Editing IPCC:AR6/WGII/Chapter-12 (section)

=== 12.3.7 Southwestern South America Sub-region ===

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==== 12.3.7.1 Hazards ====

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Significant increases in the intensity and frequency of hot extremes and significant decreases in the intensity and frequency of cold extremes have ''likely'' been observed for the region (Skansi et al., 2013; [[#Ceccherini--2016|Ceccherini et al., 2016]] ; [[#Meseguer-Ruiz--2018|Meseguer-Ruiz et al., 2018]] ; [[#Vicente-Serrano--2018|Vicente-Serrano et al., 2018]] ; [[#Dereczynski--2020|Dereczynski et al., 2020]] ; [[#Dunn--2020|Dunn et al., 2020]] ; [[#Olmo--2020|Olmo et al., 2020]] ) (WGI AR6 Table 11.13) ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ). In particular, a significant increment in the duration and frequency of heatwaves mainly in central Chile from 1961 to 2016 has been observed ( [[#Piticar--2018|Piticar, 2018]] ).

A robust drying trend for Chile (30°S–48°S) has been recorded ( ''medium confidence'' ) ( [[#Saurral--2017|Saurral et al., 2017]] ; [[#Boisier--2018|Boisier et al., 2018]] ) ''.'' However, inconsistent trends over the region in the magnitude of precipitation extremes with both decreases and increases ( [[#Chou--2014|Chou et al., 2014]] ; [[#Giorgi--2014|Giorgi et al., 2014]] ; [[#Heidinger--2018|Heidinger et al., 2018]] ; [[#Meseguer-Ruiz--2018|Meseguer-Ruiz et al., 2018]] ) (WGI AR6 Table 11.14) ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ) have been observed ( ''low confidence'' ). The glacier equilibrium line altitude has presented an overall increase over central Chilean Andes ( [[#Barria--2019|Barria et al., 2019]] ).

For central Chile, a significant increase (5% to 20% in the last 60 years) in wave heights in the sea has been observed ( [[#Martínez--2018|Martínez et al., 2018]] ). From 1982 to 2016, sea levels at central Chile have increased 5 mm yr −1 , where El Niño events of 1982–1983 and 1997–1998 caused an extreme increase of 15 to 20 cm in the mean sea level ( [[#Campos-Caba--2016|Campos-Caba, 2016]] ; [[#Martínez--2018|Martínez et al., 2018]] ).

From 1946 to 2017, the number of fires and areas burned have increased significantly in Chile ( ''high confidence'' ) ( [[#González--2011|González et al., 2011]] ; [[#Jolly--2015|Jolly et al., 2015]] ; [[#Úbeda--2016|Úbeda and Sarricolea, 2016]] ; [[#de%20la%20Barrera--2018|de la Barrera et al., 2018]] ; [[#Urrutia-Jalabert--2018|Urrutia-Jalabert et al., 2018]] ). Fires are attributed to changes in temperature regimes ( [[#González--2011|González et al., 2011]] ; [[#de%20la%20Barrera--2018|de la Barrera et al., 2018]] ; [[#Gómez-González--2018|Gómez-González et al., 2018]] ) and precipitation regimes ( ''medium confidence'' ) ( [[#Gómez-González--2018|Gómez-González et al., 2018]] ; [[#Urrutia-Jalabert--2018|Urrutia-Jalabert et al., 2018]] ).

The glaciers of the southern Andes (including the SWS and SSA regions) show the highest glacier mass loss rates worldwide ( ''high confidence'' ) contributing to SLR ( [[#Jacob--2012|Jacob et al., 2012]] ; [[#Gardner--2013|Gardner et al., 2013]] ; [[#Dussaillant--2018|Dussaillant et al., 2018]] ; [[#Braun--2019|Braun et al., 2019]] ; [[#Zemp--2019|Zemp et al., 2019]] ). Since 1985, the glacier area loss in the sub-region is in a range of 20 up to 60% ( [[#Braun--2019|Braun et al., 2019]] ; [[#Reinthaler--2019b|Reinthaler et al., 2019b]] ).

