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

==== 12.3.4.3 Vulnerability ====

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The largest expanses of remaining vegetation in the Cerrado biome are located in SAM, but the region has a small number of protected areas (only 7.5% of Cerrado vegetation occurs inside protected areas), which will leave fauna and flora with little room for moving across the landscape in the face of climate change. Protected areas—Indigenous lands included—have significantly reduced forest clear-cutting in the Amazon deforestation arc (most of which is inside SAM) ( ''high confidence'' ) ( [[#Nolte--2013|Nolte et al., 2013]] ). However nearly 100 protected areas in the Amazon, Cerrado and Pantanal biomes inside SAM have been identified as highly or moderately vulnerable to future climate change and demand serious adaptation interventions ( ''medium confidence: medium evidence, high agreement'' ) ( [[#Feeley--2016|Feeley and Silman, 2016]] ; [[#Lapola--2019b|Lapola et al., 2019b]] ). Yet the maintenance of these protected areas or even the halting of deforestation may do little to impede a large-scale persistent ecosystem shift to an alternative state (crossing a tipping point) of the Amazon rainforest or even more subtle changes caused by climate change in the region ( ''medium confidence: medium evidence, high agreement'' ) ( [[#Aguiar--2016a|Aguiar et al., 2016a]] ; [[#Boers--2017|Boers et al., 2017]] ; [[#Lapola--2018|Lapola et al., 2018]] ; [[#Lovejoy--2018|Lovejoy and Nobre, 2018]] ).

The agriculture in the region is highly dependent on the climate ( ''high confidence'' ), responsible for three-fourths of the variability in agricultural yields in the region (Table 12.4). Irrigation is an important strategy for agricultural production in part of the region, but it accounts for no more than 8% of the total agricultural area in SA and 7% in CA ( [[#OECD%20and%20FAO--2019|OECD and FAO, 2019]] ). This practice faces potential impacts from reductions in surface water availability in future climate scenarios ( [[#Ribeiro%20Neto--2016|Ribeiro Neto et al., 2016]] ; [[#Zilli--2020|Zilli et al., 2020]] ), enhanced by non-climate drivers such as land use changes ( ''medium confidence: medium evidence, high agreement'' ) ( [[#Spera--2020|Spera et al., 2020]] ). The remaining fluctuation in yields relates to issues of infrastructure, market, economy, policy and social aspects. Good infrastructure, transport logistics, quality of roads and storage strongly influence the vulnerability of the agricultural sector (Figure 12.7).

The combined effects of extreme climate events and ecosystem fragmentation, for example, by deforestation or fire, lead to changes in forest structure, with the death of taller trees and reduction in diversity of plant species, loss of productivity and carbon storage ( ''high agreement'' ) ( [[#Brando--2014|Brando et al., 2014]] ; [[#Reis--2018|Reis et al., 2018]] ). The rise of a large-scale soybean agroindustry in the early 2000s led to a faster increase in human development indicators in some regions, tightly linked to the agricultural production chain ( ''high confidence'' ) ( [[#Richards--2015|Richards et al., 2015]] ). Such a development also came at considerable cost to the environment (e.g., Neill et al. 2013) and the regional climate, even though a moratorium implemented in 2006 on new soy plantations on deforested areas reduced deforestation by a factor of five ( ''high confidence'' ) ( [[#Macedo--2012|Macedo et al., 2012]] ; [[#Kastens--2017|Kastens et al., 2017]] ). The same sort of supply chain interventions along with incentive-based public policies applied to the beef supply chain could minimise the need for agricultural expansion in the SAM deforestation frontier ( ''medium confidence: medium evidence, high agreement'' ) ( [[#Nepstad--2014|Nepstad et al., 2014]] ; [[#Pompeu--2021|Pompeu et al., 2021]] ).

SAM has a low population density, and the majority of the population is located in cities. The populations of some of these cities are reported as being highly vulnerable considering the enormous social inequalities embedded in these cities ( ''high confidence'' ) ( [[#Filho--2016|Filho et al., 2016]] ). Inequalities and uneven access to infrastructure, housing and healthcare increase populations’ vulnerability to atmospheric pollution and drier conditions ( ''high confidence'' ) (Rodrigues et al., 2019; [[#IPAM--2020|IPAM, 2020]] ; [[#Machado-Silva--2020|Machado-Silva et al., 2020]] ).

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