Editing IPCC:AR6/SRCCL/Chapter-3 (section)

=== 3.4.2 Impacts on socio-economic systems ===

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Combined impacts of desertification and climate change on socio-economic development in drylands are complex. Figure 3.9 schematically represents our qualitative assessment of the magnitudes and the uncertainties associated with these impacts on attainment of the SDGs in dryland areas (UN 2015 <sup>[[#fn:r655|655]]</sup> ). The impacts of desertification and climate change are difficult to isolate from the effects of other socio-economic, institutional and political factors (Pradhan et al. 2017 <sup>[[#fn:r656|656]]</sup> ). However, there is ''high confidence'' that climate change will exacerbate the vulnerability of dryland populations to desertification, and that the combination of pressures coming from climate change and desertification will diminish opportunities for reducing poverty, enhancing food and nutritional security, empowering women, reducing disease burden, and improving access to water and sanitation. Desertification is embedded in SDG 15 (Target 15.3) and climate change is under SDG 13. The ''high confidence'' and high magnitude impacts depicted for these SDGs (Figure 3.9) indicate that the interactions between desertification and climate change strongly affect the achievement of the targets of SDGs 13 and 15.3, pointing at the need for the coordination of policy actions on land degradation neutrality and mitigation and adaptation to climate change. The following subsections present the literature and assessments which serve as the basis for Figure 3.9.

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'''Figure 3.9'''

<span id="socio-economic-impacts-of-desertification-and-climate-change-with-the-sdg-framework."></span>
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'''Socio-economic impacts of desertification and climate change with the SDG framework.'''
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[[File:cfbc39ef1d0f510ce9eaf875d2adda06 Figure-3.9-1024x748.jpg]]

Socio-economic impacts of desertification and climate change with the SDG framework.

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==== 3.4.2.1 Impacts on poverty ====

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Climate change has a high potential to contribute to poverty particularly through the risks coming from extreme weather events (Olsson et al. 2014 <sup>[[#fn:r657|657]]</sup> ). However, the evidence rigourously attributing changes in observed poverty to climate change impacts is currently not available. On the other hand, most of the research on links between poverty and desertification (or more broadly, land degradation) focused on whether or not poverty is a cause of land degradation (Gerber et al. 2014 <sup>[[#fn:r658|658]]</sup> ; Vu et al. 2014 <sup>[[#fn:r659|659]]</sup> ; Way 2016 <sup>[[#fn:r660|660]]</sup> ) (Section 4.7.1). The literature measuring the extent to which desertification contributed to poverty globally is lacking: the related literature remains qualitative or correlational (Barbier and Hochard 2016 <sup>[[#fn:r661|661]]</sup> ). At the local level, on the other hand, there is ''limited evidence'' and ''high agreement'' that desertification increased multidimensional poverty. For example, Diao and Sarpong (2011) <sup>[[#fn:r662|662]]</sup> estimated that land degradation lowered agricultural incomes in Ghana by 4.2 billion USD between 2006 and 2015, increasing the national poverty rate by 5.4% in 2015. Land degradation increased the probability of households becoming poor by 35% in Malawi and 48% in Tanzania (Kirui 2016 <sup>[[#fn:r663|663]]</sup> ). Desertification in China was found to have resulted in substantial losses in income, food production and jobs (Jiang et al. 2014 <sup>[[#fn:r664|664]]</sup> ). On the other hand, Ge et al. (2015) <sup>[[#fn:r665|665]]</sup> indicated that desertification was positively associated with growing incomes in Inner Mongolia in China in the short run since no costs were incurred for SLM, while in the long run higher incomes allowed allocation of more investments to reduce desertification. This relationship corresponds to the Environmental Kuznets Curve, which posits that environmental degradation initially rises and subsequently falls with rising income (e.g., Stern 2017 <sup>[[#fn:r666|666]]</sup> ). There is ''limited evidence'' on the validity of this hypothesis regarding desertification.

