and agroforestry (Oliveira Duarte et al., 2019).
22
23 Adaptation strategies also concern Indigenous agriculture, i.e., the vast majority of the 44 million
24 Amerindians (CEPAL, 2014). Indigenous knowledge and local knowledge (IK and LK) can play an
25 important role in adaptation (Zavaleta et al., 2018). On one hand, they preserve the conservation of a very
26 rich agrobiodiversity that is likely to meet the challenges of climate change (high confidence) (Carneiro da
27 Cunha and Morim de Lima, 2017; Magni, 2017; Emperaire, 2018; Donatti et al., 2019) and on the other
28 hand, the sustainability of large territories that assure their livelihood (Singh and Singh, 2017; Mustonen et
29 al., 2021). In the Andes, ancient technologies increased the quantity of crops produced and allowed for
30 coping with climatic changes and water scarcity, while nutrition conditions were improved (high confidence)
31 (López Feldman and Hernández Cortés, 2016; Parraguez-Vergara et al., 2018; Carrasco-Torrontegui et al.,
32 2020 food). Also, fire prevention management, protection against forest and biodiversity loss, are recognized
33 as important elements in Indigenous knowledge (Mistry et al., 2016; Bowman et al., 2021).
34
35
36 Table 12.8: Recent studies related to climate change adaptation of agricultural systems and its determinants in the CSA
37 Region.
Authors, Countries Sampl Approach Crop Adaptation Main Main Main
year e size of the systems strategies drivers barriers barriers
(n) study promoting limiting detected
climate climate
change change
adaptation adaptation
de Souza 175 Quant. Cattle Integrated Credit Lack of Lack of
Filho et Brazil farmers crop-livestock access resources agricultur
al. (2021) and livestock- Extension al market
forestry services access
systems strategies
Magalhãe Several Farm Previous Inadequate Infrastruc
crops management experience infrastructu ture
s et al. Brazil 94 Qual. with risks re limiting
Low opportuni
(2021) purchasing ties
power
Carrer et Brazil 175 Quant. Several Agricultural Schooling Higher risk Limited
al. (2020) crops insurance propensity financial
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Technical market
assistance access
Quiroga Nicaragua 212 Quant. Coffee Several Farm size Limited Absence
et al. Quant. adaptation Awareness access to of
(2020) Qual. measures of climate rain-water climate
Quant. change change
Quant. Schooling education
Bro et al. Nicaragua 236 Quant. Coffee Crop Schooling Household Institutio
(2019) Soil and Participation size nal
Quant. water in framewor
Quant. cooperatives k to
Radio promote
cooperati
ves
Leroy Venezuela Several Irrigation Perception Degradatio Ineffectiv
(2019) crops in management of water n of fragile eness of
and 73 high scarcity areas local
altitudes Local institutio
Colombia knowledge ns
Cherubin Several Agroforestry Improving Degradatio Lack of
crops systems soil quality n of crop
et al. Colombia 6 and and biota convention diversific
pasture al pasture ation
(2019)
Costa Coffee, Affordabilit Lack of
beans y of adaptatio
Harvey et Rica, 860 and Several Awareness adaptation n
al. (2018) Honduras maize adaptation of climate practices involving
and practices change agroecolo
gical and
Guatemala socioeco
nomic
contexts
Chen et Costa Rica 559 Several Intensificatio Access to Land Lack of
al. (2018) and crops n and weather renting crop and
Nicaragua diversificatio information practices
n Participation diversific
in ation
organization
s
Credit
access
Farming
experience
Vidal Several Water Farm size Limited Lack of
crops management Capital access to site-
Merino et Peru 137 Irrigated off-farm specific
proportion activities design of
al. (2019) Small interventi
cultivated ons
area
Meldrum Potato, Diversificatio Weather Loss to Lack of
quinoa traditional resilience
et al. Bolivia 193 and n of crop information knowledge and
others actions to
(2018) portfolio
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expand
and
maintain
variety
portfolio
Lan et al. Nicaragua 180 Quant. Cocoa Crop Schooling Lack of Income
(2018) management Household income inequalit
size y
Farm size Gaps of
profitabil
ity of
practices
Benefits
of
practices
depends
of its
costs
Kongsag 125 Qual. Maize Alley Schooling Land tenure Lack of
er (2017) Belize cropping Market land
distance tenure
Degradatio Lack of
n of fragile market
areas access
Lack of
trust
Schembe 5485* Quant. Several Agroforestry Financing High Adaptatio
rgue et Brazil crops systems Presence of potential n
al. (2017) associations for condition
Credit agriculture ed by
access Lack of agricultur
climate al,
information socioeco
nomic
and
climatic
condition
s
Guatemala Coffee Ecosystem Schooling Lack of
and based Age access to
Harvey et , Honduras 300 Quant. maize adaptation Farming Lack of training
al. (2017) and Costa experience land tenure and
Access to finance
Rica technologica
l support
Roco et Chile 665 Quant. Several Water Farm size Locations Lack of
al. (2016) crops management Access to Age availabili
weather ty and
information access to
climate
change
informati
on
Mussetta Argentina 41 Qual. Vine Crop and Organization Water Lack of
and and water of producers allocation water
others management system managem
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Barriento Labour ent and
s (2015) availability distributi
Knowledge on
and strategies
information
access
Technology
access
1 Table Notes:
2 *: municipalities; Quant.: mainly quantitative; Qual.: mainly qualitative.
3
4
5 12.5.5 Cities, Settlements and Infrastructure
6
7 CSA is the second most urbanized region of the world, with 5 megacities and half of urban population in 129
8 secondary cities (UNDESA, 2019), huge metropolitan areas concentrated on the coast and an increasing
9 number of small cities by the sea (Barragán and de Andrés, 2016). Besides the many climatic events
10 threatening urban areas in the region (extreme heat, droughts, heavy storms, floods, landslides), cities by the
11 coast are also exposed to sea level rise (SLR) (Section 12.3; Figure 12.6; Dawson et al., 2018; Leal Filho et
12 al., 2018; Le, 2020). Main determinants of urban vulnerability assessed in the region are poor and unevenly
13 distributed infrastructure, housing deficits, poverty, informality and the occupation of risk areas, including
14 low elevation coastal zones (Section 12.3). Those features of urban systems increase the risks to health,
15 ecosystems and its services, water, food and energy supply (Section 12.4). Impacts of climate events on
16 urban water supply, drainage and sewer infrastructures are the most reported in the region (Section 12.3;
17 Figure 12.9).
18
19 12.5.5.1 Challenges and opportunities
20
21 Inequality, poverty and informality shaping cities in the region increase vulnerability to climate change (high
22 confidence) (Romero-Lankao et al., 2014; Rasch, 2017; Filho et al., 2019), and can hinder adaptation
23 (Section 12.5.7.1), while interventions addressing these social challenges and the existing development
24 deficits (e.g., build or improve infrastructure and housing applying climate-adapted patterns), can go hand in
25 hand with adaptation and mitigation (medium confidence: high agreement, medium evidence) (Section
26 12.5.7.3; Creutzig et al., 2016; Le, 2020; Satterthwaite et al., 2020). Over 20% of urban population in LAC
27 lives in slums and many in other forms of precarious and segregated neighbourhoods, settled in risk areas
28 and lacking infrastructure (Rasch, 2017; UN-Habitat, 2018; Rojas, 2019). This vulnerable condition is
29 boosted by unstable political and governmental institutions, which recurrently suffer from corruption, weak
30 governance and reduced capacity to finance adaptation (Rasch, 2016). Facing governance challenges by
31 including diverse stakeholders and encouraging and learning from community-based experiences has been
32 also an opportunity to improve adaptation strategies (Archer et al., 2014). The Regional Climate Change
33 Adaptation Plan of Santiago is an example of this (Krellenberg and Katrin, 2014).
34
35 12.5.5.2 Governance and Financing
36
37 Lack of a high multilevel and intersectoral governance capacity with strong multi-players horizontal and
38 vertical coordination and long-term support are limiting adaptation in the region (high confidence)
39 (Anguelovski et al., 2014; Bai et al., 2016; Chu et al., 2016; Schaller et al., 2016; Miranda Sara et al., 2017).
40 The ability to enrol stakeholders and include community based initiatives can be determinant for adaptation
41 success particularly considering its impact in the decision-making arena (high confidence) (Section 12.5.8.1;
42 Section 6.4; Anguelovski et al., 2014; Archer et al., 2014; Chu et al., 2017; Rosenzweig et al., 2018) .
43
44 Lima's Climate Action Strategy is an example (Metropolitan Municipality of Lima, 2014). It was approved
45 after a participatory and consultative process with the technical group on climate change from the
46 Metropolitan Environmental Commission, focusing on the reduction of water vulnerabilities to drought and
47 heavy rain, on the basis of which 10 (out of 51 with Callao) Lima districts municipalities are developing and
48 starting to implement their adaptation measures (Foro Ciudades Para la Vida, 2021). In 2021 Lima
49 Municipality also approved its Local Climate Change Plan (Metropolitan Municipality of Lima, 2021) under
50 a similar process. The engagement of local players was central to spreading and mobilizing different types of
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1 knowledge and creating networks able to support adaptation (Section 12.6.3; Miranda Sara and Baud, 2014;
2 Miranda Sara et al., 2017) . The inclusive process is also a goal on the example of Chile Municipalities
3 Network Facing Climate Change (RedMuniCC) engaged in developing participatory strategic plans for
4 climate adaptation and mitigation (RedMuniCC, 2021).
5
6 New forms of financing and leadership focused on community-based approaches have been developed to
7 overcome the funding challenge and enable adaptation in the region (medium confidence: medium evidence,
8 medium agreement) (Castán Broto and Bulkeley, 2013; Archer et al., 2014; Paterson and Charles, 2019).
9 Also systems for measuring, reporting and verifying adaptation financing, as in Colombia (Guzmán et al.,
10 2018), as much as national legislation geared to adaptation can help access funds. Peruvian Law on the
11 Retribution Mechanism of Eco-Systemic Services and Code (Miranda Sara and Baud, 2014; MINAM Peru,
12 2016) in addition to the Ley Marco de la Gestión y Prestación de los Servicios de Saneamiento and its Code
13 (Ministerio de Vivienda, 2017), allowed the potable water companies to add 1% to the tariff to guarantee
14 ecosystem services, water treatment and reuse with green infrastructure. Another 4% of tariffs go to develop
15 and implement adaptation plans and measures (Government of Peru, 2016).
16
17 12.5.5.3 Adaptation options in urban design and planning
18
19 Both the shape and activities of the city have an impact on carbon emissions, adaptation and mitigation
20 opportunities (high confidence) (Raven et al., 2018; Satterthwaite et al., 2018). Combining urgent measures,
21 strategic action (Chu et al., 2017) to long-term planning is central for a transformative adaptation and to
22 avoid maladaptation (Filho et al., 2019). Urban planning, considering climate risk assessments, and
23 regulation (e.g., land-use and building codes), including climate-adapted parameters, are central to
24 coordinate and foster private and public investments in adaptation, reducing risks related to the built
25 environment conditions (infrastructure and buildings) and the occupation of risk areas (e.g., threatened by
26 floods and landslides) (Rosenzweig et al., 2018). Lack of information at local scale, human resources and
27 clear liability for climate change response planning can limit adaptation (Aylett, 2015).
28
29 Strategic adaptation approaches have been adopted by many cities in dealing with the multilevel and
30 intersectoral complexity of urban systems, with gains in fostering leadership and facing the predominant
31 pattern of uneven urban development in the region (medium confidence: limited evidence, high agreement)
32 (Chu et al., 2017). Medellin's metropolitan green belt, for example, focuses on problems such as irregular
33 settlements, inequality and poor governance, articulating programs and projects of the Municipality of
34 Medellin and the municipalities of the Vale do Aburra in a strategic long-term planning. Places with
35 informal and precarious settlements were aimed to be transformed with the belt's integration areas: eco parks
36 and eco-gardens (Alcaldía de Medellín, 2012; Chu et al., 2017).
37
38 12.5.5.3.1 Housing, informality and risk areas
39 Informality and precariousness in housing is one of the most sensitive issues for adaptation in CSA cities
40 (medium confidence: medium evidence, high agreement) (Satterthwaite et al., 2018; UN-Habitat, 2018).
41 Housing deficit in 2009, as a regional baseline, estimated that 37% of households suffered from quantitative
42 or qualitative deficiencies, due to the high cost of housing and the incidence of poverty (Blanco Blanco et al.,
43 2014; McTarnaghan et al., 2016; NU CEPAL et al., 2016; Vargas et al., 2018a; Rojas, 2019).
44
45 Policies and programs have been implemented accumulating good practices and reducing the percentage of
46 population in informal and precarious settlements (33.7% in 1990 to 21% in 2014) (NU CEPAL et al., 2016;
47 Satterthwaite et al., 2018; Teferi and Newman, 2018; UN-Habitat, 2018). Slum Upgrading and built-
48 environment interventions (housing and infrastructure improvement and provision) in informal settlements
49 can enhance adaptation (high confidence) (Teferi and Newman, 2018; Núñez Collado and Wang, 2020;
50 Satterthwaite et al., 2020) while reducing floods, landslides and cascading impacts of storms, floods and
51 epidemics, as observed on the "incremental housing approach" in Quinta Monroy (Rojas, 2019) and the
52 "social urbanism" in Medellin (Garcia Ferrari et al., 2018).
53
54 The climate adaptation plans of several large CSA cities include efficient land use and occupation planning
55 and urban control systems (comprising regulation, monitoring), fostering interlocution with housing and
56 environmental policy (by means of intersectoral and multilevel governance), inhibiting and reducing the
57 occupation of risk areas (mainly flooding and landslides risks); increasing population density in areas already
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1 served by infrastructure; expanding slums urbanization and technical assistance programs for improvements
2 and expansion of social housing (high confidence) (Municipio del Distrito Metropolitano de Quito, 2020;
3 Prefeitura Municipal do Salvador, 2020; Municipalidad de Lima, 2021; Prefeitura da Cidade do Rio de
4 Janeiro, 2021; Prefeitura do Município de São Paulo, 2021).
5
6 Housing programs and initiatives that consider resilient construction, and site selection strategies, are still in
7 nascent stages (Martin et al., 2013). Initiatives in slum upgrading, social housing improvement and
8 regularizing land tenure, associated with infrastructure provision, do not usually focus on adaptation,
9 although they often focus on risk reduction. Those initiatives, associated with a housing policy that
10 guarantees access to land and decent housing, a comprehensive intervention in vulnerable neighbourhoods
11 for their adaptation to climate change, and CbA (community-based adaptation) strategies, including housing
12 self-management and the participation of cooperatives, shows the need and opportunity to move to an
13 transformative urban agenda that encompasses sustainable development, poverty reduction, disaster-risk
14 reduction, climate-change adaptation, and climate-change mitigation (high confidence) (Muntó, 2018; UN-
15 Habitat, 2018; Valadares and Cunha, 2018; Bárcena et al., 2020b; Núñez Collado and Wang, 2020;
16 Satterthwaite et al., 2020).
17
18 Several large cities are implementing municipal risk management plans and management and restoration
19 plans for hydrologically relevant areas, considering threats of drought and heat waves, integrated watershed
20 management and flood control programs (high confidence) (Municipio del Distrito Metropolitano de Quito,
21 2020; Prefeitura Municipal do Salvador, 2020; Municipalidad de Lima, 2021; Prefeitura da Cidade do Rio de
22 Janeiro, 2021; Prefeitura do Município de São Paulo, 2021). Quito and Rio de Janeiro are considered two
23 examples of comprehensive and effective city-level climate action that includes creating environment
24 protected areas, managing appropriate land use, household relocation and EWS in vulnerable to high-
25 precipitation areas associate to EbA, such as reforestation projects, to face natural hazards (ELLA, 2013;
26 Anguelovski et al., 2014; Calvello et al., 2015; Alcaldía de Quito, 2017; Sandholz et al., 2018; Prefeitura da
27 Cidade do Rio de Janeiro, 2021) (Section 12.6.1). EWS and the use of mapping tools experienced in La Paz
28 showed to be an effective adaptation measure facing increasing hydro-climatic extreme events (Aparicio-
29 Effen et al., 2018).
30
31 12.5.5.3.2 Green and grey infrastructure
32 Hybrid solutions, combining green and grey infrastructure (GGI), have been adopted for better efficiency in
33 flooding control (Ahmed et al., 2019; Drosou et al., 2019; Romero-Duque et al., 2020), sanitation, water
34 scarcity, landslide prevention and coastal protection (high confidence) (Section 12.5.6.4; Mangone, 2016;
35 Depietri and McPhearson, 2017; Leal Filho et al., 2018; McPhearson et al., 2018). The adoption of nature-
36 based solutions (NbS), which embraces well-known approaches such as green infrastructure (GI) and
37 ecosystem-based adaptation (EbA) (Pauleit et al., 2017; Le, 2020) has increased (Box 1.3). The Fund for the
38 Protection of Water (FONAG) and the Participative Urban Agriculture (AGRUPAR) are initiatives using
39 NbS in Quito (Section 12.6.1). Example of GGI is a stormwater detention pond, as a water storage solution
40 to flooding prevention, also allowing multiple uses of an urban space, adapting and revitalizing a degraded
41 area in Mesquita, Rio's metropolitan region (Jacob et al., 2019). These systemic and holistic solutions still
42 need to overcome governance and sectorial barriers to be more widely adopted (Herzog and Rozado, 2019;
43 Wamsler et al., 2020; Valente de Macedo et al., 2021).
44
45 Managing water in cities in an adaptive way has been central to reducing impacts such as floods and
46 contributes to water security (high confidence) (Van Leeuwen et al., 2016; Okumura et al., 2021). Many
47 cities facing frequent heavy storms that impact mostly underprivileged communities, slums and vulnerable
48 areas could benefit from the integrated NbS for disaster risk reduction and adaptation (high confidence)
49 (Sandholz et al., 2018; Ronchi and Arcidiacono, 2019). A study covering 70 Latin American cities estimates
50 that 96 million people would benefit from improving main watersheds with green infrastructure (Tellman et
51 al., 2018). In several municipal climate plans, NbS were introduced mainly to enhance rainwater
52 management, reduce energy consumption and urban heat areas, water quality, prevent landslides and offer
53 green areas (high confidence) (Gobierno de la Ciudad de Buenos Aires, 2020; Municipio del Distrito
54 Metropolitano de Quito, 2020; Prefeitura Municipal de Curitiba, 2020; Alcaldía de Medellín, 2021;
55 Municipalidad de Lima, 2021; Prefeitura da Cidade do Rio de Janeiro, 2021; Prefeitura do Município de São
56 Paulo, 2021). Sao Paulo's project for Jaguaré river proposes a large-scale landscape transformation applying
57 innovative multifunctional NbS instead of exclusively large, expensive and monofunctional hard engineered
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1 solutions to manage stormwater (Marques et al., 2018; Herzog and Rozado, 2019). In Bogotá, the Humedales
2 foundation has restored wetlands to enhance areas near the reserve Van Der Hammen to improve water
3 quality and quantity, restore habitat for biodiversity, and provide flood protection (Portugal Del Pino et al.,
4 2020). In Petrópolis, a medium-sized city in the hills of Rio de Janeiro state, the water service company has
5 implemented 10 NbS multifunctional micro wastewater treatment plants in low-income areas, helping to
6 reduce cascading impacts of storms, floods and epidemics (Herzog and Rozado, 2019). In Costanera Sur,
7 Buenos Aires, a public initiative to protect an auto-regenerated Plata riverbank, which had received
8 demolition material to create land, nowadays offers numerous ecosystem services for residents and attract
9 visitors activating the tourist industry and helping reducing riverine floods (Bertonatti, 2021; OICS, 2021).
10
11 Hybrid solution on water management that can merge traditional interventions on urban areas with
12 sustainable urban drainage systems (SUDS) (Davis and Naumann, 2017), considering small scale low-impact
13 development (LID) measures scattered over the watershed instead of concentrate huge hydraulic grey
14 structures, can help reduce the risk and damage of flooding (high confidence) (Miguez et al., 2014; Miguez
15 et al., 2015a; Depietri and McPhearson, 2017; Da Silva et al., 2018a; de Macedo et al., 2018). Quito's
16 climate plan explicitly cites the strategy for implementing blue and grey infrastructure to reduce risk due to
17 extreme precipitation and its associated impacts such as flooding and landslides and the possible impact of
18 water scarcity (Municipio del Distrito Metropolitano de Quito, 2020). The Integrated Iguaçu-Sarapuí River
19 Basin Flood Control Master Plan, in Rio's metropolitan area, combined different solutions for flood
20 protection, focusing on river restoration by retrofitting levee systems combined with adapting land use to
21 provide a multifunctional landscapes as an alternative to bring together green and grey solutions, composing
22 urban parks to prevent further paving and avoid irregular occupation of river banks and provide storage
23 capacity for damping flood peaks (Miguez et al., 2015b).
