The following is the established format for referencing this article:Tebboth, M. G. L., C. Singh, D. Spear, A. M. Mensah, and P. Ansah. 2023. Everyday mobility and changing livelihood trajectories: implications for vulnerability and adaptation in dryland regions. Ecology and Society 28(1):36.
Dryland regions are highly dynamic environments in which multiple pressures intersect, threatening livelihood security. Mobility is an integral feature in these environments and represents a key risk management strategy for people to respond to frequent livelihood shocks and stresses. Global environmental change scholarship has tended to articulate spatial and temporal change inadequately, portraying populations in a way that belies their socially differentiated and inherently mobile livelihoods. We explored the role of mobility as an ongoing, “everyday” adaptive response to changing environmental, economic, and social conditions. We draw on 21 Life History (LH) interviews to explore the drivers and outcomes of people’s mobility behavior in drylands of Ghana, Kenya, Namibia, and India. We present the adaptation option space (AOS) as a novel theoretical development to explore livelihood trajectories. Within our cases, we found that mobility was ubiquitous and facilitated changes to and exchanges within people’s risk profiles in three main ways: novelty (risks gained or lost), modification (risks attenuated or accentuated), and no change. Temporal analysis showed three broad trajectories in people’s lives set within broader structural constraints: upward, downward, and stable, depending on people’s abilities to manage their AOS. The analysis confirmed that the AOS was a useful heuristic to understand how people exert agency to respond to an array of converging risks while negotiating broader drivers of change. Moreover, the data demonstrated how compounding shocks had negative impacts on people, highlighting the value of temporally-sensitive approaches.
The drylands of the world are the largest global biome (Schimel 2010), covering between 41% and 45% of the earth’s surface (Prăvălie 2016) and accommodating more than a third of the globe’s population. Drylands are characterized by low and highly variable precipitation and high temperatures; limiting fresh water availability and other essential natural resources (Reynolds et al. 2007, Huang et al. 2016, IPCC 2019, ILRI 2021). These regions are experiencing multiple pressures, including increasing rates of aridity and soil degradation, poorly planned and implemented development interventions, rapid population growth, historically high rates of poverty, poor communication infrastructure, and isolation from national centers of power, stressing livelihoods reliant on natural resources (Sietz et al. 2011, Reid et al. 2014, Shackleton et al. 2015, Stringer et al. 2017). Although pastoralism dominates dryland regions, rainfed and irrigation agriculture, waged labor and other forms of employment in burgeoning towns, different forms of trade, and exploitation of natural resources are also common livelihoods.
Anthropogenic climate change poses additional risks to often already tenuous livelihood security in dryland regions (Tucker et al. 2015). For example, the drylands of East Africa will warm faster than the global mean, seeing greater incidences of extreme events, such as the number of consecutive dry days, hot spells, and storms (Osima et al. 2018). Similar changes are modeled for dryland regions of West Africa (Diedhiou et al. 2018), southern Africa (New 2018), and India (Ramarao et al. 2019), suggesting that the coming decades will become more challenging, especially when considered alongside current natural resource degradation and livelihood precarity (Stringer et al. 2017, IPCC 2019). The potential negative implications of these processes re-emphasize the importance of understanding why populations are vulnerable and the options they have to respond to livelihood threats (Cervigni et al. 2016a, Shukla et al. 2017).
Mobility, as an integral component in many people’s lives and livelihood portfolios, constitutes a key risk management strategy (Wiederkehr et al. 2018, Cundill et al. 2021). Over time, mobility behavior changes as do the risks and vulnerabilities that people experience (Adger et al. 2003, Ribot 2014, Joakim et al. 2015, Otto et al. 2017, Singh and Basu 2019). Despite the knowledge that risks and responses are dynamic and linked (recursively), temporally-sensitive research that actively seeks to explore relationships between mobility and vulnerability, adaptation, and well-being is limited (Fawcett et al. 2017). This dearth of empirical evidence and an associated corpus of theory minimizes opportunities to challenge approaches that implicitly privilege static understandings of the world and support interventions that better accommodate dynamism and flux in populations (Ford et al. 2010, Krishna 2010).
The focus of our research is on dryland regions in Africa and India, where mobility is instrumental in enabling livelihoods (de Haan et al. 2016). Despite the importance of everyday mobility to livelihoods in dryland regions, it remains a neglected area of study within global environmental change literature, and a poor relation to the much more recognized and studied forms of mobility behaviors, such as international, national, and place-based work on migration and environmental change (Boas et al. 2019, Kothari and Arnall 2019, Cundill et al. 2021). The tendency to focus on rural to urban migration or movement driven by extreme events masks the importance of everyday mobility and the crucial role these forms of movement play in people’s risk management and adaptation behavior.
We focus on mobility as an everyday adaptation response to environmental change and other dynamics in dryland regions. The novelty of our study is twofold: we develop a heuristic, the adaptation option space (AOS), to explore adaptation behavior, and we generate new empirical insights by dissolving the compartmentalized way research on mobility has been pursued in dryland regions. To do so, we use a Life History (LH) methodology (Singh et al. 2019) to understand people’s livelihood trajectories, capturing the temporality of risks, livelihood choices, and adaptation outcomes and their interrelationship. Through this approach, we shed light on the use of mobility and the dynamic nature of risks, responses, and well-being within the context of dryland regions, which remain underrepresented in the literature on climate change adaptation.
Climate change is frequently portrayed as something exceptional or abnormal, a rupture from the daily rhythms of life, which cannot be assimilated into the everyday. Yet climate change is something people live with, interpret, and act on continually based on their own particular understanding of the world around them (Hulme 2009). As we come to understand the nature, scale, and urgency of the societal changes required to respond effectively to climate change, the importance of moving away from a framing of exceptionality toward one that seeks to integrate action and understanding on climate change within the rubric of the everyday becomes more compelling (Hornidge and Scholtes 2011, Duvernoy 2020). At a broader scale, studying the everyday can appear inappropriate and ill-suited (Kothari and Arnall 2019). However, in focusing on the everyday we are required to reinterrogate how some of the larger issues in adaptation science are refracted through everyday practices. For example, Funder and Mweemba (2019:130) observe that the “less conspicuous” daily practice of climate governance is often neglected even though it is through these on-the-ground actions that climate policies and programs are implemented. Artur and Hilhorst (2012) make a similar case in relation to the discourse, asserting that climate discourse is given form only through everyday practice. Lastly, and more directly related to our focus, Schofield and Gubbels (2019:94) assert that a “gap persists between how the effects and risks of climate change are encountered as everyday realities by people experiencing them.”