<div id="section-3-4-2-2-impacts-on-food-and-nutritional-insecurity"></div>

<span id="impacts-on-food-and-nutritional-insecurity"></span>
==== 3.4.2.2 Impacts on food and nutritional insecurity ====

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About 821 million people globally were food insecure in 2017, of whom 63% in Asia, 31% in Africa and 5% in Latin America and the Caribbean (FAO et al. 2018 <sup>[[#fn:r667|667]]</sup> ). The global number of food insecure people rose by 37 million since 2014. Changing climate variability, combined with a lack of climate resilience, was suggested as a key driver of this increase (FAO et al. 2018 <sup>[[#fn:r668|668]]</sup> ). Sub-Saharan Africa, East Africa and South Asia had the highest share of undernourished populations in the world in 2017, with 28.8%, 31.4% and 33.7% respectively (FAO et al. 2018 <sup>[[#fn:r669|669]]</sup> ). The major mechanism through which climate change and desertification affect food security is through their impacts on agricultural productivity. There is ''robust evidence'' pointing to negative impacts of climate change on crop yields in dryland areas ( ''high agreement'' ) (Hochman et al. 2017 <sup>[[#fn:r670|670]]</sup> ; Nelson et al. 2010 <sup>[[#fn:r671|671]]</sup> ; Zhao et al. 2017 <sup>[[#fn:r672|672]]</sup> ) (Sections 3.4.1, 5.2.2 and 4.7.2). There is also ''robust evidence'' and ''high agreement'' on the losses in agricultural productivity and incomes due to desertification (Kirui 2016 <sup>[[#fn:r673|673]]</sup> ; Moussa et al. 2016 <sup>[[#fn:r674|674]]</sup> ; Mythili and Goedecke 2016 <sup>[[#fn:r675|675]]</sup> ; Tun et al. 2015 <sup>[[#fn:r676|676]]</sup> ). Nkonya et al. (2016a) <sup>[[#fn:r677|677]]</sup> estimated that cultivating wheat, maize, and rice with unsustainable land management practices is currently resulting in global losses of 56.6 billion USD annually, with another 8.7 billion USD of annual losses due to lower livestock productivity caused by rangeland degradation. However, the extent to which these losses affected food insecurity in dryland areas is not known. Lower crop yields and higher agricultural prices worsen existing food insecurity, especially for net food-buying rural households and urban dwellers. Climate change and desertification are not the sole drivers of food insecurity, but especially in the areas with high dependence on agriculture, they are among the main contributors.

<div id="section-3-4-2-3-impacts-on-human-health-through-dust-storms"></div>

<span id="impacts-on-human-health-through-dust-storms"></span>
==== 3.4.2.3 Impacts on human health through dust storms ====

