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

== 3.1 The nature of desertification ==

<span id="introduction"></span>
=== 3.1.1 Introduction ===

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In this report, desertification is defined as land degradation in arid, semi-arid, and dry sub-humid areas resulting from many factors, including climatic variations and human activities (United Nations Convention to Combat Desertification (UNCCD) 1994). Land degradation is a negative trend in land condition, caused by direct or indirect human-induced processes including anthropogenic climate change, expressed as long-term reduction or loss of at least one of the following: biological productivity, ecological integrity or value to humans (Section 4.1.3). Arid, semi-arid, and dry sub-humid areas, together with hyper-arid areas, constitute drylands (UNEP 1992 <sup>[[#fn:r1|1]]</sup> ), home to about 3 billion people (van der Esch et al. 2017 <sup>[[#fn:r2|2]]</sup> ). The difference between desertification and land degradation is not process-based but geographic. Although land degradation can occur anywhere across the world, when it occurs in drylands, it is considered desertification (FAQ 1.3). Desertification is not limited to irreversible forms of land degradation, nor is it equated to desert expansion, but represents all forms and levels of land degradation occurring in drylands.

The geographic classification of drylands is often based on the aridity index (AI) – the ratio of average annual precipitation amount (P) to potential evapotranspiration amount (PET, see Glossary) (Figure 3.1). Recent estimates, based on AI, suggest that drylands cover about 46.2% (±0.8%) of the global land area (Koutroulis 2019 <sup>[[#fn:r3|3]]</sup> ; Prăvălie 2016 <sup>[[#fn:r4|4]]</sup> ) ( ''low confidence'' ). Hyper-arid areas, where the aridity index is below 0.05, are included in drylands, but are excluded from the definition of desertification (UNCCD 1994 <sup>[[#fn:r5|5]]</sup> ). Deserts are valuable ecosystems (UNEP 2006 <sup>[[#fn:r6|6]]</sup> ; Safriel 2009 <sup>[[#fn:r7|7]]</sup> ) geographically located in drylands and vulnerable to climate change. However, they are not considered prone to desertification. Aridity is a long-term climatic feature characterised by low average precipitation or available water (Gbeckor-Kove 1989 <sup>[[#fn:r8|8]]</sup> ; Türkeş 1999 <sup>[[#fn:r9|9]]</sup> ). Thus, aridity is different from drought, which is a temporary climatic event (Maliva and Missimer 2012 <sup>[[#fn:r10|10]]</sup> ). Moreover, droughts are not restricted to drylands, but occur both in drylands and humid areas (Wilhite et al. 2014 <sup>[[#fn:r11|11]]</sup> ). Following the Synthesis Report (SYR) of the IPCC Fifth Assessment Report (AR5), drought is defined here as “a period of abnormally dry weather long enough to cause a serious hydrological imbalance” (Mach et al. 2014 <sup>[[#fn:r12|12]]</sup> ) (Cross-Chapter Box 5 in this chapter).

AI is not an accurate proxy for delineating drylands in an increasing CO <sub>2</sub> environment (Section 3.2.1). The suggestion that most of the world has become more arid, since the AI has decreased, is not supported by changes observed in precipitation, evaporation or drought (Sheffield et al. 2012 <sup>[[#fn:r13|13]]</sup> ; Greve et al. 2014 <sup>[[#fn:r14|14]]</sup> ). While climate change is expected to decrease the AI due to increases in potential evaporation, the assumptions that underpin the potential evaporation calculation are not consistent with a changing CO <sub>2</sub> environment and the effect this has on transpiration rates (Roderick et al. 2015 <sup>[[#fn:r15|15]]</sup> ; Milly and Dunne 2016 <sup>[[#fn:r16|16]]</sup> ; Greve et al. 2017 <sup>[[#fn:r17|17]]</sup> ) (Section 3.2.1). Given that future climate is characterised by significant increases in CO <sub>2</sub> , the usefulness of currently applied AI thresholds to estimate dryland areas is limited under climate change. If instead of the AI, other variables such as precipitation, soil moisture, and primary productivity are used to identify dryland areas, there is no clear indication that the extent of drylands will change overall under climate change (Roderick et al. 2015 <sup>[[#fn:r18|18]]</sup> ; Greve et al. 2017 <sup>[[#fn:r19|19]]</sup> ; Lemordant et al. 2018 <sup>[[#fn:r20|20]]</sup> ). Thus, some dryland borders will expand, while some others will contract ( ''high confidence'' ).

Approximately 70% of dryland areas are located in Africa and Asia (Figure 3.2). The biggest land use/cover in terms of area in drylands, if deserts are excluded, are grasslands, followed by forests and croplands (Figure 3.3). The category of ‘other lands’ in Figure 3.3 includes bare soil, ice, rock, and all other land areas that are not included within the other five categories (FAO 2016 <sup>[[#fn:r21|21]]</sup> ). Thus, hyper-arid areas contain mostly deserts, with some small exceptions, for example, where grasslands and croplands are cultivated under oasis conditions with irrigation (Section 3.7.4). Moreover, FAO (2016) <sup>[[#fn:r1786|1786]]</sup> defines grasslands as permanent pastures and meadows used continuously for more than five years. In drylands, transhumance, i.e. seasonal migratory grazing, often leads to non-permanent pasture systems, thus some of the areas under the ‘other land’ category are also used as non-permanent pastures (Ramankutty et al. 2008 <sup>[[#fn:r22|22]]</sup> ; Fetzel et al. 2017 <sup>[[#fn:r23|23]]</sup> ; Erb et al. 2016 <sup>[[#fn:r24|24]]</sup> ).

