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

==== 12.3.3.4 Impacts ====

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Suriname has experienced coastal erosion and flooding, which causes damage to infrastructure, agriculture and ecosystems, while Georgetown has suffered a significant number of floods ( [[#CAF--2014|CAF, 2014]] ). In Guyana, coastal flooding has negatively impacted agricultural activity ( [[#Tomby--2018|Tomby and Zhang, 2018]] ) (Figure 12.9). Sugarcane production has been one of the most impacted cash crops. The impact on sugar production has affected Guyana’s sugar industry ( [[#Tomby--2019|Tomby and Zhang, 2019]] ). Among the main impacts observed in the sugar industry are an increase in production costs, greater use of pesticides and fertilizers and a reduction in worker income ( [[#Tomby--2018|Tomby and Zhang, 2018]] ).

Indigenous Peoples and resource-dependent rural communities in the Amazon have been impacted over the last decade by extreme drought and flood events in various dimensions of their livelihoods ( [[#Pinho--2015|Pinho et al., 2015]] ). Food security has been strongly impacted since it is based on fishing and small-scale agriculture, two sectors highly vulnerable to climate change. During extreme events, fishing decreases due to limited access to fishing grounds ( ''medium confidence'' : ''low evidence, high agreement'' ) (Figure 12.9) ( [[#Pinho--2015|Pinho et al., 2015]] ; [[#Camacho%20Guerreiro--2016|Camacho Guerreiro et al., 2016]] . Overfishing, deforestation and dam construction are a threat to fishing in the sub-region ( [[#Lopes--2019|Lopes et al., 2019]] ) and therefore contribute to exacerbating the impacts of climate change. Small-scale agriculture practices (e.g., floodplain agriculture and slash and burn) are highly coupled with natural hydrological cycles and therefore severely affected by extreme events (Figure 12.9) ( [[#Cochran--2016|Cochran et al., 2016]] ). Livelihoods are also impacted by disruptions in land and river transport, restrictions in drinking water access, increased incidence of forest fires and disease outbreaks ( ''medium confidence'' : ''medium evidence, high agreement'' ) (Figure 12.9) ( [[#Marengo--2013|Marengo et al., 2013]] ; [[#Pinho--2015|Pinho et al., 2015]] ; [[#Marengo--2016|Marengo and Espinoza, 2016]] ; [[#Marengo--2018|Marengo et al., 2018]] ). In addition, flood events have caused losses of homes and disruption of public and commercial services (Figure 12.9) ( [[#Parry--2018|Parry et al., 2018]] ).

Several vector-driven diseases such as malaria and leishmaniasis are endemic in the Amazon region; however, socio-environmental changes are altering their natural dynamics ( [[#Confalonieri--2014b|Confalonieri et al., 2014b]] ). An important relationship between the outbreak of infectious diseases and changes in climatic events (e.g., droughts, floods, heat waves, ENSO) or environmental events (e.g., deforestation, dam construction and habitat fragmentation) has been found to exist for the Brazilian Amazon ( ''medium confidence'' : ''medium evidence, high agreement'' ) ( [[#Pan--2014|Pan et al., 2014]] ; [[#Filho--2016|Filho et al., 2016]] ; [[#Nava--2017|Nava et al., 2017]] ; [[#Ellwanger--2020|Ellwanger et al., 2020]] ). These impacts are more severe in poor populations with limited access to health services ( [[#Pan--2014|Pan et al., 2014]] ; [[#WHO%20and%20UNFCCC--2020|WHO and UNFCCC, 2020]] ). In the case of Venezuela, the impact of climate change on the epidemiology of malaria has been studied, showing significant influence on transmission in the Amazonia area of the country (Figure 12.4) ( [[#Laguna--2017|Laguna et al., 2017]] ). Other studies from Venezuela have documented the role of ENSO in dengue outbreaks ( [[#Vincenti-Gonzalez--2018|Vincenti-Gonzalez et al., 2018]] ). Table 12.1 shows the changes observed in reproduction potential for dengue in the different sub-regions due to changes in rainfall and temperature. Forest fires pose a major threat to public health in the region because they relate to an increase in hospital admissions due to respiratory problems, mainly among children and the elderly (Figure 12.5). The amount of air pollutants detected is sometimes higher than that observed in large urban areas, especially during dry seasons when biomass burning increases ( [[#Aragão--2016|Aragão et al., 2016]] ; [[#de%20Oliveira%20Alves--2017|de Oliveira Alves et al., 2017]] ; [[#Paralovo--2019|Paralovo et al., 2019]] ).

