Agricultural livelihoods, adaptation, and environmental migration in sub-Saharan drylands: A meta-analytical review

Hoffmann, Roman; Wiederkehr, Charlotte; Dimitrova, Anna; Hermans, Kathleen Article — Published Version Agricultural livelihoods, adaptation, and environmental migration in sub-Saharan drylands: A meta-analytical review Environmental Research Letters Provided in Cooperation with: Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle (Saale) Suggested Citation: Hoffmann, Roman; Wiederkehr, Charlotte; Dimitrova, Anna; Hermans, Kathleen (2022) : Agricultural livelihoods, adaptation, and environmental migration in sub-Saharan drylands: A meta-analytical review, Environmental Research Letters, ISSN 1748-9326, IOP Publishing, Bristol, Vol. 17, Iss. 8, https://doi.org/10.1088/1748-9326/ac7d65 , https://iopscience.iop.org/article/10.1088/1748-9326/ac7d65 This Version is available at: https://hdl.handle.net/10419/264384 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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Lett. 17 (2022) 083003 https://doi.org/10.1088/1748-9326/ac7d65 OPEN ACCESS RECEIVED 21 February 2022 REVISED 29 June 2022 ACCEPTED FOR PUBLICATION 30 June 2022 PUBLISHED 12 August 2022 Original content from this work may be used under the terms of the Creative Commons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. TOPICAL REVIEW Agricultural livelihoods, adaptation, and environmental migration in sub-Saharan drylands: a meta-analytical review Roman Hoffmann1,2,3,∗, Charlotte Wiederkehr4, Anna Dimitrova5and Kathleen Hermans4,6 1International Institute for Applied Systems Analysis (IIASA), Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna), Laxenburg, Austria 2Vienna Institute of Demography (OeAW), Wittgenstein Centre for Demography and Global Human Capital (IIASA, OeAW, University of Vienna), Vienna, Austria 3Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany 4Computational Landscape Ecology Department, Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany 5Department of Climate, Atmospheric Science, and Physical Oceanography at the University of California, San Diego, CA, United States of America 6Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle, Germany ∗Author to whom any correspondence should be addressed. E-mail: [email protected] Keywords: climate change, migration, adaptation, drylands, sub-Saharan Africa, systematic review, meta-analysis Supplementary material for this article is available online Abstract Drylands in sub-Saharan Africa are strongly affected by the impacts of climate change. Temperature increases, changes in rainfall patterns, and land degradation pose serious threats to food security, health, and water availability in the region. The increase in livelihood insecurity can in turn trigger migration as a way to adapt or cope with stress. Based on 89 original case studies, this study uses review and meta-analytical techniques to systematically explore the relationship between environmental change, adaptation, and migration in rural areas in sub-Saharan drylands. We show that households use a diverse range of strategies to respond to environmental hardships in different livelihood and ecological contexts. While migration is common in some communities, it is of less relevance to others, and it can take various forms. Our findings indicate that migration is often used as a complementary strategy to other forms of adaptation, which can vary depending on situational needs. We use cluster analysis to identify adaptation clusters and show how linked response strategies differ by socioeconomic conditions. We find that migration can serve as a last resort measure for highly vulnerable groups, or be used in combination with in-situ strategies for diversifying income and adapting agricultural practices. Our results have important implications highlighting the role of local conditions and complementary forms of coping and adaptation for understanding environmental migration. 1. Introduction Drylands cover about 46.2% of the global terrestrial area and are home to over 2 billion people or around one third of the global population (IPCC 2019, Hoover et al 2020). They are ecosystems characterized by high temporal and spatial rainfall variability and aridity (FAO 2019). Climate change is expected to have major impacts on these areas with increasing levels of water stress, desertification, land degradation, and a continued loss of biodiversity. By the end of this century, drylands are projected to further expand by 11% under a medium (RCP4.5) and up to 23% under a high (RCP8.5) greenhouse gas emission scenario relative to a 1961–1990 baseline (Huang et al 2016). In sub-Saharan Africa (SSA), drylands represent an important ecosystem accounting for 70% of the total cropland (Cervigni and Morris 2016). The region is highly exposed to climate change impacts, which come in form of slow-onset processes combined with the simultaneously increasing frequency and intensity of extreme events such as floods and droughts (IPCC 2018). © 2022 The Author(s). Published by IOP Publishing Ltd Environ. Res. Lett. 17 (2022) 083003 R Hoffmann et al With a high share of its population depending on agriculture, high levels of poverty, and low adaptive capacities, the region is characterized by a high vulnerability (Hoffmann 2022, IPCC et al 2022). Climate change is expected to further contribute to this vulnerability by exacerbating existing development challenges and non-climatic stressors, such