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<span id="figure-3.1"></span>
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'''Figure 3.1'''

<span id="geographical-distribution-of-drylands-delimited-based-on-the-aridity-index-ai.-the-classification-of-ai-is-humid-ai-0.65-dry-sub-humid-0.50-ai-0.65-semi-arid-0.20-ai-0.50-arid-0.05-ai-0.20-hyper-arid-ai-0.05.-data-terraclimate-precipitation-and-potential-evapotranspiration-19802015-abatzoglou-et-al.-2018."></span>
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'''Geographical distribution of drylands, delimited based on the aridity index (AI). The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).'''
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[[File:2d902f3f9347deee691548e052becdac C3_Figure-3.1-1024x455.jpg]]

Geographical distribution of drylands, delimited based on the aridity index (AI). The classification of AI is: Humid AI &gt; 0.65, Dry sub-humid 0.50 &lt; AI ≤ 0.65, Semi-arid 0.20 &lt; AI ≤ 0.50, Arid 0.05 &lt; AI ≤ 0.20, Hyper-arid AI &lt; 0.05. Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018 <sup>[[#fn:r1787|1787]]</sup> ).

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<span id="figure-3.2"></span>
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'''Figure 3.2'''

<span id="dryland-categories-across-geographical-areas-continents-and-pacific-region.-data-terraclimate-precipitation-and-potential-evapotranspiration-19802015-abatzoglou-et-al.-2018."></span>
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'''Dryland categories across geographical areas (continents and Pacific region). Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018).'''
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[[File:83a75298bfa247ed8c5a870d124591cb Figure-3.2-1024x577.jpg]]

Dryland categories across geographical areas (continents and Pacific region). Data: TerraClimate precipitation and potential evapotranspiration (1980–2015) (Abatzoglou et al. 2018 <sup>[[#fn:r1788|1788]]</sup> ).

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In the earlier global assessments of desertification (since the 1970s), which were based on qualitative expert evaluations, the extent of desertification was found to range between 4% and 70% of the area of drylands (Safriel 2007 <sup>[[#fn:r25|25]]</sup> ). More recent estimates, based on remotely sensed data, show that about 24–29% of the global land area experienced reductions in biomass productivity between the 1980s and 2000s (Bai et al. 2008 <sup>[[#fn:r26|26]]</sup> ; Le et al. 2016 <sup>[[#fn:r27|27]]</sup> ), corresponding to about 9.2% of drylands (±0.5%) experiencing declines in biomass productivity during this period ( ''low confidence'' ), mainly due to anthropogenic causes. Both of these studies consider rainfall dynamics, thus, accounting for the effect of droughts. While less than 10% of drylands is undergoing desertification, it is occurring in areas that contain around 20% of dryland population (Klein Goldewijk et al. 2017 <sup>[[#fn:r28|28]]</sup> ). In these areas the population has increased from approximately 172 million in 1950 to over 630 million today (Figure 1.1).

Available assessments of the global extent and severity of desertification are relatively crude approximations with considerable uncertainties, for example, due to confounding effects of invasive bush encroachment in some dryland regions. Different indicator sets and approaches have been developed for monitoring and assessment of desertification from national to global scales (Imeson 2012 <sup>[[#fn:r29|29]]</sup> ; Sommer et al. 2011 <sup>[[#fn:r30|30]]</sup> ; Zucca et al. 2012 <sup>[[#fn:r31|31]]</sup> ; Bestelmeyer et al. 2013 <sup>[[#fn:r32|32]]</sup> ). Many indicators of desertification only include a single factor or characteristic of desertification, such as the patch size distribution of vegetation (Maestre and Escudero 2009 <sup>[[#fn:r33|33]]</sup> ; Kéfi et al. 2010 <sup>[[#fn:r34|34]]</sup> ), Normalized Difference Vegetation Index (NDVI) (Piao et al. 2005 <sup>[[#fn:r35|35]]</sup> ), drought-tolerant plant species (An et al. 2007), grass cover (Bestelmeyer et al. 2013 <sup>[[#fn:r36|36]]</sup> ), land productivity dynamics (Baskan et al. 2017 <sup>[[#fn:r37|37]]</sup> ), ecosystem net primary productivity (Zhou et al. 2015 <sup>[[#fn:r38|38]]</sup> ) or Environmentally Sensitive Land Area Index (Symeonakis et al. 2016 <sup>[[#fn:r39|39]]</sup> ). In addition, some synthetic indicators of desertification have also been used to assess desertification extent and desertification processes, such as climate, land use, soil, and socio-economic parameters (Dharumarajan et al. 2018 <sup>[[#fn:r40|40]]</sup> ), or changes in climate, land use, vegetation cover, soil properties and population as the desertification vulnerability index (Salvati et al. 2009 <sup>[[#fn:r41|41]]</sup> ). Current data availability and methodological challenges do not allow for accurately and comprehensively mapping desertification at a global scale (Cherlet et al. 2018 <sup>[[#fn:r42|42]]</sup> ). However, the emerging partial evidence points to a lower global extent of desertification than previously estimated ( ''medium confidence'' ) (Section 3.2).