For the purpose of our research, the everyday enables us to refocus our analytical lens and disrupt the powerful notion of climate change as exceptional, and instead reframe the object of enquiry onto daily activities, behaviors, and practices (Oppermann et al. 2018). Kothari and Arnall (2019) argue that although the everyday is seen as unexceptional and normal, mundane even, it provides a valuable window to understand and explore the connections between environmental change and how people respond to those changes. Changes can include those that are more regular and predictable, such as seasonal change, as well as those that are more unusual or seen as a rupture from the norm, such as chronic drought. Despite the growth in studies using the everyday as an analytical and interpretive lens, there is surprisingly little literature that explores connections between people’s daily practices and changes in the environment and, more specifically, in dryland regions where mobility is used to respond to changing conditions at different temporal scales. Generating knowledge on the everyday responses to change is important because, although climate change is clearly an “exceptional” phenomenon, it is given form and meaning through its everyday manifestations. In essence, exploring climate change in terms of how it is grounded in the local and familiar landscapes of everyday life in dryland regions provides an opportunity to connect with and understand the real and perceived effects of climate change its impact on people (Brace and Geoghegan 2010).
Drylands and dynamic mobilities
Mobility is an essential feature of livelihoods in dryland regions (Stafford Smith et al. 2011, de Sherbinin et al. 2012). In spatial and temporal terms, people interweave different forms of movements across scales as they navigate their life course (Parsons 2017, Cundill et al. 2021); instances of mobility are not a series of compartmentalized and discrete events that interrupt longer periods of immobility. When viewed in this light, the more exceptional forms of movement, which are commonly studied but occur comparatively infrequently, are part of a spectrum of mobilities people employ at different frequencies in response to a range of dynamics and a diverse portfolio of livelihood practices (Goodall 2004, Hunter et al. 2015, Singh 2019, Gongbuzeren et al. 2021). Despite the more commonplace and everyday mobilities being the lived reality for many, it is exceptional mobility that draws attention, indicating a surprising oversight in scholarly enquiry.
Within dryland regions, the most notable and “visible” forms of mobility are pastoral mobility (Catley et al. 2013), rural to urban migration, labor, or seasonal migration (Neumann and Hermans 2015), and, more recently, mobility associated with environmental change (Borderon et al. 2019). With regards to pastoral mobility, we are seeing a decline in broad scale movements as constraints on mobility are increasingly pronounced as land becomes more fragmented and enclosed (Reid et al. 2014, Carabine et al. 2015, Nyberg et al. 2015, Greiner 2016, Mosley and Watson 2016), and there appears to be a general shift toward more sedentary lifestyles (Mganga et al. 2015, Cervigni et al. 2016b, Greiner 2016, Watson et al. 2016). As broader scale movements decline, the likely attendant increase in finer scale movements is increasingly recognized as significant (Liao et al. 2020), but remains marginal to scholarly interest. Similarly, although scrutiny has focused on the importance of rural to urban and seasonal migration as a significant and ongoing dynamic within dryland regions (e.g., Wiederkehr et al. 2018, Cattaneo and Robinson 2020), it is not the only form of mobility linked to economic opportunity. As with the example above, the broader scale movements that have received much attention are superimposed onto a pattern of finer scale movements necessary to access local markets, smaller towns, and urban centers at greater frequency (Stafford Smith et al. 2011), or signifying deeper changes as some people abandon pastoralism altogether (Catley and Aklilu 2013, Camfield et al. 2020). These two examples suggest a blind spot for the finer temporal and spatial forms of mobility despite their importance (Hunter et al. 2015).
As with mobility, vulnerability, risk, and adaptation are not static: they change temporally (Ford et al. 2010, Fawcett et al. 2017). Such dynamism is a feature of all social-ecological systems (Gunderson and Holling 2002). Yet, much scholarship implicitly portrays the world as a series of discrete points in time with only weak links between them. Studies of migration under conditions of environmental change are an example. They are not generally adept at representing dynamic elements and the interactions between them. These approaches can be grouped into five broad analytical categories: exposure, hotspot, attribution, proxy-attribution, and ethnographic (Piguet et al. 2011, McLeman 2013, Fussell et al. 2014, Eklund et al. 2016, Piguet et al. 2018; Table 1). Within these approaches, divergence occurs along a number of axes, such as scale, whether they are primarily retrospective or prospective, data type (qualitative or quantitative), and analytical approach (Thalheimer et al. 2021). The primarily quantitative approaches (attribution and proxy-attribution) tend to analyze mobility behavior to detect the environmental signal (Kniveton et al. 2008, Findlay 2011, Piguet et al. 2011), whereas mixed-methodologies and more qualitative approaches seek to understand how mobility behaviors are perceived and understood within the lived reality of people’s lives (Singh et al. 2019). Within this portfolio of methodologies, some, such as the attribution approaches, are more skillful than others at understanding and probing temporality.
Two notable issues persist. First, taking environmental change as the independent variable promotes a focus on mobility linked to environmental change. Yet, lives are not lived by prioritizing the environment above other considerations. We discussed that mobility is fluid, scalar, and multi-causal (Bakewell 2010, Bardsley and Hugo 2010). Therefore, trying to understand how mobility has been used within a person’s life provides a more contextual understanding that better values people’s well-being above a focus on when and how mobility is used in relation to environmental change (Farbotko et al. 2018). Second, even in the methodological approaches that actively conceptualize temporality, only a few get beyond simplistic models that adequately represent temporal change (Singh et al. 2019).
Risk, response, and the adaptation option space
Climate change studies have developed multiple ways to conceptualize how people negotiate and respond to risks (for comprehensive reviews of this concept see Giupponi and Biscaro 2015, Räsänen et al. 2016, Jurgilevich et al. 2017, Thomas et al. 2019, Simpson et al. 2021). Initial studies theorized vulnerability as an outcome of external stressors or hazards acting upon a system or unit of analysis, such as people or populations (Brooks 2003, Füssel and Klein 2006). However, this hazard-stressor model was critiqued for being too simplistic and linear in its understanding of complex, interacting, and multi-scalar processes of risk and response (Ford et al. 2010, Ribot 2014). Vulnerability is inherently contextual (Tucker et al. 2015), characterized by an underlying set of structural conditions (Joakim et al. 2015:147) that mediate how “climate change is experienced and which shape(s) responses available to adapt” (Ford et al. 2010:377). Building upon this view of vulnerability as structural and historically-constructed (Tschakert et al. 2013, Ribot 2014, Eriksen et al. 2021), the “risk space” can be understood as not only the exposure of systems or people to a hazard or stressor, but also a space that is critically mediated by contextual vulnerability (Fig. 1).