as conflicts (FAO 2018). With worsening climate impacts, limits may be reached beyond which adaptation becomes impossible as communities lack means and resources to adequately prepare against and tolerate hazards (Warner et al 2012, Dow et al 2013, Xu et al 2020). Under these circumstances, migration can represent a suitable strategy to cope with and adapt to the climate impacts (Foresight 2011, IPCC et al 2022). By having household members or relatives move to other locations, households can diversify income sources and spread risks, which in turn can increase their resilience (McLeman and Smit 2006, Black et al 2011b, Gemenne and Blocher 2017). Here, migration and in-situ adaptation can be two sides of the same coin, for example if households engage in migration and at the same time adapt their agricultural practices. Also the relocation of an entire household can lead to improved protection and adaptation, although researchers have also warned of maladaptation and potential detrimental effects for migrating households and their communities (Warner et al 2012, Jacobson et al 2019, Vinke et al 2020). Given that migration is just one of many coping and adaptation options, it has to be considered against the background of the whole range of options available to households (McLeman and Smit 2006, Piguet 2010). Despite an increase in public interest in the links between climate change, adaptation, and human migration, empirical evidence on the relationships remains inconclusive (Hunter et al 2015, Hoffmann et al 2020). Many studies on the topic are localized, with a focus on one community or one country, making it difficult to assess the range of coping and adaptation options used by households to respond to environmental stress and the conditions under which they change their migration behavior. In particular, with regards to the special circumstances faced by rural populations in sub-Saharan drylands, limited comparative evidence exists on climate adaptation and the migration impacts of environmental drivers. To this end, this review study synthesizes the evidence from 89 case studies from 22 countries on climate change coping and adaptation in SSA. Whereas coping refers to short-term, immediate activities to address, manage, and overcome adverse conditions, adaptation refers to sustained adjustments that are oriented toward longer-term livelihood security (IPCC 2018). As a clear distinction between the two is not always possible based on the reviewed case studies, we speak broadly of adaptation against the background of the wider literature on climate change and adaptation in developing countries (Mertz et al 2009a, Berrang-Ford et al 2011, Fankhauser 2017). Complementing previous reviews on the region (Wiederkehr et al 2018, Borderon et al 2019), we use a combination of review and quantitative meta-analytical tools to analyze the relationship between environmental change, adaptation, and migration based on a systematic screening of the empirical literature. The focus of our study is placed on rural populations of farmers and (agro-) pastoralists living in drylands south of the Sahara. The meta-data collected as part of our study allows us to effectively compare household behavior across different geographical contexts and populations and to analyze migration against the background of other adaptation activities reported in the case studies. A novelty from a methodological standpoint is that we combine evidence from both quantitative and more qualitatively oriented case studies, including studies using inference from household and expert interviews or focus group discussions. Most of the considered case studies have a small sample size and provide in-depth insights in the local and contextual settings of the considered communities. This distinguishes our work from previous meta-analyses (Beine and Jeusette 2021, Hoffmann et al 2020, Šedová et al 2021) that typically consider the environmentmigration relationship at more aggregate levels. Our findings highlight the diversity of adaptation strategies used by households, ranging from agricultural in-situ strategies, to the diversification of income sources, the support from social networks, or changes in food provision and consumption. Also, migration as a way of adapting to environmental stress is found to play an important role in some of the communities considered, but not in all of them, depending on the livelihood and ecological context. Considering the use of migration against the background of other strategies, we find that migration is closely linked to and complemented by other adaptation activities. Using cluster analysis, we identify three distinct migration clusters that are characterized by different socioeconomic profiles and levels of vulnerability, suggesting that migration in response to environmental change can take various forms along a continuum from coerced to more voluntary forms of migration. The remainder of the paper is structured as follows. Section 2provides further information on the context in SSA drylands and discusses some of the pertinent challenges faced by local populations. Section 3introduces the research design and literature basis used and presents our screening and study selection process. Section 4presents the main findings, which are discussed in section 5. Section 6 concludes. 