This assessment examines the socio-ecological links between drivers (Section 3.1) and feedbacks (Section 3.3) that influence desertification–climate change interactions, and then examines associated observed and projected impacts (Sections 3.4 and 3.5) and responses (Section 3.6). Moreover, this assessment highlights that dryland populations are highly vulnerable to desertification and climate change (Sections 3.2 and 3.4). At the same time, dryland populations also have significant past experience and sources of resilience embodied in indigenous and local knowledge and practices in order to successfully adapt to climatic changes and address desertification (Section 3.6). Numerous site-specific technological response options are also available for SLM in drylands that can help increase the resilience of agricultural livelihood systems to climate change (Section 3.6). However, continuing environmental degradation combined with climate change is straining the resilience of dryland populations. Enabling policy responses for SLM and livelihoods diversification can help maintain and strengthen the resilience and adaptive capacities in dryland areas (Section 3.6). The assessment finds that policies promoting SLM in drylands will contribute to climate change adaptation and mitigation, with co-benefits for broader sustainable development ( ''high confidence'' ) (Section 3.4).

<div id="section-3-1-1-introduction-block-5"></div>

<span id="figure-3.3"></span>
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'''Figure 3.3'''

<span id="land-use-and-land-cover-in-drylands-and-share-of-each-dryland-category-in-global-land-area.-source-fao-2016."></span>
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'''Land use and land cover in drylands and share of each dryland category in global land area. Source: FAO (2016).'''
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[[File:69315d223573506a44817d84bd4d03f4 Figure-3.3-1024x599.jpg]]

Land use and land cover in drylands and share of each dryland category in global land area. Source: FAO (2016) <sup>[[#fn:r1789|1789]]</sup> .

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<span id="desertification-in-previous-ipcc-and-related-reports"></span>
=== 3.1.2 Desertification in previous IPCC and related reports ===

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The IPCC Fifth Assessment Report (AR5) and Special Report on Global Warming of 1.5°C include a limited discussion of desertification. In AR5 Working Group I desertification is mentioned as a forcing agent for the production of atmospheric dust (Myhre et al. 2013 <sup>[[#fn:r43|43]]</sup> ). The same report had low confidence in the available projections on the changes in dust loadings due to climate change (Boucher et al. 2013 <sup>[[#fn:r44|44]]</sup> ). In AR5 Working Group II desertification is identified as a process that can lead to reductions in crop yields and the resilience of agricultural and pastoral livelihoods (Field et al. 2014 <sup>[[#fn:r45|45]]</sup> ; Klein et al. 2015 <sup>[[#fn:r46|46]]</sup> ). AR5 Working Group II notes that climate change will amplify water scarcity, with negative impacts on agricultural systems, particularly in semi-arid environments of Africa ( ''high confidence'' ), while droughts could exacerbate desertification in southwestern parts of Central Asia (Field et al. 2014). AR5 Working Group III identifies desertification as one of a number of often overlapping issues that must be dealt with when considering governance of mitigation and adaptation (Fleurbaey et al. 2014 <sup>[[#fn:r47|47]]</sup> ). The IPCC Special Report on Global Warming of 1.5°C noted that limiting global warming to 1.5°C instead of 2°C is strongly beneficial for land ecosystems and their services ( ''high confidence'' ) such as soil conservation, contributing to avoidance of desertification (Hoegh-Guldberg et al. 2018 <sup>[[#fn:r48|48]]</sup> ).

The recent Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) Land Degradation and Restoration Assessment report (IPBES 2018a <sup>[[#fn:r49|49]]</sup> ) is also of particular relevance. While acknowledging a wide variety of past estimates of the area undergoing degradation, IPBES (2018a) pointed at their lack of agreement about where degradation is taking place. IPBES (2018a) also recognised the challenges associated with differentiating the impacts of climate variability and change on land degradation from the impacts of human activities at a regional or global scale.

The third edition of the World Atlas of Desertification (Cherlet et al. 2018 <sup>[[#fn:r50|50]]</sup> ) indicated that it is not possible to deterministically map the global extent of land degradation – and its subset, desertification – pointing out that the complexity of interactions between social, economic, and environmental systems make land degradation not amenable to mapping at a global scale. Instead, Cherlet et al. (2018) presented global maps highlighting the convergence of various pressures on land resources.

<span id="dryland-populations-vulnerability-and-resilience"></span>
=== 3.1.3 Dryland populations: Vulnerability and resilience ===

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Drylands are home to approximately 38.2% (±0.6%) of the global population (Koutroulis 2019 <sup>[[#fn:r51|51]]</sup> ; van der Esch et al. 2017 <sup>[[#fn:r52|52]]</sup> ), that is about 3 billion people. The highest number of people live in the drylands of South Asia (Figure 3.4), followed by Sub-Saharan Africa and Latin America (van der Esch et al. 2017 <sup>[[#fn:r53|53]]</sup> ). In terms of the number of people affected by desertification, Reynolds et al. (2007) indicated that desertification was directly affecting 250 million people. More recent estimates show that 500 (±120) million people lived in 2015 in those dryland areas which experienced significant loss in biomass productivity between the 1980s and 2000s (Bai et al. 2008 <sup>[[#fn:r54|54]]</sup> ; Le et al. 2016 <sup>[[#fn:r55|55]]</sup> ). The highest numbers of affected people were in South and East Asia, North Africa and the Middle East (l ''ow confidence'' ). The population in drylands is projected to increase about twice as rapidly as non-drylands, reaching 4 billion people by 2050 (van der Esch et al. 2017 <sup>[[#fn:r56|56]]</sup> ). This is due to higher population growth rates in drylands. About 90% of the population in drylands live in developing countries (UN-EMG 2011 <sup>[[#fn:r57|57]]</sup> ).