24
25 Many cities are implementing adaptation measures on integrated water and flood management systems
26 (Sarkodie and Strezov, 2019), improving basic sanitation services (medium confidence: medium evidence,
27 high agreement). Main strategies are established by NAPs recurrently focusing on improving water
28 distribution network and reservoir systems, as Honduras (Government of Honduras, 2018) and Ecuador
29 (Mills-Novoa et al., 2020), sewage and effluent treatment, as Guatemala, Brazil and Paraguay (Government
30 of Brazil, 2007; Government of Guatemala, 2016; Government of Paraguay, 2017), facing water scarcity and
31 environmental degradation. Local authorities follow this guideline as in the effort to maintain and upgrade
32 existing drainage systems in Georgetown (Mycoo, 2014), or in Medellin, focusing on improving drainage
33 systems to prevent landslides or flooding (Núñez Collado and Wang, 2020; Alcaldía de Medellín, 2021). Rio
34 de Janeiro has constructed three large stormwater detention reservoirs to deal with frequent flood, (Prefeitura
35 da Cidade do Rio de Janeiro, 2015), adopting a set of exclusively grey solutions, not combined to NbS that
36 could improve urban flood resilience (Rezende et al., 2019). The main proposed actions still consider the
37 traditional approach in improving the hydraulic capacity of urban drainage systems as an adaptive measure
38 (high confidence) (Gobierno de la Ciudad de Buenos Aires, 2020; Prefeitura Municipal do Salvador, 2020;
39 Municipalidad de Lima, 2021; Prefeitura da Cidade do Rio de Janeiro, 2021). In addition to this strategy,
40 several local plans propose actions for the retention and storage of rainwater, both in the urban drainage
41 network with a smaller intervention scale (Prefeitura Municipal de Curitiba, 2020), as well as along rivers
42 and canals with large-scale works (medium confidence: medium evidence, high agreement) (Gobierno de la
43 Ciudad de Buenos Aires, 2020; Prefeitura Municipal de Curitiba, 2020; Alcaldía de Medellín, 2021;
44 Prefeitura da Cidade do Rio de Janeiro, 2021).
45
46 12.5.5.3.3 Mobility and transport system
47 Mobility and transport systems have a key role in urban resilience (high confidence) (Walker et al., 2014a;
48 Caprì et al., 2016; Espinet et al., 2016; Lee and Lee, 2016; Ford et al., 2018; Mehrotra et al., 2018; Quinn et
49 al., 2018). Examples reported in scientific literature assessed are focusing on mitigation strategies even when
50 labelled as adaptation (da Silva and Buendía, 2016; Di Giulio et al., 2018; Valderrama et al., 2019; Goes et
51 al., 2020).
52
53 The integration of transport and land use planning and the improvement of public transport, also as important
54 mitigation actions, appears as a consensus in countries' adaptation plans, nevertheless the emphasis on
55 mobility and transport systems on the many NAP published is low (medium confidence: medium evidence,
56 high agreement). Honduras, Costa Rica and El Salvador's NAP are not approaching adaptation or mitigation
57 in the sector, while Peru, Ecuador, Guatemala and Paraguay ones focus on mitigation only. Chile, Colombia
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1 and Brazil's NAP focus on both mitigation and adaptation of mobility and transport systems. Chile and
2 Colombia's plans dedicated specific action lines to adapt mobility and transport systems to climate change,
3 whilst Brazil published a NAP's complementary volume dedicated exclusively to the sectoral strategies,
4 although presents only general guidelines (Government of Peru, 2010; Government of Chile, 2014;
5 Government of Ecuador, 2015; Government of Brazil, 2016; Government of Colombia, 2016; Government
6 of Guatemala, 2016; Government of Paraguay, 2017; Government of Costa Rica, 2018; Government of
7 Honduras, 2018; Government of El Salvador, 2019).
8
9 In municipal scale, assessing the biggest cities, São Paulo, Rio de Janeiro Lima and Santiago stands out for
10 including mobility and transport as one of the strategic axes of its climatic plans, but yet prioritizing
11 mitigation, while Buenos Aires and Bogotá do not deepen the issue in their plans (Gobierno de la Ciudad de
12 Buenos Aires, 2015; Prefeitura da Cidade do Rio de Janeiro, 2016; Alcaldía Mayor de Bogotá D.C., 2018;
13 Municipalidad de Lima, 2021; Municipalidad de Santiago, 2021; Prefeitura do Município de São Paulo,
14 2021). Most of those same cities have sectoral mobility plans, which are key tools to urban resilience. Those
15 plans, however, do not focus on adaptation actions, although emphasizing mitigation (Government of Peru,
16 2005; Gobierno de la Ciudad de Buenos Aires, 2011; Prefeitura do Município de São Paulo, 2015; Alcaldía
17 Mayor de Bogotá D.C., 2017; Ilustre Municipalidad de Santiago, 2019; Município de Rio de Janeiro, 2019).
18
19 12.5.6 Health and Wellbeing
20
21 The most common adaptation strategies include the development of climate services such as epidemic
22 forecast tools, integrated climate-health surveillance and observatories and forecasting climate-related
23 disasters (floods, heat waves). GIS technologies are being used to identify locations where vulnerable
24 populations are exposed to climate hazards and associated health risks.
25
26 12.5.6.1 Climate services for health
27
28 The measures most directly linked to diminishing risk are those related to climate services for health (high
29 confidence). Climate services provide tailored, sector-specific information from climate forecasts to support
30 decision making (WHO and WMO, 2016); they allow decision makers and practitioners to plan
31 interventions in anticipation of a weather/climate event (Mahon et al., 2019). More recently, climate
32 services, such as early warning systems (EWS) and forecast models, have been promoted for the health
33 sector (WHO and WMO, 2012; WMO, 2014; WHO and WMO, 2016; Thomson and Mason, 2018) and are
34 an important adaptation measure to reduce the impacts of climate on health (high confidence). To guide this
35 process, the Global Framework for Climate Services (GFCS) issued a Health Exemplar (Lowe et al., 2014;
36 WMO, 2014) which aims for stakeholder engagement between health and climate actors at all levels to
37 promote the effective use of climate information within health research, policy and practice.
38
39 There exist at least 24 EWS in SA to avoid deaths and injuries from floods in the countries such as
40 Argentina, Colombia, Ecuador, Bolivia, Brazil, Peru, Uruguay and Venezuela (Bravo et al., 2010; Bidegain,
41 2014; Moreno et al., 2014; Dávila, 2016; del Granado et al., 2016; López-García et al., 2017; Carrizo Sineiro
42 et al., 2018). A total of 149 emergency prevention and response systems are reported in CA (UNESCO,
43 2012). In addition, some countries implement programs for the relocation of families who are in risk
44 condition, like in Bogotá and Medellin, Colombia (World Bank, 2014; Watanabe, 2015).
45
46 Epidemic forecast tools are an example of an adaptation measure being developed and/or implemented in
47 this region (high confidence). Climate-driven forecast models have been developed for dengue in Ecuador,
48 Puerto Rico, Peru, Brazil, Mexico, Dominican Republic, and Colombia (Lowe et al., 2013; Eastin et al.,
49 2014; Johansson et al., 2016; Lowe et al., 2017; Johansson et al., 2019); for Zika virus infections across the
50 Americas (Muñoz et al., 2017); for cutaneous leishmaniasis in Costa Rica and Brazil (Chaves and Pascual,
51 2006; Lewnard et al., 2014); for Aedes-borne diseases across the Americas (Muñoz et al., 2020b); and a
52 nowcast model for chikungunya virus infections across the Americas (Johansson et al., 2014). In Ecuador, a
53 prototype system utilized forecasts of seasonal climate and ENSO forecasts of to predict dengue
54 transmission, providing the health sector with warnings of increased transmission several months ahead of
55 time (Stewart-Ibarra and Lowe, 2013; Lowe et al., 2017). Despite these advances, few tools have become
56 operational and mainstreamed in decision making processes. However, Brazil and Panama have been able to
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1 operationalize an early warning system for the surveillance of dengue fever transmission (Codeço et al.,
2 2016; McDonald et al., 2016).
3
4 One of the most promising climate services for the health sector are heat and cold early warning and alert
5 systems (medium confidence). These have been developed by the national meteorological institutes in Peru,
6 Argentina, and Uruguay (Bidegain, 2014). A heat alert system was implemented in Argentina in 2017 and
7 daily alerts are issued for 57 localities across the country. A stoplight colour scheme is used to issue alerts,
8 identifying specific groups at risk and actions to be taken to reduce the risk (Herrera et al., 2018b).
9
10 The public dissemination of climate-health warnings via bulletins, websites, and other outlets can be an
11 adaptation measure to climate change and weather variability to diminish health risk (high confidence). The
12 information produced is systematized to be communicated to the authorities and general public. The
13 Caribbean Health-Climatic Bulletin has been issued quarterly since 2018 to health ministries across the
14 region, including CA and NSA. Regional climate and health authorities meet to review 3 month climate
15 forecasts and issue statements about the probable impacts on health (Trotman et al., 2018). In Panamá,
16 information on dengue is distributed in a monthly bulletin that is used by health authorities to inform vector
17 control activities (McDonald et al., 2016). Another example was the climate-driven forecast of dengue risk
18 that was produced prior to Brazil's 2014 FIFA World Cup to inform disease prevention interventions (Lowe
19 et al., 2014; Lowe et al., 2016). In Colombia, the Intersectoral National Technical Commission for
20 Environmental Health publishes a monthly bulletin with regional weather forecast and potential effects on
21 health (CONASA, 2019). Paraguay improves epidemiological surveillance and trains first level health staff
22 via information campaigns on the prevention of climate sensitive diseases, and promotes health networks
23 with the participation of civil society (Environmental Secretariat of Paraguay, 2011).
24
25 12.5.6.2 Integrated climate-health surveillance and observatories
26
27 Integrated health-climate surveillance systems are another key adaptation strategy (medium confidence). This
28 information can be used by the health sector to inform decision making about when and where to deploy a
29 public health intervention. It can also feed into an EWS, particularly if the data are compatible in format and
30 spatiotemporal scales. An integrated health-climate surveillance system for vector borne disease control was
31 developed in southern coastal Ecuador through a partnership among the climate and health sectors and
32 academia (Borbor-Cordova et al., 2016; Lowe et al., 2017). Additionally, an interdisciplinary multinational
33 team working at the border of Ecuador and Peru created a cooperation network for climate-informed dengue
34 surveillance (Quichi et al., 2016) and successful binational collaboration resulted in the local elimination of
35 malaria (Krisher et al., 2016). Similar is the innovative community-based data collection to understand and
36 find solutions to rainfall-related diarrheal diseases in Ecuador (Palacios et al., 2016).
37
38 Climate and health observatories are a promising strategy being developed at subnational, national (e.g.,
39 Brazil, Argentina) and regional levels (high confidence) (Muñoz et al., 2016; Rusticucci et al., 2020). The
40 Brazilian Observatory of Climate and Health brings together climate and health information for the Amazon
41 region of Manaus (Barcellos et al., 2016). At a national level, Brazil has created the climate and health
42 observatory, where information and data visualizations are available for various climate-sensitive health
43 indicators (Ministério da Saúde and FIOCRUZ, 2021).
44
45 12.5.6.3 Vulnerability and risk maps
46
47 Vulnerability and risk maps have been widely used as an adaptation strategy to understand the potential
48 impacts of climate on health outcomes both directly (e.g., maps of disease risk) and indirectly (e.g., maps of
49 populations vulnerable to climate disasters) (high confidence). There are many examples where climate
50 services have been used to construct vulnerability maps for health outcomes, including maps in the
51 aforementioned Climate-Health Observatories. Dengue, malaria, and Zika vulnerability maps using climate,
52 social, and environmental information has been developed in Brazil and Colombia (Cunha et al., 2016b;
53 López-Álvarez, 2016; Pereda, 2016; IDEAM, 2017). Argentina is focused on improving the health system by
54 using Climate Change Risk Map System as a tool that identifies the risks and allows assessing their
55 management (OPS and WHO, 2018).
56
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1 Vulnerability and risk maps for climate disasters have been developed at the city level, for example in
2 Bogotá, Cartagena de Indias, and Mocoa in Colombia (Yamin et al., 2013; Guzman Torres and Barrera
3 Arciniegas, 2014; Tehelen and Pacha, 2017; Zamora, 2018); and for the metropolitan district of Quito in
4 Ecuador (Tehelen and Pacha, 2017). In addition, vulnerability maps were created for the primary road
5 network of Colombia (Tehelen and Pacha, 2017). At the regional level, vulnerability maps using climate
6 change probability, disaster risk and food insecurity variables has been produced for the Andean region
7 (WFP, 2014). In Brazil, vulnerability maps considering exposure, sensitivity, and adaptive capacity, coupled
8 to climate scenarios, were designed to support the National Adaptation Plan on a municipal scale (Chang and
9 Garcia, 2018; Duval et al., 2018; Marinho and Silva, 2018; Menezes, 2018; Santos and Marinho, 2018; Silva
10 et al., 2018). A Climate Change Vulnerability Index was used to generate vulnerability maps for countries of
11 Latin American and Caribbean region (Vörösmarty et al., 2013; CAF, 2014).
12
13 12.5.6.4 Other adaptation actions
14
15 Diverse adaptation measures are being implemented through public policies, private households' responses,
16 or communal management that directly or indirectly reduce the impacts of climate change on human health
17 (high confidence) (Table 12.9). Private and communal management measures could be considered indirect
18 measures, because they might be adopted even in the absence of climate change.
19
20
21 Table 12.9: Hazards from climate change that impact human health and examples of adaptation strategies proposed or
22 implemented in CSA. Based in McMichael et al. (2006); Miller et al. (2013a); Miller et al. (2013b); Miller et al.
23 (2013c); Miller et al. (2013d); Hardoy et al. (2014); IPCC (2014); Janches et al. (2014); Lee et al. (2014); Mejia (2014);
24 Sosa-Rodriguez (2014); Vergara et al. (2014); Lemos et al. (2016); Villamizar et al. (2017); Magoni and Munoz (2018);
25 Zhao et al. (2019).
Hazard and Examples of adaptation strategies
impacts on human
health
Public Private Communal
Extreme heat and cold: · Creation of urban green · Cooling by swamp · Training of
deaths / illness by spaces/ coolers, air community health
thermal stress conditioning, open volunteers to
· Health promotion windows, wet the recognize and treat
campaigns. floors, shade trees. heat strain.
· Establish shelters during · Bioclimatic building
heat waves design
· Technology transfer for
home heating
Extreme rainfall, · Early warning systems · Green-grey · Communal efforts to
wildfire, wind speed: (EWS) for extreme climate infrastructure to clear debris from
injury / deaths from events. prevent landslides. canals to reduce
floods, storms, flood risk
cyclones, bushfires and · Safe housing programs and · Insurance mechanisms
landslides (Key risk 2, relocation and financing for long- · Cooperative efforts
Table 12.6). term recovery. to rebuild following a
· Green-grey infrastructure flood event
(e.g., channels, drainage
systems)
Drought and dryness: · Formalizing land · Water infrastructure · Incorporation of local
poor nutrition due to ownership for small and irrigation. stakeholders in
reduced food yields farmers and Indigenous formulating
and dehydration due to people. · Soil moisture retention adaptation responses.
limited or inadequate techniques
management of · Address emerging water · Recognition of
freshwater (Key risk 1, conflicts. · Insurance mechanisms. Indigenous and local
Table 12.6). · Selection of drought wisdom and
knowledge.
resistant crops.
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Changes in climate · Restoration of watersheds · Water disinfection: · Participatory water
that promote microbial · Integrated health-climate boiling, chlorination. management
proliferation: food strategies, including
poisoning, and unsafe surveillance · Purchasing water or protection of
drinking water (Key · Improve access to drinking water filters. drinking water
risk 3, Table 12.6). sources.
water, drainage, sanitation
and waste removal.
Changes in climate · Vector control · Use of bed nets and · Community
that affect vector- · EWS for epidemics screens volunteers to collect
pathogen host relations · Nature-based solutions blood smears for
and infectious disease · Use of repellent and malaria diagnosis
geography/seasonality (NbS) (e.g., forest insecticides.
(Key risk 4, Table conservation) · Community-led
12.6). · Elimination of standing elimination of vector
water. habitat.
Sea level rise and · Improve governance of · Improve water · Incorporation of local
storm surges: impaired water utilities. efficiency in stakeholders in
crop, livestock and agriculture. formulating
fisheries yields; unsafe · Address emerging water adaptation responses.
drinking water, leading conflicts.
to impaired nutrition · Recognition of
(Key risk 8, Table · Protection, restoration and Indigenous and local
12.6). soil conservation to wisdom and
recharge aquifers. knowledge.
Environmental · Long-term risk · Identification of · Community-led
degradation: loss of management planning for alternative livelihoods. efforts to reforest and
livelihoods and cities. restore/protect
displacement leading watersheds.
to poverty and adverse · Sustainable forestry
health outcomes programs.
(related to Key risk 6,
Table 12.6). · Protection and restoration
of lacustrine areas.
1
2
3 Participatory management can be relevant in the case of mosquito-borne disease prevention (e.g., dengue
4 fever or malaria), where the reduction in mosquito habitat in one area or `hot spot' can reduce the risk for all
5 surrounding households. This approach is also relevant when considering new places where vector-borne
6 diseases can emerge because of changes in climate (Andersson et al., 2015).
7
8 Adaptation strategies implemented by the public sector include a diverse suite of strategies ranging from
9 creation of green spaces in urban areas, relocation of families located in disaster prone areas, ecosystem
10 restoration, improved access to clean water, among many others (high confidence) (Table 12.9). Building
11 green-grey infrastructure (GGI) has been a popular public adaptation measure to reduce deaths and injuries
12 because of floods (Section 12.5.5.3.2). Infrastructure has been improved at schools, public buildings and
13 drainage systems in cities such as Bogota, Colombia (World Bank, 2014) and La Paz, Bolivia (Fernández
14 and Buss, 2016). In Brazil, channel works were implemented to reduce the flooding of the Tiete River,
15 which crosses the metropolitan area of Sao Paulo; these projects were designed based on simulated flood
16 scenarios (Hori et al., 2017).
17
18 Another example of a public adaptation measure is protection and restoration of natural areas, which have
19 the potential to decrease the transmission of water- and vector-borne infectious diseases (medium
20 confidence: robust evidence, low agreement). Studies have shown that these measures can diminish the cases
21 of malaria and diarrhoea in Brazil, and cases of diarrhoea in children in Colombia (Bauch et al., 2015;
22 Herrera et al., 2017; Chaves et al., 2018). However, deforestation and malaria have a complex relationship
23 that relies on local context interactions, where land use and land cover change present an important role due
24 to vector ecology alterations and social conditions of human settlements (Rubio-Palis et al., 2013). Forest
25 conservation can improve hydrological cycle control and soil erosion that can help to improve water quality
26 and reduce the burden of water-borne diseases. In addition, forest cover can help to diminish the habitat for
27 larval mosquitoes that transmit malaria. These measures can help to design policies in sites where these
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1 problems do not currently exist but can emerge as a consequence of climate change and the increase in the
2 frequency of weather extreme events.
3
4 12.5.6.5 Challenges and opportunities
5
6 Despite the proliferation of disaster EWS in the region, only 37 can be considered operational, because many
7 of these systems are not operating or functioning properly, or do not meet the requirements to be considered
8 EWS (UNESCO, 2012). Sustainable financing and political support are needed to ensure the functioning of
9 disaster EWS (high confidence) (Table 12.11). Several studies identified difficulties in implementing disaster
10 EWS due to a lack of community engagement and response to the alerts that are issued (del Granado et al.,
11 2016; López-García et al., 2017). To address these challenges, the document "Developing Early Warning
12 Systems: A Checklist" provides guidance for the implementation of a people centred approach to early
13 warning systems as proposed in the Hyogo Framework for Action 20052015 (Wiltshire, 2006).
14
15 With respect to the development of climate-driven epidemic forecasts, efforts are needed to improve the
16 utility of such forecasts for the health sector. Few such forecasts have been operationalized to inform health
17 sector decision making. A review of 73 studies that predicted and forecasted Zika virus infections (42% from
18 the Americas) identified a high degree of variation in access, reproducibility, timeliness, and incorporation of
19 uncertainty (Kobres et al., 2019). A recent systematic review of epidemic forecasting and prediction studies
20 found that no reporting guidelines exist; the development of guidance to improve transparency, quality and
21 implementation of forecast models in the public health sector was recommended (Pollett et al., 2020). An
22 earlier review of dengue early warning models found that few models incorporated both spatial and temporal
23 aspects of disease risk (Racloz et al., 2012), limiting their potential application as an adaptation strategy by
24 the health sector. Advances have been made in the last decade with respect to modelling and computing
25 tools, increasing access to digital climate information and health records, and the use of earth observations to
26 forecast climate sensitive diseases (Fletcher et al., 2021; Wimberly et al., 2021).
27
28 The growing field of implementation science defined as "a discipline focused on systematically examining
29 the gap between knowledge and action" is another opportunity to address the challenges and barriers to
30 using climate information for health sector decision making (Boyer et al., 2020). Implementation science in
31 the health sector in CSA is nascent; research in this area could help to address barriers to mainstreaming
32 climate information in the health sector as an adaptation strategy (Table 12.11; Table SM12.7).
33
34 12.5.6.6 Governance and Financing.
35
36 A description of the governance and financing dimensions of the feasibility of implementing EWS is
37 presented in Table 12.11 and Table SM12.7.
38
39 12.5.6.6.1 National Health Plans
40 Some countries have developed national plans on health including the role of climate. Chile has a Climate
41 Change Adaptation Plan of the Health Sector that proposes several actions to enhance monitoring,
42 institutions and citizens information and education (Ministry of Health of Chile and Ministry of Environment
43 of Chile, 2016). Based on the identification of vulnerability to climate change, Colombia has developed
44 eleven regional adaptation plans to strengthen institutional capacities; climate change education for
45 behavioural changes; and cost estimation to promote health resilience (WHO and UNFCCC, 2015). In
46 addition, El Salvador implemented actions to strengthen health infrastructure through high latrines for
47 housing in flood communities, as well as other measures focused on water supply and quality based on an
48 education and awareness program (Ministry of Environment and Natural Resources of El Salvador, 2013).
49 Only Brazil and Peru have implemented actions so far in the region derived from national health adaptation
50 plans, and only Brazil completed a national assessment of impacts, vulnerability and adaptation for health
51 (Watts et al., 2018). Some countries include health as a priority sector in their National Adaptation Plans, as
52 is the case of Ecuador, and Costa Rica, which has a national plan addressing the prevention and care of
53 climate-sensitive diseases coupled to a National Health Plan (2016-2020) (Ministry of Health Costa Rica,
54 2016; Jiménez, n.d.).
