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

=== 12.5.4 Food, Fibre and Other Ecosystem Products ===

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The CSA region globally has the greatest agricultural land and water availability per capita. With 15% of the world’s land area, it receives 29% of global precipitation and has 33% of globally available renewable resources ( [[#Flachsbarth--2015|Flachsbarth et al., 2015]] ). Agricultural commodities (coffee, bananas, sugar, soybean, corn, sugarcane, beef livestock) are some of the highest users of ecosystem resources such as land, water, nutrients and technology. These exports have gained importance in the past two decades as international trade and globalisation of markets have shaped the global agri-food system. However continuous overuse of the environment might account for resource depletion (deforestation, land degradation, nutrient depletion, pollution), affecting the natural capital base. The effects of climate change on humans, via ecological systems, exacerbate the impact related to the depletion of ecosystem services ( [[#Scholes--2016|Scholes, 2016]] ; [[#IPBES--2018b|IPBES, 2018b]] ; [[#Castaneda%20Sanchez--2019|Castaneda Sanchez et al., 2019]] ; [[#Clerici--2019|Clerici et al., 2019]] ; [[#Tellman--2020|Tellman et al., 2020]] ; [[#Pacheco--2021|Pacheco et al., 2021]] ).

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==== 12.5.4.1 Challenges and Opportunities ====

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Even though several regions have seen significant improvements in food availability, many countries are also experiencing a declining trend in food self-sufficiency ( [[#Porkka--2013|Porkka et al., 2013]] ; [[#Rolando--2017|Rolando et al., 2017]] ). Drought conditions in CA and the Caribbean increased in line with climate model predictions ( [[#Herrera--2018a|Herrera et al., 2018a]] ). The direct social and economic consequences for the sector are evident in CA’s so-called Dry Corridor, with a growing dependence on food imports ( [[#Porkka--2013|Porkka et al., 2013]] ), and these degrees of dependency make the region more vulnerable to price variability, climatic conditions ( [[#Bren%20d’Amour--2016|Bren d’Amour et al., 2016]] ; [[#ECLAC--2018|ECLAC, 2018]] ) and, therefore, to food insecurity in the absence of adaptation actions ( ''high confidence'' ) ( [[#Porkka--2013|Porkka et al., 2013]] ; [[#Bren%20d’Amour--2016|Bren d’Amour et al., 2016]] ; López Feldman and Hernández [[#Cortés--2016|Cortés, 2016]] ; [[#Eitzinger--2017|Eitzinger et al., 2017]] ; [[#Imbach--2017|Imbach et al., 2017]] ; [[#Lachaud--2017|Lachaud et al., 2017]] ; [[#Harvey--2018|Harvey et al., 2018]] ; [[#Niles--2018|Niles and Salerno, 2018]] ; [[#del%20Pozo--2019|del Pozo et al., 2019]] ; [[#Alpízar--2020|Alpízar et al., 2020]] ; [[#Anaya--2020|Anaya et al., 2020]] ).

Given these circumstances, some regions in CSA (Andes region and CA) will just meet, or fall below, the critical food supply/demand ratio for their populations ( [[#Bacon--2014|Bacon et al., 2014]] ; [[#Barbier--2018b|Barbier and Hochard, 2018b]] ). Meanwhile, the more temperate part of SA in the south is projected to have agricultural production surpluses ( ''low confidence'' ) ( [[#Webb--2016|Webb et al., 2016]] ; [[#Prager--2020|Prager et al., 2020]] ). The challenge for this region will be to retain the ability to feed and adequately nourish its internal population as well as making food supplies available to the rest of the world.

The access of other markets to the region’s agricultural products might be conditioned on the adoption of low-carbon-agriculture measures. Achieving net-zero emissions while improving standards of living will be possible but will also require developing transition policy frameworks to reach the target ( [[#Frank--2019|Frank et al., 2019]] ; [[#Mahlknecht--2020|Mahlknecht et al., 2020]] ; [[#Cárdenas--2021|Cárdenas et al., 2021]] ).