<div id="section-3-1-3-dryland-populations-vulnerability-and-resilience-block-2"></div>

<span id="figure-3.4"></span>
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'''Figure 3.4'''

<span id="current-and-projected-population-under-ssp2-in-drylands-in-billions.-source-van-der-esch-et-al.-2017."></span>
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'''Current and projected population (under SSP2) in drylands, in billions. Source: van der Esch et al. (2017).'''
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[[File:65c76dd134c3d3fdf2e8b85709dca4d6 Figure-3.4-1024x398.jpg]]

Current and projected population (under SSP2) in drylands, in billions. Source: van der Esch et al. (2017) <sup>[[#fn:r1790|1790]]</sup> .

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<div id="section-3-1-3-dryland-populations-vulnerability-and-resilience-block-3"></div>

Dryland populations are highly vulnerable to desertification and climate change because their livelihoods are predominantly dependent on agriculture, one of the sectors most susceptible to climate change (Rosenzweig et al. 2014 <sup>[[#fn:r58|58]]</sup> ; Schlenker and Lobell 2010 <sup>[[#fn:r59|59]]</sup> ). Climate change is projected to have substantial impacts on all types of agricultural livelihood systems in drylands (CGIAR-RPDS 2014 <sup>[[#fn:r60|60]]</sup> ) (Sections 3.4.1 and 3.4.2).

One key vulnerable group in drylands are pastoral and agropastoral households <sup>[[#fn:1|1]]</sup> . There are no precise figures about the number of people practicing pastoralism globally. Most estimates range between 100 million and 200 million (Rass 2006 <sup>[[#fn:r61|61]]</sup> ; Secretariat of the Convention on Biological Diversity 2010 <sup>[[#fn:r62|62]]</sup> ), of whom 30–63 million are nomadic pastoralists (Dong 2016 <sup>[[#fn:r63|63]]</sup> ; Carr-Hill 2013 <sup>[[#fn:r64|64]]</sup> ) <sup>[[#fn:2|2]]</sup>

Pastoral production systems represent an adaptation to high seasonal climate variability and low biomass productivity in dryland ecosystems (Varghese and Singh 2016 <sup>[[#fn:r65|65]]</sup> ; Krätli and Schareika 2010 <sup>[[#fn:r66|66]]</sup> ), which require large areas for livestock grazing through migratory pastoralism (Snorek et al. 2014 <sup>[[#fn:r67|67]]</sup> ). Grazing lands across dryland environments are being degraded, and/or being converted to crop production, limiting the opportunities for migratory livestock systems, and leading to conflicts with sedentary crop producers (Abbass 2014 <sup>[[#fn:r68|68]]</sup> ; Dimelu et al. 2016 <sup>[[#fn:r69|69]]</sup> ). These processes, coupled with ethnic differences, perceived security threats, and misunderstanding of pastoral rationality, have led to increasing marginalisation of pastoral communities and disruption of their economic and cultural structures (Elhadary 2014 <sup>[[#fn:r70|70]]</sup> ; Morton 2010 <sup>[[#fn:r71|71]]</sup> ). As a result, pastoral communities are not well prepared to deal with increasing weather/climate variability and weather/climate extremes due to changing climate (Dong 2016 <sup>[[#fn:r72|72]]</sup> ; López-i-Gelats et al. 2016 <sup>[[#fn:r73|73]]</sup> ), and remain amongst the most food insecure groups in the world (FAO 2018).

There is an increasing concentration of poverty in the dryland areas of Sub-Saharan Africa and South Asia (von Braun and Gatzweiler 2014 <sup>[[#fn:r74|74]]</sup> ; Barbier and Hochard 2016) <sup>[[#fn:r75|75]]</sup> , where 41% and 12% of the total populations live in extreme poverty, respectively (World Bank 2018 <sup>[[#fn:r76|76]]</sup> ). For comparison, the average share of global population living in extreme poverty is about 10% (World Bank 2018 <sup>[[#fn:r77|77]]</sup> ). Multidimensional poverty, prevalent in many dryland areas, is a key source of vulnerability (Safriel et al. 2005 <sup>[[#fn:r78|78]]</sup> ; Thornton et al. 2014 <sup>[[#fn:r79|79]]</sup> ; Fraser et al. 2011 <sup>[[#fn:r80|80]]</sup> ; Thomas 2008 <sup>[[#fn:r81|81]]</sup> ). Multidimensional poverty incorporates both income-based poverty, and also other dimensions such as poor healthcare services, lack of education, lack of access to water, sanitation and energy, disempowerment, and threat from violence (Bourguignon and Chakravarty 2003 <sup>[[#fn:r82|82]]</sup> ; Alkire and Santos 2010 <sup>[[#fn:r83|83]]</sup> , 2014 <sup>[[#fn:r84|84]]</sup> ). Contributing elements to this multidimensional poverty in drylands are rapid population growth, fragile institutional environment, lack of infrastructure, geographic isolation and low market access, insecure land tenure systems, and low agricultural productivity (Sietz et al. 2011 <sup>[[#fn:r85|85]]</sup> ; Reynolds et al. 2011 <sup>[[#fn:r86|86]]</sup> ; Safriel and Adeel 2008 <sup>[[#fn:r87|87]]</sup> ; Stafford Smith 2016 <sup>[[#fn:r88|88]]</sup> ). Even in high-income countries, those dryland areas that depend on agricultural livelihoods represent relatively poorer locations nationally, with fewer livelihood opportunities, for example in Italy (Salvati 2014 <sup>[[#fn:r89|89]]</sup> ). Moreover, in many drylands areas, female-headed households, women and subsistence farmers (both male and female) are more vulnerable to the impacts of desertification and climate change (Nyantakyi-Frimpong and Bezner-Kerr 2015 <sup>[[#fn:r90|90]]</sup> ; Sultana 2014 <sup>[[#fn:r91|91]]</sup> ; Rahman 2013 <sup>[[#fn:r92|92]]</sup> ). Some local cultural traditions and patriarchal relationships were found to contribute to higher vulnerability of women and female-headed households through restrictions on their access to productive resources (Nyantakyi-Frimpong and Bezner-Kerr 2015 <sup>[[#fn:r94|94]]</sup> ; Sultana 2014 <sup>[[#fn:r95|95]]</sup> ; Rahman 2013 <sup>[[#fn:r1791|1791]]</sup> ) (Sections 3.4.2 and 3.6.3, and Cross-Chapter Box 11 in Chapter 7).