55
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1 12.5.6.6.2 National Disaster Management Plans
2 National Risk Management Plans or National Disaster Response Plans are tools for adapting to climate
3 change that can help to diminish death and injuries because of disasters (high confidence). These Plans are
4 generally promoted by governments as national instruments that guide the processes of estimating,
5 preventing and reducing disaster risk. An updated national risk management plans has been found for
6 Guatemala (CONRED, 2014), Honduras (COPECO, 2014), El Salvador (Ministry of Health of El Salvador,
7 2017), Costa Rica (CNE, 2016), Ecuador (SGR, 2018), Peru (SGRD et al., 2014), Argentina (Ministerio de
8 Seguridad de Argentina, 2018), Bolivia (VIDECI, 2017), Chile (ONEMI, 2015) and Colombia (UNGRD,
9 2015). It has been shown in Brazil that information on drought conditions can be used to reduced health
10 impacts of drought using a national disaster risk reduction framework (Sena et al., 2016).
11
12 12.5.7 Poverty, Livelihood and Sustainable Development
13
14 Climate change impacts are increasing and exacerbating poverty and social inequalities, affecting those
15 already vulnerable and disfavoured, generating new and concatenated risk challenging climate resilient
16 development pathways (high confidence) (Section 8.2.1.4; Shi et al., 2016; Otto et al., 2017; Johnson et al.,
17 2021) (). Poverty, high levels of inequalities and pre-existing vulnerabilities also can be worsened by climate
18 change policies (Antwi-Agyei et al., 2018; IPCC, 2018; Roy et al., 2018; Eriksen et al., 2021). Those already
19 suffering are losing their livelihoods and reducing their development options; poor populations and countries
20 are more vulnerable and have lower adaptive capacity to climate change (very high confidence) (Section
21 8.5.2.1; Rao et al., 2017).
22
23 Inequality is growing, being a CSA structural characteristic; Gini index average for Latin American
24 countries (including Mexico) was decreasing to 0.466 in 2017, where 1% richest got 22 times more income
25 than 10% poorest (ECLAC, 2019b; Busso and Messina, 2020), but in 2018, 29.6% of Latin America were
26 poor population (increased to 182 million) and extreme poverty 10.2%; in 2018 (increased to 63 million)
27 (ECLAC, 2019b) and in 2020, due to COVID crisis, Gini coefficient projection of increases are ranging from
28 1.1% to 7.8% (ECLAC and PAHO, 2020), poverty increased to 33.7% (209 millions) and extreme poverty to
29 12.5% (78 millions) (ECLAC and PAHO, 2020; ECLAC, 2021). Those poverty and extreme poverty rates
30 are higher among children, young people, women, Indigenous Peoples (Reckien et al., 2017; Busso and
31 Messina, 2020), migrant (Dodman et al., 2019) and rural population. Climate change impacts in
32 differentiated ways, even within a household there may be important differences in relation to age, gender,
33 health and disability; these factors may intersect with one another (high confidence) (Reckien et al., 2017;
34 Busso and Messina, 2020).
35
36 In IPCC's TAR, AR4 and AR5, WG II recognized higher risks associated with poor living conditions,
37 substandard housing, inadequate services, location in hazardous sites due to no alternatives and the need to
38 work more strongly on strengthening governance structures involving residents, community organizations
39 amongst others (Wilbanks et al., 2007; Revi et al., 2014). The AR5 CSA chapter stated that poverty levels
40 remained high (45% for CA and 30% for SA in 2010) despite years of sustained economic growth. Poor and
41 vulnerable groups are disproportionately affected in negative ways by climate change (Section 8.2.1.4;
42 Section 8.2.2.3; SR15 Section 5.2 and Section 5.2.1, Roy et al., 2018) ) due to physical exposure derived
43 from the place where they live or work, illiteracy, low income and skills, political and institutional
44 marginalization tied to lack of recognition of informal settlements and employments, poor access to good
45 quality services and infrastructure, resources, information, and other factors (very high confidence) (UN-
46 Habitat, 2018; SR15 Sections 5.2.1, 5.6.2, 5.6.3, 5.6.4, Roy et al., 2018).
47
48 International agreements aim for climate resilient development pathways where efforts to eradicate poverty,
49 reduce inequalities and promote fair and cross-scalar adaptation and mitigation are strengthened. The
50 Sustainable Development Goals (SDG) first and second objectives aim to reduce poverty leaving no one
51 behind (UN General Assembly, 2015). Although researchers argue that poverty is mischaracterized having
52 multiple dimensions (Castán Broto and Bulkeley, 2013) (Section 8.1.1), that biodiversity loss, climate
53 change and pollution will undermine efforts on 80% of assessed SDG targets, that biodiversity and climate
54 change must be tackle together (Pörtner et al., 2021; United Nations Environment Programme, 2021) and
55 LAC countries due to COVID crisis have uneven SDG progress (high confidence) (ECLAC, 2020).
56
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1 12.5.7.1 Challenges and Opportunities
2
3 Climate change exacerbates pre-existing conditions and moving in the opposite direction in the search for
4 resilience, equity and sustainable development (Tanner et al., 2015b; Bartlett and Satterthwaite, 2016;
5 Kalikoski et al., 2018; Bárcena et al., 2020a). Existing inequalities in the provision and consumption of
6 services are bound to be exacerbated by future risks and uncertainties associated with climate change
7 scenarios (Miranda Sara et al., 2017). Climate change will be a major obstacle in reducing poverty (high
8 confidence) (Bartlett and Satterthwaite, 2016; Allen et al., 2017a; Hallegatte et al., 2018; UN-Habitat, 2018;
9 United Nations Environment Programme, 2021), even affecting wealthier populations that become
10 vulnerable facing climate change scenarios (WGI AR6 Chapter 12, Ranasinghe et al., 2021), dragging them
11 into poverty, erasing decades of work and asset accumulation.
12
13 CSA is highly urbanized, the poor vast majority live in urban areas (except in Central America) while urban
14 extreme poverty is becoming more relevant (Rosenzweig et al., 2018; Dodman et al., 2019; Almansi et al.,
15 2020; Sette Whitaker Ferreira et al., 2020), with those living in informal settlements and working within
16 informal economy are critical on each city's economy (Satterthwaite et al., 2018; Satterthwaite et al., 2020).
17 Many households in the region's cities live in precarious neighbourhoods with insufficient infrastructure and
18 substandard housing (Adler et al., 2018; Rojas, 2019). On average, between 21% and 25% of the urban
19 population lives in informal settlements (Jaitman, 2015; UN-Habitat, 2015; Rojas, 2019; Sandoval and
20 Sarmiento, 2019). This hides important disparities: Habitat III reports by individual countries the percentage
21 of urban population living in informal settlements ranged from 5% to 60%; in absolute terms 105 million
22 people living in precarious conditions (106 million estimated in 1990) (Section 12.5.5; Sandoval and
23 Sarmiento, 2019).
24
25 High levels of inequality and informality remain the biggest challenges for adaptation measures being
26 effective (Rosenzweig et al., 2018; Dodman et al., 2019). The interaction of projected impacts with existing
27 vulnerabilities in the region (as hunger, malnutrition and health inequalities, arising from its social, economic
28 and demographic profile), affect CSA development and well-being in different ways (Reyer et al., 2017)
29 increasing poverty and inequality risking the paths for sustainable development (Section 18.1.1; Reckien et
30 al., 2017).
31
32 The uneven enforcement of land-use regulations, relocations and evictions on behalf of environmental risk
33 management and climate adaptation is contested (Brockington and Wilkie, 2015; Lavell, 2016; Quimbayo
34 Ruiz and Vásquez Rodríguez, 2016a; Quimbayo Ruiz and Vásquez Rodríguez, 2016b; Anguelovski et al.,
35 2018; Anguelovski et al., 2019; Shokry et al., 2020; Chávez Eslava, 2021; Oliver-Smith, 2021). This points
36 to caution in framing climate adaptation and resilience related interventions as equally benefiting everyone
37 (high confidence) (Brown, 2014; Chu et al., 2016; Connolly, 2019; Romero-Lankao and Gnatz, 2019;
38 Johnson et al., 2021) and the need for incorporating equality and justice dimensions (very high confidence)
39 (Section 18.1.2.2; Agyeman et al., 2016; Meerow and Newell, 2016; Romero-Lankao et al., 2016; Shi et al.,
40 2016; Reckien et al., 2017; Leal Filho et al., 2021) ().
41
42 Poor rural households in marginal territories with low productive potential and/or far away from markets and
43 infrastructure are highly vulnerable to climate change and easily fall into poverty-environment traps (high
44 confidence) (Barbier and Hochard, 2019; Heikkinen, 2021). Climate change is one of the main threats to
45 rural livelihoods in Central America, being agriculture a pillar for rural economies and food security,
46 especially for the poorest sectors that rely on subsistence crops in areas with low soil fertility and rainfall
47 seasonality (Bouroncle et al., 2017).
48
49 Impacts are likely to occur simultaneously, exacerbating those of the poorer but also creating new groups at-
50 risk (Miranda Sara et al., 2016; Rosenzweig et al., 2018; Dodman et al., 2019). The material basis for poor
51 and vulnerable urban and rural populations' adaptation are in a critical state across the CSA region,
52 magnifying extreme events' impacts, making CSA less resilient. The consequences in terms of social
53 vulnerability and livelihood will be widely felt, insofar the security and protection of critical assets (housing,
54 infrastructure, services - water, land and ecosystem services) continues to lay behind. Small businesses are
55 usually conducted within the same home and if the house is affected so is the business (Stein and Moser,
56 2015) adding another layer of vulnerability for them.
57
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1 As productivity declines, they seek outside income generation opportunities and rely on resource extraction
2 for subsistence and as an income generation activity, further increasing their vulnerability to climate change
3 (Barbier and Hochard, 2018a). Cycles of declining productivity, environmental degradation, wildlife
4 poaching and trafficking, search of outside employment, reduced incomes, livelihood opportunities and
5 poverty have been registered in rural El Salvador, Honduras, Amazonia (López-Feldman, 2014; Graham,
6 2017; Barbier and Hochard, 2018a). The protection of communities that defend and are dependent on
7 wildlife and natural environments requires immediate attention. In Latin America there are 8 million forest-
8 dependent people which represents about 82% of the region's rural extreme poor (FAO and UNEP, 2020).
9
10 Poverty and disaster risk reduction interlinked with climate change adaptation share a focus on identifying
11 and acting on local risks and their root causes, even having different lenses through which to view risk (very
12 high confidence) (IPCC, 2014; Allen et al., 2017a; Satterthwaite et al., 2018; UN-Habitat, 2018;
13 Satterthwaite et al., 2020). Construction of climate knowledge and risk perceptions affect decision-making to
14 define implementation priorities; the poor are less able to cope and to adapt avoiding "adaptation injustices"
15 (high confidence) (Mansur et al., 2016; Miranda Sara et al., 2017; Reckien et al., 2017; Hardoy et al., 2019).
16
17 Adaptation, social policies, poverty reduction and inequality are weakly articulated to daily or chronic risk
18 reduction. Poor residents are often caught in `risk traps', accumulated cycles of everyday risks and small-
19 scale disasters (medium confidence: medium evidence, high agreement) (Bartlett and Satterthwaite, 2016 ;
20 Mansur et al., 2016; Allen et al., 2017a; Leal Filho et al., 2021), being exacerbated by climate risks and
21 COVID pandemic with the most vulnerable populations suffering. Chronic and every day risks (poor access
22 to infrastructure, services, incomes, housing, tenure, education, security, location and poor-quality
23 environment, networks and having a voice) are often exacerbated and generate new unknown risks by
24 climate change (medium confidence: medium evidence, high agreement) (Bartlett and Satterthwaite, 2016;
25 Mansur et al., 2016; Satterthwaite et al., 2018; Leal Filho et al., 2021), extreme events and risks related to
26 ENSO oscillation. All these risks need to be considered simultaneously (UN-Habitat, 2018). Risks are
27 seldom distributed equally highlighting socioeconomic inequalities and governance failures (high
28 confidence) (IPCC, 2014; Bartlett and Satterthwaite, 2016; Rasch, 2016; Romero-Lankao et al., 2018).
29
30 Adaptation, disaster risk reduction together with social and poverty reduction policies contribute to
31 sustainable development (Hallegatte et al., 2018; Satterthwaite et al., 2020), and improve prospects of
32 climate resilient pathways (Section 18.1.1). Without pro-poor interventions, adaptation options could
33 reinforce poverty cycles (Kalikoski et al., 2018). Secure locations, good quality infrastructure, services and
34 housing are critical to reduce risks from extreme climate events (Satterthwaite et al., 2018; Dodman et al.,
35 2019).
36
37 12.5.7.2 Governance and Finance
38
39 Poor and most vulnerable groups evidence limited political influence, fewer capacities and opportunities to
40 participate in decision and policy making, are less able to leverage government support to invest on
41 adaptation measures linked with poverty, inequality and vulnerability reduction (very high confidence)
42 (Chapter 8; Miranda Sara et al., 2017; Reyer et al., 2017; Kalikoski et al., 2018; Dodman et al., 2019;
43 Satterthwaite et al., 2020).
44
45 Existing unbalances on power relations, corruption, structural historic problems and high levels of risk
46 tolerance (Miranda Sara et al., 2016) constitute climate governance barriers for implementing more effective
47 adaptation and preventive measures. Corruption, particularly in the construction and infrastructure sector,
48 has proven to be a barrier for CSA development even reproducing and reconstructing risks (French and
49 Mechler, 2017; Vergara, 2018; Durand, 2019). Critical infrastructure and valuable assets continue to be
50 placed in vulnerable areas (Calil et al., 2017; Escalante Estrada and Miranda, 2020) evidencing the
51 persistence of maladaptation and adaptation deficit (Villamizar et al., 2017).
52
53 Social organization, participation and governance reconfiguration are essential for building climate resilience
54 (very high confidence) (Stein and Moser, 2015; Kalikoski et al., 2018; Satterthwaite et al., 2018; Stein et al.,
55 2018; Hardoy et al., 2019; Stein, 2019; Satterthwaite et al., 2020; Miranda Sara, 2021). Adaptation measures
56 have trade-offs that need to be acknowledged and acted upon, most importantly by developing the capacity
57 to convene discussions that draw in all key actors and commit them to do things differently (Almeida et al.,
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1 2018; Hardoy et al., 2019). Collaborative approaches integrating groups and organizations (e.g., saving,
2 women's groups, clubs, vendor associations, cooperatives) contributing to the exchange of information, to
3 visibilize people's needs, to generate safety networks, and to negotiate for improvements and enhance
4 adaptive capacity.
5
6 12.5.7.3 Adaptation options
7
8 Effective adaptation can be achieved by addressing pre-existing development deficits, particularly the needs
9 and priorities of informal settlements and economies (Revi et al., 2014; UN-Habitat, 2018). There is urgency
10 for social systems to better respond to climate related risks and increase their adaptive capacity (Lemos et al.,
11 2016) focus on path dependency, lock ins and poor specific needs (Leal Filho et al., 2021).
12
13 The linkages between climate adaptation and poverty are not clearly addressed at national level (Kalikoski et
14 al., 2018). A revision of some NDCs presented by CSA countries (https://unfccc.int), shows that NDCs are
15 developed with almost no connection to poverty and livelihoods. Exceptions include Bolivia whose NDC
16 developed the "Good life" concept, as an alternative development pathway, supporting sustainable
17 livelihoods as a mean to eradicate poverty; Honduras asserts that climate action should improve living
18 conditions; Peru defined a poverty and vulnerability reduction approach and El Salvador conditioned its
19 NDCs to macroeconomic stability, economic growth and poverty reduction. A sustainable development
20 approach permeates in proposed actions for sectors as energy, agriculture, transport, water, and forestry.
21
22 Adaptive capacity is linked to addressing climate related risks (specific capacity) and structural deficits
23 (generic capacity), synergies and a strategic balance between both is necessary (Eakin et al., 2014; Lemos et
24 al., 2016). Adaptation institutional context can undermine one form of capacity with repercussions on the
25 other compromising overall adaptation and sustainable development (Eakin et al., 2014).
26
27 Literature assessing the effectiveness of pro-poor or community based adaptation practices and livelihood
28 options continues to be weak, even though are increasingly documented, as in AR5 (Magrin et al., 2014).
29 Great variety of measures are being applied, financial instruments to strengthen and protect livelihoods and
30 assets; collective insurance schemes, micro-credits, financial instruments for transferring risks, as
31 agricultural insurance and Payments for Ecosystem Services (PES) (Dávila, 2016; Hardoy and Velásquez,
32 2016; Lemos et al., 2016; Porras et al., 2016; Kalikoski et al., 2018). Small-scale household running
33 businesses in poor neighbourhoods develop adaptation strategies to keep business going, showing how
34 household level adaptation strategies are multipurpose (Stein et al., 2018; Stein, 2019). There are emerging
35 interinstitutional communities of practice with the purpose of sharing practices and lessons learned (ECLAC,
36 2013; ECLAC, 2015; ECLAC, 2019a).
37
38 There is also increasing evidence of human mobility associated with climate change and disaster risk (IOM,
39 2021) and the adoption of sustainable tourism, diversification of livelihoods strategies, climate forecasts,
40 appropriate construction techniques, neighbourhood layout, integral urban upgrading initiatives, territorial
41 and urban planning, regulatory frameworks, water harvesting and nature-based solutions (NbS) (Stein and
42 Moser, 2014; Hardoy and Mastrangelo, 2016; Almeida et al., 2018; Barbier and Hochard, 2018a; Desmaison
43 et al., 2018; Satterthwaite et al., 2018; Villafuerte et al., 2018; Hidalgo, 2020; Satterthwaite et al., 2020).
44 Mostly, socio-economical and socio-political factors which show safety and continuity measures are critical
45 enablers of adaptation.
46
47 At municipal level study in Central America highlighted that adaptive capacity in rural areas is associated
48 with basic needs satisfaction (safe drinking water, school, quality dwelling, gender parity index), access to
49 resources for innovation and action (road density, economically active population with non-agricultural
50 employment, and rural demographic dependency ratio), and access to credit and technical support
51 (Bouroncle et al., 2017).
52
53 CSA adaptation initiatives to reduce poverty, improve livelihoods and achieve sustainable development
54 range in scale and scope, from planned and collective interventions to autonomous and individual actions.
55 Many of them are bottom up, community-led initiatives together with civil society organizations; others are
56 government-led, including local governments, or a combination of them (McNamara and Buggy, 2017;
57 Berrang-Ford et al., 2021). Vulnerable groups are a focus to achieve equity at planning and as a target
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1 including mainly rural low-income, Indigenous Peoples and women and migrants in most references.
2 Responses detected were focused on behavioural and cultural, followed by ecosystem-based responses,
3 institutional, and technological/infrastructural responses. Out of 55 articles analysed from CSA (Berrang-
4 Ford et al., 2021) about poverty, equity and adaptation options, half of them covered adaptation planning and
5 early implementation but only 2% could show evidence of risk reduction associated with adaptation efforts.
6
7 Tensions and conflicts may result from differing perceptions and knowledge on vulnerabilities and risk
8 which can hinder the acceptance of adaptation measures and implementing stronger adaptive or preventive
9 actions (Miranda Sara et al., 2016). There is a need to better understand complex interactions and community
10 responses to climate change in the Amazonian and Andean region. Climate change hotspot impacts, showed
11 that poverty reduction measures alone were not enough to improve adaptive capacity, as people will not
12 necessarily invest to enhance them (Pinho et al., 2014; Filho et al., 2016; Nelson et al., 2016; Lapola et al.,
13 2018; Zavaleta et al., 2018). Current adaptation strategies and methods may be neglecting cultural values,
14 even eroding them, in Peruvian Andes, pointing that success of adaptation practices is tied to deep cultural
15 values (Walshe and Argumedo, 2016).
16
17 Limits to adaptation include access to land, territory and resources (Mesclier et al., 2015), poor labour
18 opportunities coupled with knowledge gaps, weak multi actor coordination, and lack of effective policies and
19 supportive frameworks (Berrang-Ford et al., 2021).
20
21 Low participation of women in income earning opportunities contrasts with their role in unpaid activities
22 (ECLAC, 2019b). Despite progresses, gender differences in labour markets remain an unjustifiable form of
23 inequality (OIT, 2019) and women easily fall back to the informal labour market during crisis situations such
24 as those generated by climate events (Collodi et al., 2020).
25
26 Participatory processes are leveraging adaptation measures throughout CSA; they contribute to prioritization
27 of specific adaptation measures as well as strengthening local capacities. Showing that climate adaptation
28 needs to be part of larger transformation processes to reduce vulnerability drivers (Stein and Moser, 2015;
29 Stein et al., 2018; Stein, 2019) but stronger national policies interlinking poverty and inequality reduction to
30 adaptation, considering the coupled human-environmental systems to comprehend poor and vulnerable
31 groups' capacity to adapt are urgent. CSA does not fare very well, and several downward trends might
32 become even more acute. More effective decisive actions need to be undertaken coupled with inclusive long-
33 term planning to protect the poor and improve their underlying conditions, to meet the SDG.
34
35 12.5.8 Cross-cutting Issues in the Human Dimension
36
37 12.5.8.1 Public policies, social movements and participation
38
39 Public policies related to adaptation must be seen in the wider context of environmental policies and
40 governance, as they usually address climatic processes in synergy with other environmental and
41 socioeconomic drivers (very high confidence) (Ding et al., 2017; Aldunce Ide et al., 2020; Comisión
42 Europea, 2020; Lampis et al., 2020; Scoville-Simonds et al., 2020). Some people rather point to education,
43 sanitation or social assistance, among other sectors (Bonatti et al., 2019). In Brazil, for example, it would be
44 difficult to clearly separate climate change adaptation and urban policies (high confidence) (PBMC, 2016;
45 Barbi and da Costa Ferreira, 2017; Marques Di Giulio et al., 2017; Empresa de Pesquisa Energética, 2018;
46 Checco and Caldas, 2019; Canil et al., 2020).
47
48 Many public policies related to climate change have become symbolic, in conflict with prevailing economic
49 policies and practices (medium confidence: low evidence, high agreement). Urban adaptation plans can be in
50 conflict with other policies and there may exist insufficient support in multiple areas such as social attitudes
51 and behaviour, knowledge, education and human capital, finance, governance, institutions and policy
52 (Villamizar et al., 2017; Koch, 2018). Some policies around climatic related displacements and migrants
53 have been considered in NDCs (Priotto and Salvador Aruj, 2017; Yamamoto et al., 2018; de Salles Cavedon-
54 Capdeville et al., 2020).
55
56 As there are asymmetries among populations regarding the vulnerability and benefits of adaptation, along the
57 lines of gender, age, socioeconomic conditions and ethnicity, it has been noticed that adaptation policies and
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1 programs must be adequate to diverse conditions and actors (very high confidence) (Kaijser and Kronsell,
2 2014; Walshe and Argumedo, 2016; Baucom and Omelsky, 2017; Harvey et al., 2018).
