Editing IPCC:AR6/WGII/Chapter-9 (section)

==== 9.4.5.3 Climate Change Literacy ====

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Understanding the human cause of climate change is a strong predictor of climate change risk perception ( [[#Lee--2015|Lee et al., 2015]] ) and a critical knowledge foundation that can affect the difference between coping responses and more informed and transformative adaptation (Figure 9.11; [[#Oladipo--2015|Oladipo, 2015]] ; [[#Mutandwa--2019|Mutandwa et al., 2019]] ). At a minimum, climate change literacy includes both having heard of climate change and understanding it is, at least in part, caused by people ( [[#Simpson--2021a|Simpson et al., 2021a]] ). However, large inequalities in climate change literacy exist between and within countries and communities across Africa.

The average national climate change literacy rate in Africa is only 39% (country rates range from 23–66%) (Figure 9.11). Of 394 sub-national regions surveyed by Afrobarometer, 8% (37 regions in 16 countries) have a climate change literacy rate lower than 20%, while only 2% (8 regions) score higher than 80%, which is common across European countries ( [[#Simpson--2021a|Simpson et al., 2021a]] ). Striking differences exist when comparing sub-national units within countries. Climate change literacy rates in Nigeria range from 71% in Kwara to 5% in Kano, and within Botswana from 69% in Lobatse to only 6% in Kweneng West ( [[#Simpson--2021a|Simpson et al., 2021a]] ). Education is the strongest positive predictor of climate change literacy, particularly tertiary education, but poverty decreases climate change literacy and climate change literacy rates average 12.8% lower for women than men ( [[#Simpson--2021a|Simpson et al., 2021a]] ).

As the identified factors driving climate change literacy overlap with broader developmental challenges on the continent, policies targeting these factors (e.g., increased education) can potentially yield co-benefits for both climate change adaptation as well as progress towards SDGs, particularly education and gender equality ( [[#Simpson--2021a|Simpson et al., 2021a]] ). Progress towards greater climate change literacy affords a concrete opportunity to mainstream climate change within core national and sub-national developmental agendas in Africa towards more CRD pathways. Synergies with CS can also overcome gendered deficits, for example, although women are generally less climate change aware and more vulnerable to climate change than men in Africa, they are generally more likely to adopt climate-resilient crops when they are climate change aware and have exposure to extension services ( [[#Acevedo--2020|Acevedo et al., 2020]] ; [[#Simpson--2021a|Simpson et al., 2021a]] ).

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'''Box 9.1 | Vulnerability Synthesis'''
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Vulnerability in Africa is socially, culturally and geographically differentiated among climatic regions, countries and local communities, with climate change impacting the health, livelihoods and food security of different groups to different extents ( [[#Gan--2016|Gan et al., 2016]] ; [[#Onyango--2016a|Onyango et al., 2016a]] ; [[#Gumucio--2020|Gumucio et al., 2020]] ). This synthesis emphasises intersectionality within vulnerable groups as well as their position within dynamic social and cultural contexts ( [[#Wisner--2016|Wisner, 2016]] ; [[#Kuran--2020|Kuran et al., 2020]] ), and highlights the differential impacts of climate change and restricted adaptation options available to vulnerable groups across African countries (see also Cross-Chapter Box GENDER in Chapter 18).

Vulnerability and exposure to the impacts of climate change are complex and affected by multiple, interacting non-climatic processes, which together influence risk, including socioeconomic processes ( [[#Lwasa--2018|Lwasa et al., 2018]] ; [[#UNCTAD--2020|UNCTAD, 2020]] ), resource access and livelihood changes ( [[#Jayne--2019b|Jayne et al., 2019b]] ) and intersectional vulnerability among social groups (Figure Box 9.1.1; [[#Rao--2020|Rao et al., 2020]] ). Socioeconomic processes encompass broader social, economic and governance trends, such as expanded investment in large energy and transportation infrastructure projects ( [[#Adeniran--2020|Adeniran and Daniell, 2020]] ), rising external debt ( [[#Edo--2020|Edo et al., 2020]] ), changing role of the state in social development ( [[#Wunsch--2014|Wunsch, 2014]] ), environmental management ( [[#Ramutsindela--2019|Ramutsindela and Büscher, 2019]] ) and conflict, as well as those emanating from climate change mitigation and adaptation projects ( [[#Beymer-Farris--2012|Beymer-Farris and Bassett, 2012]] ; [[#van%20Baalen--2018|van Baalen and Mobjörk, 2018]] ; [[#Simpson--2021b|Simpson et al., 2021b]] ). These macro trends shape both urban and rural livelihoods, including the growing diversification of rural livelihoods through engagement in the informal sector and other non-farm activities, and are mediated by complex and intersecting factors like gender, ethnicity, class, age, disability and other dimensions of social status that influence access to resources ( [[#Luo--2019|Luo et al., 2019]] ). Research increasingly highlights the intersectionality of multiple dimensions of social identity and status that are associated with greater susceptibility to loss and damage ( [[#Caparoci%20Nogueira--2018|Caparoci Nogueira et al., 2018]] ; [[#Li--2018|Li et al., 2018]] ).