Despite these environmental, socio-economic and institutional constraints, dryland populations have historically demonstrated remarkable resilience, ingenuity and innovations, distilled into ILK to cope with high climatic variability and sustain livelihoods (Safriel and Adeel 2008 <sup>[[#fn:r96|96]]</sup> ; Davis 2016 <sup>[[#fn:r97|97]]</sup> ; Davies 2017 <sup>[[#fn:r98|98]]</sup> ) (Sections 3.6.1 and 3.6.2, and Cross-Chapter Box 13 in Chapter 7). For example, across the Arabian Peninsula and North Africa, informal community by-laws were successfully used for regulating grazing, collection and cutting of herbs and wood, and which limited rangeland degradation (Gari 2006 <sup>[[#fn:r99|99]]</sup> ; Hussein 2011 <sup>[[#fn:r100|100]]</sup> ). Pastoralists in Mongolia developed indigenous classifications of pasture resources which facilitated ecologically optimal grazing practices (Fernandez-Gimenez 2000 <sup>[[#fn:r101|101]]</sup> ) (Section 3.6.2). Currently, however, indigenous and local knowledge and practices are increasingly lost or can no longer cope with growing demands for land-based resources (Dominguez 2014 <sup>[[#fn:r102|102]]</sup> ; Fernández-Giménez and Fillat Estaque 2012 <sup>[[#fn:r103|103]]</sup> ; Hussein 2011 <sup>[[#fn:r104|104]]</sup> ; Kodirekkala 2017 <sup>[[#fn:r105|105]]</sup> ; Moreno-Calles et al. 2012 <sup>[[#fn:r106|106]]</sup> ) (Section 3.4.2). Unsustainable land management is increasing the risks from droughts, floods and dust storms (Sections 3.4.2 and 3.5). Policy actions promoting the adoption of SLM practices in dryland areas, based on both indigenous and local knowledge and modern science, and expanding alternative livelihood opportunities outside agriculture can contribute to climate change adaptation and mitigation, addressing desertification, with co-benefits for poverty eradication and food security ( ''high confidence'' ) (Cowie et al. 2018 <sup>[[#fn:r107|107]]</sup> ; Liniger et al. 2017 <sup>[[#fn:r108|108]]</sup> ; Safriel and Adeel 2008 <sup>[[#fn:r109|109]]</sup> ; Stafford-Smith et al. 2017 <sup>[[#fn:r110|110]]</sup> ).

<span id="processes-and-drivers-of-desertification-under-climate-change"></span>
=== 3.1.4 Processes and drivers of desertification under climate change ===

<div id="section-3-1-4-1-processes-of-desertification-and-their-climatic-drivers"></div>

<span id="processes-of-desertification-and-their-climatic-drivers"></span>
==== 3.1.4.1 Processes of desertification and their climatic drivers ====

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'''Processes of desertification''' are mechanisms by which drylands are degraded. Desertification consists of both biological and non-biological processes. These processes are classified under broad categories of degradation of physical, chemical and biological properties of terrestrial ecosystems. The number of desertification processes is large and they are extensively covered elsewhere (IPBES 2018a <sup>[[#fn:r111|111]]</sup> ; Lal 2016 <sup>[[#fn:r112|112]]</sup> ; Racine 2008 <sup>[[#fn:r113|113]]</sup> ; UNCCD 2017 <sup>[[#fn:r114|114]]</sup> ). Section 4.2.1 and Tables 4.1 and 4.2 in Chapter 4 highlight those which are particularly relevant for this assessment in terms of their links to climate change and land degradation, including desertification.

'''Drivers of desertification''' are factors which trigger desertification processes. Initial studies of desertification during the early-to-mid 20th century attributed it entirely to human activities. In one of the influential publications of that time, Lavauden (1927) <sup>[[#fn:r115|115]]</sup> stated that: “Desertification is purely artificial. It is only the act of the man…” However, such a uni-causal view of desertification was shown to be invalid (Geist et al. 2004 <sup>[[#fn:r116|116]]</sup> ; Reynolds et al. 2007 <sup>[[#fn:r117|117]]</sup> ) (Sections 3.1.4.2 and 3.1.4.3). Tables 4.1 and 4.2 in Chapter 4 summarise the drivers, linking them to the specific processes of desertification and land degradation under changing climate.

