Editing IPCC:AR6/WGII/Chapter-7 (section)

==== 7.3.2.2 Interactions with Non-climatic Determinants and Projections of Future Migration Flows ====

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Only a very small number of studies have attempted to make systematic projections of future regional or global migration and displacement numbers under climate change. Key methodological challenges for making such projections include the availability of reliable data on migration within and between countries, definitional ambiguity in distinguishing climate-related migration from migration undertaken for other reasons, and accounting for the future influence of non-climatic factors. The most reliable example of such studies to date is a World Bank report by [[#Rigaud--2018|Rigaud et al. (2018)]] that generated projections of future internal population displacements in south Asia, sub-Saharan Africa and Latin America by 2050 using multiple climate and development scenarios, resulting in a very large range of possible outcomes (from 31 to 143 million people being displaced, depending on assumptions). An important outcome is the study’s emphasis on how the potential for future migration and displacement will be strongly mediated by socioeconomic development pathways in low- and middle-income countries. [[#Hoffmann--2020|Hoffmann et al. (2020)]] used meta-regression-based analyses to project that future environmental influences on migration are ''likely'' to be greatest in low- and middle-income countries in Latin America and the Caribbean, sub-Saharan Africa, the Middle East and most of continental Asia.

''Research reviewed in AR4 and AR5 observed that at higher rates of socioeconomic development, the'' in situ ''adaptive capacity of households and institutions rises, and climatic influences on migration correspondingly decline. Recent evidence adds further support for such conclusions'' ( ''high confidence'' ) ''( [[#Kumar--2018b|Kumar et al., 2018b]] ; [[#Mallick--2019|Mallick, 2019]] ; [[#Gray--2020|Gray et al., 2020]] ; Box 7.5)'' . Population growth rates are currently highest in low-income countries (UN DESA Population Division, 2019), many of which have high rates of exposure to climatic hazards associated with population displacement, further emphasising the importance of socioeconomic development and adaptive capacity-building. Although country-specific scenarios for socioeconomic development and population are embedded in SSPs, research into future migration flows under climate change has not made great use of these. One of the few studies to do so found that safe and orderly international migration tends to increase wealth at regional and global scales in all SSP narratives, which in turn reduces income inequality between countries ( [[#Benveniste--2021|Benveniste et al., 2021]] ). International barriers to safe and orderly migration may potentially impede progress towards attainment of the objectives described in the SDGs and increase exposure to climatic hazards in low- and middle-income countries ( [[#McLeman--2019|McLeman, 2019]] ; [[#Benveniste--2020|Benveniste et al., 2020]] ).

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'''Box 7.5 | Uncertainties in projections of future demographic patterns at global, regional and national scales'''
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Projections of future numbers of people exposed to climate change-related hazards described in this chapter and elsewhere in this report are heavily influenced by assumptions about population change over time at global, regional and national scales. One challenge concerns global and regional variability of baseline data for current populations, which is typically aggregated from national censuses that vary considerably in terms of frequency, timing and reliability, especially in low-income countries. A number of gridded mapping dataset initiatives emerged in recent years to support population–environment modelling research at global and regional levels, common ones being the Gridded Population of the World, the Global Rural Urban Mapping Project, and LandScan Global Population dataset ( [[#McMichael--2020|McMichael et al., 2020]] ). For future population projections at national levels, researchers commonly draw upon data generated by the Population Division of the United Nations Department of Economic and Social Affairs, which publishes periodic projections for future fertility, mortality, and international migration rates for over 200 countries, the most recent projections being for the 2020 to 2100 period (UN DESA Population Division, 2019). There have been debates among demographers regarding the precision of DESA projections, and whether these overestimate or underestimate future population growth in some regions ( [[#Ezeh--2020|Ezeh et al., 2020]] ). Population growth rates are highly influenced by socioeconomic conditions, meaning that future population levels at local, national and regional scales are ''likely'' to respond to relative rates of progress towards meeting the Sustainable Development Goals ( [[#Abel--2016|Abel et al., 2016]] ). The Shared Socioeconomic Pathways (SSPs) used in climate impacts and adaptation research include a variety of assumptions about future mortality, fertility and migration rates and provide a range of population growth scenarios that diverge after the year 2030 according to future development trajectories ( [[#Samir--2017|Samir and Lutz, 2017]] ) and are then further modified and downscaled by researchers for national-level studies. Understanding future risks of climate change will benefit from continued efforts by the international community to collect and share data on observed population numbers and trends, and to work towards better projected data for population characteristics that strongly influence vulnerability to climate risks, such as gender, age and indigeneity.

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