2 Environ. Res. Lett. 17 (2022) 083003 R Hoffmann et al 2. The context: drylands in sub-Saharan Africa Drylands are commonly defined on the basis of the aridity index (AI), which is the ratio of annual potential evaporation to precipitation (Safriel et al 2005). Drylands are areas with an AI of 0.65 or less. They can be further divided into hyper arid (AI < 0.05), arid (0.05 ⩽AI < 0.20), semi-arid (0.20 ⩽AI < 0.50), and dry sub-humid (0.50 ⩽AI < 0.65) zones. Higher aridity within drylands is typically associated with lower population density, with hyper arid zones being only sparsely populated. Drylands are important for food production in SSA, accounting for 66% of cereal production and 82% of livestock holdings in the region (Cervigni and Morris 2016). Livelihood strategies are centered around agriculture, with populations in drier areas being mainly involved in pastoralism and those in less arid areas relying on rain-fed cultivation. Drylands arecharacterizedbychallengingagroclimatic conditions, including high precipitation variability and chronic water scarcity (figure 1). They are exposed to a number of environmental hazards and changes and are frequently affected by weather extremes and droughts, which can result in widespread crop and livestock loss (Huho et al 2011, Middleton and Sternberg 2013). Although dryland inhabitants are adapted to their environments, the frequency and severity of climatic shocks is increasing under climate change (Diffenbaugh et al 2017) putting additional pressure on local livelihoods (Thornton et al 2011). For pastoralists and agro-pastoralists, the shrinkage of grazing areas is a major problem and these mobile populations respond by travelling further distances. Farmers are affected by delays in rainy season onset, mid-season heatwaves and heavy rains resulting in crop loss and low yields (Connolly-Boutin and Smit 2016). Frequent exposure to environmental hazards has been linked with the depletion of household assets, particularly among the poor who are not able to smooth consumption (Carter et al 2005, Ansah et al 2020). Moreover, population growth and environmental degradation are fueling disputes in the sub-Saharan drylands. An increase in conflict between farmers and semi-nomadic herders has been documented due to the increased competition for resources between the two groups (UNEP 2011, Brottem 2016). Certain population subgroups are also socially and politically marginalized, which further exacerbates their vulnerability to climate change and conflicts (Fjelde and von Uexkull 2012). Besides climate change, human activity is also speeding up land degradation in the area, which is expected to have far-reaching consequences for food security, economic activity, and population health in the region (United Nations Economic and Social Council 2007). Land degradation is often the result of unsustainable use of land by smallholder farmers who lack the capacity to invest in more sustainable practices (Shiferaw et al 2014). Consequently, land degradation increases vulnerability to environmental stress even further, which leaves subsistence farmers in a vicious cycle. Given that populations in sub-Saharan drylands are directly dependent on the natural environment for their livelihoods and are frequently affected by severe weather events, poverty is pervasive in the region (Middleton et al 2011). In fact, droughtsensitive countries in SSA have seen an increase in the prevalence of undernutrition from 17.7% in 2010 to 21.8% in 2018 (FAO, IFAD, UNICEF 2019). In the past years, extreme events triggered several million internal displacements, most notably in Eastern and Western Africa. Across all regions, an increase in internal and international migration was also observable (supplementary figure S1). 3. Review methods and study selection 3.1. Literature search and screening The literature search for this study was conducted in two stages—a first stage in June 2017 and a second stage in March 2020 when newer studies were added totheinitialselection (Wiederkehret al 2018). We followed a stepwise procedure to identify relevant studies for our review. In a first step, a systematic search of studies was carried out on the scientific search platform ‘Web of Science’, which provides comprehensive citation data for various academic fields. We used relevant keywords, including the names of all countries in SSA, terms related to environmental change and associated hazards, and the terms ‘adapt’ and ‘cope’. More information on the specific search terms can be found in supplementary material B. The entire search process yielded a preliminary selection of 3625 papers, which were further examined and filtered (see supplementary figure S2 for a PRISMA diagram). The filtering involved two steps. First, the relevance of papers was assessed based on their titles, keywords, and abstracts. In a second step, the full texts were thoroughly assessed for eligibility based on predefined inclusion criteria. We only considered peer-reviewed articles published in English. The following inclusion criteria were used to determine the eligibility of studies. A paper was considered eligible, if it (i) comprised primary data from a local case study, (ii) focused on populations in predominantly rural and (semi-)arid areas characterized by subsistence livelihoods or small-scale agricultural activities, (iii) reported an environmental change process7, (iv) presented data at the household 7In our screening, the text-based information was interpreted literally, i.e. dynamic terms like ‘increase’, ‘decrease’, or ‘degradation’ were understood as reflecting change processes. 