Erosion refers to removal of soil by the physical forces of water, wind, or often caused by farming activities such as tillage (Ginoux et al. 2012 <sup>[[#fn:r118|118]]</sup> ). The global estimates of soil erosion differ significantly, depending on scale, study period and method used (García-Ruiz et al. 2015 <sup>[[#fn:r119|119]]</sup> ), ranging from approximately 20 Gt yr– <sup>1</sup> to more than 200 Gt yr– <sup>1</sup> (Boix-Fayos et al. 2006 <sup>[[#fn:r120|120]]</sup> ; FAO 2015 <sup>[[#fn:r121|121]]</sup> ). There is a significant potential for climate change to increase soil erosion by water, particularly in those regions where precipitation volumes and intensity are projected to increase (Panthou et al. 2014 <sup>[[#fn:r122|122]]</sup> ; Nearing et al. 2015 <sup>[[#fn:r123|123]]</sup> ). On the other hand, while it is a dominant form of erosion in areas such as West Asia and the Arabian Peninsula (Prakash et al. 2015 <sup>[[#fn:r124|124]]</sup> ; Klingmüller et al. 2016 <sup>[[#fn:r125|125]]</sup> ), there is ''limited evidence'' concerning climate change impacts on wind erosion (Tables 4.1 and 4.2 in Chapter 4, and Section 3.5).

Saline and sodic soils (see Glossary) occur naturally in arid, semi-arid and dry sub-humid regions of the world. Climate change or hydrological change can cause soil salinisation by increasing the mineralised groundwater level. However, secondary salinisation occurs when the concentration of dissolved salts in water and soil is increased by anthropogenic processes, mainly through poorly managed irrigation schemes. The threat of soil and groundwater salinisation induced by sea level rise and seawater intrusion are amplified by climate change (Section 4.9.7).

Global warming is expected to accelerate soil organic carbon (SOC) turnover, since the decomposition of the soil organic matter by microbial activity begins with low soil water availability, but this moisture is insufficient for plant productivity (Austin et al. 2004 <sup>[[#fn:r126|126]]</sup> ) (Section 3.4.1.1). SOC is also lost due to soil erosion (Lal 2009 <sup>[[#fn:r127|127]]</sup> ); therefore, in some dryland areas leading to SOC decline (Sections 3.3.3 and 3.5.2) and the transfer of carbon (C) from soil to the atmosphere (Lal 2009 <sup>[[#fn:r128|128]]</sup> ).

Sea surface temperature (SST) anomalies can drive rainfall changes, with implications for desertification processes. North Atlantic SST anomalies are positively correlated with Sahel rainfall anomalies (Knight et al. 2006 <sup>[[#fn:r129|129]]</sup> ; Gonzalez-Martin et al. 2014 <sup>[[#fn:r130|130]]</sup> ; Sheen et al. 2017 <sup>[[#fn:r131|131]]</sup> ). While the eastern tropical Pacific SST anomalies have a negative correlation with Sahel rainfall (Pomposi et al. 2016 <sup>[[#fn:r132|132]]</sup> ), a cooler North Atlantic is related to a drier Sahel, with this relationship enhanced if there is a simultaneous relative warming of the South Atlantic (Hoerling et al. 2006 <sup>[[#fn:r133|133]]</sup> ). Huber and Fensholt (2011) <sup>[[#fn:r134|134]]</sup> explored the relationship between SST anomalies and satellite observed Sahel vegetation dynamics, finding similar relationships but with substantial west–east variations in both the significant SST regions and the vegetation response. Concerning the paleoclimatic evidence on aridification after the early Holocene ‘Green Sahara’ period (11,000 to 5000 years ago), Tierney et al. (2017) <sup>[[#fn:r135|135]]</sup> indicate that a cooling of the North Atlantic played a role (Collins et al. 2017 <sup>[[#fn:r136|136]]</sup> ; Otto-Bliesner et al. 2014 <sup>[[#fn:r137|137]]</sup> ; Niedermeyer et al. 2009 <sup>[[#fn:r138|138]]</sup> ) similar to that found in modern observations. Besides these SST relationships, aerosols have also been suggested as a potential driver of the Sahel droughts (Rotstayn and Lohmann 2002 <sup>[[#fn:r139|139]]</sup> ; Booth et al. 2012 <sup>[[#fn:r140|140]]</sup> ; Ackerley et al. 2011 <sup>[[#fn:r141|141]]</sup> ). For eastern Africa, both recent droughts and decadal declines have been linked to human-induced warming in the western Pacific (Funk et al. 2018 <sup>[[#fn:r142|142]]</sup> ).

Invasive plants contributed to desertification and loss of ecosystem services in many dryland areas in the last century ( ''high confidence'' ) (Section 3.7.3). Extensive woody plant encroachment altered runoff and soil erosion across much of the drylands, because the bare soil between shrubs is very susceptible to water erosion, mainly in high-intensity rainfall events (Manjoro et al. 2012 <sup>[[#fn:r143|143]]</sup> ; Pierson et al. 2013 <sup>[[#fn:r144|144]]</sup> ; Eldridge et al. 2015 <sup>[[#fn:r145|145]]</sup> ). Rising CO <sub>2</sub> levels due to global warming favour more rapid expansion of some invasive plant species in some regions. An example is the Great Basin region in western North America where over 20% of ecosystems have been significantly altered by invasive plants, especially exotic annual grasses and invasive conifers, resulting in loss of biodiversity. This land-cover conversion has resulted in reductions in forage availability, wildlife habitat, and biodiversity (Pierson et al. 2011, 2013 <sup>[[#fn:r146|146]]</sup> ; Miller et al. 2013 <sup>[[#fn:r147|147]]</sup> ).