Arid and semi-arid countries in the Sahelian belt and the greater Horn of Africa are often identified as the most vulnerable regions on the continent ( [[#Closset--2017|Closset et al., 2017]] ; [[#Serdeczny--2017|Serdeczny et al., 2017]] ). Particularly vulnerable groups include pastoralists ( [[#Wangui--2018|Wangui, 2018]] ; [[#Ayanlade--2019|Ayanlade and Ojebisi, 2019]] ), fishing communities ( [[#Belhabib--2016|Belhabib et al., 2016]] ; [[#Muringai--2019a|Muringai et al., 2019a]] ), small-scale farmers ( [[#Ayanlade--2017|Ayanlade et al., 2017]] ; [[#Mogomotsi--2020|Mogomotsi et al., 2020]] ; see [[#9.8.1|Section 9.8.1]] ) and residents of formal and informal urban settlements (see [[#9.9|Section 9.9]] ). Research has identified key macro drivers, as well as multiple dimensions of social status that mediate differential vulnerability in different African contexts. For example, the contemporary vulnerability of small-scale rural producers in semi-arid northern Ghana has been shaped by colonial economic transformations ( [[#Ahmed--2016|Ahmed et al., 2016]] ), more recent neoliberal reforms reducing state support ( [[#Fieldman--2011|Fieldman, 2011]] ) and the disruption of local food systems due to increasing grain imports ( [[#Nyantakyi-Frimpong--2015|Nyantakyi-Frimpong and Bezner-Kerr, 2015]] ). Age interacts with other dimensions of social status, shaping differential vulnerability in several ways. Projected increases in mean temperatures and longer and more intense heat waves (Figure Box 9.1.1) may increase health risks for children and elderly populations by increasing risks associated with heat stress ( [[#Bangira--2015|Bangira et al., 2015]] ; [[#Cairncross--2018|Cairncross et al., 2018]] ). Temperature extremes are associated with increased risk of mortality in Ghana, Burkina Faso, Kenya and South Africa, with greatest increases among children and the elderly ( [[#Bangira--2015|Bangira et al., 2015]] ; [[#Amegah--2016|Amegah et al., 2016]] ; [[#Omonijo--2017|Omonijo, 2017]] ; [[#Wiru--2019|Wiru et al., 2019]] ; see [[#9.10.2.3.1|Section 9.10.2.3.1]] ).

Rural African women are often disadvantaged by traditional, patriarchal decision-making processes and lack of access to land—issues compounded by kinship systems (that, is matrilineal or patrilineal), migrant status, age, type of household, livelihood orientation and disability in determining their adaptive options ( [[#Ahmed--2016|Ahmed et al., 2016]] ; see [[#9.8.1|Section 9.8.1]] ; 9.11.1.2; Box 9.8). Differential agricultural productivity between men and women is about 20–30% or more in dryland regions of Ethiopia and Nigeria ( [[#Ghanem--2011|Ghanem, 2011]] ) and challenges women’s ability to adapt to climate change. Limited access to agricultural resources and limited benefits from agricultural policies, compounded by other social and cultural factors, make women more vulnerable to climatic risks ( [[#Shukla--2021|Shukla et al., 2021]] ). Kinship systems can contribute to their vulnerability and capacity to adapt. Women in matrilineal systems have greater bargaining power and have access to more resources than those in patrilineal systems ( [[#Chigbu--2019|Chigbu, 2019]] ; [[#Robinson--2021|Robinson and Gottlieb, 2021]] ; See section 9.8.1; 9.11.1.2).

[[File:4ddb413fc96ddcab0e88da98e9bff167 IPCC_AR6_WGII_Figure_9_Box_9_1_1.png]]