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The frequency and intensity of dust storms are increasing due to land-use and land-cover changes and climate-related factors (Section 2.4) particularly in some regions of the world such as the Arabian Peninsula (Jish Prakash et al. 2015 <sup>[[#fn:r678|678]]</sup> ; Yu et al. 2015 <sup>[[#fn:r679|679]]</sup> ; Gherboudj et al. 2017 <sup>[[#fn:r680|680]]</sup> ; Notaro et al. 2013 <sup>[[#fn:r681|681]]</sup> ; Yu et al. 2013 <sup>[[#fn:r682|682]]</sup> ; Alobaidi et al. 2017 <sup>[[#fn:r683|683]]</sup> ; Maghrabi et al. 2011 <sup>[[#fn:r684|684]]</sup> ; Almazroui et al. 2018 <sup>[[#fn:r685|685]]</sup> ) and broader Middle East (Rashki et al. 2012 <sup>[[#fn:r686|686]]</sup> ; Türkeş 2017 <sup>[[#fn:r687|687]]</sup> ; Namdari et al. 2018 <sup>[[#fn:r688|688]]</sup> ) as well as Central Asia (Indoitu et al. 2015 <sup>[[#fn:r689|689]]</sup> ; Xi and Sokolik 2015 <sup>[[#fn:r690|690]]</sup> ), with growing negative impacts on human health ( ''high confidence'' ) (Díaz et al. 2017 <sup>[[#fn:r691|691]]</sup> ; Goudarzi et al. 2017 <sup>[[#fn:r692|692]]</sup> ; Goudie 2014 <sup>[[#fn:r693|693]]</sup> ; Samoli et al. 2011 <sup>[[#fn:r694|694]]</sup> ). Dust storms transport particulate matter, pollutants, pathogens and potential allergens that are dangerous for human health over long distances (Goudie and Middleton 2006 <sup>[[#fn:r695|695]]</sup> ; Sprigg 2016 <sup>[[#fn:r696|696]]</sup> ). Particulate matter (PM; that is, the suspended particles in the air of up to 10 micrometres (PM10) or less in size), have damaging effects on human health (Díaz et al. 2017 <sup>[[#fn:r697|697]]</sup> ; Goudarzi et al. 2017 <sup>[[#fn:r698|698]]</sup> ; Goudie 2014 <sup>[[#fn:r699|699]]</sup> ; Samoli et al. 2011 <sup>[[#fn:r700|700]]</sup> ). The health effects of dust storms are largest in areas in the immediate vicinity of their origin, primarily the Sahara Desert, followed by Central and eastern Asia, the Middle East and Australia (Zhang et al. 2016 <sup>[[#fn:r701|701]]</sup> ), however, there is ''robust evidence'' showing that the negative health effects of dust storms reach a much wider area (Bennett et al. 2006 <sup>[[#fn:r702|702]]</sup> ; Díaz et al. 2017 <sup>[[#fn:r703|703]]</sup> ; Kashima et al. 2016 <sup>[[#fn:r704|704]]</sup> ; Lee et al. 2014 <sup>[[#fn:r705|705]]</sup> ; Samoli et al. 2011 <sup>[[#fn:r706|706]]</sup> ; Zhang et al. 2016 <sup>[[#fn:r707|707]]</sup> ). The primary health effects of dust storms include damage to the respiratory and cardiovascular systems (Goudie 2013 <sup>[[#fn:r708|708]]</sup> ). Dust particles with a diameter smaller than 2.5μm were associated with global cardiopulmonary mortality of about 402,000 people in 2005, with 3.47 million years of life lost in that single year (Giannadaki et al. 2014 <sup>[[#fn:r709|709]]</sup> ). Although globally only 1.8% of cardiopulmonary deaths were caused by dust storms, in the countries of the Sahara region, Middle East, South and East Asia, dust storms were suggested to be the cause of 15–50% of all cardiopulmonary deaths (Giannadaki et al. 2014 <sup>[[#fn:r710|710]]</sup> ). A 10 μgm- <sup>3</sup> increase in PM10 dust particles was associated with mean increases in non-accidental mortality from 0.33% to 0.51% across different calendar seasons in China, Japan and South Korea (Kim et al. 2017 <sup>[[#fn:r711|711]]</sup> ). The percentage of all-cause deaths attributed to fine particulate matter in Iranian cities affected by Middle Eastern dust storms (MED) was 0.56–5.02%, while the same percentage for non-affected cities was 0.16–4.13% (Hopke et al. 2018 <sup>[[#fn:r712|712]]</sup> ). Epidemics of meningococcal meningitis occur in the Sahelian region during the dry seasons with dusty conditions (Agier et al. 2012 <sup>[[#fn:r713|713]]</sup> ; Molesworth et al. 2003 <sup>[[#fn:r714|714]]</sup> ). Despite a strong concentration of dust storms in the Sahel, North Africa, the Middle East and Central Asia, there is relatively little research on human health impacts of dust storms in these regions. More research on health impacts and related costs of dust storms, as well as on public health response measures, can help in mitigating these health impacts.

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==== 3.4.2.4 Impacts on gender equality ====