The wildfire is a driver of desertification, because it reduces vegetation cover, increases runoff and soil erosion, reduces soil fertility and affects the soil microbial community (Vega et al. 2005 <sup>[[#fn:r148|148]]</sup> ; Nyman et al. 2010 <sup>[[#fn:r149|149]]</sup> ; Holden et al. 2013 <sup>[[#fn:r150|150]]</sup> ; Pourreza et al. 2014 <sup>[[#fn:r151|151]]</sup> ; Weber et al. 2014 <sup>[[#fn:r152|152]]</sup> ; Liu and Wimberly 2016 <sup>[[#fn:r153|153]]</sup> ). Predicted increases in temperature and the severity of drought events across some dryland areas (Section 2.2) can increase chances of wildfire occurrence ( ''medium confidence'' ) (Jolly et al. 2015 <sup>[[#fn:r154|154]]</sup> ; Williams et al. 2010 <sup>[[#fn:r155|155]]</sup> ; Clarke and Evans 2018 <sup>[[#fn:r156|156]]</sup> ) (Cross-Chapter Box 3 in Chapter 2). In semi-arid and dry sub-humid areas, fire can have a profound influence on observed vegetation and particularly the relative abundance of grasses to woody plants (Bond et al. 2003 <sup>[[#fn:r157|157]]</sup> ; Bond and Keeley 2005 <sup>[[#fn:r158|158]]</sup> ; Balch et al. 2013 <sup>[[#fn:r159|159]]</sup> ).

While large uncertainty exists concerning trends in droughts globally (AR5) (Section 2.2), examining the drought data by Ziese et al. (2014) <sup>[[#fn:r160|160]]</sup> for drylands only reveals a large inter-annual variability combined with a trend toward increasing dryland area affected by droughts since the 1950s (Figure 1.1). Thus, over the period 1961–2013, the annual area of drylands in drought has increased, on average, by slightly more than 1% per year, with large inter-annual variability.

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==== 3.1.4.2 Anthropogenic drivers of desertification under climate change ====

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The literature on the human drivers of desertification is substantial (e.g., D’Odorico et al. 2013 <sup>[[#fn:r161|161]]</sup> ; Sietz et al. 2011 <sup>[[#fn:r162|162]]</sup> ; Yan and Cai 2015 <sup>[[#fn:r163|163]]</sup> ; Sterk et al. 2016 <sup>[[#fn:r164|164]]</sup> ; Varghese and Singh 2016 <sup>[[#fn:r165|165]]</sup> ) and there have been several comprehensive reviews and assessments of these drivers very recently (Cherlet et al. 2018 <sup>[[#fn:r166|166]]</sup> ; IPBES 2018a <sup>[[#fn:r167|167]]</sup> ; UNCCD 2017 <sup>[[#fn:r168|168]]</sup> ). IPBES (2018a) identified cropland expansion, unsustainable land management practices including overgrazing by livestock, urban expansion, infrastructure development, and extractive industries as the main drivers of land degradation. IPBES (2018a) also found that the ultimate driver of land degradation is high and growing consumption of land-based resources, e.g., through deforestation and cropland expansion, escalated by population growth. What is particularly relevant in the context of the present assessment is to evaluate if, how and which human drivers of desertification will be modified by climate change effects.

Growing food demand is driving conversion of forests, rangelands, and woodlands into cropland (Bestelmeyer et al. 2015 <sup>[[#fn:r169|169]]</sup> ; D’Odorico et al. 2013 <sup>[[#fn:r170|170]]</sup> ). Climate change is projected to reduce crop yields across dryland areas (Sections 3.4.1 and 5.2.2), potentially reducing local production of food and feed. Without research breakthroughs mitigating these productivity losses through higher agricultural productivity, and reducing food waste and loss, meeting the increasing food demands of growing populations will require expansion of cropped areas to more marginal areas (with most prime areas in drylands already being under cultivation) (Lambin 2012 <sup>[[#fn:r171|171]]</sup> ; Lambin et al. 2013 <sup>[[#fn:r172|172]]</sup> ; Eitelberg et al. 2015 <sup>[[#fn:r173|173]]</sup> ; Gutiérrez-Elorza 2006 <sup>[[#fn:r174|174]]</sup> ; Kapović Solomun et al. 2018 <sup>[[#fn:r175|175]]</sup> ). Borrelli et al. (2017) <sup>[[#fn:r176|176]]</sup> showed that the primary driver of soil erosion in 2012 was cropland expansion. Although local food demands could also be met by importing from other areas, this would mean increasing the pressure on land in those areas (Lambin and Meyfroidt 2011 <sup>[[#fn:r177|177]]</sup> ). The net effects of such global agricultural production shifts on land condition in drylands are not known.

Climate change will exacerbate poverty among some categories of dryland populations (Sections 3.4.2 and 3.5.2). Depending on the context, this impact comes through declines in agricultural productivity, changes in agricultural prices and extreme weather events (Hertel and Lobell 2014 <sup>[[#fn:r178|178]]</sup> ; Hallegatte and Rozenberg 2017 <sup>[[#fn:r179|179]]</sup> ). There is ''high confidence'' that poverty limits both capacities to adapt to climate change and availability of financial resources to invest into SLM (Gerber et al. 2014 <sup>[[#fn:r180|180]]</sup> ; Way 2016 <sup>[[#fn:r181|181]]</sup> ; Vu et al. 2014 <sup>[[#fn:r182|182]]</sup> ) (Sections 3.5.2, 3.6.2 and 3.6.3).