'''Table 12.1 |''' Environmental suitability for transmission of dengue by ''Aedes aegypti'' as modelled by the influence of temperature and rainfall on vectorial capacity and vector abundance; this is overlaid on human population density data to estimate the reproduction potential for these diseases (R 0 , expected number of secondary infections resulting from one infected person). The southwestern South America (SWS) and southern South America (SSA) sub-regions are not presented because the vector is not abundant in these areas and the estimated R 0 is lower than 0.01. Data were derived from Romanello et al. (2021).

{| class="wikitable"
|-
! '''Sub-region'''

! '''Average R''' 0 '''1950–1954'''

! '''Average R''' 0 '''2016–2020'''

! '''Absolute change in R''' 0 '''from 1950–1954 to 2016–2020'''

! '''Percentage change in R''' 0 '''from 1950–1954 to 2016–2021'''

|-
| Central America (CA)

| 3.00

| 3.53

| 0.53

| 18%

|-
| Northwestern 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%

|-
| Northeastern South America (NES)

| 2.11

| 2.47

| 0.36

| 17%

|-
| Southeastern South America (SES)

| 0.64

| 0.81

| 0.17

| 26%

|}

Climate-change impacts have also been observed in the oceans, coastal ecosystems (coral reefs and mangroves), EEZs and saltmarshes in NSA; further impacts are expected in coral reefs, estuaries, mangroves and EEZs in the sub-region (Figure 12.9). Species in freshwater ecoregions (e.g., the Orinoco and Amazon Rivers and their flooded forests) are predicted to suffer a decrease in range and climatic suitability ( ''medium confidence: low evidence, high agreement'' ) (Section [https://www.ipcc.ch/chapter/12#CCP1.2.3 CCP1.2.3] ; [[#Manes--2021|Manes et al., 2021]] ). A significant decrease in climate refugia (90%) for multiple vertebrate and plant species in the region has been projected for a 4°C scenario, with considerable benefits of mitigation and reducing risks to 40% for a 2°C scenario ( [[#Warren--2018|Warren et al., 2018]] ).

Droughts in 2009/2010 and 2015/2016 increased tree mortality rate in Amazon forests ( [[#Doughty--2015|Doughty et al., 2015]] ; [[#Feldpausch--2016|Feldpausch et al., 2016]] ; [[#Anderson--2018b|Anderson et al., 2018b]] ), while productivity showed no consistent change; some authors reported a drop in productivity ( [[#Feldpausch--2016|Feldpausch et al., 2016]] ), while others found no significant changes ( [[#Brienen--2015|Brienen et al., 2015]] ; [[#Doughty--2015|Doughty et al., 2015]] ). Nevertheless, the combined effect of increasing tree mortality with variations in growth results in a long-term decrease in C stocks in forest biomass, compromising the role of these forests as a C sink ( ''high confidence'' ) ( [[#Brienen--2015|Brienen et al., 2015]] ; [[#Rammig--2020|Rammig, 2020]] ; [[#Sullivan--2020|Sullivan et al., 2020]] ) (Figure 12.9). Under the RCP8.5 scenario for 2070, drought will increase the conversion of rainforest to savannah ( ''medium confidence'' : ''medium evidence, high agreement'' ) ( [[#Anadón--2014|Anadón et al., 2014]] ; [[#Olivares--2015|Olivares et al., 2015]] ; [[#Sampaio--2019|Sampaio et al., 2019]] ). The transformation of rainforest into savannah will bring forth biodiversity loss and alterations in ecosystem functions and services ( ''medium confidence'' : ''medium evidence, high agreement'' ) ( [[#Anadón--2014|Anadón et al., 2014]] ; [[#Olivares--2015|Olivares et al., 2015]] ; [[#Sampaio--2019|Sampaio et al., 2019]] ). In the Amazon basin, the synergistic effects of deforestation, fire, expansion of the agricultural frontier, infrastructure development, extractive activities, climate change and extreme events may exacerbate the risk of savannisation ( ''medium confidence'' : ''medium evidence, high agreement'' ) ( [[#Nobre--2016b|Nobre et al., 2016b]] ; [[#Bebbington--2019|Bebbington et al., 2019]] ; [[#Sampaio--2019|Sampaio et al., 2019]] ; [[#Rammig--2020|Rammig, 2020]] ).

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