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==== 12.5.4.2 Governance and Barriers for Adaptation ====

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The governance of adaptation for CSA implies modifying agricultural, socioeconomic and institutional systems in response to and in preparation for actual or expected impacts of climate variability and change, to reduce harmful effects and exploit beneficial opportunities ( ''high confidence'' ). CSA agriculture has a diversity of systems and segments of producers. While small-scale farmers contribute significantly to food production and food security, especially in developing economies, they face global policies oriented towards global commodity markets ( [[#Knapp--2017|Knapp, 2017]] ; [[#Fernández--2019|Fernández et al., 2019]] ). Climate action initiatives that consider CSA’s high levels of poverty and inequality to reduce these pervasive problems are central for adaptation in the region ( [[#Crumpler--2020|Crumpler et al., 2020]] ; [[#Locatelli--2020|Locatelli et al., 2020]] ).

Since AR5, important advances at the institutional level have occurred based on the development and implementation of NAPs for the agriculture and forestry sector among countries. Adapting to climate change entails the interaction of decision makers, stakeholders and institutions at different scales of government, from local to national. The Climate-Adapted Sustainable Agriculture Strategy for the region of the Central American Integration System (EASAC) of the Central American Agricultural Council of Ministers of Agriculture constitutes a valuable example of how to undertake climate action in the agricultural sector, as a block of countries and in an intersectoral manner, to enhance results and make better use of resources ( [[#IICA--2019|IICA, 2019]] ).

In Brazil, the Low-Carbon Agriculture (LCA) programme (Programa ABC) funds practices for reducing GHG emissions in the sector ( [[#Government%20of%20Brazil--2012|Government of Brazil, 2012]] ), accounting for about 15% of the total agriculture official finance portfolio, although it faces challenges to advance ( [[#Souza%20Piao--2021|Souza Piao et al., 2021]] ). Costa Rica offers an example on how reforestation can help achieve Paris Agreement objectives. Reforestation through natural regeneration on abandoned pastures boosted forest cover from 48% in 2005 to 53.4% in 2010 ( [[#Reid--2019|Reid et al., 2019]] ; [[#Cárdenas--2021|Cárdenas et al., 2021]] ). Some key success factors included a strong institutional context, fiscal and financial incentives for reforestation, conservation measures such as payment for environmental services, cattle ranch subsidy reform and a historically strong enforcement and focus on land titles that favoured the restoration of lands. Uruguay offers another example, with the farm sector contribution of 32.8% of all exports and 73.8% of the country’s emissions, so decarbonisation is not just an environmental issue but an economic competitiveness one as well. In the Intended Nationally Determined Contributions (INDCs) submitted to the UNFCCC in 2015, Uruguay set a specific target for the agriculture sector to reduce enteric methane emissions intensity per kilogram of beef (live weight) by 33% to 46% in 2030 by improving efficiency of beef production by controlling the grazing intensity to increase animal intake, reproductive efficiency and daily weight gain ( [[#Picasso--2014|Picasso et al., 2014]] ).

It is relevant to create conditions for the development of sustainable agricultural practices in a framework where factors associated with climate have become important for producers, given recent experiences of drought and lack of water ( ''high confidence'' ) ( [[#Clarvis--2014|Clarvis and Allan, 2014]] ; [[#Roco--2016|Roco et al., 2016]] ; [[#Hurlbert--2017|Hurlbert and Gupta, 2017]] ; [[#Pérez-Escamilla--2017|Pérez-Escamilla et al., 2017]] ; [[#Cruz--2018|Cruz et al., 2018]] ; [[#Zúñiga--2021|Zúñiga et al., 2021]] ). Solutions that consider relevant drivers that have demonstrated a positive effect in diffusion of adaptation strategies are more efficient (Table 12.8). Some conditions, such as the promotion of education programmes, participation in cooperatives, credit access and land tenure security, can help. In the same line, in CSA some elements, such as technology and information access and local knowledge, reinforce climate-change adaptation ( [[#Khatri-Chhetri--2019|Khatri-Chhetri et al., 2019]] ; [[#Piggott-McKellar--2019|Piggott-McKellar et al., 2019]] ). As stated in Table 12.8, barriers of various origins persist in connection with climate-change adaptation in the region increasing the vulnerability of farming systems and rural livelihoods.