Labour mobility is another key human driver that will interact with climate change. Although strong impacts of climate change on migration in dryland areas are disputed, in some places, it is ''likely'' to provide an added incentive to migrate (Section 3.4.2.7). Out-migration will have several contradictory effects on desertification. On one hand, it reduces an immediate pressure on land if it leads to less dependence on land for livelihoods (Chen et al. 2014 <sup>[[#fn:r183|183]]</sup> ; Liu et al. 2016a). Moreover, migrant remittances could be used to fund the adoption of SLM practices. Labour mobility from agriculture to non-agricultural sectors could allow land consolidation, gradually leading to mechanisation and agricultural intensification (Wang et al. 2014 <sup>[[#fn:r184|184]]</sup> , 2018 <sup>[[#fn:r185|185]]</sup> ). On the other hand, this can increase the costs of labour-intensive SLM practices due to lower availability of rural agricultural labour and/or higher rural wages. Out-migration increases the pressure on land if higher wages that rural migrants earn in urban centres will lead to their higher food consumption. Moreover, migrant remittances could also be used to fund land-use expansion to marginal areas (Taylor et al. 2016 <sup>[[#fn:r186|186]]</sup> ; Gray and Bilsborrow 2014 <sup>[[#fn:r187|187]]</sup> ). The net effect of these opposite mechanisms varies from place to place (Qin and Liao 2016 <sup>[[#fn:r188|188]]</sup> ). There is very little literature evaluating these joint effects of climate change, desertification and labour mobility (Section 7.3.2).

There are also many other institutional, policy and socio-economic drivers of desertification, such as land tenure insecurity, lack of property rights, lack of access to markets, and to rural advisory services, lack of technical knowledge and skills, agricultural price distortions, agricultural support and subsidies contributing to desertification, and lack of economic incentives for SLM (D’Odorico et al. 2013 <sup>[[#fn:r189|189]]</sup> ; Geist et al. 2004 <sup>[[#fn:r190|190]]</sup> ; Moussa et al. 2016 <sup>[[#fn:r191|191]]</sup> ; Mythili and Goedecke 2016 <sup>[[#fn:r192|192]]</sup> ; Sow et al. 2016 <sup>[[#fn:r193|193]]</sup> ; Tun et al. 2015 <sup>[[#fn:r194|194]]</sup> ; García-Ruiz 2010 <sup>[[#fn:r195|195]]</sup> ). There is no evidence that these factors will be materially affected by climate change, however, serving as drivers of unsustainable land management practices, they do play a very important role in modulating responses for climate change adaptation and mitigation (Section 3.6.3).

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==== 3.1.4.3 Interaction of drivers: Desertification syndrome versus drylands development paradigm ====

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Two broad narratives have historically emerged to describe responses of dryland populations to environmental degradation. The first is ‘desertification syndrome’ which describes the vicious cycle of resource degradation and poverty, whereby dryland populations apply unsustainable agricultural practices leading to desertification, and exacerbating their poverty, which then subsequently further limits their capacities to invest in SLM (MEA 2005 <sup>[[#fn:r196|196]]</sup> ; Safriel and Adeel 2008 <sup>[[#fn:r197|197]]</sup> ). The alternative paradigm is one of ‘drylands development’, which refers to social and technical ingenuity of dryland populations as a driver of dryland sustainability (MEA 2005; Reynolds et al. 2007 <sup>[[#fn:r198|198]]</sup> ; Safriel and Adeel 2008 <sup>[[#fn:r199|199]]</sup> ). The major difference between these two frameworks is that the ‘drylands development’ paradigm recognises that human activities are not the sole and/or most important drivers of desertification, but there are interactions of human and climatic drivers within coupled social-ecological systems (Reynolds et al. 2007 <sup>[[#fn:r200|200]]</sup> ). This led Behnke and Mortimore (2016) <sup>[[#fn:r201|201]]</sup> , and earlier Swift (1996) <sup>[[#fn:r202|202]]</sup> , to conclude that the concept of desertification as irreversible degradation distorts policy and governance in dryland areas. Mortimore (2016) <sup>[[#fn:r203|203]]</sup> suggested that instead of externally imposed technical solutions, what is needed is for populations in dryland areas to adapt to this variable environment which they cannot control. All in all, there is ''high confidence'' that anthropogenic and climatic drivers interact in complex ways in causing desertification. As discussed in Section 3.2.2, the relative influence of human or climatic drivers on desertification varies from place to place ( ''high confidence'' ) (Bestelmeyer et al. 2018 <sup>[[#fn:r204|204]]</sup> ; D’Odorico et al. 2013 <sup>[[#fn:r205|205]]</sup> ; Geist and Lambin 2004 <sup>[[#fn:r206|206]]</sup> ; Kok et al. 2016 <sup>[[#fn:r207|207]]</sup> ; Polley et al. 2013 <sup>[[#fn:r208|208]]</sup> ; Ravi et al. 2010 <sup>[[#fn:r209|209]]</sup> ; Scholes 2009 <sup>[[#fn:r210|210]]</sup> ; Sietz et al. 2017 <sup>[[#fn:r211|211]]</sup> ; Sietz et al. 2011 <sup>[[#fn:r212|212]]</sup> ).

<span id="observations-of-desertification"></span>