3
4 Effective adaptation and mitigation depend on policies and measures at multiple scales, especially on the
5 involvement of the more exposed and vulnerable people. The participation of experts, communities and
6 citizens has shown to be effective (FAO and Fundación Futuro Latinoamericano, 2019) particularly through
7 partnership of grassroots organizations with impoverished communities providing valued expertise and
8 capacities to support the implementation of government climate resilience strategies (World Bank Group,
9 2015). More inclusive planning processes correspond to higher climate equity and justice outcomes in the
10 short term, but also an emphasis on building dedicated multi-sector governance institutions may enhance
11 long-term programs stability, while ensuring civil society voice in adaptation planning and implementation
12 (Chu et al., 2016). Some local organizations and people have succeeded when they were in charge of their
13 own resiliency efforts, where international projects and protocols proved less effective (Doughty, 2016). At
14 times, decentralized governmental programs have tried to increase public responsiveness to the adaptation
15 needs of people; however, proving to only be mildly successful and provoking the mobilization of
16 communities against existing governance structures (Thompson, 2016).
17
18 Indigenous knowledge and local knowledge (IK and LK) participation is thought to be more considered in
19 adaptation policies, as it has good results (high confidence) (Nagy et al., 2014b; Jurt et al., 2015; Arias et al.,
20 2016; Stensrud, 2016). IK has been adaptive for long periods in the Andes (Cuvi, 2018), but there might be
21 limits to adaptation in the face of present climatic and other environmental and socioeconomic drivers
22 (Postigo, 2019). Approaches integrating IK with more formal sciences, to address research and policies, have
23 improved adaptation processes, but they are no exempt of complications (high confidence) (Doswald et al.,
24 2014; Metternicht et al., 2014; Tengö et al., 2014; Drenkhan et al., 2015; Keenan, 2015; Lasage et al., 2015;
25 Camacho Guerreiro et al., 2016; Hurlbert and Gupta, 2016; Roco et al., 2016; Santos et al., 2016; Walshe
26 and Argumedo, 2016; Uribe Rivera et al., 2017; Kasecker et al., 2018; Cuesta et al., 2019; Ulloa, 2019;
27 Ariza-Montobbio and Cuvi, 2020). More interdisciplinary and transdisciplinary research helps to better
28 understand and manage the relationship between governance, implementation, management priorities, wealth
29 distribution and trade-offs between adaptation, mitigation and the Sustainable Development Goals (SDG).
30
31 Representations of climate change can also emerge as critiques and resistances, that expose that climate
32 change labelled politics or interventions have posed even bigger risks, or do not address poverty issues
33 (medium confidence: medium evidence, high agreement) (Lampis, 2013; Pokorny et al., 2013; Ojeda, 2014).
34 Indigenous and social movements have joined with climate justice activists, claiming for action against
35 climate change (Hicks and Fabricant, 2016; Ruiz-Mallén et al., 2017; Charles, 2021). The Bolivian Platform
36 against Climate Change, a coalition of civil society and social movement organizations working to address
37 the effects of global warming in Bolivia and to influence the broader global community, reflects an
38 innovative dimension that, albeit at time conflictual, has flagged how increasing climate variability hinders
39 the right of Indigenous Peoples to the conservation of their culture and practices and illustrates how grass-
40 root movements are increasingly appropriating climate change policy in the region (Hicks and Fabricant,
41 2016). Social movements have engaged with international networks as Blokadia, which surged after COP 23,
42 whose vindications try to go beyond the protection of the environment, delving into issues of democracy and
43 resource control (Martínez-Alier et al., 2018).
44
45 Many social movements address adaptation to climate change. Some engage and participate in policy and
46 planning, often having good results at the local level. On the contrary, top-down approaches without
47 participation have shown to be less effective (high confidence) (Krellenberg and Katrin, 2014; Nagy et al.,
48 2014b; Stein and Moser, 2014; Ruiz-Mallén et al., 2015; Sherman et al., 2015; Waylen et al., 2015; Bizikova
49 et al., 2016; Chelleri et al., 2016; Merlinsky, 2016; Villamizar et al., 2017).
50
51 Some conflicts in which the direct biophysical impacts of climate change play a major role can unleash
52 social protests and strengthen social movements (Section 12.6.4). In Cartagena, since 2010, the increase in
53 precipitation increasingly impacted the barrio Policarpa, causing the residents to claim solutions for the
54 problems caused by the coupled effect of flooding and industrial pollution. Also, in El Cambray II, in
55 Guatemala City, in 2015 the nearby hill collapsed, causing the death of 280 people, 70 disappeared and the
56 destruction of hundreds of homes. The affected community entered into a conflict with the municipality
57 asking for resettlement and a reform of land-use planning (Stein Heinemann, 2018).
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1
2 12.5.8.2 Perceptions
3
4 Perception and understanding of climate change can be seen as an adaptive feature. In CSA, the
5 consciousness of it as a threat is burgeoning, a situation related to a growth in climate justice activism, as
6 well as to the occurrence of extreme weather events of all kinds (high confidence) (Forero et al., 2014;
7 Magrin et al., 2014; Capstick et al., 2015). Perception is positively associated across countries with the
8 Human Development Index and ND-Gain Readiness Index, and negatively associated with the Vulnerability
9 Index, and within countries, with the education level, while they are negatively associated with the degree of
10 political affinity for the market economy (Azócar et al., 2021). Anyhow, some communities do not associate
11 their problems with the scientific concept, so discussions as if it is human induced, the causes, or relations
12 with other problems, can become irrelevant (Sapiains Arrué and Ugarte Caviedes, 2017). Even communities
13 affected by the same changes do not necessarily perceive them in the same way (Bonatti et al., 2016). The
14 interpretations of change, its causes and effects, can widely vary (Paerregaard, 2018; Scoville-Simonds,
15 2018). Rather than adapting to climate change, some peoples adapt climate change to their social worlds
16 (Rasmussen, 2016a).
17
18 Perceptions tend to be different in rural and urban areas (Sherman et al., 2015). In the rural areas, it is highly
19 related with temperature rise and changes in rainfall patterns, changes in agriculture (pests, calendars),
20 biodiversity loss, solar radiation or changes in the oceans, and their impacts sometimes are related or even
21 more attributed to socioeconomic and environmental drivers, and also related with financial negative
22 outcomes (high confidence) (Infante and Infante, 2013; Postigo, 2014; Jacobi et al., 2015; Barrucand et al.,
23 2017; Harvey et al., 2018; Martins and Gasalla, 2018; Meldrum et al., 2018; Córdoba Vargas et al., 2019;
24 Leroy, 2019; Viguera et al., 2019; Gutierrez et al., 2020; Iniguez-Gallardo et al., 2020; Lambert and Eise,
25 2020). In places as the Amazonia, there is an increased perception with age (Funatsu et al., 2019). In
26 Mediterranean Chile, younger, more educated producers and those who own their land tend to have a clearer
27 perception than older, less educated, or tenant farmers, but they do not have a clear perception or how it may
28 affect their yields and farming operation (Roco et al., 2015). In some dry and humid Ecuadorian montane
29 forests, peasants perceive in the same way as scientific data, but they are at odds to predict the changes and
30 consider that they may not be prepared and only can be reactive (Herrador-Valencia and Paredes, 2016). In
31 an Andean community, perceptions of climate change are homogeneous and do not vary according to
32 gender, age or ethnicity (Cáceres-Arteaga et al., 2020). Among representatives of five municipalities of
33 Lima, it was found that climate change is not well understood and they have trouble distinguishing it from
34 other environmental issues (Siña et al., 2016). In an Amazonian region, farmers provided a more accurate
35 description than regional institutions of how it affects the local livelihood system (Altea, 2020). In Cuenca
36 Auqui peasants attribute recently experienced challenges in agricultural production mainly to perceived
37 changes in precipitation patterns, but statistical analyses of daily precipitation records at nearby stations do
38 not corroborate those perceived changes (Gurgiser et al., 2016).
39
40 12.5.8.3 Gender and intersectionality
41
42 There is ample empirical evidence that the impacts of climate change are not of equal scope for men and
43 women. Women, particularly the poorest, are more vulnerable and are impacted in greater proportion. Often,
44 for several economic and social reasons, they have less capacity to adapt, further widening structural gender
45 gaps (high confidence) (Box 7.4; Arana Zegarra, 2017; Casas Varez, 2017; Segnestam, 2017; Acosta et al.,
46 2019; Aldunce Ide et al., 2020; Olivera et al., 2021; Silva Rodríguez de San Miguel et al., 2021). Gender
47 equity is thought to be central to discussions on climate change adaptation policies. In issues such as
48 drinking water, energy, natural disasters, impacts on health and agriculture, capacity to migrate, women
49 (poor women in particular) are affected in greater proportion, further widening structural gender gaps. In a
50 rural community vulnerable to drought, short-term coping was more common among the women, especially
51 among female heads of household, while adaptive actions were more usual among the men; there are
52 gendered inequalities in access to and control over different forms of capital that lead to a gender-
53 differentiated capacity to adapt, where men are better able to adapt and women experience a downward
54 spiral in their capacity to adapt and increasing vulnerability to drought (Segnestam, 2017).
55
56 However, women are not always the more vulnerable group. While in a broad sense climate change impacts
57 more severely on women, there are situations where they have reacted, adapted better to, and been more
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1 resilient. Grassroots women self-help groups can be active agents of change for their communities, designing
2 and delivering gender-responsive adaptation solutions (Huairou Commission, 2019). Some studies suggest
3 that women establish a friendlier relationship with the environment and towards natural resources; studies on
4 masculinities and environment confirm this tendency (Brough et al., 2016). In a multi country study, some
5 female headed households tend to be slightly less vulnerable and more resilient than male headed
6 households, even though some exceptions were found when looking at sub-groups (Andersen et al., 2017). In
7 Chile, women are more likely to modernize irrigation and infrastructure, and gender appears as an important
8 element for drought adaptation (Roco et al., 2016). A change to agro-ecological practices has improved
9 gender equalities and adaptive capacity to climate change (Cáceres-Arteaga et al., 2020).
10
11 Recent studies emphasize that a gender approach to social inequalities ought to move beyond just looking at
12 men and women as experiencing the impacts in a differentiated manner; rather, an intersectional analysis
13 illuminates how different individuals and groups relate differently to climate change, due to their
14 situatedness in power structures based on context-specific and dynamic social categorizations (high
15 confidence) (Kaijser and Kronsell, 2014; Djoudi et al., 2016; Thompson-Hall et al., 2016; Olivera et al.,
16 2021). Thus, the relationship between gender and adaptation demands an analytical framework that connects
17 environmental problems with social inequalities in a complex way (Godfrey, 2012). An intersectional
18 approach contributes to better capture the diversity of adaptive strategies that men and women adopt vis-à-
19 vis climate change. Particular constellations of race, gender, class, age or nationality reveal more complex
20 realities (high confidence).
21
22 12.5.8.4 Migrations and displacements
23
24 Migration and displacements are multi-causal phenomena, and climate may exacerbate political, social,
25 economic or other environmental drivers (high confidence) (Kaenzig and Piguet, 2014; Brandt et al., 2016;
26 Priotto and Salvador Aruj, 2017; Sudmeier-Rieux et al., 2017; Radel et al., 2018; Heslin et al., 2019;
27 Hoffmann et al., 2020; Silva Rodríguez de San Miguel et al., 2021). In the region there are many case
28 studies, but data to assess and monitor precisely the effects of climate -and weather- related disasters in
29 migration and displacements in a broad perspective is still inaccurate (Priotto and Salvador Aruj, 2017;
30 Abeldaño Zuñiga and Fanta Garrido, 2020). The most common climatic drivers include tropical storms and
31 hurricanes, heavy rains, floods and droughts (Kaenzig and Piguet, 2014). Positive climatic conditions also
32 can facilitate migration (Gray and Bilsborrow, 2013). Peru, Colombia and Guatemala are amongst the
33 countries with the largest average displacements caused by hydro meteorological causes; Brazil had 295,000
34 people displaced because of disasters in 2019 (Global Internal Displacement Database, https://www.internal-
35 displacement.org/database/displacement-data).
36
37 These processes can be interpreted as impacts in vulnerable peoples, but also as adaptation strategies to
38 manage the risks and reduce the exposure, when people continue with their lives, temporary or permanently,
39 in a different but stable situation, or when members of the families send remittances to those that remain in
40 the affected areas (Section 7.4.3.2; Cross-Chapter Box MIGRATE in Chapter 7). The remittances create
41 opportunities for adaptive capacity building, as they reduce some vulnerabilities in the form of
42 infrastructures, agricultural supplies, food, education or health, as in northern CA (NU CEPAL, 2018).
43 Anyhow, migration as adaptation is not available to everyone (Kaenzig and Piguet, 2014), and the idea has
44 also been contested as it may not help to overcome structural problems or point to in situ options (Radel et
45 al., 2018; Ruiz-de-Oña et al., 2019). The causal processes are complex. Surveys of migrants usually find that
46 the main reported reason for migration is to find a job or to increase the household income (Wrathall and
47 Suckall, 2016; OIM, 2017; Radel et al., 2018), but the underlying reason for the lack of job or income is
48 rarely examined, and at times may be related with climatic hazards.
49
50 Migration most often originates in rural areas, with people moving to other rural or urban areas within their
51 home countries (Table Cross-Chapter Box MIGRATE 1 in Chapter 7). In the Amazon, approximately 80%
52 of the population is concentrated in cities due to rural-urban migrations in search of better income,
53 livelihoods and services, in cases associated with extreme floods and droughts (Pinho et al., 2015). In
54 Ecuador, environmental variables are most likely to enhance international than internal migration (Gray and
55 Bilsborrow, 2013). Hurricanes have been seen as positive triggers for international migration in CA (Spencer
56 and Urquhart, 2018). In the highlands of Peru, there are different patterns, including daily circular migration
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1 to combine the scarce income from agricultural production with urban income, rather than abandoning the
2 farming land (Milan and Ho, 2014; Zimmerer, 2014; Bergmann et al., 2021).
3
4 Migration to cities can mean opportunities for migrants and for the urban areas, but also can worsen the
5 problems, as urban poor people can become even more exposed and vulnerable, and the pressure on urban
6 capacities may not be well absorbed (high confidence) (Chisari and Miller, 2016; Gemenne et al., 2020).
7 Internal migration to cities is likely to exacerbate pre-existing vulnerabilities related to inequality, poverty,
8 indigence and informality (Warn and Adamo, 2014). Immigration can make cities/residents more vulnerable
9 to climate change risks (Section 12.5.5; Section 12.5.7). Groups as children, Indigenous Peoples or the poor
10 are usually amongst the most vulnerable in the migrations and displacements, which poses challenges to
11 national policies and international aid (Sedeh, 2014; Gamez, 2016; Ulla, 2016; Priotto and Salvador Aruj,
12 2017; Ramos and de Salles Cavedon-Capdeville, 2017; Amar-Amar et al., 2019; Gemenne et al., 2020). In
13 forced migration or displacement by climatic effects, women are prone to lose their leadership, autonomy
14 and voice, especially in new organizational structures imposed by authorities. This is especially the case in
15 temporary accommodation camps created after disasters, exacerbating differentiated vulnerabilities existing
16 (Aldunce Ide et al., 2020). International migration has become more dangerous and difficult as border
17 controls have become stricter, but programs such as the one of temporary agricultural workers from
18 Guatemala to Canada have proven to be successful (Gabriel and Macdonald, 2018). At the same time,
19 emigration may lead to the loss of IK and LK for adaptation (Moreno et al., 2020b).
20
21 Some areas are more sensitive to generate climatic migration: the Andes, the dry areas of the Amazonia,
22 northern Brazil, and the northern countries in CA (high confidence). Northeast Brazil would lose population
23 that will move to the south, deepening the existing inequalities (Oliveira and Pereda, 2020). In a study of 8
24 countries around the world, including Guatemala and Peru, a link was found between rainfall variability and
25 food insecurity which could lead to migration in areas of high prevalence of rainfed agriculture and low
26 diversification (Warner and Afifi, 2014). In CA, younger individuals are more likely to migrate in response
27 to hurricanes and especially to droughts (Baez et al., 2017).
28
29 The perception of gradual changes lowers the likelihood for internal migration, while sudden-onset events
30 increase movement (Koubi et al., 2016). On the other hand, it has been seen that extreme events like floods
31 or droughts can hinder population mobility, immobilizing them in their localities (Thiede et al., 2016). These
32 immobilized populations are supposed to face a double set of risks: they are unable to move away from
33 environmental threats, and their lack of capital makes them especially vulnerable to environmental changes
34 (Black et al., 2011). In CSA, migrating to the U.S. is becoming dangerous and expensive, as that country is
35 restricting the entries; these trends expose local populations to the risk of becoming immobile in the near
36 future in a place where they are extremely vulnerable (Ruano and Milan, 2014; McLeman, 2019). A survey
37 in Guatemala found no correlation between migration to the U.S. and severe food insecurity in households,
38 but the correlation became significant if the level of food insecurity was moderate, suggesting that families
39 in extreme hardship did not have the resources to migrate (Aguilar et al., 2019). At the same time, some
40 populations just have chosen not to move, as in Peru, where immobility in dissatisfied people is more likely
41 to be caused by attachment to place than resource constraints (Adams, 2016; Correia and Ojima, 2017).
42 Some populations have chosen to adapt relying in their IK and LK (Boillat and Berkes, 2013).
43
44 Migration is often the last resort for rural communities facing water stress problems (Magrin et al., 2014;
45 Ruano and Milan, 2014). In Bolivia, glacial retreat has not triggered new migration flows and had a limited
46 impact on the existing migratory patterns (Kaenzig, 2015). In SA, climatic variability increases the
47 likelihood of inter-province migration, rather than trapping populations. In a study of interprovincial
48 migration motivated by temperature, an exception arose in Bolivia, and even if that could suggest an
49 immobilized population (Thiede et al., 2016), it is not clear if they want to stay and adapt. In some cases,
50 people want to move but wait for relocation after the climate related disasters (Priotto and Salvador Aruj,
51 2017).
52
53 12.5.8.5 Financing
54
55 Climate change financing is unequally distributed among CSA countries (high confidence). Financing of
56 climate change adaptation remains very much delegated to multilateral and bilateral cooperation and the
57 governments in the region have heavily relied on it. Still, there are some concerns regarding justice in the
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1 distribution of these funds (Khan et al., 2020). The UNFCCC has created financing mechanisms throughout
2 its functioning years, but there is a wide range of issues that can present challenges for access by the
3 recipients (Hickmann et al., 2019). These include; lack of technical capacity; difficulties in following the
4 procedures established by the various financial entities; and low levels of awareness about the need for
5 action, as well as the different sources of funds available. The fiscal policies of the different countries have
6 contributed to government financing in the fight against climate change (World Bank, 2021). Since the Paris
7 Agreement, countries have pledged NDCs which introduce the need to design and implement carbon budgets
8 with respective consideration of the efficiency and costs and benefits involved in each mitigation or
9 adaptation to climate change projects (Fragkos, 2020).
10
11 According to UNFCCC, Latin America and the Caribbean, for the period 20152016 obtained 22% of
12 climate finance from multilateral climate funds. In this section we use data from:
13 https://climatefundsupdate.org/data-dashboard, most of the reported information for Latin-American and the
14 Caribbean includes Mexico, since the scope of this chapter does not includes Mexico we have rely in the raw
15 data included in the data-dashboard mentioned in the link (see also: Guzmán et al. (2016)). 76% went to
16 mitigation projects with the remaining 24% going to adaptation. Of the total finance provided by the
17 multilateral climate funds to the Region, 51% took the form of concessional loans, while 47% was provided
18 as grants. For the region, approvals in the 20152016 period were concentrated in Argentina, Chile, Brazil,
19 and Colombia, where large-scale mitigation projects were launched supported by the Green Climate Fund
20 (GCF) and the Clean Technology Fund (CTF). For the period 2003-2019, total contribution to South
21 America and the Caribbean is about USD 3,558 million. The largest contributors to climate finance in the
22 region come from the GCF, which approved USD 824.2 million for 23 projects. Brazil is the top recipient
23 with USD 195 million, followed by Argentina with about USD 162 million. The second provider is the
24 Amazon Fund with USD 717 million assigned to 102 projects in Brazil. In 2018, the CTF has become the
25 third source of financing with USD 483 million dollars approved for 24 projects; the main recipient is Chile
26 with USD 16,207 million followed by Colombia with USD 170 million. The five largest projects approved in
27 the region in 2018 were through the GCF. Brazil (USD 195 million) received support for reducing energy
28 intensity across Brazilian cities, while Argentina (USD 103 million) received support to scale up investments
29 by Small and Medium sized Enterprises (SMEs) in renewable energy and energy efficiency. In both cases
30 finance is predominantly provided as concessional loans.