'''Table 12.8 |''' Recent studies related to climate-change adaptation of agricultural systems and its determinants in Central and South America region.

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

! '''Countries'''

! '''Sample size (n)'''

! '''Study approach'''

! '''Crop systems'''

! '''Adaptation strategies'''

! '''Main drivers promoting climate-change adaptation'''

! '''Main barriers limiting climate-change adaptation'''

! '''Main barriers detected'''

|-
| [[#de%20Souza%20Filho--2021|de Souza Filho et al. (2021)]]

| Brazil

| 175

| Quant.

| Cattle farmers

| Integrated crop-livestock and livestock-forestry systems

| Credit access, extension services

| Lack of resources

| Lack of agricultural market access strategies

|-
| [[#Magalhães--2021|Magalhães et al. (2021)]]

| Brazil

| 94

| Qual.

| Several crops

| Farm management

| Previous experience with risks

| Inadequate infrastructure, low purchasing power

| Opportunities limited by infrastructure

|-
| [[#Carrer--2020|Carrer et al. (2020)]]

| Brazil

| 175

| Quant.

| Several crops

| Agricultural insurance

| Schooling, technical assistance

| Higher risk propensity

| Limited financial market access

|-
| [[#Quiroga--2020|Quiroga et al. (2020)]]

| Nicaragua

| 212

| Quant.

| Coffee

| Several adaptation measures

| Farm size, awareness of climate change, schooling

| Limited access to rain water

| Absence of climate-change education

|-
| [[#Bro--2019|Bro et al. (2019)]]

| Nicaragua

| 236

| Quant.

| Coffee

| Crop,

soil and water

| Schooling, participation in cooperatives, radio

| Household size

| Institutional framework to promote cooperatives

|-
| [[#Leroy--2019|Leroy (2019)]]

| Venezuela and Colombia

| 73

| Qual.

| Several crops at high altitudes

| Irrigation management

| Perception of water scarcity, local knowledge

| Degradation of fragile areas

| Ineffectiveness of local institutions

|-
| Cherubin et al. (2019)

| Colombia

| 6

| Quant.

| Several crops and pasture

| Agroforestry systems

| Improving soil quality and biota

| Degradation of conventional pasture

| Lack of crop diversification

|-
| [[#Harvey--2018|Harvey et al. (2018)]]

| Costa Rica, Honduras and Guatemala

| 860

| Quant.

| Coffee, beans and maize

| Several adaptation practices

| Awareness of climate change

| Affordability of adaptation practices

| Lack of adaptation involving agroecological and socioeconomic contexts

|-
| [[#Chen--2018|Chen et al. (2018)]]

| Costa Rica and Nicaragua

| 559

| Quant.

| Several crops

| Intensification and diversification

| Access to weather information, participation in organisations, credit access, farming experience

| Land renting

| Lack of crop and practices diversification

|-
| [[#Vidal%20Merino--2019|Vidal Merino et al. (2019)]]

| Peru

| 137

| Quant.

| Several crops

| Water management

| Farm size, capital, irrigated proportion

| Limited access to off-farm activities, small cultivated area

| Lack of site-specific design of interventions

|-
| [[#Meldrum--2018|Meldrum et al. (2018)]]

| Bolivia

| 193

| Quant.

| Potato, quinoa and others

| Diversification of crop portfolio

| Weather information

| Loss to traditional knowledge

| Lack of resilience and actions to expand and maintain variety portfolio

|-
| [[#Lan--2018|Lan et al. (2018)]]

| Nicaragua

| 180

| Quant.

| Cocoa

| Crop management

| Schooling, household size, farm size

| Lack of income

| Income inequality, gaps of profitability of practices, benefits of practices depends on costs

|-
| [[#Kongsager--2017|Kongsager (2017)]]

| Belize

| 125

| Qual.