3 Environ. Res. Lett. 17 (2022) 083003 R Hoffmann et al Figure 1. Exposure to environmental hazards for different regions in SSA. The panels show changes in the drought index SPEI and the number of people affected by disasters (in million) for (a) Western, (b) Central, (c) Eastern, and (d) Southern Africa. The map displayed in panel (e) shows the different dryland zones in the continent and the locations of the case studies included in this review. Data: SPEI data were calculated from precipitation and potential evapotranspiration data from the Climatic Research Unit at the University of East Anglia (Harris et al 2020), data on the number of affected by disasters are from the emergency events database (EM-DAT) (CRED 2022). The background map of dryland zones is based on UNEP-WCMC (2007). Figure 2. Characteristics of case studies included in the meta-analytical review. Panel (a) shows the livelihood strategies of the populations covered in the 89 case studies. Since some studies considered populations, which use a combination of different livelihood strategies, the total percentage reported exceeds 100%. Panel (b) shows the distribution of the sample size and panel (c) the methods employed by the case studies. As some studies use multiple methods, the pie chart summarizes the share over all methods used across studies, resulting in a total of 100%. level, (v) provided information on multiple coping and adaptation strategies (excluding preferred or planned actions), and (vi) provided information on the percentage of households in a study population adopting specific strategies. The search and selection procedure resulted in a total sample of 89 individual case studies covering more than 21 thousand households in 22 countries (see supplementary table S1 for a full list of studies). Information on the case studies were retrieved from 53 distinct articles, which were published between 2004 and 2019. The studies were conducted in different regions in SSA and used a variety of research designs and methods (figure 2(c)). Household surveys, focus groups, and key informant or expert interviews were the most common data collection methods, often complemented by semistructured interviews and field or participant observations. Sample sizes ranged from 15 to 623 participants, with most studies based on fewer than 200 participants (figure 2(b)). The dryland locations covered by our sample of case studies are exposed to a range of environmental changes and hazards. Most commonly, 4 Environ. Res. Lett. 17 (2022) 083003 R Hoffmann et al studies reported changes8in the amount of rainfall (71.9% of studies) as well as more unpredictable and erratic rainfall (48.3%), increasing temperature levels (67.4%), and drought (41.5%) as major sources of environmental stress. Also, risks related to the degradation of land (58.4%) and water bodies (31.5%) were frequently mentioned. These include issues related to soil erosion (10 study cases), lake drying (4 cases), and the desiccation of floodplains (1 case). Other mentions relate to risks of flooding (18.0%) and stress related to wind (10.1%), especially increasing wind speeds (7 study cases) or the occurrence of dust storms (4 cases). 3.2. Data and measurement From each article, we extracted information about the study location(s), period of data collection, other study characteristics and results, which became the basis of our meta-data. We use this information to compare result patterns across studies and explore whether these were influenced by contextual factors at the household and community level. We are primarily interested in the adaptation strategies used by households, which we classify in 14 broad categories. In each category, we calculated the percentage of households among the study population who reported the adoption of a specific type of strategy. Table S1 in the supplementary materials gives examples of adaptation measures reported in each of the 14 categories. Typically, the households reported the use of several measures belonging to one category at a time. This means that in certain categories several percentage values were recorded, the sum of which may exceed the value of 100%. Based on the information retrieved from the studies, we constructed two main outcome variables for each of the 14 adaptation categories: (i) A dummy variable taking the value of one if any measures belonging to a specific category were reported in the study population and zero otherwise, and (ii) a continuous variable which corresponds to the share of households using the most common measure in a category. The latter measure provides a conservative lower bound estimate of the share of households using measures in each of the 14 adaptation categories. For our main analyses, we rely on the continuous outcome. Results using the dummy variable are reported in the supplementary materials (supplementary figure S3). Importantly, both the dummy and the continuous outcome variables are comparable across categories and across studies, which allows us to investigate what the most common forms of 8Depending on the study, this information is based on perceptions by the local study population, measurements by the respective researchers, or secondary data. adaptation are, and in which context they are most likely to be used. In addition to the measures described above, we retrieved information from each article about the mode of data collection, characteristics of the interviewed households, indications of environmental change processes, and