31
32 Climate financing in CSA is mainly focused on mitigation actions (high confidence). In South America and
33 the Caribbean, 73% (USD 2,579 million) of funding to date has supported mitigation. Only 21% (USD 761
34 million) of the funding supports adaptation projects and the remaining 4% (USD 217 million) supports
35 multi-focus projects. Of the 51 new projects in South America and the Caribbean approved in 2018-2019, the
36 GCF financed USD 508 million in ten projects. Amazon Fund was next with USD 81 million in 10 projects.
37 While 32 the GCF focuses on large and transformative projects and programs and on a broader reform of the
38 policy framework in the Region, the Amazon Fund targets smaller project interventions.
39
40 Climate finance in the region is concentrated in Brazil receiving one third of the region's funding, and 41
41 mitigation activities receiving more than six times that of adaptation from multilateral climate funds. By the
42 size of its PGB, Brazil is receiving the largest amount of financing; this leaves the poorest countries with
43 little or no financing and therefore reinforces a vicious circle of poverty and vulnerability. If this is due to
44 Brazil being more successful presenting eligible projects, lack of commitment from other developing
45 countries or some other structural factors is an open question. In any case, compensation schemes for the
46 most vulnerable countries appear as required, given the differences in vulnerability to climate damages
47 (Antimiani et al., 2017). This is aggravated by the fact that funds management is in the hands of
48 supranational entities while inequalities remain in regions within a country, particularly in countries highly
49 centralized as is the case for countries in the region.
50
51 COVID-19 recovery plans can present synergistic effects for climate change adaptation (medium confidence:
52 low evidence, high agreement). A key decision point for adaptation will be how the world responds to the
53 pandemic. The global recovery can serve as a catalyst to increased and more equitable climate financing.
54 Globally, recovery packages will likely have the power to change the global trajectory towards meeting the
55 targets of the Paris Agreement and building a more just future (Forster et al., 2020). Several factors are
56 relevant to the design of economic recovery packages: the long run economic multiplier, contributions to the
57 productive asset base and national wealth, speed of implementation, affordability, simplicity, impact on
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1 inequality, and various political considerations (Hepburn et al., 2020). A key objective of any recovery
2 package is to stabilize expectations, restore confidence, and to channel surplus desired savings into
3 productive investment. However, `business as usual' implies temperature increases over 3°C, implying great
4 future uncertainty, instability, and climate damages. An alternative way to restore confidence is to steer
5 investment towards a productive and balanced portfolio of sustainable physical capital, human capital, social
6 capital, intangible capital, and natural capital assets (Zenghelis et al., 2020), consistent with global goals on
7 climate change. Finally, any recovery package, including climate-friendly recovery, is unlikely to be
8 implemented unless it also addresses existing societal and political concerns--such as poverty alleviation,
9 inequality, and social inclusion--which vary from country to country.
10
11 12.5.9 Adaptation Options to Address Key Risks in CSA
12
13 This section integrates, in the table 12.10 below, the sectoral assessment of adaptation options (see Sections
14 12.5.1 to 12.5.8) with the eight key risks assessed in the region (see Section 12.4). Table 12.10 presents a list
15 of the summarized adaptation options, which are detailed in their adaptation sections, from 12.5.1 to 12.5.8
16 in this chapter.
17
18
19 Table 12.10: Adaptation options addressing key risks organized by sector. See the note at the end for descriptions of
20 the sector names abbreviations.
1. Risk of food insecurity due to frequent/extreme droughts
T&F. ecosystems Ecosystem-based adaptation (EbA): Agroecosystem resilience practices
O&C ecosystems
Water Not Assessed (NA)
Food Water infrastructure and irrigation; Nature-based solution (NbS) & Payment for
ecosystem services (PES); Participatory water management; Multi-purpose water use
Climate information services; Early warning system (EWS); Insurance; Land use
planning; Low-Carbon Agriculture (LCA) strategies; Agroforestry; Indigenous
Knowledge and Local knowledge (IK and LK)
Cities NA
Health and wellbeing EWS; Insurance; Participatory water management; Water infrastructure and irrigation
Poverty and SD Community-based adaptation (CbA); Government and institutional support
Human Dimension Participatory management; Incorporation of IK and LK in water and crop
management; Education and communication
2. Risk to life and infrastructure due to floods and landslides
T&F ecosystems NA
O&C ecosystems NA
Water NbS; Land-use regulation; EWS; Integrated risk management.
Food NA
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Cities Urban planning; Climate-adapted parameters in land use and building regulation;
Intersectoral and multilevel governance; Slum upgrading; Social housing
improvement; Urban control systems; CbA; Risk management plans; Integrated
watershed management; Flood control programs; Environment protected areas;
Households relocation; EWS; NbS; Mapping tools; Green-grey infrastructure (GGI);
Water storage solutions; Wetland restoration; sustainable urban drainage systems
(SUDS); low-impact development (LID); River restoration; Multifunctional
landscapes; Improving basic sanitation services
Health and wellbeing EWS; GGI; Community led and managed relocation; Insurance
Poverty and SD Secure location; Social housing policies; EWS
Human dimensions Education and communication
3. Risk of water insecurity
T&F ecosystems Monitoring Systems; EbA; Forest protection and restoration; Watershed protection
O&C ecosystems CbA; Land use and development regulation
Water
Water infrastructure and irrigation; NbS & PES; Participatory water management;
Food Multi-purpose water use
Management and planning; NbS; Soil and water conservation
Cities Intersectoral and multilevel governance; CbA; Risk management plans; Integrated
Health and wellbeing watershed management; Environment protected areas; NbS; GGI; Wetland restoration;
Poverty and SD Improving basic sanitation services; Reservoir system
Protection and restoration; National Adaptation Plans; Participatory water
management
NbS: Water harvesting; Equitable water distribution
Human dimensions Participatory management; Incorporation of IK and LK in water management;
Education and communication
4. Risk of severe health effects due to increasing epidemics
T&F ecosystems NA
O&C ecosystems NA
Water
Food Water infrastructure; Sanitation improvement
Cities NA
Health and wellbeing NA
EWS; Health-climate surveillance systems; National plans on health; Communal
Poverty and SD management; GGI; Protection and Restoration.
CbA; Transparent democratic governance; Equitable services; Education
Human dimensions Education and communication
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5. Systemic risks of surpassing infrastructure and public service systems
T&F ecosystems NA
O&C ecosystems EWS; EbA; Territorial planning; CbA; Land use and development regulation; GGI
Water Water infrastructure; Land-use regulation; Water retention capacity; EWS; Capacity
Food building
Cities
NA
Health and wellbeing
Poverty and SD Urban planning; Climate-adapted parameters in land use and building regulation;
Intersectoral and multilevel governance; Slum upgrading; Social housing
improvement; CbA; Improving basic sanitation services; Micro wastewater treatment
plants
EWS; Vulnerability and risk maps; National Adaptation Plans; GGI
Transparent, democratic governance
Human dimensions NA
6. Risk of large-scale changes and biome shifts in the Amazon
T&F ecosystems Monitoring Systems; EbA; Protected areas; Forest protection and restoration and
O&C ecosystems restoration; Watershed protection
NA
Water Integrated water resource management
Food Territorial planning
Cities NA
Health and wellbeing Protection and restoration
Poverty and SD Insurance; Micro-credits; PES; CbA
Human dimensions Participatory management; Incorporation of IK and LK in forest management;
Education and communication
7. Risk to coral reef ecosystems due to coral bleaching
T&F ecosystems NA
O&C ecosystems Zoning schemes; MPAs; EbA; CbA; Adhesion of international treaties
Water NA
Food NA
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Cities NA
Health and wellbeing Protection and restoration
Poverty and SD NA
Human dimensions NA
8. Risks to coastal socio-ecological systems due to sea level rise, storm surges and coastal erosion
T&F ecosystems NA
O&C ecosystems EbA; Planned relocation; GGI
Water NA
Food NA
Cities
Urban planning; Climate-adapted patterns in land use and building regulation;
Health and wellbeing Intersectoral and multilevel governance; CbA; Risk management plans; Households
relocation; NbS; GGI
GGI; Communal management; Protection and restoration
Poverty and SD Secure location; CbA relocation
Human dimensions Participatory management; Education and communication
1 Table Notes:
2 Some sectors are presented by abbreviations: Terrestrial and freshwater ecosystems and their services (T&F.
3 ecosystems); Ocean and coastal ecosystems and their services (O&C ecosystems); Food, fibre and other ecosystem
4 products (Food); Cities, settlements and key infrastructure (Cities); Poverty, livelihood and sustainable development
5 (Poverty and SD); Cross cutting issues in the Human Dimension (Human Dimensions).
6
7 Feasibility Assessment of Adaptation Options
8 12.5.10
9
10 This section assesses the feasibility of selected adaptations options by sector, relevant for CSA, in five
11 dimensions (economic, technological, institutional, social, environmental and geophysical), according to the
12 methodology developed by Singh et al. (2020a). Table 12.11 shows the summary of results and Table
13 SM12.7 the details of the assessment and the supporting literature.
14
15
16 Table 12.11: Feasibility assessment of selected adaptation options for CSA region.
System Adaptation Evidence Agreement Dimension assessed
option
Economic Technologi Institutio Social Environme Geophy
cal nal ntal sical
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Food, Agroforest Medium High Insignific Mixed Significa Mixed Insignifica Mixed
fibre ry nt barriers effect
and ant effect nt effect
other
ecosyst barriers barriers
em
produc
ts
Health Early Robust High Insignific Mixed Significa Mixed Insignifica Mixed
and warning nt barriers effect
wellbei systems ant effect nt effect
ng
barriers barriers
Water Multi-use Robust Medium Insignific Mixed Mixed Mixed Mixed Insigni
of water effect effect effect ficant
storage ant effect barrier
approache s
s barriers
Freshw Ecosystem Medium High Mixed Mixed Insignifica Insignifica Insigni
ater -based effect effect nt barriers nt barriers ficant
and adaptation Insignific barrier
terrestr (EbA) ant s
ial barriers
ecosyst
ems
1
2
3 12.5.10.1 Food, fibre and other ecosystem products - Agroforestry
4
5 For the agri-food systems, the adoption of agroforestry provides a more diverse and sustainable agricultural
6 production, where farmers maintain or improve their current production by incorporating suitable trees that
7 ameliorate climatic conditions. Thus, in the same unit of land, these systems incorporate exotic tree species
8 or managed native forests into farming systems allowing the simultaneous production of trees, crops and
9 livestock with different spatial arrangements or temporal sequences. On the other hand, it is recognized that
10 the initial investment and time until trees start to produce may create economic vulnerability. Therefore,
11 there is a need to design adequate programs and allocate resources for agroforestry systems implementation,
12 as well technical assistance and training (medium confidence). Also, some market schemes such as payment
13 for ecosystem services and certification can assist to reduce this vulnerability.
14
15 12.5.10.2 Health and Wellbeing - Early Warning Systems
16
17 For the health sector, we assessed the barriers and facilitators for the implementation of climate-driven early
18 warning systems under natural disasters and epidemic situations. We found institutional dimensions as
19 potential barriers, including the legal and regulatory feasibility, the institutional capacity and administrative
20 feasibility, transparency, and political acceptability (high confidence). The fewest barriers were identified for
21 the economic and environmental dimensions.
22
23 One of the main institutional challenges is the lack of policy with climate-health linkages. Opportunities
24 include a national plan for the health sector to address the impacts of climate by formalizing collaborations
25 via agreements (MOUs). Another key barrier is that relatively few institutions in the region have the human
26 technical and administrative capacity to implement and operate an EWS. Regional platforms may provide a
27 solution for technical assistance at national levels.
28
29 On the other hand, the economic dimensions had relatively few barriers, although the initial costs of
30 designing, implementing, equipping, and maintaining the system are a potential barrier for health sectors
31 with reduced budgets. However, the health benefits and economic savings (due to averted epidemics or
32 damages from disasters) may offset these costs. The resilience built in the health sector by these systems may
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1 be applicable to other economic sectors that can benefit from an early warning of an oncoming extreme
2 event and associated health impacts.
3
4 12.5.10.3 Water - Multi-use of water storage approaches
5
6 For the water sector, geophysical and economic dimensions do not pose a major barrier due to the potential
7 reduction of flood hazard exposure, physical-technical viability of project implementation, different suitable
8 economic mechanisms for joint public-private financing and more efficient water use. However, limited
9 institutional capacities and the social-environmental impacts of large water infrastructure (Section 12.5.3)
10 reduce the institutional, social, environmental and, to some extent, technological feasibility. This may be a
11 potential barrier to the adaptive approach of multi-use water storage (medium confidence).
12
13 12.5.10.4 Freshwater and terrestrial ecosystems - Ecosystem-based adaptation (EbA)
14
15 In the terrestrial and freshwater ecosystems sector, we assessed the feasibility of implementing EbA options
16 in the CSA region. Given that EbA encompasses a wide range of projects, techniques and political and
17 socioeconomic arrangements, extreme care should be taken to apply these general findings to particular
18 cases. EbA can enhance food sovereignty and carbon stocks and foster SDG by protecting and restoring
19 ecosystems health and productivity. EbA is a strategy that frequently involves bottom-up decision making
20 and local communities' empowerment and usually contributes to inequality reduction. EbA tends to benefit
21 vulnerable groups, but aspects such as the impact on socioeconomic inequalities when implemented should
22 be taken into account.
23
24 In general, EbA does not require high technologies for local communities. However, limitations in technical
25 assistance and funding for specific key technologies and training may act as a barrier for EbA adoption
26 (medium confidence). EbA practices can reduce risk in several ways by increasing awareness among
27 communities and providing food diversity and production. EbA is recognized as a desirable policy for most
28 stakeholders in CSA, particularly for being a strategy that incorporates environmental and social concerns.
29 Nonetheless, it is important that all stakeholders agree on the goals and methods for EbA to be effective.
30 Lack of institutional coordination, clear goals and strategies were identified as a potential barrier for EbA
31 implementation. EbA is heavily based in local and Indigenous knowledge, as well as ecological academic
32 knowledge.
33
34 For the adaptation options analysed, significant barriers and mixed effects were observed for the institutional
35 dimension, which indicates the relevance of the design and implementation of public policies and
36 institutional arrangements for effective adaptation in the region. Considering the results, there is a need to
37 advance initiatives, programs and projects that facilitate adaptation to climate change. In the same way,
38 barriers were evidenced in the technological dimension, which indicates the importance of increasing access
39 and diffusion of appropriate techniques and technologies in order to face the challenges of climate change in
40 the region.
41
42
43 12.6 Case Studies
44
45 12.6.1 Nature-based Solutions in Quito, Ecuador
46
47 Nature-based Solutions (NbS) are related to the maintenance, enhancement, and restoration of biodiversity
48 and ecosystems as a means to address multiple concerns simultaneously (Kabisch et al., 2016). NbS can
49 trigger sustainability transitions. For example, conservation and restoration of natural ecosystems are prone
50 to promote synergy between mitigation, adaptation and sustainable development. Ecosystem-based
51 Adaptation- EbA can be seen as a type of NbS deployed in response to climate change vulnerability and risk
52 (Greenwalt et al., 2018), combining the objectives of reducing the vulnerability of human and increasing the
53 resilience of natural systems (IPCC, 2014).
54
55 The Municipal Quito District in Ecuador covers 4235 km2 of mountainous territory that ranges from 500 to
56 5000 m.a.s.l. That territory has followed a pattern of urbanization common in Latin America: its population
57 has increased from around 500,000 people in the 1970s, to nearly 3 million inhabitants by 2020, of which
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1 80% live in urban areas (Municipio del Distrito Metropolitano de Quito, 2016). A massive inflow of people
2 immigrated in the early 1970s due to various causes, including the search for the rents created as a result of
3 the oil boom in the Ecuadorian Amazon, better working conditions, health, education and cultural services,
4 in comparison with the rural areas or in mid-sized cities. As a result, the city underwent an exponential
5 growth, claiming valuable agricultural and forestry areas, and natural ecosystems, in the peripheries. Many
6 of the new neighbourhoods were established through land invasions or informal markets, in many cases over
7 steep slopes, in water sources and agricultural or conservation areas (high confidence) (Cuvi, 2015; Gómez
8 Salazar and Cuvi, 2016). That exponential population growth, coupled with urban sprawl, poses many
9 challenges to the city, including those related to climate change.
10
11 Mean air temperature and annual rainfall (measured through instruments since 1891 and inferred through
12 historical records of rogation ceremonies since 1600), are increasing, combined with an increase in
13 seasonality (i.e., longer periods of drought) and extreme weather events, particularly stronger precipitations
14 (Serrano Vincenti et al., 2017; Domínguez-Castro et al., 2018). Two impacts related to warmer air conditions
15 are the displacement of the freezing line currently placed at 5100 m.a.s.l. (Basantes-Serrano et al., 2016),
16 followed by glacier retreat and the upward displacement of mountainous ecosystems (very high confidence)
17 (Vuille et al., 2018; Cuesta et al., 2019). The key ecosystem that regulates water provision for the city is the
18 paramo, and only about 5% of this process is related with glaciers, so the combined effects of climate change
19 on both systems, coupled with land use change and fires, can reduce the availability of water for agriculture,
20 human consumption and hydropower. Other important climatic hazards and impacts are the increase of solar
21 radiation, the heat island effect and fires (high confidence) (Anderson et al., 2011; Armenteras et al., 2020;
22 Ranasinghe et al., 2021). Almost half of the days of each year, Quito's population is exposed to levels of UV
23 radiation above 11 according to the World Health Organization scale (Municipio del Distrito Metropolitano
24 de Quito, 2016).
25
26 Various policies, programs and projects have been created for the promotion of urban green spaces,
27 protected areas, water sources and watersheds monitoring, conservation and ecosystem restoration, air
28 pollution monitoring and control, and urban agriculture. Among those actions, three recent are commonly
29 highlighted. The first is the Fund for the Protection of Water (FONAG), established in 2000 with funds of
30 national and international organizations, to promote the protection of the water basins that supply most of the
31 drinking water. It is a PES-Scheme (Payment for Ecosystem Services) enabled through a public-private
32 escrow. The projects include conservation, ecological restoration, and environmental education for a new
33 culture of water, in a context opposed to the commodification of natural resources (Kauffman, 2014; Bremer
34 et al., 2016; Coronel T, 2019). FONAG was innovative in the use of trust funds in a voluntary, decentralized
35 mechanism and has inspired more than 21 other water funds in the region; nevertheless, its narrative of
36 success has also been said to over-simplify and misrepresent some complex interactions between
37 stakeholders as well as within communities and their land management practices (Joslin, 2019).
38
39 The second highlighted initiative is the project AGRUPAR (Participative Urban Agriculture), launched as a
40 public initiative in 2002 with international cooperation funds at the beginning. It was aimed to provide
41 assistance to poorer urban and peri-urban populations, to initiate and manage orchards as well as domestic
42 animals such as chickens and guinea pigs, dedicated for self-sustenance and commerce. AGRUPAR provides
43 and finances training, seeds and seedlings, greenhouses, certifications and marketing support, spaces where
44 farmers can sell directly their products to consumers. In 2016, AGRUPAR gave assistance to more than 4000
45 farmers managing orchards of various scales that combined produce, annually, more than 500 tonnes. The
46 program has direct impacts on nutrition, generation of work for women, production of healthy food,
47 reduction of runoff, recycling of organic waste, social cohesion, among others (very high confidence)
48 (Thomas, 2014; Cuvi, 2015; Rodríguez-Dueñas and Rivera, 2016; Clavijo Palacios and Cuvi, 2017).
49
50 A third initiative is the creation of a municipal system of protected areas, locally named Áreas de
51 Conservación y Uso Sustentable (ACUS). This system covers an area of 1320 km², nearly one third of the
52 Municipal Quito District. Half of this landscape (680 km2) is covered by montane forests and paramos
53 (Torres and Peralvo, 2019). These forests provide direct water, food and fibres for about 20,000 people, and
54 indirectly a rural landscape for a growing number of urban citizens and foreign tourists that practice
55 ecotourism and look for fresh and healthy food. During the last three decades, this area has witnessed a high
56 density of public and private conservation and restoration efforts that aim to regain ecological integrity and
57 improve human well-being in deforested and degraded landscapes (Mansourian, 2017; Zalles, 2018; Wiegant
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1 et al., 2020). Quito's system of protected areas constitutes a primary strategy for fostering links between
2 urban and rural citizens as a means of understanding the ecological dependence of urban metropolises to
3 their surrounding natural landscapes. Along the same lines, these areas constitute a key element to increase
4 the adaptive capacity of rural livelihoods and contribute to mitigating climate change through landscape
5 restoration, sustainable production and forest conservation (high confidence).
6
7 Other NbS' actions have been the restoration of small basins, locally named quebradas, under different
8 schemes of management and participation (medium evidence, very high agreement) (da Cruz e Sousa and
9 Ríos-Touma, 2018), or the transformation since 2013 of a larger portion of the old Quito airport into an
10 urban park. Nevertheless, Quito city still has to deal with challenges in social, economic, infrastructural and
11 environmental spheres. A major pending environmental issue is air pollution, as there is a high level of
12 pollutants affecting the city in general, and specially the most vulnerable groups (high confidence)
13 (Zalakeviciute et al., 2018; Alvarez-Mendoza et al., 2019; Estrella et al., 2019; Hernandez et al., 2019;
14 Rodríguez-Guerra and Cuvi, 2019). Another major issue is the continuous sprawl of new neighbourhoods,
15 mainly through informal processes, that diminish the urban resilience because of the destruction of
16 conservation and food production areas, sources of water, and the dispersion of settlements without primary
17 services, among other consequences (Gómez Salazar and Cuvi, 2016).
18
19 12.6.2 Anthropogenic Soils, an Option for Mitigation and Adaptation to Climate Change in Central and
20 South America. Learning from the "Terras Pretas de Índio" in the Amazon
21
22 Amazon Dark Earths (ADEs), also known as "Terras Pretas de Índio", are anthropogenic soils derived from
23 the activities associated to settlements and agricultural practices of pre-Hispanic societies in the Amazon
24 (Woods and McCann, 1999; Lehmann et al., 2003; Sombroek et al., 2003). Most of the ADEs identified so
25 far are 500 to 2500 years old (de Souza et al., 2019). According to Maezumi et al. (2018a) polyculture
26 agroforestry allowed the development of complex societies in the eastern Amazon around 4500 years ago.