| Maize

| Alley cropping

| Schooling

| Land tenure, market distance, degradation of fragile areas

| Lack of land tenure, lack of market access, lack of trust

|-
| [[#Schembergue--2017|Schembergue et al. (2017)]]

| Brazil

| 5485 a

| Quant.

| Several crops

| Agroforestry systems

| Financing, presence of associations, credit access

| High potential for agriculture, lack of climate information

| Adaptation conditioned by agricultural, socioeconomic and climatic conditions

|-
| [[#Harvey--2017|Harvey et al. (2017)]]

| Guatemala, Honduras and Costa Rica

| 300

| Quant.

| Coffee and maize

| Ecosystem-based adaptation

| Schooling, age, farming experience, access to technological support

| Lack of land tenure

| Lack of access to training and finance

|-
| [[#Roco--2016|Roco et al. (2016)]]

| Chile

| 665

| Quant.

| Several crops

| Water management

| Farm size, access to weather information

| Locations, age

| Lack of availability and access to climate-change information

|-
| [[#Mussetta--2015|Mussetta and Barrientos (2015)]]

| Argentina

| 41

| Qual.

| Vine and others

| Crop and water management

| Organisation of producers, labour availability, knowledge and information access, technology access

| Water allocation system

| Lack of water management and distribution strategies

|}

Notes:

(a) municipalities; Quant.: mainly quantitative; Qual.: mainly qualitative.

Limited information regarding cost-benefit analyses of adaptation is available in the region and regarding avoiding maladaptation effects and promoting site-specific and dynamic adaptation options considering available technologies ( ''medium confidence'' ) ( [[#Roco--2017|Roco et al., 2017]] ; [[#Zavaleta--2018|Zavaleta et al., 2018]] ; [[#Ponce--2020|Ponce, 2020]] ; [[#Shapiro-Garza--2020|Shapiro-Garza et al., 2020]] ).

Climate information services has an important role in climate-change adaptation and there is a recognised gap between climate science and farmers ( ''high confidence'' ) ( [[#Vaughan--2017|Vaughan et al., 2017]] ; [[#Loboguerrero--2018|Loboguerrero et al., 2018]] ; [[#Tall--2018|Tall et al., 2018]] ; [[#Thornton--2018|Thornton et al., 2018]] ; [[#Ewbank--2019|Ewbank et al., 2019]] ). Such services should address the challenges of ensuring that climate information and advisory services are relevant to the decisions of smallholder and family farmers, providing timely climate service access to remote rural communities with marginal infrastructure and ensuring that farmers own climate services and shape their design and delivery. An interesting case facing this gap is the implementation of local technical agro-climatic committees in Colombia, which make it possible to share and validate climatic and weather forecasts, as well as crop model results for seasonal drought events ( [[#Loboguerrero--2018|Loboguerrero et al., 2018]] ). Another example is the web service AdaptaBrasil-MCTI, which forecasts the risk of climate-change impacts on strategic sectors (e.g., food, energy, water) in Brazil ( [[#Government%20of%20Brazil--2021|Government of Brazil and Ministry of Science Technology and Innovation Secretariat of Policies and Programs, 2021]] ).

Barriers to financial access are present in the region, restricting effective adaptation to extreme weather events ( ''high confidence'' ) ( [[#Chen--2018|Chen et al., 2018]] ; [[#Fisher--2019|Fisher et al., 2019]] ; [[#Piggott-McKellar--2019|Piggott-McKellar et al., 2019]] ; [[#Vidal%20Merino--2019|Vidal Merino et al., 2019]] ; [[#de%20Souza%20Filho--2021|de Souza Filho et al., 2021]] ). In 2014, the penetration rate of this type of insurance in the region averaged 0.03% of GDP, and a few countries dominate the market (Brazil, Argentina). Beyond these countries, some initiatives also exist in Uruguay, Paraguay, Chile and Ecuador. In most Latin American and Caribbean countries, the public sector plays an important role in providing insurance or reinsurance and coexists with private-sector companies ( [[#Cárdenas--2021|Cárdenas et al., 2021]] ). Insurance protections represent a strategy to transfer climate risk to protect the well-being of vulnerable small farmers and accelerate uptake (recovery) after a climate-related extreme weather event. Lack of finance and proper infrastructure is compounded by limited knowledge of sustainable farming practices and high rates of financial illiteracy ( ''high confidence'' ) ( [[#Hurlbert--2017|Hurlbert and Gupta, 2017]] ; [[#Piggott-McKellar--2019|Piggott-McKellar et al., 2019]] ).