other environmental and nonenvironmental factors relevant for the local context. One key piece of information which was retrieved from the studies is the predominant livelihood strategy among interviewed households. We used this information to categorize study populations in three types: sedentary farmers, (agro-)pastoralists, and mixed populations who use a combination of both farming and (agro-)pastoralism (figure 2(a)). Among the different livelihood strategies, farming was the most common across study populations, with nearly 80% of households on average involved in some form of farming activities. We aimed to collect the precise global positioning system (GPS) coordinates (latitude and longitude) of the study populations. Some studies did not report GPS coordinates, but we managed to determine the approximate location of study sites based on available information, for example the name of the district in which the study was carried out. Once the GPS coordinates of each study location were determined, we were able to join the meta-data retrieved from the articles with external data sources. In particular, we added information about the overall socioeconomic conditions in the region, which may influence the adaptation options available to households. We retrieved information about the overall socioeconomic conditions from Demographic and Health Surveys (DHS)—large and nationally representative household surveys conducted in over 90 lowand middle-income countries, including most countries in SSA. The DHS data are representative at the subnational level, which is usually based on the census enumeration areas in the respective country (for example region or district). Various contextual information were obtained from DHS and aggregated at the lowest representative enumeration area for the respective DHS survey. In particular, we calculated: (i) the percentage of households employed in agriculture, including both farmers and (agro-) pastoralists, as a proxy for agricultural dependence, (ii) the percentage of households with access to electricity and with a finished (non-natural) floor as wealth proxies, and (iii) the percentage of households with secondary education and higher as a proxy for adaptive capacity related to education. To assign accurate background information to the case studies, we used DHS data from the same period when the data for the original studies were collected. If studies were missing information about the exact data collection period, we used the publication year as reference point. 5 Environ. Res. Lett. 17 (2022) 083003 R Hoffmann et al 3.3. Analytical tools: identifying adaptation patterns across studies We employed a range of analytical tools to identify adaptation patterns across the studies included in the analysis. The texts were comprehensively screened and relevant data concerning study context, methods, and findings were extracted into a spreadsheet. The distribution of adaptation patterns across studies was explored and described using quantitative methods and descriptive graphs for illustration. In addition, we reviewed and coded the texts to contextualize the findings from the studies and to provide an in-depth perspective and examples on how the study populations responded to environmental changes. Here, we primarily identified common protective and adaptive activities employed by households as well as challenges reported. In this study, we are particularly interested in migration and how it is used in combination with other strategies depending on the ecological and socioeconomic context. The primary goal is not to consider migration in isolation, but to understand its links to adaptation in a community more broadly. To this end, we consider differences in response patterns conditional on characteristics of the local populations represented by the studies. Matching case study locations with external socioeconomic data derived from DHS allows us to complement the information provided in the studies with wider contextual measures and effectively compare the different study contexts with each other. Cluster analysis is used to identify adaptation clusters within the case study sample, i.e. populations using similar strategies, and to determine the socioeconomic conditions associated with certain combinations of adaptation activities. For the clustering, we use a centroid-based k-means clustering approach, which partitions the observed study cases x into a set C of k different clusters so as to minimize the within-cluster sum of squares (WCSS), i.e. the difference of each observation from the mean µiwithin each cluster Ci. arg min S k ∑ i=1 ∑ x∈Ci ||x−µi||2(1) The number of clusters kis defined prior to the clustering and we employ various tests to identify the optimal number in our application (see supplementary materials E). xrepresents a vector of the percentage of households in a study sample using the different adaptation strategies. The cluster analysis is performed in R using the cluster package (Maechler et al 2021) and the Hartigan and Wong algorithm (1979). The algorithm assigns data points to a randomly created initial set of clusters based on their difference to the cluster centroids and calculates changes in the WCSS (1) if the data point were to be included in another cluster. If the resulting WCSS is smaller than in the original assignment, the data point is assigned to this new cluster. This iteration continues until the assignment is stable, i.e. no more improvements in