Four sets of downscaling simulations based on the Eta Regional Climate Model forced by two global climate models ( [[#Chou--2014|Chou et al., 2014]] ) projected warmer conditions (more than 1°C) for the entire sub-region by 2050 under the RCP4.5 scenario ( ''medium confidence'' ). Extremely warm December–January–February days as well as the number of heatwaves per season are expected to increase by 5–10 times in northern Chile ( [[#Feron--2019|Feron et al., 2019]] ), ''likely'' increasing in the intensity and frequency of hot extremes over the entire region (WGI AR6 Table 11.13) ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ). Drier conditions ( ''medium confidence'' ), by means of a decrease in total annual and extreme precipitation, are expected to increase for southern Chile, but inconsistent changes are expected in the sub-region ( ''low confidence'' ) ( [[#Chou--2014|Chou et al., 2014]] ) (WGI AR6 Table 11.14) ( [[#Seneviratne--2021|Seneviratne et al., 2021]] ) with ''high confidence'' upon an increase in fire weather and a decrease in permafrost and snow extent (WGI AR6 Table 12.6, [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ).

Regional sea-level change for the region predicted by 2100 shows that total mean SLR along the coast will lie between 34 and 52 cm for the RCP4.5 scenario and between 46 and 74 cm for the RCP8.5 scenario with ''high confidence'' ( [[#Albrecht--2016|Albrecht and Shaffer, 2016]] ; WGI AR6 Table 12.6, [[#Ranasinghe--2021|Ranasinghe et al., 2021]] ).

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==== 12.3.7.2 Exposure ====

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There is ''high confidence'' that age and socioeconomic status are key factors determining health exposure and quality of life in SWS, where low-income areas show an insufficient number of public spaces to provide acceptable environmental quality in comparison with the high-income areas ( [[#Romero-Lankao--2013|Romero-Lankao et al., 2013]] ; [[#Fernández--2016|Fernández and Wu, 2016]] ; [[#Paz--2016|Paz et al., 2016]] ; [[#Hystad--2019|Hystad et al., 2019]] ; [[#Smith--2019|Smith and Henríquez, 2019]] ; [[#Jaime--2020|Jaime et al., 2020]] ; [[#Pino-Cortés--2020|Pino-Cortés et al., 2020]] ).

Profound social inequalities, urban expansion and inadequate city planning (e.g., drainage network) increase exposure to flooding events and landslides ( ''high confidence'' ) ( [[#Müller--2014|Müller and Höfer, 2014]] ; [[#Rojas--2017|Rojas et al., 2017]] ; [[#Lara--2018|Lara et al., 2018]] ), heat hazards such as heatwaves ( ''high confidence'' ) ( [[#Welz--2014|Welz et al., 2014]] ; [[#Qin--2015|Qin et al., 2015]] ; [[#Inostroza--2016|Inostroza et al., 2016]] ; [[#Welz--2016|Welz and Krellenberg, 2016]] ; [[#Krellenberg--2017|Krellenberg and Welz, 2017]] ) and the loss and fragmentation of green infrastructure (GI) ( [[#Hernández-Moreno--2018|Hernández-Moreno and Reyes-Paecke, 2018]] ). SWS cities show the highest levels of air pollution of CSA ( ''medium confidence: medium evidence'' , ''high agreement'' ) ( [[#Pino--2015|Pino et al., 2015]] ; [[#Huneeus--2020|Huneeus et al., 2020]] ; [[#González-Rojas--2021|González-Rojas et al., 2021]] ), where state air quality alerts have limited effect on protective health behaviours, since public perceptions about air pollution vary widely among the population ( [[#Boso--2019|Boso et al., 2019]] ). In particular, human communities living in coastal cities show a negative safety perception about the performance of the infrastructure and coastal defences to flood events ( ''low confidence'' ) ( [[#González--2017|González and Holtmann-Ahumada, 2017]] ; [[#Igualt--2019|Igualt et al., 2019]] ).