27 Agroforestry was combined with the cultivation of multiple crops and the active and progressive increase in
28 the proportion of edible plant species in the forest, along with hunting and fishing. The formation of ADEs,
29 as a result of these activities, provided the basis for a food production system that supported a growing
30 human populations in the area (Maezumi et al., 2018a).
31
32 Amazon Dark Earths are the result of the accumulation and incomplete combustion of waste materials such
33 as ceramic artefacts and organic residues from harvest, weeding, food processing (including cooking) and
34 other activities (Lima et al., 2002; Hecht, 2003; Kämpf et al., 2003). ADEs are characterized by their
35 increased fertility in relation to adjacent soils; with high contents of organic carbon (C) (mainly as charcoal)
36 as well as inorganic nutrients, especially phosphorus (P) and calcium (Ca); and high Carbon/Nitrogen ratios
37 (high confidence) (Moline and Coutinho, 2015; Alho et al., 2019; Barbosa et al., 2020; Pandey et al., 2020;
38 Soares et al., 2021; Zhang et al., 2021). They also exhibit high cation exchange capacity (CEC) and moisture
39 retention among others properties (Hecht, 2003; Kämpf et al., 2003; Falcão et al., 2009). Charcoal content is
40 a key indicator of pre-Hispanic fire activity and sedentary occupation, which is evidence of the anthropic
41 origin of these soils (high confidence) (Hecht, 2017; Maezumi et al., 2018b; Alho et al., 2019; Barbosa et al.,
42 2020; Iriarte et al., 2020; Montoya et al., 2020; Shepard et al., 2020).
43
44 Accumulation of organic residues and low intensity fires management are recognized as key elements for
45 ADEs formation. ADEs originating around settlements show a relatively high density of ceramic artefacts
46 and are named Terras pretas. They present a higher content of Ca and P than those originated from
47 agriculture activities which are known as Terras mulatas (Hecht, 2003).
48
49 There is a robust and growing body of research from different disciplines that gives high relevance to ADEs
50 in the region. It has been shown through archaeological and paleoclimatic data that Amazonian societies
51 which based their agricultural management on "Terras Pretas de Índio", were more resilient to the changing
52 climate due to increased soil fertility and water retention capacity (de Souza et al., 2019). Additionally, low
53 organic carbon degradability over long time periods, associated with high contents of charcoal or pyrogenic
54 carbon, makes these soils an important C sink (medium confidence: robust evidence, medium agreement)
55 (Lehmann et al., 2003; Guo, 2016; Trujillo et al., 2020), which is particularly relevant in an area like the
56 Amazon, that could change from a net carbon sinks to a net carbon source as a consequence of
57 anthropogenic climate change (Maezumi et al., 2018b).
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1
2 The Indigenous agricultural practices which originated ADEs are thought to be associated with a more
3 sedentary agricultural model than the current slash and burn and shifting cultivation practices. Although this
4 is a controversial topic, as the precise definition of slash and burn and shifting cultivation is presently under
5 discussion (Hecht, 2003); several present-day local and Indigenous agricultural practices, including in-field
6 burning and nutrient additions from food processing and residue management, have been recognized as
7 promoting high organic carbon and nutrient soil contents similar to the ones found in ADEs (Hecht, 2003;
8 Winklerprins, 2009).
9
10 At present, ADEs are estimated to cover up to 3.2% of the Amazon basin and are highly valued for their
11 persistent fertility, becoming a key resource for sustainable agriculture for Amazon communities in a climate
12 change context (Altieri and Nicholls, 2013; Maezumi et al., 2018a; de Souza et al., 2019). Based on the
13 lessons learned from the Terras Pretas de Índio, some researches have proposed the development of
14 technologies to promote a new generation of anthropogenic soils (e.g., Kern et al. (2009); Lehmann (2009);
15 Schmidt et al. (2014); Bezerra et al. (2016); Kern et al. (2019)). Among the technologies based on ADEs
16 learnings Biochar, obtained by slow pyrolysis of agricultural residues, is the most explored application found
17 in literature (Mohan et al., 2018; Matoso et al., 2019; Amoah-Antwi et al., 2020). The dual purpose of
18 increased soil fertility and carbon sequestration is considered an important goal in order to develop
19 sustainable agriculture in a climate change context (Kern et al., 2019).
20
21 Preservation of the practices and knowledge associated with these soils is vital for sustainable agriculture in
22 a climate change scenario in the Amazon. It will greatly contribute to the preservation of valuable
23 Indigenous knowledge as well as the contribution to the development of new adaptation and mitigation
24 technologies among other unexplored solutions.
25
26 12.6.3 Towards a Metropolitan Water-related Climate Proof Governance (re)configuration? The case of
27 Lima, Perú
28
29 Lima-Callao Metropolitan City, capital of Perú is facing recurrent climate disasters showing lessons on
30 water-related climate-proof governance reconfiguration: 1) when disasters affect the poor and rich
31 population, dominant actors prioritize the integral city's resilience and development, and coordinate and
32 collaborate within a concertation manner across institutional levels and geographical scales (Hommes and
33 Boelens, 2017; Miranda Sara, 2021), even having different ideas, discourses, and power, recognizing that no
34 one single actor has enough power; 2) water-related climate change scenarios require comprehensive,
35 transverse, multi-sectoral, multi-scalar, multiple types of actor´s knowledge (expert, tacit, codified and
36 contextual embedded (Pfeffer, 2018) and transparent information to manage the tensions and even conflicts
37 when some knowledge is not shared or restricted particularly when lower risk perception and higher risk
38 tolerance are present; 3) a concertative (processes which involve a variety of actors and has become
39 mandatory in Peru) strategy to localize the climate action shows quicker, more effective and transparent
40 results (medium confidence, robust evidence, medium agreement) (Miranda Sara and Baud, 2014; Pepermans
41 and Maeseele, 2016; Siña et al., 2016; Miranda Sara et al., 2017).
42
43 Being the second driest city in the world, Lima is highly vulnerable to drought and heavy rainfall in the
44 nearby Andean highlands (Schütze et al., 2019). Located on the Pacific Coast with more than 10 million
45 inhabitants, suffers from both flooding, mudslides disasters and water stress, being more frequently affected
46 by heavy rain peak events (1970, 1987, 1998, 2012, 2014, 2015 and 2017) (very high confidence) (Mesclier
47 et al., 2015; Miranda Sara et al., 2016; French and Mechler, 2017; Vázquez-Rowe et al., 2017; Escalante
48 Estrada and Miranda, 2020). In addition to water unequal distribution in quantity and pricing, one million
49 inhabitants lack water connections (Ioris, 2016; Miranda Sara et al., 2017; Vázquez-Rowe et al., 2017) as a
50 result of a lack of long-term city planning and lack of integration with water and risk management. Climate
51 change scenarios were ignored or denied, particularly when the budget allocation for preventive actions was
52 necessary (high confidence) (Miranda Sara et al., 2016; Allen et al., 2017a).
53
54 In 2014, the Water Company (SEDAPAL) together with the Lima Metropolitan Municipality (LMM), ANA,
55 and other organizations agreed on a Lima Action Plan for Water (Schütze et al., 2019). The same year, the
56 Lima Metropolitan Municipality (LMM) approved the Climate Change Strategy defining adaptation and
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1 mitigation measures (Miranda Sara and Baud, 2014), based on technical and scientific action research within
2 interactive, and iterative concertation multi-actor processes.
3
4 However, in 2015, municipal elections shifted Lima's and later Peru's political power to parties associated
5 with climate deniers at a high cost to the people, city infrastructure, and housing. Beginning of 2017,
6 buildings along rivers, ravines, and slopes suffered from floods, huaycos (mudslides), the whole city suffered
7 potable water cuts (Vázquez-Rowe et al., 2017) and vector-borne diseases affecting particularly the poorer
8 but also richer inhabitants.
9
10 "Coastal Niño", affected the whole country, as a consequence, in 2018, the Peruvian government passed the
11 Framework Law for Climate Change, Law No. 30754, a unique political decision, to assure the integration of
12 climate change concerns in public policies and investment projects. The law defines local governments
13 mandates on Local Climate Action Plans. The 2019 municipal elections brought new local authorities to
14 Lima and by 2020, 19 district municipalities developed their Adaptation Measures adopting the Metropolitan
15 Climate Change Strategy with support of Cities for Life Foro and GIZ (Foro Ciudades Para la Vida, 2021),
16 in 2021 LMM approved its Local Climate Change Plan (LCCP) and other 10 (out of 51 with Callao)
17 municipalities concluded the elaboration of their LCCP with support of the Global Covenant of Mayors and
18 the European Union.
19
20 The institutionalized culture of participation in Peru did lead to a broader concept of concertation, wherein
21 practices of collaborative planning were developed to allow actors to build up socially supported agreements,
22 decisions and take actions without losing sight of their principles. These processes have been applied to
23 reduce risks, to adapt and to anticipate uncertain and unknown futures; and introducing climate change
24 concerns within a complex political and institutional environment surrounded by corruption scandals
25 (Vergara, 2018; Durand, 2019) and growing political polarization.
26
27 Several processes have been set in motion to engage citizen participation and promote climate action
28 planning: 1) The LMM with the Climate Action Plan processes reopened the Climate Change Technical
29 Group of the Municipal Environmental Commission whose work ended in the approval of the Lima Local
30 Action Plan of Climate Change (MML, 2021), 2) The River Basin Council is developing the River Basin
31 Management Plan led by the National Authority of Water (ANA); 3) The Metropolitan Lima Urban
32 Development Plan is finalizing a citizen consultation, with the support of a high-level Consultation Group.
33
34 Such processes include strong discussions, conflicts, and the recognition of other's discourses and types of
35 knowledge, to build up scenarios that "visualize" and anticipate what might happen. These processes require
36 democratic, transparent, and decentralized institutions, providing clear mandates and strong political will to
37 support them, so the views of the poor and vulnerable are included, being able to make themselves heard,
38 even if their power remains limited (Chu et al., 2016). Opportunities for the reconfiguration of socio-political
39 and technological water governance are emerging based on socially supported agreements (Miranda Sara and
40 Baud, 2014; Miranda Sara, 2021). Although the water governance configuration faces the paradox that
41 current water demands of all users combined may no longer be feasible within ecological limits and future
42 climate change consequences (Miranda Sara et al., 2016; Schütze et al., 2019).
43
44 12.6.4 Strengthening Water Governance for Adaptation to Climate Change: Managing Scarcity and
45 Excess of Water in the Pacific Coastal area of Guatemala
46
47 Guatemala experiences high climate inter-annual variability now increased from the effect of climate change
48 (INSIVUMEH, 2018; Bardales et al., 2019). Impacts on human settlements, agriculture and ecosystems
49 result from both excess and reduced precipitation (high confidence) (Section 12.3.1.4). Guerra (2016) argues
50 that deficient integrated water resource management in the country is the main reason for those impacts. A
51 case in point is that of rivers Madre Vieja and Achiguate where an intense El Niño event triggered dryer
52 conditions and, in turn, a crisis and conflict that reached national proportions. Progress in local water
53 governance helped to solve that crisis and contributed to tackle challenges posed by reduced precipitation
54 and flood risk in southern Guatemala.
55
56 The ENSO event that started in November 2014 and ended in July 2016 (CIIFEN, 2016) has been the most
57 intense since records commenced in 1950 (NOAA, 2019). Its effects were felt in different parts of the world
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1 and, Guatemala and the rest of Central America experienced an intense water scarcity due to a significant
2 reduction in rainfall (high confidence) (IICA, 2015; Scientific American, 2015). River flow in the dry
3 months is related to precipitation levels in the previous rainy season and thus, ENSO has an effect on river
4 flow rates. Two of the main rivers in the Pacific coast of Guatemala, Madre Vieja and Achiguate, dried out
5 completely at the beginning of 2016, triggering a nearly violent local conflict that caught attention at the
6 national level (Guerra, 2016; Gobernación de Escuintla et al., 2017). In addition to the severe drought, the
7 rivers dried because of over-extraction by multiple users (60 in the case of Madre Vieja). This had happened
8 before to a lesser extent in the last 20 years during the critical months of the dry season. Lack of regulation,
9 coordination mechanisms, information, and other elements of water governance was the root cause of the
10 problem, exacerbated by the drier conditions during the intense El Niño resulting in the intensification of an
11 existing conflict (high confidence) (Guerra, 2016).
12
13 Roundtables were set up to foster dialogue between numerous stakeholders including communities, agri-
14 export companies, governmental organisations, municipalities, all led by the local governor (Gobernación de
15 Escuintla et al., 2017). Agreements included: to keep a minimum of the rivers flowing all the way to the sea;
16 to set up a monitoring and verification system for levels of river flow; and to restore riparian forests. A
17 system was set up to monitor river flow in different points along the rivers on a daily basis in the dry season
18 using a simple WhatsApp-based system to communicate the warnings and monitor compliance. Four years
19 on, the rivers had not dried out and conflict was kept to a minimum. Rural communities can use rivers for
20 recreational purposes and for fishing all year round, whilst plantations (large and small) can use water for
21 irrigation (rationally) and keep producing. Similar schemes and interactions started happening in other rivers
22 in the Pacific coast of Guatemala, with positive results, particularly keeping the rivers flowing all through the
23 dry season as can be seen in the report of river flows for years 2017, 2018 and 2019 (ICC, 2019b).
24
25 A key actor in the improvement of water governance has been the Private Institute for Climate Change
26 Research (ICC). This is a unique initiative that was created in 2010 and is funded primarily by the private
27 sector of Guatemala to help the country advance in climate change mitigation and adaptation (Guerra, 2014).
28 The institute works alongside local governments, communities and private companies in several topics apart
29 from integrated water management. Its role is merely technical-scientific, being in charge of the water
30 monitoring system, generating data on weather and hydrology, and providing support to other stakeholders.
31
32 Local governance was also essential for the implementation of flood risk management actions (high
33 confidence). Guerra et al. (2017) explained how impacts were significantly reduced in the Coyolate river
34 watershed, also in the Pacific coast of Guatemala, thanks to flood protection that was designed and
35 implemented in a technical and integrated manner. This was a result of strong and active participation of
36 local communities, companies and the local municipality who demanded the central government to invest
37 effectively. The stakeholders provided some resources (financial and in-kind) and inspected the works. Some
38 flat areas of the lower Coyolate watershed used to flood annually causing economic damage for
39 communities. The areas covered by flood risk measures have not flooded which has avoided losses as well as
40 created conditions for investment to come and create jobs, improving life conditions for locals. Other
41 processes of participation and interaction between the authorities, the private sector and communities have
42 taken place in other watersheds for planning, action and investment for flood risk management. The ICC has
43 played a role by studying flood-prone areas, building capacities in communities, fostering public-private
44 coordination mechanisms, and providing much-needed technical assistance to local governments (ICC,
45 2019a).
46
47 Although some may argue that water governance is in the realm of development, it has made contributions in
48 reducing direct and indirect impacts of climate events and therefore, it can be seen as a key element for
49 climate adaptation (high confidence).
50
51
52 12.7 Knowledge Gaps
53
54 Data deficiencies and heterogeneity in quantity, quality and geographical bias in knowledge limit the
55 understanding of climate change, the evaluation of its impacts, and the implementation of adaptation and
56 mitigation measures (Harvey et al., 2018) in CSA. The number of publications is not representative with
57 respect to the sensitivity to climate change and vulnerability contexts of different subregions and sectors.
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1 This lack of representation in the mainstream literature may lead to a bias and, therefore, an underestimation
2 of the overall climate-related impact for some CSA subregions (Sietsma et al., 2021). The reason for
3 relatively few quantitative studies might be the complexities of socio-demographic and economic factors,
4 and the lack of long-term and reliable data in these areas (Harvey et al., 2018), along with other social,
5 economic and technical constraints.
6
7 Most studies that assess vulnerability to climate change do not yet follow the concept adopted since the Fifth
8 Assessment Report (AR5) which separates exposure as an external variable (WGII AR5 Figure SPM 1)
9 (IPCC, 2014), and many still use the A and B system of climate change scenarios from AR4, as adoption of
10 the RCP models has been slow. There is still limited literature on severe risks and little specific and explicit
11 consideration of risk drivers in the region. Moreover, limits to adaptation and the effectiveness of adaptation
12 measures in CSA remain largely understudied.
13
14 The research of the interactions between climate change and socioeconomic processes is underdeveloped
15 (Barnes et al., 2013; Leichenko and O'Brien, 2019; Thomas et al., 2019). There is limited understanding of
16 the multilevel synergistic effects of climate change and other drivers including economic development from
17 household to country level (Wilbanks and Kates, 2010; Leichenko and Silva, 2014; Tanner et al., 2015a;
18 Carey et al., 2017). In the region, this deficit is deeper for sectors other than agriculture, water and food.
19
20 12.7.1 Knowledge Gaps in the Subregions
21
22 The knowledge gaps in the eight subregions are quite heterogeneous. In CA, climate change research is
23 notably insufficient in all sectors included in this report, considering that climatic change, variability, and
24 extremes are and will severely impact this subregion, and the vulnerability of the social and natural systems
25 is high. Data deficiencies must be overcome as renewed research on climate change updates models,
26 scenarios, and projected impacts across sectors and levels (i.e., household to country). In NWS, there is a
27 lack of studies on the relationships with increased fire events, and the impacts on the infrastructure of all
28 kinds, on certain lowland, marine and coastal ecosystems, and on ecosystem functioning and the provision of
29 environmental services. Experimental studies are rare, most necessary to identify critical ecological
30 thresholds to support the decision-making processes, linking glacier retreat to its consequences on
31 biodiversity and ecosystems, combined with different land-use trajectories. Complex interactions with
32 processes such as peace agreements in Colombia are yet to be studied (Salazar et al., 2018). In NSA, there is
33 still a limited amount of peer-reviewed literature, addressing the implications of climate change on
34 Indigenous cultures and their livelihoods. In SAM, further data are needed on the vulnerability of traditional
35 populations, impacts on water availability and soil degradation, risks to biodiversity and resilience of
36 ecosystems, attributed to climate change.
37
38 There is a knowledge gap about the likely impact of climate change on NES biodiversity, soil degradation,
39 and best adaptation measures. SES is the most urbanized sub-region of CSA, but there is a strong knowledge
40 deficits related to the design, implementation and evaluation of adaptation policy plans to climate change.
41 Forecasts related to risk prevention require new studies that address down-scaled climate change models
42 with concrete solutions to increase the city's resilience. In SWS, there is a lack of long-term studies
43 addressing climate change impacts in terrestrial, freshwater and marine ecosystems which is mainly due to
44 the lack of integrated observational systems. There is a lack of studies projecting future impacts of climate
45 change on the cryosphere, water resources, hazards, risks and disasters on natural and human systems. This
46 is mainly due to the lack of systematic documentation, analysis and evaluation of adaptation strategies
47 adopted, as well as their limitations and the lessons learned from maladaptation processes. There is low
48 evidence about transformational adaptation to climate change and systems resilience. In SSA, there is a need
49 for information related to vulnerability and impacts of the direct effects of future climate change on cities,
50 energy infrastructure and health. Also, there is a gap of knowledge about financing of climate change
51 adaptation in SSA.
52
53 12.7.2 Knowledge Gaps by Sector
54
55 12.7.2.1 Terrestrial and Freshwater Ecosystems and their Services
56
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1 Advances on scientific knowledge on risks of climate change impact, vulnerability and resilience of
2 ecosystems is needed (Bustamante et al., 2020). Persistent climate change in tropical rainforest needs further
3 understanding, overall on the role of nutrients, deep-water availability and biodiversity. Further research is
4 needed to understand feedback to the climate systems of large-scale changes in the land surface in South
5 America biomes. The region has important freshwater Global-200 Ecoregions, including the Orinoco River
6 and Flooded Forests, Upper Amazon river and streams, and Amazon River and Flooded Forests being,
7 therefore, a priority for freshwater biodiversity conservation at a global scale (Manes et al., 2021) (Cross-
8 Chapter Paper 1; Figure 12.8). There is, however, a clear knowledge gap on the impacts of climate change on
9 freshwater biodiversity in the region (Cross-Chapter Paper 1.2.3; Manes et al., 2021) . Lastly, more
10 interdisciplinary research is needed regarding conservation strategies and stable financial resources focusing
11 on adaptation of ecosystems in the region (Mistry et al., 2016; Gebara and Agrawal, 2017; Ruggiero et al.,
12 2019; To and Dressler, 2019).
13
14 12.7.2.2 Ocean and Coastal Ecosystems and their Service
15
16 There is an important lack of knowledge about the health state of the ocean and coastal ecosystems along
17 CSA (i.e., social-ecological data integration, poor sampling efforts, lack of information about the value of
18 ecosystem services, lack of information about ecosystems cover and distribution, lack of studies
19 about climate change perception and social concerns), including marine fisheries (i.e., landing statistics
20 not available, lack of reliable information on the scope of resource extraction, among others). Poor or absent
21 monitoring programs (physical, environmental and biological variables) that feed alert and surveillance
22 systems are missing for CSA. There is a general absence of a continuous line of scientific research or an
23 adequate baseline information about the impacts of climate change, as well as a continuous monitoring of the
24 adaptation plans adopted in ocean and coastal ecosystems which limit the formulation of adequate
25 conservation and management programs. When studies are performed, inadequate access to data limits the
26 analyses of the existing information making difficult to detect climate change trends and impacts, as well as
27 the development of effective adaptation strategies.
28
29 12.7.2.3 Water
30
31 As in other sectors and environmental systems, for the water sector there are important limitations in terms
32 of monitoring and data collection. High-quality, long-term hydrological data are unevenly available for
33 different subregions and limit a better understanding of changes in river runoff, lake or groundwater changes.