the WCSS criterion can be reached by changing cases between clusters. In this situation, any change would make the clusters more internally variable or more externally similar and thus increase the WCSS. 4. Results 4.1. Households rely on diverse adaptation strategies Households use a diverse range of strategies to cope with and adapt to the environmental changes observed (figure 3). Agricultural strategies, including measures related to crop cultivation (41.2%), livestock keeping (24.4%), and soil and water management (21.5%), are clearly the most common, likely reflecting the predominance of sedentary farmers in our sample of studies. This also indicates a tendency of households to adapt in-situ and continue with agriculture rather than completely abandon cropping or herding.Thereliance on in-situ activities could be due to socio-cultural reasons that induce people to stay in their current place of residence, such as place attachment (Vinke et al 2020), or it could be due to barriers and constraints in mobility (Cattaneo and Peri 2016). The agricultural strategies cover a broad range of activities further highlighting the diversity of adaptation measures used by rural households. As part of the most commonly reported category, crop management, households report changes in their use of fertilizer and compost (e.g. Barbier et al 2009, in Burkina Faso; Mertz et al 2009b, in Senegal), the use of more resistant crop varieties (e.g. Tambo and Abdoulaye 2013, in Nigeria; Okpara et al 2016, in Chad), the diversification of crops (e.g. Gebrehiwot and Van Der Veen 2013, in Ethiopia; Antwi-Agyei et al 2014, in Ghana), changes in crop rotation (e.g. Padonou et al 2014, in Benin; Yila and Resurreccion 2014, in Nigeria), and modifications in the farmland (e.g. Snorek et al 2014, in Niger; Tesfaye and Seifu 2016, in Ethiopia). A broad variety of other (non-agricultural) strategies are also used by the households. These include short-term strategies, such as the search for aid (8.7%) or support within the social network (13.7%), or financial measures, such as taking loans or dissolving savings (7.6%). Changes in food consumption and provision are also often reported (15%). In many study contexts, these changes reflect adaptation challenges and heightened levels of vulnerability of affected populations. Some studies report changes in diets, such as an increase in the consumption of wild plants or fruits (Osbahr et al 2010, in South Africa; Bola et al 2014, in Zimbabwe) or low quality famine foods (McKune and Silva 2013, in Nigeria). 6 Environ. Res. Lett. 17 (2022) 083003 R Hoffmann et al Figure 3. Adaptation strategies used by households in the 89 case studies. Bar values indicate the average percentage of households who mentioned using the specific adaptation strategies across all case studies. Migration is the third most commonly reported strategy in the sample after strategies addressing crop management and livestock. Note that the percentage values displayed reflect the average share of households reporting to have used an adaptation strategy across all case studies, which represent the units of observation in our review. Others find that households reduce their food consumption to cope with environmental stress, e.g. by eating less (Silvestri et al 2012, in Kenya), eating fewer meals per day or skipping meals (Hänke et al 2017 in Madagascar; Mubaya and Mafongoya 2017, in Zimbabwe; Pauline et al 2017, in Tanzania), or refraining from eating for a whole day (McKune and Silva 2013, in Nigeria). In some communities, households were forced to sell their assets and livestock to buy food (Chianu et al 2004, in Nigeria; Yaffa 2013, in Gambia) or relied on external support and food aid (Silvestri et al 2012, in Kenya; Ariti et al 2015, in Ethiopia). Of all households considered in the studies, on average 7.8% reported to not have used any adaptation strategy. While this might reflect lower levels of exposure to hazards, it could also indicate the presence of adaption barriers. For the case of Ethiopia, Gebrehiwot and Van Der Veen (2013) show that lack of information on adaptation measures and insufficient access to finance are two important factors inhibiting adaptation to climate change (see also Tambo and Abdoulaye 2013, for Ghana, Gbetibouo et al 2010, for South Africa). The availability of information and experiences influence whether and how people perceive environmental risks and how they respond to them. At the same time, adaptation requires financial and other resources, which might not be accessible to all households, e.g. because of insufficient access to agricultural inputs, technologies or credit markets. To better understand household responses to environmental changes, there is a need to consider the wider context in which they take decisions, including their perception of environmental hazards and potential resource constraints (Koubi et al 2016). 