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Environmental issues such as desertification and impacts of climate change have been increasingly investigated through a gender lens (Bose (n.d.) <sup>[[#fn:r715|715]]</sup> ; Broeckhoven and Cliquet 2015 <sup>[[#fn:r716|716]]</sup> ; Kaijser and Kronsell 2014 <sup>[[#fn:r717|717]]</sup> ; Kiptot et al. 2014 <sup>[[#fn:r718|718]]</sup> ; Villamor and van Noordwijk 2016 <sup>[[#fn:r719|719]]</sup> ). There is ''medium evidence'' and ''high agreement'' that women will be impacted more than men by environmental degradation (Arora-Jonsson 2011 <sup>[[#fn:r720|720]]</sup> ; Gurung et al. 2006 <sup>[[#fn:r721|721]]</sup> ) (Cross-Chapter Box 11 in Chapter 7). Socially structured gender-specific roles and responsibilities, daily activities, access and control over resources, decision-making and opportunities lead men and women to interact differently with natural resources and landscapes. For example, water scarcity affected women more than men in rural Ghana as they had to spend more time in fetching water, which has implications on time allocations for other activities (Ahmed et al. 2016 <sup>[[#fn:r722|722]]</sup> ). Despite the evidence pointing to differentiated impact of environmental degradation on women and men, gender issues have been marginally addressed in many land restoration and rehabilitation efforts, which often remain gender-blind. Although there is ''robust evidence'' on the location-specific impacts of climate change and desertification on gender equality, there is l ''imited evidence'' on the gender-related impacts of land restoration and rehabilitation activities. Women are usually excluded from local decision-making on actions regarding desertification and climate change. Socially constructed gender-specific roles and responsibilities are not static because they are shaped by other factors such as wealth, age, ethnicity and formal education (Kaijser and Kronsell 2014 <sup>[[#fn:r723|723]]</sup> ; Villamor et al. 2014 <sup>[[#fn:r724|724]]</sup> ). Hence, women’s and men’s environmental knowledge and priorities for restoration often differ (Sijapati Basnett et al. 2017 <sup>[[#fn:r725|725]]</sup> ). In some areas where sustainable land options (e.g., agroforestry) are being promoted, women were not able to participate due to culturally embedded asymmetries in power relations between men and women (Catacutan and Villamor 2016 <sup>[[#fn:r726|726]]</sup> ). Nonetheless women, particularly in the rural areas, remain heavily involved in securing food for their households. Food security for them is associated with land productivity and women’s contribution to address desertification is crucial.

<div id="section-3-4-2-5-impacts-on-water-scarcity-and-use"></div>

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==== 3.4.2.5 Impacts on water scarcity and use ====

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Reduced water retention capacity of degraded soils amplifies floods (de la Paix et al. 2011 <sup>[[#fn:r727|727]]</sup> ), reinforces degradation processes through soil erosion, and reduces annual intake of water to aquifers, exacerbating existing water scarcities (Le Roux et al. 2017 <sup>[[#fn:r728|728]]</sup> ; Cano et al. 2018 <sup>[[#fn:r729|729]]</sup> ). Reduced vegetation cover and more intense dust storms were found to intensify droughts (Cook et al. 2009 <sup>[[#fn:r730|730]]</sup> ). Moreover, secondary salinisation in the irrigated drylands often requires leaching with considerable amounts of water (Greene et al. 2016 <sup>[[#fn:r731|731]]</sup> ; Wichelns and Qadir 2015 <sup>[[#fn:r732|732]]</sup> ). Thus, different types of soil degradation increase water scarcity both through lower water quantity and quality (Liu et al. 2017 <sup>[[#fn:r733|733]]</sup> ; Liu et al. 2016c <sup>[[#fn:r734|734]]</sup> ). All these processes reduce water availability for other needs. In this context, climate change will further intensify water scarcity in some dryland areas and increase the frequency of droughts ( ''medium confidence'' ) (IPCC 2013 <sup>[[#fn:r735|735]]</sup> ; Zheng et al. 2018 <sup>[[#fn:r736|736]]</sup> ) (Section 2.2). Higher water scarcity may imply growing use of wastewater effluents for irrigation (Pedrero et al. 2010 <sup>[[#fn:r737|737]]</sup> ). The use of untreated wastewater exacerbates soil degradation processes (Tal 2016 <sup>[[#fn:r738|738]]</sup> ; Singh et al. 2004 <sup>[[#fn:r739|739]]</sup> ; Qishlaqi et al. 2008 <sup>[[#fn:r740|740]]</sup> ; Hanjra et al. 2012 <sup>[[#fn:r741|741]]</sup> ), in addition to negative human health impacts (Faour-Klingbeil and Todd 2018 <sup>[[#fn:r742|742]]</sup> ; Hanjra et al. 2012 <sup>[[#fn:r743|743]]</sup> ). Climate change will thus amplify the need for integrated land and water management for sustainable development.