The well-established and large body of research spanning social anthropology, critical human geography, political ecology, and hazards (Watts and Bohle 1993, Forsyth 2003, Blaikie 2004, Ribot 2010, Otto et al. 2017, Ford et al. 2018, Thomas et al. 2019) shows that vulnerability is socially generated and not an intrinsic characteristic of a given unit of analysis. Recognizing that the risk and response spaces have their roots in society maintains an analytical focus on the more immediate actions, opportunities, and limitations, as well as the ways society produces and reproduces conditions that can result in negative outcomes, such as loss and damage to assets, impacts on livelihoods, or loss of dignity (Wiederkehr et al. 2018). Contextual vulnerability varies temporally between places and populations, is relational, scalar, and dynamic, and is a crucial element within the AOS framework. The incorporation of contextual vulnerability within the framework enables one to explore how vulnerability is socially differentiated and how it interacts with the AOS (Haasnoot et al. 2020). For instance, by understanding how contextual vulnerability differs along lines of gender and ethnicity-based marginalization we can explore how this influences the risks populations are exposed to and the responses that are available to them (Thompson-Hall et al. 2016, Boas et al. 2022).
To cope with and adapt to risk, actors practice multiple risk management strategies. Several heuristics have been put forth to conceptualize this range of risk management behaviors and examine why different people undertake different responses. Using a livelihoods lens, Osbahr et al. (2010:1–2) articulate the “response space” as “the set of options open to actors trying to enact multiple livelihood and development outcomes,” and it includes short-term reactive coping strategies as well as longer-term, more planned adaptation responses (Fig. 2). Singh et al. (2016) stretch the response space heuristic further to define a “response continuum,” which spans responses from undertaking no response, through maintaining the status quo to coping, which is typically short-term and may lead to adaptations or exacerbate vulnerability, and finally, adaptation, implying a more permanent, forward-facing change. Such a definition acknowledges that people may undertake several responses simultaneously and that these are mediated by cross-scale drivers and actions. Schipper (2020) extends this idea of a continuum to showcase how risk management can lead to adaptation and/or maladaptation, with implications on whose vulnerability is reduced or not.
A smaller subset of the response space is the “adaptation space” (Adger 2003:401), that alludes to the availability of and access to adaptation options that a person possesses and is able to enact. Adger et al. (2003:193) argue that safeguarding and strengthening this adaptation space is “a central development imperative” but do define not the term comprehensively. The adaptation space has also been used to highlight issues of politics and agency in adaptation decision making (Pelling et al. 2015:113) through a framing of the “adaptation activity space” that includes seven coevolving sites: the individual, technology, livelihoods, discourse, behavior, the environment, and institutions. More recently, the idea of adaptation space has been used to examine how past development decisions have impacted ecological and social systems to affect present-day adaptive capacity and availability of adaptation options (Gajjar et al. 2018).
Other adaptation scholarship invokes the idea of lost opportunity costs to take advantage of “unique windows of opportunity” (Hallegatte 2009:246) to reduce future adaptation needs, and staying within “adaptation limits” because “opportunities and resources to adapt may be finite for many social actors” (Dow et al. 2013:305). These heuristics suggest that the space to adapt is limited, it varies over time and by social grouping, and that different people have different levels of access to this space. Looking to the future, adaptation pathways approaches (Werners et al. 2021) emphasize how, without urgent action, the space to adapt can become constrained, especially for vulnerable populations who lack the means to respond to livelihood stressors effectively.
Figure 3 consolidates our understanding of the AOS, which is determined by the amount of risk a person or population is exposed to and their ability to respond. Both the risk space and the response space can move independently but are linked through the AOS and change temporally. For example, the risks that a person is exposed to, such as drought causing failed crops or livestock death, can increase or decrease, whereas their response space remains static, resulting in top-heavy and unstable AOS (Fig. 3b). Conversely, through social networks or entrepreneurship for example, the response space can increase whereas the risk space remains static. In this formulation, the AOS, with a wider base, is more stable and desirable (Fig. 3c).
We apply this AOS framing to conceptualize livelihood decisions and outcomes for risk management in drylands with recent advances in climate change vulnerability and adaptation research, arguing that this framing pays explicit attention to (1) contextual vulnerability and the structural factors that shape choice and decision making; (2) the agency and barriers to risk management and livelihood choices; and (3) temporality by focusing on dynamic decisions.
Life History (LH) methodologies provide a useful counterpoint to the larger scale and more quantitative approaches that dominate the literature on mobility and environmental change. The use of LHs to understand temporal change within people’s lives is common in other areas of social science, for instance migration (but not from an environmental change perspective), education, and studies on youth transitions (Thomson et al. 2002, Langevang 2008, Holland and Thomson 2009, Porter et al. 2010, Porter et al. 2011, Ansell et al. 2014, Etzold 2016). Despite the obvious strengths of understanding trajectories of change (Krishna 2010, Ayeb-Karlsson et al. 2016, 2020), LH methodology has rarely been applied to explore vulnerability and adaptation in relation to risks associated with climate change (Singh 2018).
The LH methodology is employed here to understand the role of mobility within the portfolio of individual and household risk management strategies. We drew on a total of 14 cases generated through 21 long-form, semi-structured LH interviews in dryland regions of Ghana, Kenya, Namibia, and India that were undertaken during 2016 and 2017 (Fig. 4). The research was part of a five-year, multi-country project, called Adaptation at Scale in Semi-Arid Regions (ASSAR), through which we investigated livelihood dynamics within the context of social and environmental change in the semi-arid regions of west, east, and southern Africa and Asia. In each of the four countries, different cases of two household members were purposively from locations within the wider research area. Davies et al. (2018) and Singh (2018) provide a more detailed description of the LH method we employed, including its strengths and weaknesses. We only report on the dynamics associated with mobility, livelihoods, well-being, vulnerability, and adaptation; the research design, site selection, and identification of participants were informed by other research within the wider project.