4.2. Migration is common and used in a variety of ways Besides agricultural strategies, migration is among the most common strategies reported by the interviewed households. Across all case studies, nearly one out of four households stated to have used some sort of migration as a means to deal with environmental change. As such, it constitutes an integral part of the adaptation options used by rural households in SSA. The in-situ diversification of income sources, which often goes hand in hand with migration (Wuepper et al 2018), was reported by 22.1% of households. In our classification, we treated in-situ diversification and migration as two separate categories to distinguish them in the analysis. Migration can serve the purpose todiversifyincomesources exsitu,whichwas also mentioned as an important motive for migration by several of the reviewed studies (Osbahr et al 2010, Dumenu and Obeng 2016). Of the 17 case studies with very high levels of migration (mentioned by >50% of all households), 12 (70.6%) were conducted in the Sahel region. Typically, the migration patterns reported by households 7 Environ. Res. Lett. 17 (2022) 083003 R Hoffmann et al in these studies were internal within the same country or region. For example, vulnerable communities in Northern Ghana had a long history of migration to Southern Ghana, especially by young men, to engage in farm or off-farm wage labor (Antwi-Agyei et al 2014, Ngwese et al 2018). A similar pattern was observed in a study from Northern Burkina Faso, where household members primarily migrated to the South of the country where land was still available or to neighboring Ivory Coast to work on cocoa plantations (Barbier et al 2009). In Niger, households reported the neighboring countries of Libya and Nigeria as primary migration destinations (McKune and Silva 2013). Seasonal migration for a restricted time was very common among the study populations. In Chad, Botswana, and Burkina Faso, for example, households were found to travel to resource-abundant areas for collectivelivestockgrazing orfishing(Motsholapheko et al 2012, Okpara et al 2016), highlighting the importance of mobility for communities depending on herding and transhumance (see also section 4.3). In Kenya, Turkana herders frequently moved across borders, especially to Uganda, South Sudan, or Ethiopia, to access resources and markets (Opiyo et al 2015). Similar patterns of livestock-related seasonal mobility were reported for Ethiopia (Berhanu and Beyene 2015) and Zimbabwe (Mubaya and Mafongoya 2017). While temporal forms of mobility were found to be common in the considered sample of studies, also more permanent forms of outmigration were used. In Burkina Faso, for example, the majority of study participants considered permanent migration to other parts of Burkina Faso or to Ghana/Ivory coast a viable strategy if climate change impacts worsen (Zampaligré et al 2014). New international destinations are also becoming more attractive for migration from the region. For example, international labor migration from Ethiopia and other Eastern African countries to the Arab states of the Persian Gulf is a growing trend (Mersha and Van Laerhoven 2016). If migration is used, it is typically only individual household members who migrate and not the entire household (Smucker and Wisner 2008, Barbier et al 2009, Dumenu and Obeng 2016). In the sub-Saharan context, migrants are usually young men who migrate for economic reasons to find work or to engage in seasonal jobs. In search for better opportunities, many migrate internally toward urban centers (Clement et al 2021), which is also reflected in several of the case studies (e.g. Yaffa 2013, in Gambia; Dumenu and Obeng 2016, Kumasi et al 2019, in Ghana). This contributes to the rapid urban growth observed in SSA, which is the world region with some of the fastest growing cities worldwide (Hoffmann and Muttarak 2021). Remittances play an important role for mobility in the area and migrants usually maintain close ties to their home regions. Even if migration in the considered studies is not explicitly framed as ‘economic’, it is often mentioned in association with job search or remittances (Snorek et al 2014, Yila and Resurreccion 2014, Ngwese et al 2018). This also highlights the multicausal nature of mobility, which is typically influenced not only by one, but a range of different economic, sociopolitical, demographic, and environmental factors (Black et al 2011a). 4.3. Livelihoods and ecological conditions shape migration patterns The relationship between environmental factors and migration is not uniform but depends on the local livelihood and ecological conditions (figure 4). While in-situ adaptation strategies, such as changes in cultivation practices or soil and water management, are most often reported in studies focusing on farmer populations, migration is clearly most common among (agro-)pastoralists. In those highly mobile communities, the role of environmental change processes has to be understood against the background of existingformsofmobility (e.g.transhumance),which are influenced by a range of factors (Boas et al 2019). These populations are also more likely to report diversification (38.8%) and changes in food consumption (37.3%) as ways to cope and adapt when confronted with environmental changes and hazards (figure 4(a)). In many instances, migration in search for better economic opportunities were also reported. In Ngamiland, Botswana, for instance, high percentages of respondents stated to migrate to towns for wage labor in the context of pastoral rangeland degradation (Basupi et al 2019). Similarly, a study from Kenya mentions out-migration of agro-pastoralists in search of paid work (Smucker and Wisner 2008). There might be several reasons for the higher prevalence of migration among (agro-)pastoralist households, which we discuss in greater detail in section 5. In rare cases, households reported the reduction of mobility (4.2%) as a way to deal with an environmental hardship (McKune and Silva 2013). This strategy was again most commonly reported