Insufficient access to digital services and technologies further widens the gap between the rural poor and more urban populations of Latin America and the Caribbean ( ''medium confidence: insufficient evidence, high agreement'' ). In turn, these factors compromise productivity and competitiveness. Support for the rural poor can be focused on both economic competitiveness and social development. Finally, to align the identified adaptation options as a priority for achieving future food security in the NDCs of CSA countries to mitigation commitments, it will be essential to highlight synergies by generating evidence (national research) in relation to progress towards increasing productivity and resilience and reducing GHG, in addition to demonstrating its added value as a development initiative ( [[#Rudel--2015|Rudel et al., 2015]] sustainable; [[#Loboguerrero--2019|Loboguerrero et al., 2019]] ).

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==== 12.5.4.3 Adaptation Options ====

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To contextualise the adaptation options at the regional level, the majority of the NDCs of the CSA countries reported observed and/or projected climate-related hazards: occurrence of droughts and floods (80% of countries each), followed by storms (45%) and landslides (30%), as well as extreme heat, wildfire and invasion by pests and non-native species in agriculture (25% each) ( [[#Crumpler--2020|Crumpler et al., 2020]] ).

The main adaptation options for climate change in the region include preventive measures against soil erosion; climate-smart agriculture, which provides a framework for synergies between adaptation, mitigation and improved food security; climate information systems; land use planning; shifting plantations at high altitudes to avoid temperature increases and plagues; and improved varieties of pastures and cattle ( [[#Lee--2014|Lee et al., 2014]] ; [[#Jat--2016|Jat et al., 2016]] ; [[#Crumpler--2020|Crumpler et al., 2020]] ; [[#Moreno--2020a|Moreno et al., 2020a]] ; [[#Aragón--2021|Aragón et al., 2021]] ). Agricultural technologies are not necessarily changing, but the economic activity is shifting to accommodate increasing climate variation and adapt to changes in water availability and ideal growing conditions ( ''high confidence'' ), as is observed in Argentina, Colombia and Brazil ( [[#McMartin--2018|McMartin et al., 2018]] ; [[#Rolla--2018|Rolla et al., 2018]] ; [[#Sloat--2020|Sloat et al., 2020]] ; [[#Gori%20Maia--2021|Gori Maia et al., 2021]] ). Coffee plantations are moving further up mountain regions, with the land at lower elevations converted for other uses. In Brazil, crop modelling suggests the need for the development of new cultivars, with a longer crop cycle and with higher tolerance to high temperatures, a necessary technological advance for maize, an essential staple crop, to be produced in the future. Additionally, irrigation becomes essential for sustaining productivity in adverse climate-change scenarios in several regions of CSA ( [[#McMartin--2018|McMartin et al., 2018]] ; [[#Lyons--2019|Lyons, 2019]] ; [[#Reay--2019|Reay, 2019]] ).