Although climate change is critically important for the current and future status of mining activity in SWS ( [[#Odell--2018|Odell et al., 2018]] ), and SWS areas subjected to mining activities are highly exposed to water risk ( [[#Northey--2017|Northey et al., 2017]] ), to date there is ''low evidence'' of climate change impacting mining activities ( [[#Corzo--2018|Corzo and Gamboa, 2018]] ; [[#Odell--2018|Odell et al., 2018]] ).

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==== 12.3.7.3 Vulnerability ====

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Rapid changes in temperature and precipitation regimes make terrestrial ecosystems highly vulnerable to climate change ( ''high confidence'' ) ( [[#Salas--2016|Salas et al., 2016]] ; [[#Fuentes-Castillo--2020|Fuentes-Castillo et al., 2020]] ) (Figure 12.7). Terrestrial ecosystems dominated by exotic species (e.g., pine) with lower landscape heterogeneity and degraded soils and that are close to settlements and roads are highly vulnerable to wildfires in comparison to forests dominated by native trees ( ''high confidence'' ) ( [[#Altamirano--2013|Altamirano et al., 2013]] ; [[#Castillo-Soto--2013|Castillo-Soto et al., 2013]] ; [[#Cóbar-Carranza--2014|Cóbar-Carranza et al., 2014]] ; [[#Salas--2016|Salas et al., 2016]] ; [[#Bañales-Seguel--2018|Bañales-Seguel et al., 2018]] ; [[#Gómez-González--2018|Gómez-González et al., 2018]] ; [[#Sarricolea--2020|Sarricolea et al., 2020]] ). Changes in land use, artificial forestation, deforestation, agricultural abandonment and urbanisation have provoked a permanent degradation of old-growth forests, putting at risk the biodiversity, recreation and ecotourism ( ''medium confidence: medium evidence, high agreement'' ) ( [[#Rojas--2013|Rojas et al., 2013]] ; [[#Nahuelhual--2014|Nahuelhual et al., 2014]] ). Marine coastal ecosystems such as dunes, sandy beaches and wetlands show high deterioration, decreasing their ability to mitigate extreme events ( ''medium confidence: low evidence'' , ''high agreement'' ) ( [[#González--2017|González and Holtmann-Ahumada, 2017]] ; [[#Ministerio%20de%20Medio%20Ambiente%20de%20Chile--2019|Ministerio de Medio Ambiente de Chile, 2019]] ).

The water sector shows a very high vulnerability ( ''high confidence'' ) (Figure 12.7) mainly due to weak water governance focused on market aspects (e.g., inter-sectoral water transactions, setting rates, granting concessions, waiving the water right) ( ''high confidence'' ) ( [[#Hurlbert--2013|Hurlbert and Diaz, 2013]] ; [[#Valdés-Pineda--2014|Valdés-Pineda et al., 2014]] ; [[#Barría--2019|Barría et al., 2019]] ; [[#Hurlbert--2019|Hurlbert and Gupta, 2019]] ; [[#Muñoz--2020a|Muñoz et al., 2020a]] ; [[#Urquiza--2020b|Urquiza and Billi, 2020b]] ). Potable water and adequate sanitation are available in SWS; however, water availability in Chile is unevenly distributed in rural communities ( ''high confidence'' ) ( [[#Valdés-Pineda--2014|Valdés-Pineda et al., 2014]] ; [[#Nelson-Nuñez--2019|Nelson-Nuñez et al., 2019]] ). Spatial differences in water availability are enhanced by strong population growth, economic development, mining activities and the high dependence of agriculture on irrigation ( ''high confidence'' ) ( [[#Stathatou--2016|Stathatou et al., 2016]] ; [[#Northey--2017|Northey et al., 2017]] ; [[#Fercovic--2019|Fercovic et al., 2019]] ). Droughts in SWS are a major threat to water security ( ''high confidence'' ) ( [[#Aitken--2016|Aitken et al., 2016]] ; [[#Núñez--2017|Núñez et al., 2017]] ) as river streamflows are highly dependent on the interannual to decadal climate conditions, snow melting processes and rainfall events ( [[#Boisier--2016|Boisier et al., 2016]] ) and impacted by land uses and changes in irrigated agriculture ( ''medium confidence: medium evidence, high agreement'' ) ( [[#Vicuña--2013|Vicuña et al., 2013]] ; [[#Fuentes--2021|Fuentes et al., 2021]] ).