<div id="section-3-4-2-6-impacts-on-energy-infrastructure-through-dust-storms"></div>

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==== 3.4.2.6 Impacts on energy infrastructure through dust storms ====

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Desertification leads to conditions that favour the production of dust storms ( ''high confidence'' ) (Section 3.3.1). There is ''robust evidence'' and ''high agreement'' that dust storms negatively affect the operational potential of solar and wind power harvesting equipment through dust deposition, reduced reach of solar radiation and increasing blade-surface roughness, and can also reduce effective electricity distribution in high-voltage transmission lines (Zidane et al. 2016 <sup>[[#fn:r744|744]]</sup> ; Costa et al. 2016 <sup>[[#fn:r745|745]]</sup> ; Lopez-Garcia et al. 2016 <sup>[[#fn:r746|746]]</sup> ; Maliszewski et al. 2012 <sup>[[#fn:r747|747]]</sup> ; Mani and Pillai 2010 <sup>[[#fn:r748|748]]</sup> ; Mejia and Kleissl 2013 <sup>[[#fn:r749|749]]</sup> ; Mejia et al. 2014 <sup>[[#fn:r750|750]]</sup> ; Middleton 2017 <sup>[[#fn:r751|751]]</sup> ; Sarver et al. 2013 <sup>[[#fn:r752|752]]</sup> ; Kaufman et al. 2002 <sup>[[#fn:r753|753]]</sup> ; Kok et al. 2018 <sup>[[#fn:r754|754]]</sup> ). Direct exposure to desert dust storm can reduce energy generation efficiency of solar panels by 70–80% in one hour (Ghazi et al. 2014 <sup>[[#fn:r755|755]]</sup> ). (Saidan et al. 2016 <sup>[[#fn:r756|756]]</sup> ) indicated that in the conditions of Baghdad, Iraq, one month’s exposure to weather reduced the efficiency of solar modules by 18.74% due to dust deposition. In the Atacama desert, Chile, one month’s exposure reduced thin-film solar module performance by 3.7–4.8% (Fuentealba et al. 2015 <sup>[[#fn:r757|757]]</sup> ). This has important implications for climate change mitigation efforts using the expansion of solar and wind energy generation in dryland areas for substituting fossil fuels. Abundant access to solar energy in many dryland areas makes them high-potential locations for the installation of solar energy generating infrastructure. Increasing desertification, resulting in higher frequency and intensity of dust storms imposes additional costs for climate change mitigation through deployment of solar and wind energy harvesting facilities in dryland areas. Most frequently used solutions to this problem involve physically wiping or washing the surface of solar devices with water. These result in additional costs and excessive use of already scarce water resources and labour (Middleton 2017 <sup>[[#fn:r758|758]]</sup> ). The use of special coatings on the surface of solar panels can help prevent the deposition of dusts (Costa et al. 2016 <sup>[[#fn:r759|759]]</sup> ; Costa et al. 2018 <sup>[[#fn:r760|760]]</sup> ; Gholami et al. 2017 <sup>[[#fn:r761|761]]</sup> ).

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==== 3.4.2.7 Impacts on transport infrastructure through dust storms and sand movement ====

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Dust storms and movement of sand dunes often threaten the safety and operation of railway and road infrastructure in arid and hyper-arid areas, and can lead to road and airport closures due to reductions in visibility. For example, the dust storm on 10 March 2009 over Riyadh was assessed to be the strongest in the previous two decades in Saudi Arabia, causing limited visibility, airport shutdown and damages to infrastructure and environment across the city (Maghrabi et al. 2011 <sup>[[#fn:r762|762]]</sup> ). There are numerous historical examples of how moving sand dunes led to the forced decommissioning of early railway lines built in Sudan, Algeria, Namibia and Saudi Arabia in the late 19th and early 20th century (Bruno et al. 2018 <sup>[[#fn:r763|763]]</sup> ). Currently, the highest concentrations of railways vulnerable to sand movements are located in north-western China, Middle East and North Africa (Bruno et al. 2018 <sup>[[#fn:r764|764]]</sup> ; Cheng and Xue 2014 <sup>[[#fn:r765|765]]</sup> ). In China, sand dune movements are periodically disrupting the railway transport on the Linhai–Ceke line in north-western China and on the Lanzhou–Xinjiang High-speed Railway in western China, with considerable clean-up and maintenance costs (Bruno et al. 2018 <sup>[[#fn:r766|766]]</sup> ; Zhang et al. 2010 <sup>[[#fn:r767|767]]</sup> ). There are large-scale plans for expansion of railway networks in arid areas of China, Central Asia, North Africa, the Middle East, and eastern Africa. For example, The Belt and Road Initiative promoted by China, the Gulf Railway project by the Cooperation Council for the Arab States of the Gulf or Lamu Port–South Sudan–Ethiopia Transport (LAPSSET) Corridor in Eastern Africa. These investments have long-term return and operation periods. Their construction and associated engineering solutions will therefore benefit from careful consideration of potential desertification and climate change effects on sand storms and dune movements.