Livestock production is for small farmers one of the main sources of protein and contributes to food security ( [[#Rodríguez--2016|Rodríguez et al., 2016]] ). The importance of this sub-sector in CSA will continue to increase as the demand for meat products does as well in the coming years, driven by growing incomes in the region ( [[#OECD%20and%20FAO--2019|OECD and FAO, 2019]] ). However, the increase in animal production has been associated with land degradation, triggered by the conversion of native vegetation to pastureland and aggravated by overgrazing and abandoning of the degraded pastures ( [[#Baumann--2017|Baumann et al., 2017]] ; [[#ECLAC--2018|ECLAC, 2018]] ; [[#Müller-Hansen--2019|Müller-Hansen et al., 2019]] ). Sá et al. (2017) simulated the adoption of agricultural systems based on LCA strategies towards 2050. According to the simulation, the adoption of LCA strategies in the SA region can alter the growing trend of land use and land use change emissions, and at the same time, it can increase meat production by 55 Mt for the entire period (2016–2050). The restoration of degraded pasture and livestock intensification account for 71.2% and integrated crop–livestock–forestry system contributes 28.8% of total meat production for the entire period. These results indicate that combined actions in agricultural management systems in SA can result in synergistic responses that can be used to make agriculture and livestock production an important part of the solution of global climate change and advance food security ( ''medium confidence: insufficient evidence and high agreement'' ) ( [[#Zu%20Ermgassen--2018|Zu Ermgassen et al., 2018]] ; [[#Pompeu--2021|Pompeu et al., 2021]] ). Crop–livestock–forestry systems are also important for climate-change adaptation as they provide multiple benefits, including the coproduction of food, animal feed, organic fertilizers and soil organic carbon sequestration ( [[#Sharma--2016|Sharma et al., 2016]] ; [[#Rodríguez--2021|Rodríguez et al., 2021]] ), achieving mitigation and adaptation goals ( ''high confidence'' ) ( [[#Picasso--2014|Picasso et al., 2014]] ; [[#Modernel--2016|Modernel et al., 2016]] , 2019; [[#Rolla--2019|Rolla et al., 2019]] ; [[#Locatelli--2020|Locatelli et al., 2020]] ). A recent analysis of agroforestry in Brazil showed positive and relevant impacts on the heads/pasture area rate in livestock production and that the system may have also stimulated a shift towards other production activities with higher gross added value ( [[#Gori%20Maia--2021|Gori Maia et al., 2021]] ). Agroforestry has also proven to have protective benefits to obtain more stable, less fluctuating yields due to climate-related damage in coffee production ( ''high confidence'' ) ( [[#Bacon--2017|Bacon et al., 2017]] ; [[#Durand-Bessart--2020|Durand-Bessart et al., 2020]] ; [[#Ovalle-Rivera--2020|Ovalle-Rivera et al., 2020]] ). In the same way, the production of plant-based fibre can be less vulnerable to economic and climatic variability through farming system diversification. Textile fibre crops for the case of cotton include crop rotation, agroecological intercropping and agroforestry ( [[#Oliveira%20Duarte--2019|Oliveira Duarte et al., 2019]] ).

Adaptation strategies also concern Indigenous agriculture, that is, the vast majority of the 44 million Amerindians ( [[#CEPAL--2014|CEPAL, 2014]] ). IKLK can play an important role in adaptation ( [[#Zavaleta--2018|Zavaleta et al., 2018]] ). On one hand, they ensure the conservation of a very rich agrobiodiversity that is likely to meet the challenges of climate change ( ''high confidence'' ) ( [[#Carneiro%20da%20Cunha--2017|Carneiro da Cunha and Morim de Lima, 2017]] ; [[#Magni--2017|Magni, 2017]] ; [[#Emperaire--2018|Emperaire, 2018]] ; [[#Donatti--2019|Donatti et al., 2019]] ), while on the other hand, the sustainability of large territories that assure their livelihood ( [[#Singh--2017|Singh and Singh, 2017]] ; [[#Mustonen--2021|Mustonen et al., 2021]] ). In the Andes, ancient technologies increased the quantity of crops produced and made it possible to cope with climatic changes and water scarcity, while nutrition conditions were improved ( ''high confidence'' ) (López Feldman and Hernández [[#Cortés--2016|Cortés, 2016]] ; [[#Parraguez-Vergara--2018|Parraguez-Vergara et al., 2018]] ; [[#Carrasco-Torrontegui--2020|Carrasco-Torrontegui et al., 2020]] food). Also, fire prevention management and protection against forest and biodiversity loss are recognised as important elements in IK ( [[#Mistry--2016|Mistry et al., 2016]] ; [[#Bowman--2021|Bowman et al., 2021]] ).

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