34 Groundwater data is particularly scarce. There are important gaps related to projections of water resources
35 for the future. Much of the current knowledge on future changes in water resources and water scarcity and
36 flood risks is based on information from global-scale studies because studies specific to this region are
37 scarce. Several elements which are important for integrated water resource management such as water
38 quality, water demand, privatization and other economic dynamics, and nutrient, pollutant and sediment flux,
39 are poorly known currently due to missing data and insufficient efforts to monitor them.
40
41 12.7.2.4 Food, Fibre and other Ecosystem Products
42
43 Integrative evaluation on impacts on food security, including agricultural production, distribution and access,
44 leading to adaptation strategies is limited within the region. Limited information regarding cost-benefit
45 analyses of adaptation in the food production sector is available in the region. It is also important to advance
46 in a better understanding of the adaptation effects to avoid maladaptation and promote site-specific and
47 dynamic adaptation options considering available technologies. Compiling and systematizing existing
48 scientific and local knowledge on the relationship between forest, land cover/use, and hydrological services,
49 is a gap to be filled, in a broader perspective in the region, that can contribute to provide recommendations
50 and inform restoration practices and policies. The literature also highlights widespread gaps between
51 farmers' information needs and services that are routinely available. There is evidence that when Climate
52 Information Services are constructed with farmer input and are targeted in a timely and inclusive manner,
53 they are a positive determinant of adaptation through the adoption of more resilient farm level practices.
54 However, currently assessments of the economic impact of Climate Information Services are scarce; hence
55 increased frequency of such studies is needed
56
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1 12.7.2.5 Cities, Settlements and Infrastructure
2
3 Despite the high level of urbanization in the region, studies on urban adaptation initiatives are still
4 underreported by municipalities and several practical results have not yet been demonstrated (Araos et al.,
5 2016). It is particularly relevant to medium sized cities, as most of the literature and data available on
6 adaptation refers to the major capital cities. The potential of applying new resilient parameters in building
7 and land use regulation for adaptation is virtually underreported. The same can be said about the impact of
8 housing improvement and slum upgrading on climate resilience, even when initiatives are focused on
9 reducing environmental and climate risk. Also relevant in the region is a gap in research about NbS applied
10 to urban areas adaptation, as in the case of the urban forestry potential for adaptation (Barona et al., 2020).
11 Even though the importance of urban ecological infrastructure in providing ecosystem services, as flood
12 control, is reasonably documented, its practical application in urban planning in CSA is still limited
13 (Romero-Duque et al., 2020). Added to this is the lack of monitoring data on adaptation initiatives in
14 general, and in particular, on adaptation initiatives in water systems, that have already been implemented,
15 and its effects on risk reduction. Lack of monitoring data contributes to the lack of information about
16 maladaptation in urban areas and its consequences. Mobility and transport systems adaptation options are
17 virtually non-studied, while mitigation options receive a lot of attention.
18
19 12.7.2.6 Health and Wellbeing
20
21 There is a growing body of evidence that climate variability and climate change (CVC) cause harm to human
22 health in CSA. However, there is a lack of information about the current and future projected impact of CVC
23 events on overall illness and death in this region. It is challenging to attribute specific health outcomes to
24 CVC in models and field experiments due multiple factors including:
25 · lack of long-term high-quality health surveillance data
26 · multiple interacting infectious disease and chronic health issues
27 · mismatch in the spatial and temporal scales of CVC and health measurements
28 · complex climate and human system dynamics including nonlinear time-lags
29 · limited longitudinal data on non-climate factors that influence health outcomes (e.g., public health
30 interventions, migration of human populations, seasonal patterns in livelihoods).
31
32 The uncertainty inherent in predictive models also makes it challenging to expand current localized
33 knowledge on the impacts of infectious diseases associated with CVC to other regions or future climate
34 scenarios (UNEP, 2018).
35
36 Improved risk assessments based on better models and empirical research are needed to bridge the
37 knowledge gap and inform the design of adaptation strategies. A systematic multi-scalar analysis of the
38 impact of CVC on human health is needed across distinct social-ecological contexts. Data collection systems
39 need to be strengthened to accurately estimate the burden of mortality and morbidity from heat and extreme
40 events. The data deficit is a common problem in functioning civil registration and vital statistics systems,
41 including lack of information on causes of death (UNEP, 2018). In addition, there is a lack of consensus on
42 globally accepted and operational definitions for both climate-related extremes and exposures/outcomes.
43
44 For infectious disease (vector-borne and water-borne), the technology available to estimate current and
45 future risk areas is often limited by human or financial resource constraints in developing countries. There is
46 a geographical mismatch between the areas producing the technology and knowledge (in the global north),
47 and the areas most affected by CVC (in the global south). User-friendly tools that bring together climate and
48 health information--without the need for modelling or GIS expertise-- are needed for health sector decision
49 makers.
50
51 There is a lack of studies that assess the feasibility of health adaptation measures (see Section 12.5.10), thus
52 limiting the ability of decision makers to compare different health interventions and identify bottlenecks for
53 implementation. The growing field of implementation science could help to address barriers to
54 mainstreaming climate information in the health sector as an adaptation strategy.
55
56 Finally, there is an almost complete void of studies that address relationships of climate change with
57 wellbeing in CSA, broadly understood as including emotions and moods, satisfaction with life, sense of
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1 meaning, and positive functioning, including the capacity for unimpaired cognitive functioning and
2 economic productivity (Section 7.1.4.1).
3
4 12.7.2.7 Poverty, Livelihood and Sustainable Development
5
6 Climate change is becoming a major obstacle in reducing poverty and overcoming poverty traps. There is a
7 need to better understand how poor and vulnerable communities are affected and the more effective ways to
8 prevent it. The large majority of the poor in the region are living in urban areas (UNDESA, 2019); urban
9 extreme poverty is increasingly more relevant, including the needs and priorities of informal settlements and
10 economies, but less studied within the interaction with climate change. There is little reporting of major
11 adaptation options implemented by or for vulnerable and poor urban dwellers (Ryan and Bustos, 2019;
12 Berrang-Ford et al., 2021).
13
14 Adaptation options are progressively being documented for poverty-related impacts in spite of the uncertain
15 context from climate impacts not being uniform across communities and the very local scale of the type of
16 adaptation responses needed (Miranda Sara et al., 2016; Rosenzweig et al., 2018; Dodman et al., 2019).
17 There is a huge gap in understanding how the poor are responding to climate change, what is needed to
18 support them, and the interconnections between development policies, poverty and risk reduction with
19 climate change actions (Ryan and Bustos, 2019; Satterthwaite et al., 2020).
20
21 The literature to assess the effectiveness of pro-poor or low-income adaptation options continues to be weak,
22 a very small proportion show results associated with adaptation efforts (Magrin et al., 2014; Berrang-Ford et
23 al., 2021). Without this kind of approach and in depth understanding there is the risk that top down climate
24 change adaptation options could reinforce poverty cycles and neglect cultural values, even eroding them
25 (Bartlett and Satterthwaite, 2016; Walshe and Argumedo, 2016; Allen et al., 2017a; Hallegatte et al., 2018;
26 Kalikoski et al., 2018; UN-Habitat, 2018).
27
28 The impacts of climate change on vulnerable groups are still understudied. There is little or no climate data
29 on remote mountain regions of CSA as well as research measuring the vulnerability of smallholders living
30 there, making it hard to assess the expected changes or the possible adaptation measures (Pons et al., 2017;
31 Donatti et al., 2019).
32
33 12.7.2.8 Cross Cutting Issues it the Human Dimension
34
35 There is a significant number of studies addressing the impacts of climate change on the Amazon forest
36 (Brienen et al., 2015; Doughty et al., 2015; Feldpausch et al., 2016; Rammig, 2020; Sullivan et al., 2020);
37 however, the assessment of tangible and intangible impacts of climate change on Indigenous Peoples
38 cultures and livelihoods in this forest, need to be further advanced (Brondízio et al., 2016; Hoegh-Guldberg
39 et al., 2018).
40
41 Studies on the perception of climate change in rural and urban populations throughout the region have
42 increased, but there is a lack of more specific research on the perception of specific groups, such as
43 economic or political actors, that influence public institutions and policies at the local, national level and
44 regional.
45
46 While studies on climate change gender differentiated impacts have grown over the past ten years in Central
47 and South America, studies on how gender intersects with other dimensions such as race, ethnicities, age or
48 rural/urban settings are still needed. This will help to further understand how gender inequalities are
49 connected to broader power structures of societies and, thus, to produce evidence on the importance of an
50 intersectional approach to climate change.
51
52 Regarding the relation of social movements and climate change adaptation, institutions and politics, two
53 major issues stem out: youth movements for climate change and the resistances, mainly urban, to climate
54 change adaptation policies. Little connection is found in research concentrating on resistance to climate
55 change adaptation policies and their interaction with the politics of place. Conflictivity related to climate
56 change is another under-studied issue.
57
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1 Although there are several case studies on migrations and displacements caused by strong and immediate
2 climatic threats, such as hurricanes or floods, and on slow-onset impacts, such as droughts or temperature
3 increase, there are gaps in the attribution or relative weight of climate change in these processes.
4
5 Still important to note is that synergies between mitigation, adaptation, risk reduction and sustainable
6 development have not been jointly explored, which would better facilitate adaptation policy approaches.
7
8 There are critical knowledge gaps in the interlinkages between social and environmental dynamics that are
9 important for climate change adaptation, as in Andean forest landscapes. A salient knowledge gap in this
10 thematic area is the need to characterize how multilevel and multi-actor governance systems can enable
11 sustainable land management practices, including ecosystem restoration (Mathez-Stiefel et al., 2017). More
12 capacities are needed to increase the generation of relevant knowledge. Even small grant programs can
13 sustain research projects that target the linkages between knowledge and decision making at multiple scales
14 (Báez et al., 2020).
15
16
17 12.8 Conclusion
18
19 Central and South America (CSA) is a broadly heterogeneous region in its topography, ecosystems, urban
20 and rural territories, demography, economy, cultures and climates. The region relies on a strong agrarian
21 economy in which small producers and large industries participate, but also large industrialized urban
22 centres, oil production and mining. The region is one of the most urbanized of the world and home to many
23 Indigenous Peoples, some still in isolation, and exhibits one of the highest rates of inequality, which is a
24 structural and growing characteristic in CSA. Poverty and extreme poverty rates are higher among children,
25 young people, women, Indigenous Peoples, migrant and rural populations but urban extreme poverty is also
26 growing (very high confidence). Socioeconomic challenges are intensified by COVID crisis. Most countries
27 in CA are already ranked as the highest risk level worldwide due to its exposure combined to high
28 vulnerability and low adaptive capacity; the lack of climate data and proper downscaling are challenging the
29 adaptation process (high confidence).
30
31 Many extreme events are already impacting the region and projected to intensify including warming
32 temperatures and dryness, sea level rise, coastal erosion, ocean and lake acidification resulting in coral
33 bleaching, and increasing frequency and severity of droughts in some regions, with associated decrease in
34 water supply, that impact agricultural production, traditional fishing, food security and human health (high
35 confidence). In Central America (CA), 10.5 million people are living in the so-called Dry Corridor, a region
36 with an extended dry season and now more erratic rainfall patterns. A water crisis in Brazil affected the
37 major cities of the country between 2014 and 2016, becoming more frequent since then. Severe droughts
38 have also been reported in Paraguay and Argentina. In contrast, the urbanised areas of Northern South
39 America (NSA) are highly exposed to extreme floods (41% of urban population in the Amazon Delta and
40 Estuaries). Urban areas in the region are vulnerable for many reasons, notably high rates of poverty and
41 informality, poor and unevenly distributed infrastructure, housing deficits, and the recurrent occupation of
42 risk areas (high confidence).
43
44 Socio-ecological systems in the region are highly vulnerable to climate change, which acts in synergy with
45 other drivers such as land use change and deep socioeconomic inequalities. Most biodiversity-rich spots in
46 the region will be negatively impacted. The Cerrado and the Atlantic Forest (two important biodiversity-rich
47 spots where about 72% of Brazil's threatened species can be found) are exposed to different hazards
48 (extreme events, mean temperature increase) due to climate change. Many coastal areas and its concentrated
49 urban population and assets are exposed to sea level rise. Climate change is threatening several systems
50 (glaciers in the Andes, coral reefs in Central America, the Amazon forest) that are already approaching
51 critical conditions under risk of irreversible damage.
52
53 Extreme heat, droughts and floods will seriously affect CSA terrestrial and freshwater ecosystems. The high
54 poverty level increases the vulnerability to droughts, both in cities and rural areas, where people already
55 suffer from natural water scarcity (high confidence). The conversion of natural ecosystems to other land uses
56 exacerbate the adaptation challenges. Indigenous knowledge and local knowledge play an important role in
57 adaptation but are also threatened by climate change (high confidence). Ecosystem-based Adaptation (EbA)
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1 and Community-based Adaptation (CbA) have increased since AR5, with emphasis on freshwater
2 ecosystems and forests, including protected areas. Inadequate access to finance and technology are widely
3 identified as adaptation barriers (high confidence).
4
5 Many impacts in the economy are expected from climate change. Subsistence farmers and urban poor are
6 expected to be the most impacted by droughts and variable rainfall in the region (high confidence). The
7 increasing water scarcity is and will continue to impact food security, human health and well-being. The
8 impacts of the many landslides and floods affect mainly the urban poor neighbourhoods and are responsible
9 for the majority of the deaths related to natural disasters. Sea-level rise and intense storm surges are expected
10 to impact the tourism and industry in general. Internal and international migrations and displacements are
11 expected to increase (high confidence). Climatic drivers such as droughts, tropical storms and hurricanes,
12 heavy rains and floods, interact with social, political, geopolitical and economical drivers (high confidence).
13
14 The common patterns and problems, however, highlight also the possibilities for collaboration and learning
15 among the countries and institutions in the region in order to strengthen the interface between knowledge and
16 policy in climate change adaptation. All countries in the region have submitted their first and updated NDC,
17 and many have published their NAP, establishing priorities and formulating their own policies to cope with
18 climate change.
19
20 Various adaptation initiatives have been initiated in different sectors, focused on reducing poverty,
21 improving livelihood and achieving sustainable and resilient development. There is an increase in planned
22 and autonomous initiatives, led by community, government or the combination of both, engineering or
23 Nature-based Solutions (NbS). Climate smart agriculture is an effective option, in several conditions and
24 regions, to mitigate negative impacts of climate change. Disaster reduction solutions are increasingly used,
25 such as Early Warning Systems (EWS). Many and diverse initiatives are still poorly reported and evaluated
26 in the scientific literature, leading to challenges in its assessment and improvements, including the
27 consideration of the tacit Indigenous knowledge and Local Knowledge (IK and LK). The lack of climate data
28 and proper downscaling, weak governance, hindrance on financing, and inequality are constraining the
29 adaptation process (high confidence).
30
31 Adaptation measures have been increased and improved since AR5 in ocean and coastal ecosystems. The
32 majority of these measures are focused on EbA application through the application of protection and
33 recovery of already impacted ecosystems. Another battery of measures is focused on the management and
34 sustainability of marine resources subjected to fisheries, however these measures are not assessing current
35 and future climate change impacts but they are focused on decreasing the impact of other non-climate factors
36 such as overfishing or pollution. To date, along CSA there is an important lack of long-term research
37 addressing ocean and coastal ecosystems health and their species through continuous monitoring which is
38 one of the main barriers to adaptation. The number and type of adaptation measures for ocean and coastal
39 ecosystems and their contributions to humans are highly different among CSA countries which highlight in
40 number those measures related to increase the scientific research and monitoring followed by the
41 conservation of biodiversity, and changes in legislation (high confidence). On the other hand, those measures
42 that include the changes in financing (an important barrier) or the incorporation of traditional knowledge are
43 not always considered in national adaptation plans by CSA countries.
44
45 In the water sector a lack of systematic analysis and evaluation of adaptation measures prevail, although
46 important progress has been made since the AR5 in terms of understanding interlinkages between climate
47 change, human vulnerabilities, governance, policies and adaptation success (high confidence). NbS, Payment
48 for Ecosystems Services (PES), integrated water resource management, and integration of IK and LK have
49 proven potential of success, in particular if adopting approaches with inclusive negotiation formats for water
50 management with clear, just and transparent rights and responsibilities.
51
52 Climate change poses several challenges to the agri-food sector, impacting the agricultural production and
53 productivity, and posing at risk the food and nutritional security and the economy (high confidence).
54 Adapting agriculture while conserving the environment is a challenge for a sustainable and resilient food
55 production (high confidence). Adaptation in the region presents persistent barriers and limitations (Table
56 12.8), associated with investments and knowledge gaps (medium confidence). Climate change urges to
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1 advance in initiatives to improve education, technology and innovation of farming systems in the CSA
2 region.
3
4 Urban adaptation is limited by financing constraints, weak intersectoral and multilevel governance, and
5 deficits in the housing and infrastructure sectors, the overcoming of which is an opportunity for
6 transformative adaptation (high confidence). Short-term interventions are prevailing over long-term planning
7 (high confidence). Adaptation experiences in planning, land use and building regulation, urban control
8 systems and risk management have taken place throughout the region. Initiatives in social housing are
9 reducing risk, overcoming urgent deficits, but also adding to a transformative adaptation pathway (high
10 confidence). Hybrid (green-grey) infrastructure has been adopted for better efficiency in flood control,
11 sanitation, water scarcity and landslide prevention and coastal protection (high confidence). NbS including
12 green infrastructure and EbA are increasing in urban areas (high confidence), although isolated engineering
13 solutions are still widely practiced. The integration of transport and land use plans and the improvement of
14 public transport are key to urban adaptation; mitigation prevails over adaptation in the sector (high
15 confidence).
16
17 There is a growing body of evidence that climate variability and climate change are causing harm to human
18 health in CSA including the increasing transmission of vector borne and zoonotic diseases, heat stress,
19 respiratory illness associated with fires, food and water insecurity associated with drought, among others
20 (medium confidence). In response, countries in the region are developing innovative adaptation strategies to
21 inform health decision making such as integrated climate-health surveillance systems and observatories,
22 forecasting of climate-related disasters, and epidemic forecast tools. However, institutional barriers (limited
23 resources, administrative feasibility, and political mandates) need to be addressed to ensure the sustained
24 implementation of adaptation strategies (high confidence).
25
26 Poor and vulnerable groups evidence limited political influence, fewer capacities and opportunities to
27 participate in decision and policy making being less able to leverage government support to invest on
28 adaptation measures (very high confidence). Participatory processes are developing adaptation measures
29 strengthening local capacities; literature assessing the success of such initiatives remains limited. Limits to
30 adaptation include access to land, territory and resources, labour and livelihood opportunities, knowledge
31 gaps and poor multi actor coordination. Social organization, participation and governance reconfiguration are
32 essential for building climate resilience (very high confidence).
33
34 Social organization, participation, governance, education and communications to increase perception and
35 knowledge, are essential for building the resilience to adapt and overcome expected and unexpected climate
36 impacts (very high confidence). The focus on inclusion and enrolling of the full range of actors in adaptation
37 processes, including vulnerable populations, has shown good results in the region (high confidence).
38 However, existing poverty and inequality, unbalances on power relations, corruption, weak governance and
39 institutions, structural problems and high levels of risk tolerance may reinforce poverty and inequality cycles
40 (high confidence). In addition, the continued exposure of critical infrastructure and valuable assets are signs
41 of persisting maladaptation.
42
43 The development model prevailing in the region for the last decades has proven to be unsustainable, with the
44 emphasis on financial sources based on natural resource depletion and extraction and the persistence and
45 growing inequality. It is well recognized that climate adaptation measures, if carefully selected considering
46 the coupled human-environment systems, will provide significant contributions to the sustainable
47 development pathways of the region and to achieve the sustainable development goals (SDG) if implemented
48 together with comprehensive strategies to reduce poverty, inequality, and risks (high confidence). Adaptation
49 and the construction of resilience offer not only an opportunity to reduce climate change impacts, but also
50 the opportunity to reduce inequality and development gaps, to achieve dynamic economies, and to regulate
51 the sustainable use and transformation of the territory.
52
53
54 [START FAQ 12.1 HERE]
55
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1 FAQ 12.1: How are inequality and poverty limiting options to adapt to climate change in Central and
2 South America?
3
4 Poverty and inequality decrease human capacity to adapt to climate change. Limited access to resources
5 may reduce the ability of individuals, households and societies to adapt to the impacts of climate change and
6 variability because of the narrow response portfolio. Inequality limits responses available to vulnerable
7 segments as most adaptation options are resource-dependent.
8
9 Though poverty in Central and South America has decreased over the last 12 years, inequality remains as a
10 historic and structural characteristic of the region. In 2018, 29.5% of Latin America's population (including
11 Mexico) were poor (182 million) and 10.2% were extremely poor (63 million), more than half of them living
12 in urban areas. In 2020, due to COVID crisis Gini coefficient projection of increases is ranging from 1.1% to
13 7.8%, poverty increased to 33.7% (209 millions) and extreme poverty to 12.5% (78 millions).
14
15 Poor populations have little or no access to good quality education, information, health systems and financial
16 services. They have lower chances to access resources such as land and water, good quality housing, risk
17 reducing infrastructure and services such as running water, sanitation and drainage. Their lack of political
18 clout and endowments limit their access to assets for withstanding and recovering from shocks and stresses.
19 Poverty, inequality, and high vulnerability to climate change are interrelated processes. Poor populations
20 are highly vulnerable to impacts from climate change and are usually located in areas of high exposure to
21 extreme events. The constant loss of assets and livelihoods both in urban and rural areas drives communities
22 into chronic poverty traps, exacerbating local poverty cycles and creating new ones.
23
24 For instance, climaterelated reduced yields in crops, fisheries, and aquaculture have a substantial impact on
25 the livelihoods and food security of families and affect their options to cope and adapt to climate change and
26 variability. The impact of climate change in agriculture for Central and South America depends on
27 determinants such as availability of natural resources, access to markets, diversity of inputs and production
28 methods, quality and coverage of infrastructure, as well as socioeconomic characteristics of the population.