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==== 3.4.2.8 Impacts on conflicts ====

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There is ''low confidence'' in climate change and desertification leading to violent conflicts. There is ''medium evidence'' and ''low agreement'' that climate change and desertification contribute to already existing conflict potentials (Herrero 2006 <sup>[[#fn:r768|768]]</sup> ; von Uexkull et al. 2016 <sup>[[#fn:r769|769]]</sup> ; Theisen 2017 <sup>[[#fn:r770|770]]</sup> ; Olsson 2017 <sup>[[#fn:r771|771]]</sup> ; Wischnath and Buhaug 2014 <sup>[[#fn:r772|772]]</sup> ) (Section 4.7.3). To illustrate, Hsiang et al. (2013) <sup>[[#fn:r773|773]]</sup> found that each one standard deviation increase in temperature or rainfall was found to increase interpersonal violence by 4% and intergroup conflict by 14% (Hsiang et al. 2013 <sup>[[#fn:r774|774]]</sup> ). However, this conclusion was disputed by Buhaug et al. (2014) <sup>[[#fn:r775|775]]</sup> , who found no evidence linking climate variability to violent conflict after replicating Hsiang et al. (2013) <sup>[[#fn:r776|776]]</sup> by studying only violent conflicts. Almer et al. (2017) <sup>[[#fn:r777|777]]</sup> found that a one standard deviation increase in dryness raised the likelihood of riots in Sub-Saharan African countries by 8.3% during the 1990–2011 period. On the other hand, Owain and Maslin (2018) <sup>[[#fn:r778|778]]</sup> found that droughts and heatwaves were not significantly affecting the level of regional conflict in East Africa. Similarly, it was suggested that droughts and desertification in the Sahel played a relatively minor role in the conflicts in the Sahel in the 1980s, with the major reasons for the conflicts during this period being political, especially the marginalisation of pastoralists (Benjaminsen 2016 <sup>[[#fn:r779|779]]</sup> ), corruption and rent-seeking (Benjaminsen et al. 2012 <sup>[[#fn:r780|780]]</sup> ). Moreover, the role of environmental factors as the key drivers of conflicts was questioned in the case of Sudan (Verhoeven 2011 <sup>[[#fn:r781|781]]</sup> ) and Syria (De Châtel 2014 <sup>[[#fn:r782|782]]</sup> ). Selection bias, when the literature focuses on the same few regions where conflicts occurred and relates them to climate change, is a major shortcoming, as it ignores other cases where conflicts did not occur (Adams et al. 2018 <sup>[[#fn:r783|783]]</sup> ) despite degradation of the natural resource base and extreme weather events.

<div id="section-3-4-2-9-impacts-on-migration"></div>

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==== 3.4.2.9 Impacts on migration ====