Energy and water needs of large-scale mining activities make this socioeconomic sector particularly vulnerable to climate change; additionally, the relative lack of power of resource-poor communities living in areas where such mining makes claims on water and energy resources renders these communities even more vulnerable ( [[#Odell--2018|Odell et al., 2018]] ). Given new conditions generated by changes in a growing demand and climate change, mining companies will need to increase resilience to extreme events; additionally, the declining concentrations of minerals of interest in raw materials require greater energy input for extraction and processing and new methods to avoid associated emissions are required ( [[#Hodgkinson--2018|Hodgkinson and Smith, 2018]] ).

Urban and agriculture sectors are vulnerable to climate change ( ''medium confidence: medium evidence, high agreement'' ) (Figure 12.7), increasing problems and demand for water ( ''high confidence'' ) ( [[#Monsalves-Gavilán--2013|Monsalves-Gavilán et al., 2013]] ; [[#Meza--2014|Meza et al., 2014]] ; [[#Fercovic--2019|Fercovic et al., 2019]] ). Important health problems (e.g., pathogenic infections, changes in vector-borne diseases, heat-related mortality, lower neurobehavioural performance) have been associated with agriculture, mining and thermal power production activities in SWS ( ''high confidence'' ) ( [[#Muñoz-Zanzi--2014|Muñoz-Zanzi et al., 2014]] ; [[#Valdés-Pineda--2014|Valdés-Pineda et al., 2014]] ; [[#Pino--2015|Pino et al., 2015]] ; [[#Cortés--2016|Cortés, 2016]] ; [[#Berasaluce--2019|Berasaluce et al., 2019]] ; [[#Muñoz--2019a|Muñoz et al., 2019a]] ; [[#Ramírez-Santana--2020|Ramírez-Santana et al., 2020]] ).

Large-scale agricultural growth has increased vulnerability to climate change by disfavouring traditional agriculture, the homogenisation of the biophysical landscape and the replacement of traditional crops and native forests with exotic species like pines and eucalyptus ( ''high confidence'' ) ( [[#Torres--2015|Torres et al., 2015]] ), where farmers’ perceptions of climate change are highly dependent on educational level and access to meteorological information ( ''low confidence'' ) ( [[#Roco--2015|Roco et al., 2015]] ). Agricultural systems owned by Indigenous Peoples (i.e., Mapuche, Quechua and Aymara farmers) seem to pose a lower level of vulnerability to drought and higher response capacity than non-Indigenous farmers thanks to the use of the traditional knowledge of specific management techniques and the tendency to conserve species or varieties of crops tolerant to water scarcity ( ''low confidence'' ) ( [[#Montalba--2015|Montalba et al., 2015]] ; [[#Saylor--2017|Saylor et al., 2017]] ; [[#Meldrum--2018|Meldrum et al., 2018]] ). Fishery- and aquaculture-related livelihoods are vulnerable to climate and non-climate drivers ( ''medium confidence: medium evidence, high agreement'' ), such as sea surface warming and precipitation reduction ( [[#Handisyde--2017|Handisyde et al., 2017]] ; [[#Soto--2019|Soto et al., 2019]] ; [[#González--2021|González et al., 2021]] ), changes in upwelling intensity ( ''low confidence'' ) ( [[#Oyarzún--2019|Oyarzún and Brierley, 2019]] ; [[#Ramajo--2020|Ramajo et al., 2020]] ), eutrophication and harmful algal bloom (HAB) events ( [[#Almanza--2019|Almanza et al., 2019]] ), a lack of observational elements and data management ( [[#Garçon--2019|Garçon et al., 2019]] ) and events such as earthquakes and tsunamis ( [[#Marín--2019|Marín, 2019]] ).