'''Figure Box 9.1.1 |''' '''Factors contributing to the progression of vulnerability to climate change in African contexts considering socioeconomic processes, resource access, livelihood changes, and intersectional vulnerability among social groups.''' This figure reflects a synthesis of vulnerability across sections of this chapter and highlights how the interactions of multiple dimensions of vulnerability compound each other to increase overall vulnerability ( [[#Potts--2008|Potts, 2008]] ; [[#Nielsen--2010|Nielsen and Reenberg, 2010]] ; [[#Akresh--2011|Akresh et al., 2011]] ; [[#Eriksen--2011|Eriksen et al., 2011]] ; [[#Beymer-Farris--2012|Beymer-Farris and Bassett, 2012]] ; Davis et al., 2012; [[#Adom--2014|Adom, 2014]] ; [[#Akello--2014|Akello, 2014]] ; [[#Headey--2014|Headey and Jayne, 2014]] ; [[#Otzelberger--2014|Otzelberger, 2014]] ; [[#Wunsch--2014|Wunsch, 2014]] ; [[#Conteh--2015|Conteh, 2015]] ; [[#Huntjens--2015|Huntjens and Nachbar, 2015]] ; [[#Spencer--2015|Spencer, 2015]] ; [[#Adetula--2016|Adetula et al., 2016]] ; [[#Djoudi--2016|Djoudi et al., 2016]] ; [[#Kuper--2016|Kuper et al., 2016]] ; [[#Stark--2016|Stark and Landis, 2016]] ; [[#Allard--2017|Allard, 2017]] ; [[#Anderson--2017|Anderson, 2017]] ; [[#Asfaw--2017|Asfaw et al., 2017]] ; [[#Hufe--2017|Hufe and Heuermann, 2017]] ; [[#Hulme--2017|Hulme, 2017]] ; Paul and wa G ĩ th ĩ nji, 2017; [[#Rao--2017|Rao et al., 2017]] ; [[#Serdeczny--2017|Serdeczny et al., 2017]] ; [[#Tesfamariam--2017|Tesfamariam and Zinyengere, 2017]] ; [[#Tierney--2017|Tierney et al., 2017]] ; [[#Waha--2017|Waha et al., 2017]] ; [[#Chihambakwe--2018|Chihambakwe et al., 2018]] ; [[#Cholo--2018|Cholo et al., 2018]] ; [[#Jenkins--2018|Jenkins et al., 2018]] ; [[#Keahey--2018|Keahey, 2018]] ; [[#Lwasa--2018|Lwasa et al., 2018]] ; [[#Makara--2018|Makara, 2018]] ; [[#Nyasimi--2018|Nyasimi et al., 2018]] ; [[#Petesch--2018|Petesch et al., 2018]] ; [[#Schuman--2018|Schuman et al., 2018]] ; [[#Theis--2018|Theis et al., 2018]] ; [[#van%20Baalen--2018|van Baalen and Mobjörk, 2018]] ; [[#van%20der%20Zwaan--2018|van der Zwaan et al., 2018]] ; [[#Adepoju--2019|Adepoju, 2019]] ; [[#Adzawla--2019b|Adzawla et al., 2019b]] ; [[#Bryceson--2019|Bryceson, 2019]] ; [[#Grasham--2019|Grasham et al., 2019]] ; [[#Jayne--2019a|Jayne et al., 2019a]] ; [[#Lowe--2019|Lowe et al., 2019]] ; [[#Lunga--2019|Lunga et al., 2019]] ; [[#OGAR--2019|OGAR and Bassey, 2019]] ; [[#Onwutuebe--2019|Onwutuebe, 2019]] ; [[#Ramutsindela--2019|Ramutsindela and Büscher, 2019]] ; [[#Sulieman--2019|Sulieman and Young, 2019]] ; [[#Torabi--2019|Torabi and Noori, 2019]] ; [[#Adeniran--2020|Adeniran and Daniell, 2020]] ; [[#Alexander--2020|Alexander, 2020]] ; [[#Clay--2020|Clay and Zimmerer, 2020]] ; [[#Devonald--2020|Devonald et al., 2020]] ; [[#Dolislager--2020|Dolislager et al., 2020]] ; [[#Edo--2020|Edo et al., 2020]] ; [[#Kaczan--2020|Kaczan and Orgill-Meyer, 2020]] ; [[#Lammers--2020|Lammers et al., 2020]] ; [[#World%20Bank--2020b|World Bank, 2020b]] ; [[#Asiama--2021|Asiama et al., 2021]] ; [[#Azong--2021|Azong and Kelso, 2021]] ; [[#Birgen--2021|Birgen, 2021]] ; [[#Paalo--2021|Paalo and Issifu, 2021]] ; [[#Simpson--2021b|Simpson et al., 2021b]] ).

Knowledge gaps on Vulnerability in Africa and Uneven Acces to Resources

The differential impacts of climate change and adaptation options available to vulnerable groups in Africa are a critical knowledge gap. More research is needed to examine the intersection of different dimensions of social status on climate change vulnerability in Africa ( [[#Thompson-Hall--2016|Thompson-Hall et al., 2016]] ; [[#Oluwatimilehin--2021|Oluwatimilehin and Ayanlade, 2021]] ). More analysis of vulnerability based on gender and other social and cultural factors is needed to fully understand the impacts of climate change, the interaction of divergent adaptive strategies, as well as the development of targeted adaptation and mitigation strategies, for example, for women in patrilineal kinship systems, people living with disabilities, youth, girls and the elderly. Finally, there is an urgent need to build capacity among those conducting vulnerability assessments, so that they are familiar with this intersectionality lens.

Additional information and capacity development through education and early warning systems could enhance vulnerable groups’ ability to cope and adapt their livelihoods ( [[#Jaka--2018|Jaka and Shava, 2018]] ). However, some groups of people may struggle to translate information into actual changes ( [[#Makate--2019|Makate et al., 2019]] ; [[#McOmber--2019|McOmber et al., 2019]] ). Lack of access to assets and social networks, for example, among older populations, are critical limitations to locally driven or autonomous adaptation and limit potential benefits from planned adaptation actions (e.g., adoption of agricultural technologies or effective use of early warning systems).

There is an urgent need for societal and political change to realise potential benefits for these vulnerable groups in the long term ( [[#Nyasimi--2018|Nyasimi et al., 2018]] ). There is a need for gender-sensitive climate change policies in many African countries and gender-responsive policies, implementation plans and budgets for all local-level initiatives ( [[#Wrigley-Asante--2019|Wrigley-Asante et al., 2019]] ).

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