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Environmentally induced migration is complex and accounts for multiple drivers of mobility as well as other adaptation measures undertaken by populations exposed to environmental risk ( ''high confidence'' ). There is ''medium evidence'' and ''low agreement'' that climate change impacts migration. The World Bank (2018) <sup>[[#fn:r784|784]]</sup> predicted that 143 million people would be forced to move internally by 2050 if no climate action is taken. Focusing on asylum seekers alone, rather than the total number of migrants, Missirian and Schlenker (2017) <sup>[[#fn:r785|785]]</sup> predict that asylum applications to the European Union will increase from 28% (98,000 additional asylum applications per year) up to 188% (660,000 additional applications per year) depending on the climate scenario by 2100. While the modelling efforts have greatly improved over the years (Hunter et al. 2015 <sup>[[#fn:r786|786]]</sup> ; McLeman 2011 <sup>[[#fn:r787|787]]</sup> ; Sherbinin and Bai 2018 <sup>[[#fn:r788|788]]</sup> ) and in particular, these recent estimates provide an important insight into potential future developments, the quantitative projections are still based on the number of people exposed to risk rather than the number of people who would actually engage in migration as a response to this risk (Gemenne 2011 <sup>[[#fn:r789|789]]</sup> ; McLeman 2013 <sup>[[#fn:r790|790]]</sup> ) and they do not take into account individual agency in migration decision nor adaptive capacities of individuals (Hartmann 2010 <sup>[[#fn:r791|791]]</sup> ; Kniveton et al. 2011 <sup>[[#fn:r792|792]]</sup> ; Piguet 2010 <sup>[[#fn:r793|793]]</sup> ) (see Section 3.6.2 discussing migration as a response to desertification). Accordingly, the available micro-level evidence suggests that climate-related shocks are one of the many drivers of migration (Adger et al. 2014 <sup>[[#fn:r794|794]]</sup> ; London Government Office for Science and Foresight 2011 <sup>[[#fn:r795|795]]</sup> ; Melde et al. 2017 <sup>[[#fn:r796|796]]</sup> ), but the individual responses to climate risk are more complex than commonly assumed (Gray and Mueller 2012a <sup>[[#fn:r797|797]]</sup> ). For example, despite strong focus on natural disasters, neither flooding (Gray and Mueller 2012b <sup>[[#fn:r798|798]]</sup> ; Mueller et al. 2014 <sup>[[#fn:r799|799]]</sup> ) nor earthquakes (Halliday 2006 <sup>[[#fn:r800|800]]</sup> ) were found to induce long-term migration; but instead, slow-onset changes, especially those provoking crop failures and heat stress, could affect household or individual migration decisions (Gray and Mueller 2012a <sup>[[#fn:r801|801]]</sup> ; Missirian and Schlenker 2017 <sup>[[#fn:r802|802]]</sup> ; Mueller et al. 2014 <sup>[[#fn:r803|803]]</sup> ). Out-migration from drought-prone areas has received particular attention (de Sherbinin et al. 2012 <sup>[[#fn:r804|804]]</sup> ; Ezra and Kiros 2001 <sup>[[#fn:r805|805]]</sup> ). A substantial body of literature suggests that households engage in local or internal migration as a response to drought (Findlay 2011 <sup>[[#fn:r806|806]]</sup> ; Gray and Mueller 2012a <sup>[[#fn:r807|807]]</sup> ), while international migration decreases with drought in some contexts (Henry et al. 2004 <sup>[[#fn:r808|808]]</sup> ), but might increase in contexts where migration networks are well established (Feng et al. 2010 <sup>[[#fn:r809|809]]</sup> ; Nawrotzki and DeWaard 2016 <sup>[[#fn:r810|810]]</sup> ; Nawrotzki et al. 2015 <sup>[[#fn:r811|811]]</sup> , 2016 <sup>[[#fn:r812|812]]</sup> ). Similarly, the evidence is not conclusive with respect to the effect of environmental drivers, in particular desertification, on mobility. While it has not consistently entailed out-migration in the case of Ecuadorian Andes (Gray 2009, 2010 <sup>[[#fn:r813|813]]</sup> ), environmental and land degradation increased mobility in Kenya and Nepal (Gray 2011 <sup>[[#fn:r814|814]]</sup> ; Massey et al. 2010 <sup>[[#fn:r815|815]]</sup> ), but marginally decreased mobility in Uganda (Gray 2011 <sup>[[#fn:r816|816]]</sup> ). These results suggest that in some contexts, environmental shocks actually undermine households’ financial capacity to undertake migration (Nawrotzki and Bakhtsiyarava 2017 <sup>[[#fn:r817|817]]</sup> ), especially in the case of the poorest households (Barbier and Hochard 2018 <sup>[[#fn:r818|818]]</sup> ; Koubi et al. 2016 <sup>[[#fn:r819|819]]</sup> ; Kubik and Maurel 2016 <sup>[[#fn:r820|820]]</sup> ; McKenzie and Yang 2015 <sup>[[#fn:r821|821]]</sup> ). Adding to the complexity, migration, especially to frontier areas, by increasing pressure on land and natural resources, might itself contribute to environmental degradation at the destination (Hugo 2008 <sup>[[#fn:r822|822]]</sup> ; IPBES 2018a <sup>[[#fn:r823|823]]</sup> ; McLeman 2017 <sup>[[#fn:r824|824]]</sup> ). The consequences of migration can also be salient in the case of migration to urban or peri-urban areas; indeed, environmentally induced migration can add to urbanisation (Section 3.6.2.2), often exacerbating problems related to poor infrastructure and unemployment.