Chile has experienced accelerated economic growth, which has reduced poverty; however, important geographical, economic and educational inequalities remain ( [[#Repetto--2016|Repetto, 2016]] ). The Chilean healthcare system has become more equitable and responsive to the population’s needs (e.g., the Bono AUGE healthcare reform programme); however, the high relative inequalities in terms of income ( [[#OECD--2018|OECD, 2018]] ), education level and rural–urban factors are determinants of quality of care, health system barriers and differential access to healthcare ( ''high confidence'' ) ( [[#Frenz--2014|Frenz et al., 2014]] ). Exposure and vulnerability to psychosocial risks in SWS show significant inequalities in times of disasters such as earthquakes according to socioeconomic, geographic and gender factors ( ''high confidence'' ) ( [[#Labra--2002|Labra, 2002]] ; [[#Vitriol--2014|Vitriol et al., 2014]] ; [[#Quijada--2018|Quijada et al., 2018]] ), which are increased by the absence of local planning and drills and the lack of coordination ( [[#Vitriol--2014|Vitriol et al., 2014]] ). Indigenous Peoples have the highest levels of vulnerability in Chile in terms of income, basic needs and access to services to climate change ( ''low confidence'' ) ( [[#Parraguez-Vergara--2016|Parraguez-Vergara et al., 2016]] ).

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==== 12.3.7.4 Impacts ====

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Increasing temperatures in SWS have impacted temperate forests ( ''high confidence'' ) ( [[#Peña--2014|Peña et al., 2014]] ; [[#Urrutia-Jalabert--2015|Urrutia-Jalabert et al., 2015]] ; [[#Camarero--2017|Camarero and Fajardo, 2017]] ; [[#Fontúrbel--2018|Fontúrbel et al., 2018]] ; [[#Venegas-González--2018b|Venegas-González et al., 2018b]] ; [[#Peña-Guerrero--2020|Peña-Guerrero et al., 2020]] ). Increasing temperatures and decreasing precipitation have increased the impacts of wildfires on terrestrial ecosystems ( ''high confidence'' ) ( [[#Boisier--2016|Boisier et al., 2016]] ; [[#Díaz-Hormazábal--2016|Díaz-Hormazábal and González, 2016]] ; [[#Martinez-Harms--2017|Martinez-Harms et al., 2017]] ; [[#de%20la%20Barrera--2018|de la Barrera et al., 2018]] ; [[#Gómez-González--2018|Gómez-González et al., 2018]] ; [[#Urrutia--2018|Urrutia et al., 2018]] ; [[#Bowman--2019|Bowman et al., 2019]] ), creating conditions for future landslides and floods ( [[#de%20la%20Barrera--2018|de la Barrera et al., 2018]] ).

Future projections show important changes in the productivity, structure and biogeochemical cycles of SWS temperate and rainforests ( ''medium confidence: medium evidence, high agreement'' ) ( [[#Gutiérrez--2014|Gutiérrez et al., 2014]] ; [[#Correa-Araneda--2020|Correa-Araneda et al., 2020]] ) and their fauna ( ''low confidence'' ) ( [[#Glade--2016|Glade et al., 2016]] ; [[#Bourke--2018|Bourke et al., 2018]] ). The Chilean Winter Rainfall-Valdivian Forests are a biodiversity hotspot ( [[#Manes--2021|Manes et al., 2021]] ) (Section [https://www.ipcc.ch/chapter/12#CCP1.2.2 CCP1.2.2] ) projected to suffer habitat change, with loss of vegetation cover in the future due to climate change ( ''medium confidence: medium evidence, high agreement'' ) ( [[#Jantz--2015|Jantz et al., 2015]] ; [[#Mantyka-Pringle--2015|Mantyka-Pringle et al., 2015]] ). Species are projected to suffer changes in their distribution, including a decrease in climatic refugia for vertebrates ( ''low confidence'' ) ( [[#Cuyckens--2015|Cuyckens et al., 2015]] ; [[#Warren--2018|Warren et al., 2018]] ).