by pastoralist populations, who might have had to settle temporarily if they were unable to sustain their livelihood with a nomadic lifestyle. This is also exemplified by Basupi and colleagues (Basupi et al 2019), who report an increasing dependency of pastoralists on social welfare programs due to the high uncertainty of pastoral income (resulting i.a. from livestock diseases and restricted access to productive rangelands) and lacking alternative income sources. Whether or not migration is used by communities in the drylands is found to also depend on the reported environmental changes (figure 4(b)). Most commonly, households listed migration as a strategy in the context of land degradation (28.4%), rainfall variability (27.8%), flooding (24.7%) and drought 8 Environ. Res. Lett. 17 (2022) 083003 R Hoffmann et al geographic location of communities, which is especially challenging for mobile nomadic communities. Despite of the explorative character of our analysis, it provides a comprehensive overview of central findings in the literature and yields important insights into the role environmental changes and adaptation play for migration and the importance of contextual influences in shaping the processes. 6. Conclusion Drawing from comprehensive empirical data from 89 case studies covering more than 21 thousand rural households, our review study illustrates the diversity of ways communities in sub-Saharan drylands deal with environmental change and hazards. Measures related to agricultural and livestock management were identified as most common, followed by migration, income diversification, and soil and water conservation. Most importantly, our findings show that the relevance of migration as adaptation strategy depends on the respective livelihood and ecological context. Migration was found to be more prominent among (agro-)pastoralists than farming households, and was reported most often in the context of rainfall variability, land degradation, droughts and floods. Our results indicate that migration is closely linked to and complemented by other strategies, in particular livestock-related forms of adaptation, the diversification of income sources, the search for social support, and changes in food provision and consumption. This corroborates that a holistic perspective, which considers migration in connection with other adaptation strategies, is indispensable to advance research on environmental migration. Our cluster analysis reveals three distinct migration clusters shaped by different socioeconomic profiles and varying levels of vulnerability. This confirms that environmental migration occurs in contexts of both low and high social and ecological vulnerability. In other words, depending on the circumstances, migration can be a strategy of last resort due to high environmental stress and lacking in-situ alternatives or a proactive choice of individuals and households with potentialpositive synergy effects with other strategies, increasing household resilience. Policy interventions should generally be designed to increase the agency of vulnerable population groups and aim to facilitate movement of those who wish to migrate and to assist in-situ adaptation of those who wish to stay. Empowering households exposed to environmental risks to take selfdetermined decisions will be key to increase the adaptive and beneficial potential of migration. Moreover, our results underline the necessity of carefully tailoring policy measures to the respective livelihood and ecological context given the range of situational needs and household capacities. Migration as an adaptation strategy itself is embedded in a range of other activities carried out by households that should likewise be a focus of holistic policy responses to changing environmental conditions. Climate change will have major implications for drylands in SSA. The development of foresighted and anticipatory policy instruments and the strengthening of the adaptive capacities and capabilities of vulnerable populations are hence key to prevent and mitigate negative impacts in the future (Gemenne and Blocher 2017, Cattaneo et al 2019). Data availability statement The data that support the findings of this study are available upon reasonable request from the authors. The full list of studies considered in this review are displaced in supplementary table S1. Acknowledgment We are grateful to Lena Hubertus for her valuable assistance in the coding and preparation of the data. R H gratefully acknowledges funding from IIASA and the National Member Organizations that support the institute, and from the International Climate Initiative (IKI) of the German Federal Ministry for the Environment, Nature Conservation and Nuclear Safety (BMU) under the EPICC (East Africa Peru India Climate Capacities) Project. CW and KH acknowledge funding from the German Federal Ministry of Education and Research (BMBF) within the Junior Research Group MigSoKo (01UU1606). The research reported in this paper contributes to the Programme on Ecosystem Change and Society (http:// www.pecs-science.org/). ORCID iDs Roman Hoffmann https://orcid.org/0000-00033512-1737 Charlotte Wiederkehr https://orcid.org/00000002-3624-4061 Anna Dimitrova https://orcid.org/0000-00032715-9276 Kathleen Hermans https://orcid.org/0000-00028475-9019 References Ansah I G K, Gardebroek C and Ihle R 2020 Shock interactions, coping strategy choices and household food security Clim. 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