The three sites in the Upper West Region of Ghana were Jirapa (a business and government hub), Nandom (a smaller farming community situated closer to Burkina Faso’s south-western border), and Lawra (a predominantly business and farming community). Most livelihoods are agriculture-based, including crop farming and goat rearing. In Kenya, the three sites were two rural villages within Isiolo County, Kachuru (a small settlement of Meru and Boran pastoralists and traders situated at the foot of the Nyambene Hills), and Kulamawe (a large pastoral village dominated by Boranas), and Isiolo Town (the capital of Isiolo County, where livelihoods are predominantly focused on farming, livestock trading, and entrepreneurship). In India, the study sites in North Karnataka were Kolar district, where diversification to non-farm labor and daily commuting to Bangalore is common, and Gulburga district, where agricultural livelihoods dominate and there has been historical outmigration to large cities. In Namibia, the study sites were Epalela (a small business center), Onesi (a small settlement and district capital with some government offices and shops), and Ruacana (a small town and district capital with some tourist accommodation).
Participants (anonymized with pseudonyms) were purposively identified to sample a diversity of vulnerable households and mobility types. Sampling was informed by gender (male or female-headed households), age (all of productive age but sampled to include older and younger people), livelihood type (farming, pastoral, agro-pastoral, wage labor, business), level of transience (nature of the mobility), and exposure to environmental change and other risks, such as floods, droughts, or conflict (Table 2). The selection criteria were informed by in-depth research, including household surveys, key informant interviews, focus group discussions, and semi-structured interviews, undertaken in the research sites during 2015 and 2016. For this study, the LH interviews focused on understanding the householders’ perspectives of key events, temporal changes, and their implications within their productive lives (normally within the last 10 years), and reflections on their well-being and aspirations for their families and the future (Davies et al. 2018, Singh 2018). Most of the interviews (thematically structured) took between two and three hours and wherever possible, we interviewed two members within a household to examine dynamics in their decision-making processes in relation to each other (for more details on methodology, interviewing process, and how we triangulated data see Singh et al. 2019).
The interviews were transcribed and analyzed using descriptive codes that were inductively developed based on emerging themes from the interviews. The research team co-developed the codes over two workshops to facilitate robust and comparative analysis. Through an iterative process of analysis, four large coding families were developed: (1) description of livelihood dynamics (risks, responses, type of livelihood shifts), (2) intra-household dynamics and decision making, (3) outcomes of responses (e.g., trade-offs, well-being outcomes), and (4) household pathways (e.g., of poverty, future aspirations). A key element of the analysis was the development of visual trajectories (Figs. 5, 6, and 7) that capture key (self-identified) points of significance (indicated by red dots in Figs. 5, 6, and 7) within the lives of our cases and the impact that it had on their well-being. The changes in the risk and response spaces within the visual trajectories were inferred based on the qualitative analysis undertaken by the research team.
Across the four dryland regions, mobility was an essential feature of many livelihoods (e.g., pastoralism, natural resource-based, and trading): it enabled people to access work opportunities (e.g., through commuting), provided a means to relocate and swap one location for another, and helped people manage risks linked with environmental and other changes.
Dynamic risks and responses
Empirical analysis showed that mobility intersected with other drivers and acted on people’s and households’ risk portfolios in one of three ways. Some risks were completely lost through mobility whereas others emerged representing new threats that required management (novelty), other risks were either attenuated or accentuated (modification), and the final category shows some risks move with people but, in essence, remained relatively static (no change).
Within all cases, mobility was a key strategy employed to manage ongoing and emergent risks and highlighted the multi-causal nature of people’s responses. Looking at the specific classes of risk, for novelty, mobility was often employed to relocate from one settlement to another, in so doing people obviated risks associated with contextual vulnerability linked to their position within society in terms of gendered risks or caste-based discrimination for instance.
In the village, we were subservient to the Gowdas [landowning caste] and depended upon them for sustenance and livelihood. In the city, we can lead independent lives [Sriram].
He [husband] had sold one piece of land and they started evicting us wanting even to kill him....They continued fighting and even killed his animals...That’s when he come down here [Makena].
However, although moving helped to reduce some risks, it increased the exposure to other risks, such as flooding in the case of Sriram and occupational health associated with new forms of employment in the case of Ramesh.
We faced difficulties [flooding] when we initially moved into Bangalore....[We were] new to the city [Sriram].
The work [as a painter] is hazardous as one has to take the support of ropes to stand on while painting the exteriors of a building. It has given me a dust allergy. I fell ill two years ago...was exposed to a lot of dust [Ramesh].
The quotes above emphasize how mobility is often a double-edged sword; moving can eradicate or reduce some risks (linked to contextual vulnerability in the examples above), while simultaneously expose people to novel risks. Most of the emergent risks were linked to the new location, which was often urban and included issues associated with increased living costs, the precarious nature of urban livelihoods, and higher exposure to hazards.
The LHs demonstrate how people modify risk by moving. For example, to minimize exposure to drought, Neira and Sibiri took advantage of extended family connections, and Maria increased her skills and diversified her livelihood.
It [diversified income sources] brought more benefits to the family because I helped pay my sister’s schooling when I was working at Oshakati [Maria].
The quality of my life changed [for the better] when I moved out of the village to settle with my Aunty [Sibiri].
In some cases, despite people’s best intentions, exposure to risks increased. The most obvious example within our cases was shown in the ways conflict and familial deaths impact livelihoods in dryland Kenya (Adan and Aisha) and Ghana (Fuseini), accentuating risks and making it more difficult to practice one’s livelihood.
Yes, there is a time I used to buy livestock and add to my herds as profit...before the conflict...but after that it was just a struggle [Adan].
When I moved, my financial situation started going down because of all the challenges I had with my farming activities and the tragedies (deaths) that occurred in my family [Fuseini].
Although the risks themselves were strongly associated with specific livelihoods, they also hint at the additional ways contextual vulnerability was produced in society. In these cases, chronic conflict, which erupts periodically and was simply unavoidable for many, and the often-inadequate social floor undermined the already marginal livelihoods practiced.
In other cases, whether mobility was utilized or not, it was simply impossible to eradicate risks (no change) that one was exposed to. For example, the high costs of urban living (Sibiri) and the multifaceted nature of poverty (Fatima) showed that mobility has not brought about improvements in well-being and that daily survival remained the paramount concern.