Increasing temperatures have enlarged the number and areal extent of glacier lakes in the central Andes, northern Patagonia and southern Patagonia ( ''high confidence'' ) ( [[#Wilson--2018|Wilson et al., 2018]] ), while decreased rainfall and rapid glacier melting have provoked changes in the environmental, biogeochemical and biological properties of central-southern and Andes Chilean lakes ( ''low confidence'' ) ( [[#Pizarro--2016|Pizarro et al., 2016]] ).

Increasing glacier lake outburst floods (GLOFs), ice and rock avalanches, debris flows and lahars from ice-capped volcanoes have been observed in SWS ( [[#Iribarren%20Anacona--2015|Iribarren Anacona et al., 2015]] ; [[#Jacquet--2017|Jacquet et al., 2017]] ; [[#Reinthaler--2019b|Reinthaler et al., 2019b]] ). There is ''low evidence'' on the effects of warming and degrading permafrost on slope instability and landslides in these regions ( [[#Iribarren%20Anacona--2015|Iribarren Anacona et al., 2015]] ).

Increasing temperatures, decreasing precipitation regimes and an unprecedented long-term drought have decreased the annual average river streamflows that supply SWS megacities such as Santiago ( ''high confidence'' ) ( [[#Meza--2014|Meza et al., 2014]] ; [[#Muñoz--2020a|Muñoz et al., 2020a]] ), with important and negative effects on water quality ( [[#Bocchiola--2018|Bocchiola et al., 2018]] ; [[#Yevenes--2018|Yevenes et al., 2018]] ), threatening irrigated agriculture activities ( ''medium confidence: medium evidence, high agreement'' ) ( [[#Yevenes--2018|Yevenes et al., 2018]] ; [[#Oertel--2020|Oertel et al., 2020]] ; [[#Peña-Guerrero--2020|Peña-Guerrero et al., 2020]] ). Large reductions in the availability of groundwater in the SWS region ( [[#Meza--2014|Meza et al., 2014]] ) and a sustained decrease in the mean annual flows ( [[#Ragettli--2016|Ragettli et al., 2016]] ; [[#Bocchiola--2018|Bocchiola et al., 2018]] ), especially during the snowmelt season (Vargas et al., 2013), have been observed in SWS. Drought has affected wetlands ( ''low confidence'' ) ( [[#Zhao--2016|Zhao et al., 2016]] ; [[#Domic--2018|Domic et al., 2018]] ) and desert ecosystems ( ''medium confidence: medium evidence, high agreement)'' ( [[#Acosta-Jamett--2016|Acosta-Jamett et al., 2016]] ; [[#Neilson--2017|Neilson et al., 2017]] ; [[#Díaz--2019|Díaz et al., 2019]] ).