<div id="section-3-4-2-10-impacts-on-pastoral-communities"></div>

<span id="impacts-on-pastoral-communities"></span>
==== 3.4.2.10 Impacts on pastoral communities ====

<div id="section-3-4-2-10-impacts-on-pastoral-communities-block-1"></div>

Pastoral production systems occupy a significant portion of the world (Rass 2006 <sup>[[#fn:r825|825]]</sup> ; Dong 2016 <sup>[[#fn:r826|826]]</sup> ). Food insecurity among pastoral households is often high (Gomes 2006 <sup>[[#fn:r827|827]]</sup> ) (Section 3.1.3). The Sahelian droughts of the 1970s–1980s provided an example of how droughts could affect livestock resources and crop productivity, contributing to hunger, out-migration and suffering for millions of pastoralists (Hein and De Ridder 2006 <sup>[[#fn:r828|828]]</sup> ; Molua and Lambi 2007 <sup>[[#fn:r829|829]]</sup> ). During these Sahelian droughts low and erratic rainfall exacerbated desertification processes, leading to ecological changes that forced people to use marginal lands and ecosystems. Similarly, the rate of rangeland degradation is now increasing because of environmental changes and overexploitation of resources (Kassahun et al. 2008 <sup>[[#fn:r830|830]]</sup> ; Vetter 2005 <sup>[[#fn:r831|831]]</sup> ). Desertification coupled with climate change is negatively affecting livestock feed and grazing species (Hopkins and Del Prado 2007 <sup>[[#fn:r832|832]]</sup> ), changing the composition in favour of species with low forage quality, ultimately reducing livestock productivity (D’Odorico et al. 2013 <sup>[[#fn:r833|833]]</sup> ; Dibari et al. 2016 <sup>[[#fn:r834|834]]</sup> ) and increasing livestock disease prevalence (Thornton et al. 2009 <sup>[[#fn:r849|849]]</sup> ). There is ''robust evidence'' and ''high agreement'' that weak adaptive capacity, coupled with negative effects from other climate-related factors, are predisposing pastoralists to increased poverty from desertification and climate change globally (López-i-Gelats et al. 2016 <sup>[[#fn:r835|835]]</sup> ; Giannini et al. 2008 <sup>[[#fn:r836|836]]</sup> ; IPCC 2007 <sup>[[#fn:r837|837]]</sup> ). On the other hand, misguided policies such as enforced sedentarisation, and in certain cases protected area delineation (fencing), which restrict livestock mobility have hampered optimal use of grazing land resources (Du 2012 <sup>[[#fn:r838|838]]</sup> ). Such policies have led to degradation of resources and out-migration of people in search of better livelihoods (Gebeye 2016 <sup>[[#fn:r839|839]]</sup> ; Liao et al. 2015 <sup>[[#fn:r840|840]]</sup> ). Restrictions on the mobile lifestyle are reducing the resilient adaptive capacity of pastoralists to natural hazards including extreme and variable weather conditions, drought and climate change (Schilling et al. 2014 <sup>[[#fn:r841|841]]</sup> ). Furthermore, the exacerbation of the desertification phenomenon due to agricultural intensification (D’Odorico et al. 2013 <sup>[[#fn:r842|842]]</sup> ) and land fragmentation caused by encroachment of agriculture into rangelands (Otuoma et al. 2009 <sup>[[#fn:r843|843]]</sup> ; Behnke and Kerven 2013 <sup>[[#fn:r844|844]]</sup> ) is threatening pastoral livelihoods. For example, commercial cotton ( ''Gossypium hirsutum'' ) production is crowding out pastoral systems in Benin (Tamou et al. 2018 <sup>[[#fn:r845|845]]</sup> ). Food shortages and the urgency to produce enough crop for public consumption are leading to the encroachment of agriculture into productive rangelands and those converted rangelands are frequently prime lands used by pastoralists to produce feed and graze their livestock during dry years (Dodd 1994 <sup>[[#fn:r846|846]]</sup> ). The sustainability of pastoral systems is therefore coming into question because of social and political marginalisation of those systems (Davies et al. 2016 <sup>[[#fn:r847|847]]</sup> ) and also because of the fierce competition they are facing from other livelihood sources such as crop farming (Haan et al. 2016 <sup>[[#fn:r848|848]]</sup> ).

<span id="future-projections"></span>