Even though I had moved I didn’t want to because I realized I may not achieve my aspirations at city so I had to come back home [Sibiri].
Life is very hard here also when you don’t have a job, there are school fees, and business is not doing well for the last two and half years and if am given opportunity I can even go back to Gafarsa [Fatima].
In these examples, risks that were more structural or integral reproduced themselves regardless of change in location or livelihood and clearly showed the importance of considering contextual vulnerability within climate change vulnerability and adaptation research.
The focus on risks showed the variety of responses (of which mobility was often essential) that people employ to actively manage and respond to ongoing and emergent risks. However, this tells only part of the story. Understanding a person’s trajectory requires knowing how they have responded at a particular point in time and the consequences of their actions and how they enable or inhibit subsequent response.
Trajectories of change
The dynamic relationship between livelihood shocks and responses is evident in our data, and the data reveals great diversity in the nature, severity, duration, and frequency of shocks and the different ways that people respond, resulting in a range of well-being outcomes. Broadly speaking, there are three clusters of cases. At one end of the spectrum are households that manage to maintain an upward trajectory in terms of well-being despite facing a myriad of shocks, whereas at the other extreme, another cluster demonstrates a downward trajectory. In between these poles are a further cluster of cases that show fluctuation, but, ultimately, tend to retain a relatively flat trajectory, equating to no real improvement in well-being but also no deterioration. Across the responses and within people’s personal trajectories, mobility is often crucial.
Navigating a downward trajectory
Within the cases showing a downward trajectory (Fuseini, Jilma, Ramesh, and Makena; Fig. 5), different risks interact with each other and limit the AOS. This cycle of increasingly severe impacts of risk events allied to an ever-smaller AOS locks people into a downward trajectory or cycle and is typified by Fuseini,
At some point within the past 10 years it [well-being] was going down because of all the challenges I had with my farming activities and the tragedies that occurred in my family [Fuseini].
In other examples, we can see that Makena elected to relocate to Kachuru, and Ramesh perceived better opportunities in cities, such as Hyderabad, Pune, and Bangalore. Makena and Ramesh utilized their knowledge and skills, existing assets, and social networks to develop and pursue livelihood options in new locations. However, in attenuating some risks, such as low income and threats of violence, they open themselves up to other emergent risks. Ramesh moved to Bangalore city as a painter but fell ill repeatedly as a result of his work and had to return to the village since he had no ties in the city and hospitals were prohibitively expensive leading him to conclude that,
There is no significant improvement in my life compared to that of my parents. I am unable to break this cycle of poverty that my parents also had to face. We are unable to come out of this and move forward in life [Ramesh].
Similarly, Makena and her husband exposed themselves to increased risks of violence that ultimately resulted in the death of Makena’s husband.
When he [husband] died I continued with my jobs there is no time I have ever gotten enough money.
The agency that the cases demonstrate as they attempt to navigate through a shifting terrain are often confounded by larger social, political, and economic changes, the contextual vulnerability that limit or otherwise inhibit the range and effectiveness of responses. Such was the despair that Makena felt that she concluded that, “my only hope is my children.”
These contextual vulnerabilities act to trap people in a downward trajectory limiting their well-being and offering little hope of improvement without external assistance or changes to underlying societal conditions.
Iterating risks and responses but ultimately stable
Cycles of drought and recovery are a feature of many dryland livelihoods. Sometimes, we see people’s lives fluctuating as they experience and navigate different stresses and shocks in their lives. Adan is a case in point and has been able to recover from successive droughts and ethnic conflict by focusing more on trading of livestock than subsistence pastoralism. Through trade, the enclosure of land, and good knowledge of economic conditions and appropriate markets for purchasing and selling livestock, he is able to better manage his herd and respond to price fluctuations. This enables him to maximize his profits and maintain a reasonably stable life despite the frequent livelihood shocks he and his family have experienced.
I can attribute it [my recovery] to my livestock trade which was able to take away my daily expenses and I can sell my sheep and goats for paying school fees [Adan].
[My] husband has better livestock, even the parents had livestock but not as big as my husband’s and [we are] not badly off [Aisha].
Livelihood diversification is also adopted by Venkata (Fig. 6). Living in Kolar, a drought-prone and increasingly water-scarce district 80 km away from Bangalore city, smallholders like Venkata have few options during prolonged drought. With the district being declared drought-hit since 2013, Venkata narrated finding it very difficult to continue farming.
Growing up, I have seen my father struggle to feed the family. The only way he could do so was [to] be incrementally selling off his land.” Whereas now, “At least they [his children] have finished secondary school and can support themselves and the family if needed [Venkata].
He took loans to dig borewells and tap into groundwater to use as protective irrigation but each of his three borewells stopped yielding water after 8–12 months of use. Compounding this setback was the large expense needed for his daughter’s marriage and dowry, which finally motivated him to move out of agriculture and look for a “more stable and remunerative” job. Today, Venkata commutes to Bangalore daily where he works as a gardener while his elderly mother and wife continue to work in the fields and tend to their livestock. Despite this shift away from farming, Venkata is still unable to pay for his daughter’s dowry and so she has taken up work in Bangalore as a domestic helper to save enough for her marriage.
In different ways, the two cases highlight the importance of everyday mobility in facilitating diversification as a means through which inhabitants in the rural dryland regions seek to minimize risk and maintain their AOS. For Adan, this has seen him focus increasingly on trading livestock, enabling him to respond more flexibly to the variability in the environment and economic conditions, and at times, constrained access to markets (mediated by conflict). Venkata has employed mobility to help his family diversify their income sources to include gardening in the city while continuing to farm in their rural area. The interaction of the risk space and response space over time shows Adan increasing his AOS through the adoption of trading as a more agile livelihood augmented by the enclosure of land to provide a more reliable source of fodder for his livestock. For Adan, although the risk space has remained relatively static, his ability to manage livelihood shocks has improved. For Venkata, similar (unsuccessful) attempts were made by digging borewells, limiting his AOS and leaving him vulnerable to drought (in part driven by contextual factors encouraging greater exploitation of groundwater). As a result, Venkata elected to diversify by working in the city as a gardener ensuring that the family have at least one source of income that is relatively insulated from the impacts of drought. In these examples, we see lives punctuated by shocks and under varying degrees of stress, yet well-being remains relatively stable as a consequence of the continual adjustments and innovations people make to manage their evolving risk profile.