There is ''low evidence'' on shoreline retreat attributed to climate change ( [[#Martínez--2018|Martínez et al., 2018]] ; [[#Ministerio%20de%20Medio%20Ambiente%20de%20Chile--2019|Ministerio de Medio Ambiente de Chile, 2019]] ), although increasing wind intensity along the central Chilean coast has caused serious damage in coastal infrastructure and buildings ( [[#Winckler--2017|Winckler et al., 2017]] ) and changes in seawater properties and processes ( ''low confidence'' ) ( [[#Schneider--2017|Schneider et al., 2017]] ; [[#Aguirre--2018|Aguirre et al., 2018]] ). Ocean and coastal ecosystems in SWS are sensitive to upwelling intensity, which affects the abundance, diversity, physiology and survivorship of coastal species ( ''high confidence'' ) ( [[#Anabalón--2016|Anabalón et al., 2016]] ; [[#Jacob--2018|Jacob et al., 2018]] ; [[#Ramajo--2020|Ramajo et al., 2020]] ) (Figure 12.8). Increasing radiation and temperatures and reduced precipitation, in conjunction with increased nutrient load, have increased HAB events, producing massive fauna mortalities ( ''high confidence'' ) ( [[#León-Muñoz--2018|León-Muñoz et al., 2018]] ; [[#IPCC--2019b|IPCC, 2019b]] , SPM A8.2 and B8.3; [[#Quiñones--2019|Quiñones et al., 2019]] ; [[#Soto--2019|Soto et al., 2019]] ; [[#Armijo--2020|Armijo et al., 2020]] ). Multiple resources subjected to fisheries and aquaculture are highly vulnerable to storms, alluvial disasters, ocean warming, ocean acidification, increasing ENSO extreme events and lower oxygen availability ( ''high confidence'' ) (Figure 12.8; [[#García-Reyes--2015|García-Reyes et al., 2015]] ; [[#Silva--2015|Silva et al., 2015]] ; [[#Duarte--2016|Duarte et al., 2016]] , 2018; [[#Lagos--2016|Lagos et al., 2016]] ; [[#Navarro--2016|Navarro et al., 2016]] ; [[#Lardies--2017|Lardies et al., 2017]] ; [[#IPCC--2019b|IPCC, 2019b]] ; [[#Mellado--2019|Mellado et al., 2019]] ; [[#Ramajo--2019|Ramajo et al., 2019]] ; [[#Silva--2019a|Silva et al., 2019a]] ; [[#Bertrand--2020|Bertrand et al., 2020]] ). Ocean and coastal ecosystems, especially EEZs, will be highly impacted by climate change in the near and long term ( ''high confidence'' ) (Figure 12.8; Table SM12.3; [[#Silva--2015|Silva et al., 2015]] ; [[#Silva--2019a|Silva et al., 2019a]] ).

Changes in temperature and droughts have impacted crops significantly ( ''medium confidence: medium evidence, high agreement'' ) ( [[#Ray--2015|Ray et al., 2015]] ; [[#Zambrano--2016|Zambrano et al., 2016]] ; [[#Lesjak--2017|Lesjak and Calderini, 2017]] ; [[#Ferrero--2018|Ferrero et al., 2018]] ; [[#Piticar--2018|Piticar, 2018]] ; [[#Haddad--2019|Haddad et al., 2019]] ; [[#Zúñiga--2021|Zúñiga et al., 2021]] ). Table 12.4 shows the changes in crop growth duration, which affects yields. Higher negative numbers then indicate yield reduction for the crop. Increasing temperatures and decreasing precipitation are expected to impact the agriculture sector (i.e., fruits crops and forests) across the entire sub-region, with the largest impacts in the northern and central zone ( ''high confidence'' ) ( [[#Mera--2015|Mera et al., 2015]] ; [[#Zhang--2015|Zhang et al., 2015]] ; [[#Silva--2016|Silva et al., 2016]] ; [[#Lizana--2017|Lizana et al., 2017]] ; [[#Reyer--2017|Reyer et al., 2017]] ; [[#Toro-Mujica--2017|Toro-Mujica et al., 2017]] ; [[#Beyá-Marshall--2018|Beyá-Marshall et al., 2018]] ; [[#Lobos--2018|Lobos et al., 2018]] ; [[#O’Leary--2018|O’Leary et al., 2018]] ; [[#Aggarwal--2019|Aggarwal et al., 2019]] ; [[#Ávila-Valdés--2020|Ávila-Valdés et al., 2020]] ; [[#Fernandez--2020|Fernandez et al., 2020]] ; [[#Melo--2021|Melo and Foster, 2021]] ). Observed impacts and future projections warn that increasing temperatures and decreasing precipitation will largely impact water demand by agricultural sectors ( ''high confidence'' ) ( [[#Novoa--2019|Novoa et al., 2019]] ; [[#Peña-Guerrero--2020|Peña-Guerrero et al., 2020]] ; [[#Webb--2020|Webb et al., 2020]] ). Extreme climate events have caused Indigenous Peoples (e.g., Mapuche, Uru and Aymara) to experience water scarcity, a reduction in agricultural production and a displacement of their traditional knowledge and practices ( ''medium confidence: low evidence, high agreement'' ) ( [[#Parraguez-Vergara--2016|Parraguez-Vergara et al., 2016]] ; [[#Meldrum--2018|Meldrum et al., 2018]] ; [[#Perreault--2020|Perreault, 2020]] ).