29 Impacts from climate change on smallscale farmers compromise the livelihoods and food security of rural
30 areas and consequently the food supply for urban areas.
31
32 Governments in the region have implemented several povertyreduction programs. However, policies of
33 income redistribution and poverty alleviation do not necessarily improve climate risk management, hence
34 complementary policies integrating both social and material conditions are required. A study in Northern
35 Brazil shows risk management strategies for droughts and food insecurity did not change poverty incidences
36 between 19971998 and 20112012. Major shocks, such as climate and weather extreme events (e.g., floods,
37 heavy rains, droughts, frosts), reduce and destroy public and private property. For instance, the ENSO event
38 of 2017 in Peru caused losses estimated between USD 6 to 9 billion, affected more than a million inhabitants
39 and generated 370,000 new poor. In total, losses by unemployment, deaths, destruction and damage of
40 infrastructure and houses were around 1.3% of the Gross Domestic Product of Peru.
41
42 Low public expenditure on social infrastructure (health, education etc.), ethnic discrimination and social
43 exclusion reduce healthcare access, leaving poor people in entire regions mostly undiagnosed or untreated. In
44 a context of privatization policies of health care systems, research shows marginal people lack identifying
45 documents needed to access public services in Buenos Aires (Argentina), Mexico City (Mexico) and
46 Santiago de Chile (Chile), some of the most developed cities in the region. Consequences of this situation are
47 under reporting, low diagnosis, and low treatment of diseases such as vectorborne diseases such as dengue
48 and risk of diarrheal diseases originated by frequent floods in Amazonian riverine communities. Bias on
49 reporting access to healthcare and incidence of diseases in marginal populations are usually region
50 dependent. For example, in Brazil's Amazonian North in 2018, there were 2.2 medical doctors per 1000
51 inhabitants, while 4.95 medical doctors per 1000 inhabitants in São Paulo and 9.52 doctors in Santa Catarina.
52 Another example: pregnant women in remote Amazonian municipalities receive less prenatal care than
53 women in urban areas. These social inequities underlie systemic biases in health dataquality hindering
54 reliable estimation of disease burdens such as distribution of disease or birth and death registrations. For
55 Example, in Guatemala alternative Indigenous healthcare systems are responding to local needs by Mayan
56 communities. However, this remains unrecognized. The existence of health institutions based on Indigenous
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1 knowledge can reinforce the lack of universal coverage by central government healthcare, addressing the
2 miscalculation of morbidity, mortality, and causeofdeath among disadvantaged groups.
3
4 Inequality, informality and precariousness are particularly relevant barriers for adaptation. A significant part
5 of the construction sector in the region is informal and does not follow regulations for land use and
6 construction safety codes, and there is a lack of public strategies for housing access. Adaptive construction is
7 based upon uptodate regulation and codes, appropriate design and materials, and access to infrastructure
8 and services. Decreasing inequality and eradicating poverty are crucial for achieving proper adaptation to
9 climate change in the region. Some experiences to fight poverty such as savings groups, microfinance for
10 improving housing or assets and community enterprises may also support specific adaptive measures. These
11 mechanisms should be widely accessible to poor groups and be complemented by comprehensive poverty
12 alleviation programs that include climate change adaptation.
13
14 [END FAQ 12.1 HERE]
15
16
17 [START FAQ 12.2 HERE]
18
19 FAQ 12.2: How have urban areas in Central and South America adapted to climate change so far,
20 which further actions should be considered within the next decades and what are the limits of
21 adaptation and sustainability?
22
23 Cities are becoming focal points for climate change impacts. The rapid urbanization in Central and South
24 America, together with accelerating demand for housing, resource supplies and social and health services,
25 put pressure on the already stretched physical and social infrastructure. In addition, migration is negatively
26 affecting the opportunities of cities to adapt to climate change.
27
28 Central and South America is the second most urbanized region in the world after North America with 81%
29 percent of its population being urban. 129 secondary cities with 500,000 inhabitants concentrate half of the
30 region's urban population (222 million). Another 65 million people live in megacities over 10 million each.
31 The population migrates among cities, resulting in more secondary cities and creating mega regions and
32 urban corridors.
33
34 Rapid growth in cities has increased the urban informal housing sector (e.g., slums, marginal human
35 settlements and others), which increased from 6 to 26 percent of the total residences from 1990 to 2015.
36 Coastal areas in Central and South America increasingly concentrate more urban centres. Researchers
37 indicate that between 3 to 4 million inhabitants will experience coastal flooding and erosion from sealevel
38 rise in all emission scenarios by 2100 considering Southern America alone.
39
40 A study on cities with more than 100,000 inhabitants shows the number of coastal cities significantly
41 increased from 42 to 420 between 1945 and 2014; they are located close to fragile ecosystems such as bays,
42 estuaries and mangrove forests, resulting in higher concentrations of population and economic activities.
43 This process degraded the ability of coastal ecosystems, such as mangroves, to reduce risks and provide
44 essential ecosystem services which help to prevent coastal erosion or maintain fish stocks. Moreover, it
45 reduced ports, tourism, along with income opportunities.
46
47 Climate change impacts on cities in Central and South America are strongly influenced by El Niño Southern
48 Oscillation (ENSO) associated with an increase of more extreme rainfall events. Urban areas are increasingly
49 dealing with floods, landslides, storms, tropical cyclones, water stress, fires, spread of vectorborne and
50 infectious diseases, damaging infrastructure, economic activities, built and natural environments and the
51 population's overall wellbeing.
52
53 Glacier retreat in the mountains will affect water runoff and water provision to Metropolitan cities such as
54 Lima, La Paz, Quito and Santiago who rely on rivers that originate in the high Andes. Lima, the second
55 driest capital city in the world, is vulnerable to drought and heavy rain peak events associated with climate
56 change. In Bogota lower precipitations and a tendency of increasing extreme events are expected in the
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1 coming decades. Hence, the protection of fragile ecosystems such as `paramo' (fields at 3000 to 4000
2 m.a.s.l.) will be crucial for water supply to the city.
3
4 Sea level rise impacts cities located in low elevation coastal zones, not only because of direct coastal
5 flooding, coastal erosion and subsidence; but also because it aggravates the impact of storm surges, heat
6 wave energy and saltwater intrusion. 68 percent of the population of Surinam and 31 percent of the
7 population in Guyana live below 5 meters above sea level, while many sectors of Georgetown, the capital of
8 Guyana, are below sea level. Floods with increased frequency and severity of storm surges will also impact
9 the Rio de la Plata estuary and lower delta of the Parana River where Metropolitan Buenos Aires is located.
10
11 Over 80 percent of losses associated with climate-related risks concentrate in urban areas, and between 40
12 and 70 percent losses occur in cities with less than 100,000 inhabitants, most probably as a result of limited
13 capacities to manage disaster risks and low level of investments.
14
15 Despite consistent political and economic barriers, many cities in the region have adopted sustainable local
16 development agendas, which work to address a balanced urban development. The shortcomings of poor
17 development patterns are still very present in the cities and present important obstacles to adaptation
18 investment, as public investment in basic needs (mainly housing and sanitation) must be prioritized.
19
20 Cities struggle to address the immediate needs of their population while addressing longerterm needs
21 associated with climate adaptation, emissions reduction and sustainable development. Some cities are
22 moving forward to transformative adaptation, addressing drivers of vulnerability, building robust systems
23 and anticipating impacts. Besides governmentled adaptation planning and action, individuals, communities
24 and enterprises have been incrementally adapting to climate changes autonomously over time. Municipalities
25 from Argentina, Peru, Chile, Equator, Brazil and Costa Rica are developing and implementing their Local
26 Climate Action Plans, experimenting and displaying best practices in adaptation. Both anticipatory
27 adaptation measureschoosing safe locations, building structurallysafe houses, choosing elevated places to
28 store valuables, building on stiltsand reactive adaptation measures are used; the latter incorporating
29 measures such as relocation, stabilization of slopes, afforestation, and greening of riverbanks. With
30 variations, these cities have included mechanisms to work across sectors and actors understanding it is
31 collective planning and actions, which will ensure that long term programs continue independently of
32 particular city administrations.
33
34 Cities are interconnected systems operating beyond administrative boundaries. Improved collaboration and
35 coordination is needed for integrated responses. Aside from good planning, cities need access to external
36 adaptation funds. Climate change adaptation requires longterm funding and investments, which are beyond
37 cyclical political terms. It is key to rethink how to make international adaptation funds reach cities and
38 innovate. For example, member cities of Global Covenant of Mayors in the region, together with Cities for
39 Life Forum in Peru, the Red Argentina de Municipios por el Cambio Climático (RAMCC), the Capital Cities
40 of the Americas facing Climate Change (CC35) and others, are pursuing this goal and applying directly for
41 international grants. New funding sources are required to help local governments and civil society. Cities and
42 locally driven adaptation initiatives can be funded by national governments and international organizations.
43
44 [END FAQ 12.2 HERE]
45
46
47 [START FAQ 12.3 HERE]
48
49 FAQ 12.3: How do climatic events and conditions affect migration and displacement in Central and
50 South America, will this change due to climate change, and how can communities adapt?
51
52 Migration and displacements associated with climatic hazards are becoming more frequent in Central and
53 South America, and it is expected they will continue to increase. These complex processes require
54 comprehensive actions in the places of origin and reception, both to improve adaptation in the more affected
55 places, and the conditions of the mobilizations.
56
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1 Migration of individuals, families and groups, voluntary and involuntary, is common in Central and South
2 America. People migrate nationally and internationally, temporarily or permanently, predominantly from
3 rural areas often immersed in poverty to urban areas. Common social drivers of migration in the region
4 are the economy, politics, land tenure and land management change, lack of access to markets, lack of
5 infrastructures, and violence; environmental drivers include loss of water, crops and livestock, land
6 degradation and sudden or gradual onset of climate hazards.
7
8 The increasing frequency and magnitude of droughts, tropical storms, hurricanes, and heavy rains producing
9 landslides and floods, have amplified internal movements, overall rural to urban. For instance, rural to urban
10 migration in Northern Brazil, or international migration from Guatemala, Honduras and El Salvador to North
11 America, are partly a consequence of prolonged droughts, which have increased the stress of food
12 availability in these highly impoverished regions. Diminished access to water is also a result of privatization
13 of that resource. In Central America, the majority of migrants are young men, reducing the labour force in
14 the places of origin. However, the migrants send back substantial amounts of money that have become the
15 main source of foreign exchange for their countries, and the main source of income for their families.
16
17 As poor people have less resources to adapt to changing conditions, they are usually the most impacted by
18 climate hazards, as they are already struggling to survive under normal conditions. These populations are the
19 most susceptible to migration, chiefly because of the loss of their livelihoods, their precarious housing and
20 settlements and the lack of money and international aid. Other important factors are the minimal
21 governmental support and assistance through social safety nets and extension services, the scarcity and low
22 quality of education and health services, the isolation and marginality, and the insecurity of land rights.
23 These same conditions, though, may hinder their mobility or even render them immobile. Nevertheless, in
24 some cases, despite worsening conditions, people decide not to move.
25
26 The magnitude and frequency of droughts and hurricanes are projected to keep increasing by 2050, which
27 may force millions of people to leave their homes. Climate models show some dry regions will become even
28 dryer in the coming decades, increasing the stress on small farmers who rely on rainfall to water their fields.
29 Glacier retreat and water scarcity are becoming strong drivers of migration in the Andes. Sea level rise
30 influences activities such as fishing and tourism, which will foster further migration. In Brazil, at least 0.9
31 million more people will migrate interregionally under future climate conditions.
32
33 Addressing migration and displacement requires diverse interventions: in dry regions it is recommended to
34 improve the water management in the places of origin of migration, including storage, distribution and
35 irrigation. Wet regions, lowlands, and floodplains will benefit from preventing construction on areas prone to
36 landslides and flooding. Government and international aid are also important for improving people's options
37 to adapt and enhance their resilience to climate impacts. In northern Brazil, for example, government
38 financial support has significantly reduced the migration caused by droughts. Between Guatemala and
39 Canada there is a temporary migration program to bring in migrant workforce during the harvest season. The
40 United States is also increasing these types of legal temporary migration.
41
42 [END FAQ 12.3 HERE]
43
44
45 [START FAQ 12.4 HERE]
46
47 FAQ 12.4: How is climate change impacting and expected to impact food production in Central and
48 South America in the next 30 years and what effective adaptation strategies are and can be
49 adopted in the region?
50
51 Agriculture is a fundamental sector to the development of societies from the economic and social
52 perspectives, and so it is a major component of the adaptive strategies for Central and South America
53 countries. Implementation of sustainable agriculture practices such as improved management on native
54 grasslands or agroforestry systems for crop and livestock production, can increase productivity while
55 improving adaptability.
56
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1 Over the last two decades, countries throughout Central and South America have been developing rapidly.
2 The agriculture sector is fundamental to this development from economic and social perspectives. Some
3 countries of the region are amongst major food exporters in the world:
4 · Corn: three of the top ten exporters are Brazil, Argentina and Paraguay;
5 · Soybean exports: Brazil and Argentina are among the top five; Paraguay and Bolivia figure within
6 the twelfth;
7 · Coffee exports: five of the top ten export countries are Brazil, Colombia, Honduras, Peru and
8 Guatemala;
9 · Fruits: two of the top 10 fresh fruit export countries are Chile and Ecuador,
10 · Fishmeal exports globally are led by Peru, Chile and Ecuador;
11 · Beef: four of the top exporting countries are from this region Brazil, Argentina, Uruguay and
12 Paraguay.
13
14 CSA is one of the regions with the highest potential to increase food supplies particularly to more densely
15 populated regions in Asia, Middle East and Europe. Better understanding the impact of the economy on the
16 environment and the contribution of the environment to the economy, is critical to identify opportunities for
17 innovation and promoting activities that could lead to sustainable economic growth without depleting natural
18 resources and increasing sensitivity to climate change and climate variability. The consideration of food as
19 a commodity instead of a common resource, leads to the accumulation of under-priced food
20 resources at the expense of natural capital. Without serious emissions reduction measures, climate
21 models project an average 1 to 4°C increase in maximum temperatures, and a 30 percent decrease in rainfall
22 towards 2050, across Central and South America. Tropical South America is projected to warm at higher
23 rates than the southern part of South America. Given these circumstances, some regions in Central and South
24 America (Andes region and Central America) will just meet, or fall below, the critical food supply/demand
25 ratio for their population. Meanwhile, the more temperate part of South America in the south is projected to
26 have agricultural production surplus. The challenge for this region will be to retain the ability to feed and
27 adequately nourish its internal population as well as making an important contribution to the food supplies
28 available to the rest of the world.
29
30 The Nationally Determined Contributions (NDCs) of most of the countries of Central and South America
31 expressly included agriculture as a major component of their adaptive strategy. From the recommendations
32 presented, five general adaptive themes, or imperatives, emerge: 1) inclusion of climate change projections
33 as a key element for Ministries of Agriculture and research institutes in their decision-making processes; 2)
34 support research and adoption of drought- and heat-tolerant crop varieties; 3) promotion of sustainable
35 irrigation as an effective adaptive strategy; 4) recovery of degraded lands and sustainable intensification of
36 agriculture to prevent further deforestation; and 5) implementation of climate smart practices and
37 technologies to increase productivity while improving adaptability.
38
39 Climate smart-practices provide a framework to operationalize actions aimed at understanding synergies
40 among productivity, adaptation and mitigation. Significant amount of evidence supports the potential for
41 climate smart-practices technologies to produce such triple wins as natural pastoral systems in the southern
42 region of South America. Such systems allow the combination of food production and environmental
43 sustainability. The production of meat based on native grasslands with grazing management that optimizes
44 forage allowance can achieve high production levels, while providing multiple ecosystem benefits. Optimal
45 forage allowance means offering the animals enough forage in order to meet requirements and while
46 avoiding overgrazing. This management practice simultaneously increases productivity, reduces greenhouse
47 gas emissions while improving soil carbon sequestration, and minimizes other environmental impacts such
48 as excess of nutrients, fossil energy use, and biodiversity loss. Pastoral farming systems that manage grazing
49 and feeding efficiently, are an example of integration between food security, environmental conservation and
50 nature-based adaptation to climate change.
51
52 Agroforestry systems are present in the tropical region of Central and Southern America. Trees are present in
53 a large part of the agricultural landscape of this region, either dispersed or in lines; supporting the production
54 of coffee, cocoa, fruits, pastures and livestock in various agroforestry configurations. In Central America,
55 shade-grown coffee reduces weed control and improves quality and taste of the product. Agroforestry uses
56 nitrogen-fixing trees (Leguminosae), such as Leucaena in Colombia, Inga in Brazil, to restore soil nitrogen
57 fertility. Tropical forest soils are generally nutrient-poor and unsuited to long-term agricultural use. Land
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1 converted to agriculture by cutting and burning natural vegetation tends to remain productive for only a few
2 years. Agroforestry and the so called silvopastoral systems, which incorporate trees into crop and livestock
3 systems, have been shown to make a dramatic impact on the maintenance and restoration of long term
4 productivity in agricultural landscapes, including degraded and abandoned land. Agroforestry systems can
5 provide major benefits through enhanced food security, stronger local economies, and increased ecosystem
6 services such as carbon storage, regulation of climate and water cycles, control of pests and diseases, and
7 maintenance of soil fertility. Because of these multiple goods and services, agroforestry practices are
8 considered one of the key strategies for the development of climate smart agriculture.
9
10 [END FAQ 12.4 HERE]
11
12
13 [START FAQ 12.5 HERE]
14
15 FAQ 12.5: How can Indigenous knowledge and practices contribute to adaptation initiatives in
16 Central and South America?
17
18 Indigenous Peoples have knowledge systems and practices that allow them to adapt to many climatic
19 changes. Adaptation initiatives based on Indigenous knowledge and practices are more sustainable and
20 legitimate among local communities. It is important to build effective and respectful partnerships among
21 Indigenous and nonindigenous researchers to coproduce climate relevant knowledge to enhance
22 adaptation planning and action in the region.
23
24 There are 28 million Indigenous Peoples in Central and South America (around 6.6% of the whole
25 population of the region). They belong to more than 800 groups living in territories covering a wide range of
26 ecosystems from drylands to tropical forests to savannahs, coasts to mountains and that share the land
27 with many other cultural and ethnic groups. In the region, Indigenous Peoples are often categorized as a
28 group highly vulnerable to climate change as they are frequently affected by socioeconomic inequalities and
29 the dominance by external powers. They often experience internal and external pressures over their
30 communal lands in forms of pollution, oil and mining, industrial agriculture, and urbanization. On the other
31 hand, it is important to recognize that Indigenous Peoples have knowledge systems and practices that allow
32 them to adapt to many climatic changes. Increasing scientific evidence shows that adaptation initiatives
33 based on Indigenous knowledge and practices are more sustainable and legitimate among local communities.
34
35 The wide range of adaptation practices based on Indigenous knowledge in the region include, among others:
36 increasing species and genetic diversity in agricultural systems through community seed exchanges;
37 promotion of highly diverse crop systems; ancient systems to collect and conserve water; fire prevention
38 strategies; observing and monitoring changes in communal ecologicalagricultural calendar cycles;
39 recognizing changes in ecological indicators like migration patterns in birds, behaviour of insects and other
40 invertebrates and phenology of fruit and flowering species; and systematization and knowledge exchange
41 among communities. These practices represent a valuable cultural and biological heritage.
42
43 The Kichwa in the Ecuadorian Amazon cultivate Chakras (plots) within the rainforest. These plots combine
44 crops and medicinal herbs for both selfconsumption and selling. Similar systems, like the Chakras in the
45 high Andes, the Milpas in Central America, and the Conucos in northern South America have been resilient
46 to social and environmental disturbances due to their outstanding agrobiodiversity (more than 40 species and
47 varieties can be present in one plot), microhabitat management and the associated knowledge and
48 institutions.
49
50 Traditional fire management among Indigenous Peoples of Venezuela, Brazil and Guyana is another
51 adaptation strategy based on a finetuned understanding of environmental indicators, associated with their
52 culture and worldviews. In these countries, Indigenous lands have the lowest incidence of wildfires,
53 significantly contributing to maintaining and enhancing biodiversity. These traditional practices have helped
54 to prevent largescale and destructive wildfires, reducing the risk from rising temperature and dryness due to
55 climate change.
56
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1 Traditional agriculture of Mapuche Indigenous Peoples in Chile includes a series of practices that result in a
2 system more resilient to climate and nonclimate stressors. Practices include water management, native seed
3 conservation and exchange with other producers (trafkintu), crop rotation, polyculture, and treecrop
4 association. Similar practices can be found in Mayan communities in Guatemala at the other end of the
5 subcontinent.
6
7 Despite the increasing recognition and integration of Indigenous knowledge in adaptation practices and
8 policies in the region, important barriers for a more effective and transformative integration remain. Some of
9 the most relevant barriers include limited participation of Indigenous Peoples and local communities in
10 adaptation planning and the lack of sufficient consideration of nonclimatic socioeconomic drivers of
11 vulnerability such as poverty and inequality. Also, scientific knowledge is commonly prioritized over
12 traditional, Indigenous knowledge, and local knowledge. However, some transformative efforts are emerging
13 Bolivian Indigenous organizations provide a notable example by contesting normative conceptions of
14 development as economic growth with more comprehensive views like harmony with Mother Earth and
15 "Sumak Kawsay" or "Good Living".
16
17 Several strategies have been proposed to overcome existing barriers, including building effective and
18 respectful partnerships among Indigenous and nonindigenous researchers to coproduce climate change
19 relevant knowledge, and recognizing Indigenous Peoples as active actors who are continually developing
20 autonomous strategies to preserve their practices, beliefs and knowledge. The implementation of these and
21 other strategies can significantly enhance adaptation planning and action in the region.
22
23 [END FAQ 12.5 HERE]
24
25
26
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