Three cases (Asana, Maria, and Sriram) showed an upward trajectory within our data, two of which we now expand upon. Asana lost her husband, which resulted in her household’s animals, land, and property being transferred to her late husband’s family as is customary, highlighting the contextual vulnerability linked with gendered norms (Fig. 7). Without any support from her husband’s relatives, Asana struggled to make ends meet. She had to take out loans and pull her son out of school, which caused major disagreements within the household. Then, she decided to send two children to live with another family member and to move back in with her parents in another settlement, called Jirapa. These responses reduced the demands on her and helped her to secure access to farmland.
My social mobility has improved for the better because of the hard work to improve the life of my household. Even physically, I used to be very lanky but now I have put on some weight and command respect among my own family and the late husband’s family as well. They sometimes see me as their “god” because of the way I have managed to improve in life out of the difficulty [Asana].
Subsequently, and in addition to farming, she got some casual work cleaning and laboring, which enabled her to pay off the loans she took out to send her children back to school. She is now remarried and settled in Jirapa.
Looking over a longer duration, Maria used her extended family in Oshakati to train as a seamstress. Through her brother she managed to locate premises for her sewing business reasonably close to her family.
Perhaps if I didn’t move away from home then things could have been bad and I could have suffered too. [I]f I couldn’t move away from home then there could not be some infrastructures at home like the running water and the electricity because otherwise no one could get the income to bring some changes [Maria].
She now works there and commutes back and forth to her family home. By diversifying her income sources, she has mitigated the worst impacts of drought periods and also survived shocks of a more personal nature, including the death of two of her brothers and her father. Despite these events, she has managed to improve her quality of life (illustrated through the provision of piped water and solar power for example) demonstrating the upwardly mobile nature of her livelihood trajectory.
In both cases, the mobility that Asana and Maria employ signifies the endemic and important role it plays within dryland livelihoods. For Asana and Maria, the shock of losing the support of male family members on their livelihoods did not appear to have a detrimental and long-lasting impact. This was in part due to the presence of supportive social networks (ability to move back in with family, having children live with other family members, or the support of brothers). As a result, both cases were able to increase their AOS and concurrently reduce their risk space, leaving them well placed to respond and cope with future challenges as and when they occur.
Contextual vulnerability interactions with the adaptation option space
Using the heuristic of the AOS, we explore the trajectories of people’s lives by examining how they manage their risk and response space. Through this conceptualization, we foreground the role of more structural issues, through contextual vulnerability and changing risk profiles, which are often poorly captured within vulnerability and adaptation research (Tschakert et al. 2013, Thomas et al. 2019, Barrett et al. 2021). For example, when moving to Bangalore, Latha initially moved to an area that was prone to flooding. Such an example highlights how, despite moving, the vulnerability that people experience in one location can move with them, supporting similar findings in Latin America (Few et al. 2017, 2021a). Similarly, Makena, in moving to escape the threat of violence in the highlands in Kenya, relocated to an area that was facing ethnic conflict that ultimately resulted in the death of her husband. In these two cases, one set of risks are exchanged for another, highlighting the contextual, often chronic conditions that act to limit one’s AOS and make the risk space particularly hard to manage.
Conversely, people reduce risks on an almost daily basis through autonomous, individual actions. This process of reducing risks can challenge structures that are presented as immutable. For example, Sriram talks about how his caste identity, which was crippling in his village where the rural landowning caste holds the most power, is less of a barrier within the city of Bangalore. In Kenya, the vulnerability that two women (Makena and Hadiya) experienced in the highlands was substantially reduced by relocating to a settlement with a high proportion of female-headed households, because this reduced the threat of violence to them. Although the roles of caste and gender in mediating vulnerability and adaptation practices is increasingly recognized (Sultana 2014, Rao et al. 2020, Garcia et al. 2021), they are often addressed insubstantially or seen as a narrow binary rather than intersectional and relational (Carr and Thompson 2014, Tavenner and Crane 2019, Garcia et al. 2021, Boas et al. 2022).
Krishna (2010), in a cross-country study exploring people’s movement into or out of poverty, discussed the interaction of more structural reasons with individual circumstances in explaining people’s escape from or descend into poverty. Our analysis similarly highlights the strong links (constraints or opportunities) that exist between risks and adaptation decisions and contextual vulnerability. Through the cases, we show how various axes of differentiation, such as gender, caste, livelihood, or location, constrain opportunities differently for different people. In India, caste mediates the AOS, in Kenya gender played a key role, whereas in Ghana, patriarchal social norms were significant. Moreover, risks and vulnerabilities associated with apparently entrenched socio-structural conditions, such as caste, gender, and patriarchy, can be challenged in certain circumstances, questioning the assumption that people at the bottom of economic and social hierarchies lack agency to influence the wider structures that mediate the AOS (Rao et al. 2019, Deshingkar 2022).
Mobility is typically viewed and understood in more bounded and dichotomous ways, delimited through specific temporal or spatial scales, such as labor migration, rural to urban migration, and transhumance (Wiederkehr et al. 2018). This bounded approach has two significant weaknesses. First, it excludes the more everyday mobilities that underpin people’s livelihoods within drylands, and second, it abstracts one form of mobility from the other forms of mobility (occluding interrelations between the different forms) that are deployed to manage and respond to risks. Through the illustrative cases, we show that mobility is fluid and dynamic with people employing it in different ways depending on their needs (Hunter et al. 2015). Seeing mobility through the lens of the everyday helps to dissolve the categories through which mobility is often refracted and sheds light on the varied and important contributions smaller-scale spatial and temporal mobility plays for well-being.
Relatedly, the LH approach, and the greater power it provides the narrator to tell their own story, supports focusing adaptation on people’s everyday lives and offers a counterpoint to the dominant and often apolitical and technocratic ways that adaptation is framed (Ayeb-Karlsson et al. 2016, Eriksen et al. 2021). The portrayal of mobility by the interviewees reveals its normalcy, reflecting its commonplace, yet central importance within lives and livelihoods and the very fluid way it is employed. This normalizing narrative contrasts the exceptionalism that frequently underpins discussions about mobility, particularly within literature on environmental change. Through this recentered view of adaptation and the challenge it poses to dominant framings of events and practices, we can shift the focus to more critical questions that have been of marginal influence on mainstream policy and practice (Ayeb-Karlsson et al. 2016). For instance, in India, promotion of borewells in our case study area is government policy, a specific technical solution to the (biophysical) problem of water scarcity, which helps to shift the focus away from the larger water footprint of urban areas or the role of the caste system in limiting opportunities for specific sections of the rural population (Singh 2021). In Kenya and Namibia, the focus on humanitarian relief during periods of drought is in sharp contrast to the neglected area of longer-term recovery despite its importance in promoting more a more stable AOS (Few et al. 2021b). Additionally, in Ghana, despite years of government programs and subsidies to smallholder farming communities in northern dryland areas to support irrigation and farming during the dry season, the relative economic inequalities of the north-south divide still persist.