SWS cities have been largely impacted by wildfires, water scarcity and landslides affecting highways and local roads, as well as potable water supply ( [[#Sepúlveda--2015|Sepúlveda et al., 2015]] ; [[#Araya-Muñoz--2016|Araya-]] [[#Muñoz--2016|Muñoz et al., 2016]] ). Increasing temperature and heat extreme events in cities have increased the demand for water, damage to urban infrastructure ( [[#Monsalves-Gavilán--2013|Monsalves-Gavilán et al., 2013]] ) and accelerated ageing and death of trees ( ''high confidence'' ) ( [[#Moser-Reischl--2019|Moser-Reischl et al., 2019]] ). Increasing temperature will modify energy demand in cities in northern and central Chile ( [[#Rouault--2019|Rouault et al., 2019]] ).

Increasing temperature, heat extreme events and air pollution in SWS have significantly impacted population health (cardiac complications, heat stroke and respiratory diseases) ( ''high confidence'' ) (Table 12.2; Leiva G et al., 2013; [[#Monsalves-Gavilán--2013|Monsalves-Gavilán et al., 2013]] ; [[#Pino--2015|Pino et al., 2015]] ; [[#Herrera--2016|Herrera et al., 2016]] ; [[#Henríquez--2017|Henríquez and Urrea, 2017]] ; [[#Ugarte-Avilés--2017|Ugarte-Avilés et al., 2017]] ; [[#de%20la%20Barrera--2018|de la Barrera et al., 2018]] ; [[#Johns--2018|Johns et al., 2018]] ; [[#Bowman--2019|Bowman et al., 2019]] ; [[#González--2019|González et al., 2019]] ; Matus C and Oyarzún G, 2019; [[#Sánchez--2019|Sánchez et al., 2019]] ; [[#Terrazas--2019|Terrazas et al., 2019]] ; [[#Cakmak--2021|Cakmak et al., 2021]] ; [[#Zenteno--2021|Zenteno et al., 2021]] ). There is ''low confidence'' regarding areal changes in Chagas disease ( [[#Tapia-Garay--2018|Tapia-Garay et al., 2018]] ; [[#Garrido--2019|Garrido et al., 2019]] ) and transmission rates in the future ( [[#Ayala--2019|Ayala et al., 2019]] ).

'''Table 12.4 |''' Average percentage change in crop growth duration for the period 2015–2019. Crop growth duration refers to the time taken in a year for crops to accumulate the reference period (1981–2010) average growing season accumulated temperature total (ATT). As temperatures rise, the ATT is reached earlier (higher negative changes), the crop matures too quickly, and thus yields are lower. “No data” means no data are available for the growth of that crop in the specified region. NP means that the crop is not present in significant areas in that region. Data were derived from Romanello et al. (2021).

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

! '''Winter wheat'''

! '''Spring wheat'''

! '''Rice'''

! '''Maize'''

! '''Soybean'''

|-
| Central America (CA)

| −4.8%

| No data

| −1.9%

| −5.0%

| −4.7%

|-
| Northwestern 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%

|-
| Northeastern South America (NES)

| −1.0%

| −1.3%

| −0.7%

| −3.5%

| −2.6%

|-
| Southeastern South America (SES)

| −2.3%

| −3.5%

| −2.3%

| −2.4%

| −2.7%

|-
| Southwestern 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

|}

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