Temporality in risk and response
We know that societies are socially differentiated and there is clearly a need for more refined and sensitive approaches that privilege heterogeneity, intersectionality, and situatedness when exploring the risks and stresses that characterize the lives of vulnerable people (Johansson and Vinthagen 2014, Rao et al. 2019). Furthermore, these socially-differentiated risks are experienced dynamically; populations are constantly responding to the changing environmental, social, political, economic, and cultural world around them (Krishna 2010, Fawcett et al. 2017, Thomas et al. 2019). To date, vulnerability and adaptation research has tended to conceptualize the risk and response space as static, with temporality poorly conceived and inadequately represented (Singh et al. 2019, Barrett et al. 2021) despite the knowledge that risks and responses are intimately linked and feedback on each other over time (Tschakert et al. 2013, Simpson et al. 2021). The value of temporally-sensitive approaches to exploring risks and responses is evident in the data on compounding shocks over time. In certain cases (Fuseini, Jilma, Ramesh, and Makena), compounding shocks result in a downward trajectory that is rapid and appears to offer minimal hope of recovery. Here, we see how people’s AOS is influenced not only by their present actions but also by past behavior that ripples forward enabling and constraining subsequent decisions and options (Singh et al. 2021:91).
Understanding a person’s trajectory and the conditions shaping this trajectory is important as it reveals whether the move is in a positive or negative direction, thereby offering a crucial advantage over more static approaches to understanding people’s lives (Haddad and Frankenbeger 2003, West 2013). The constrained choices that the people experience, their contextual vulnerability, illustrate the challenges of recovery when the overall trajectory within one’s life is negative (Rigg and Salamanca 2015, Otto et al. 2017). As the risk space expands and the response space contracts, the consequences for well-being become ever more irreversible, resulting in an increasingly unstable AOS. In these instances, the abilities of individuals are stifled to such an extent that it becomes increasingly impossible to reverse the downward trajectory without challenging the broader conditions that inhibit effective responses (Deb and Haque 2011). In terms of interventions, knowledge about a trajectory and the nature of the risks and adaptation options available to a person or household also provides a good indication of the nature of interventions that are or are not likely to be required and thus effective (Grothmann and Patt 2005, Ford et al. 2010, Krishna 2010, Ayeb-Karlsson et al. 2016).
To understand the contexts that shape everyday mobilities and the outcomes these have on people and households over time, we followed a temporal approach, thereby moving away from more static forms of inquiry. Such an approach demonstrates that risks and responses change, and this widening and narrowing space that people negotiate is what we call the “adaptation option space.” We offer this heuristic to demonstrate how risks and responses change over time, are embedded in people’s contextual vulnerability, and, more crucially, how risks and responses interact to mediate how and why people adapt. Moreover, promisingly, we find that risks and vulnerabilities associated with apparently entrenched socio-structural conditions, such as caste, gender, and patriarchy, can be challenged in certain circumstances and help to explain why some people are able to adapt to change more successfully than others (Deshingkar 2022). Such insights force us to question the assumption that the poorest and more marginalized people lack the agency to influence wider structures that mediate the AOS.
Within the literature on mobility and environmental change, everyday mobility remains marginal to mainstream research and public discourse that tends to focus on more extraordinary, often one-time or international migration. That this form of mobility is under-researched is surprising, given its centrality to people’s lives and livelihoods, and hence, clearly warrants more attention. Through the application of the everyday as an analytical lens we offer a counterpoint to some of the dominant framings that occupy adaptation science and seek to ground often abstract ideas and concepts within people’s everyday practices. We show how the everyday offers scope to dismantle some of the oppositional binaries (such as normal versus exceptional), and explore what climate or environmental change means in practice and the sorts of responses that populations are enacting. In so doing, we stress that far from being exceptional, this everyday mobility is ubiquitous and much removed from alarmist discourses of “climate migration” that view movement as solely climate-driven and exceptional (Bettini and Gioli 2015, Bettini et al. 2017, Thalheimer et al. 2021). Instead, mobility is normalized within lives and livelihoods and these movements (sometimes mundane, sometimes more exceptional) are central to managing an evolving portfolio of risks, especially in the context of increasing climate variability.
Most mobility, especially that in which environmental change is of some influence, is and will remain “local.” Focusing research and interventions here offers potential to positively impact on the lives and livelihoods of populations who reside in often marginal environments by targeting support that recognizes the general trajectory within one’s life and the contextual vulnerability and risks within which the trajectory operates. For instance, if a household is on a positive trajectory, then support for enhancing livelihoods may be more important and have a greater positive impact on their well-being. Conversely, if a person is on a downward trajectory, then more foundational support addressing basic needs may be required to maintain an appropriate social floor. The challenge, and this is not to be underestimated, lies in identifying what trajectory people are on and ensuring that suitable resources and support are available.
RESPONSES TO THIS ARTICLE
Responses to this article are invited. If accepted for publication, your response will be hyperlinked to the article. To submit a response, follow this link. To read responses already accepted, follow this link.
Mark Tebboth: conceptualization, methodology, formal analysis, investigation, writing (original draft, writing), review & editing, funding acquisition; Chandni Singh: conceptualization, methodology, formal analysis, investigation, writing (original draft, writing), review & editing; Dian Spear: formal analysis, investigation, writing (original draft); Adelina Mensah: formal analysis, investigation, writing (original draft); Prince Ansah: formal analysis, investigation, writing (original draft)
This work was carried out with financial support from the UK Government’s Foreign, Commonwealth & Development Office, and the International Development Research Centre, Ottawa, Canada. The views expressed herein are those of the creators and do not necessarily represent those of the UK Government’s Foreign, Commonwealth & Development Office, IDRC or its Board of Governors. The paper also benefitted from funding through the South African Department of Science and Technology. We would like our respondents across Ghana, India, Kenya, and Namibia for sharing their life stories with us, Catherine Locke for ideas and comments during initial stages of the paper, and Adaptation Workshop organizers at the University of Michigan, and participants who were influential in shaping later drafts of the paper.
Data/code sharing is not applicable to this article because no data/code were analyzed in this study that can be shared without breaching confidentiality and anonymity agreements of the interviewees.
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Table 1. Summary of the main approaches researching environment migration relationships (Piguet et al. 2010, Bilsborrow and Henry 2012, McLeman 2013, Fussell et al. 2014, Eklund et al. 2016, Piguet et al. 2018).
|Type||Description||Data and analytical approach||Ability to represent temporal issues||Examples|
|Exposure approach||Measures exposure to some sort of environmental change for a given area and models the expected number of people to migrate away should that change take place.||Socio-economic data often combined with biophysical data on, for example, sea level rise, flood risk, forest condition, etc., to enable an integrated assessment of vulnerability. Analysis tends to be at the level of the country or region.||Poor. Explores those exposed to a potential hazard and infers the likelihood that they will utilize migration as a response/adaptation. Prospective.||Black et al. 2008, Nicholls et al. 2008, Ellison 2015, Davis et al. 2018b, Guidi et al. 2018|
|Hotspot approach||Assumes a relationship between some sort of environmental change and undertakes research to probe for evidence of a relationship.||Data generated through a combination of methods including interviews (key informant, individual, and group) and surveys. Often populations of interest are over sampled. Data tends to be generated at the level of the community or household through case studies.||Poor. Tends to focus on a single event or change process without exploring change over longer periods of time. Retrospective.||Warner 2011, Warner and Afifi 2013, Rigaud et al. 2018, Maharjan et al. 2020|
|Attribution approach||Probes for a quantitative relationship between population and environmental change. The approach incorporates change over time and can more easily show causal links between change in migration behavior and environmental change.||Large n surveys or census-type data combined with data on environmental change processes. Data often analyzed at a single scale (although there are some multi-scale studies) using techniques such as hazard or event history analysis.||Reasonable. Recreates migration histories in relation to an environmental change event or process. Focus often on one movement/change of residence within a fixed period of time. Retrospective.||Henry et al. 2004a, Henry et al. 2004b, Fussell et al. 2010, Gray and Bilsborrow 2010, Henry and Dos Santos 2013, Grace et al. 2018, Thalheimer et al. 2021|
|As above but samples the same group of people at different points in time to understand the timing of the migration behavior with the environmental change process.||Often (but not exclusively) large n panel data combined with data on environmental change processes. Analytical approaches are similar to those above but also include fixed-effect models.||Reasonable. Focuses on a series of fixed points in time to support attribution but does not probe links between these points (retrospective).||Gray and Mueller 2012, Hunter et al. 2013|
|Uses past migration behavior to develop a set of hypotheses that are used to model behavior.||Survey data employed to establish hypothesis that are used to parameterize e.g., Agent Based Models. Models used to analyze interaction of individual behavior and to explore group dynamics.||Good. Relies heavily on model parameterization. Prospective.||Kniveton et al. 2011, Smith 2014, Entwisle et al. 2016, Thober et al. 2018|
|Proxy-attribution approach||Uses variables/sectors that are sensitive to changing environmental conditions such as agriculture. Changes in variables correlated with migration change to infer link with environmental variables.||Census and data for variables (such as crop yield) sensitive to environmental change processes or events and climatic variables used to develop models to explore migration behaviors on a regional or national scale.||Reasonable. Relies on adequate representation of semi-elasticity of relationships between key variables. Prospective.||Barbieri et al. 2010, Feng et al. 2010|
|Ethno-graphic approach||More qualitative and ethnographic and interested in generating insights into people’s perceptions of change and their own explanations into the links between mobility and environmental change.||Individual cases (that tend to be either a person or household) through which qualitative data are generated and analyzed to understand the importance of environmental change in migration behavior.||Good. Supports multi-causal approach to understanding migration dynamics. Retrospective.||Ayeb-Karlsson et al. 2016, Singh and Basu 2019, Ayeb-Karlsson 2020|
Table 2. Key characteristics of cases by location.
|Ghana||Jirapa||Asana, 50-year-old female, widowed, household head, three children; Dede, 22-year-old female, eldest daughter of Asana||Farming, laboring, some casual work||Loss of assets due to family death, debts|
|Nandom||Fuseini, 60-year-old, male, household head, married to Jilma. Jilma, 42-year-old female. They have five children||Farming, petty trade, and seasonal migrant||Debts, drought, family bereavement|
|Lawra||Neira, 35-year-old female, unmarried. Sibiri, 24-year-old male, nephew of Neira||Entrepreneur, subsistence farming||Poor crop yields, no local livelihood opportunities|
|India||Bangalore/Kolar||Venkata, 48-year-old male, married. His wife and elderly mother live in the village and daughter has migrated to Bangalore.||Gardener in Bangalore city and a smallholder farmer in Kolar||Drought, falling water table|
|Kolar||Latha, a female “Gram Panchayat” (local governance body) member, who is married. Her family are upper caste and relatively well off.||Farmer||High input costs, drought, falling water table|
|Bangalore||Sriram, a permanent migrant from Gulbarga and lives with his family of five in an informal settlement in Bangalore city.||Government employee, wife manages a shop||Drought in rural areas|
|Bangalore/Gulbarga||Ramesh, a 28-year-old man who moved from his village in Gulbarga to support the family.||Working as a painter in Bangalore and laborer in Golbarga||Debt, poor working conditions, drought|
|Kenya||Kule Mawe||Adan, 52-year-old, male household head. Aisha, 47-year-old female, married to Adan. They have nine children aged from three to 29 years||Livestock and livestock trading||Drought, conflict between Meru and Borana|
|Kachuru||Makena, 40-year-old female, widowed, with seven children aged between two and 17. Hadiya, 37-year-old female, widowed, has 12 children. Shares child caring duties||Collecting firewood, petty trade and miraa business, some livestock||Debt, conflict, gender-based violence, drought|
|Isiolo||Fatima, 29-year-old female, married with five children aged between one and 13 years||Runs small shop and husband trades miraa||Drought, conflict|
|Jafar, 27-year-old, male, married, and head of household||Casual laboring||Lack of work/poor working conditions|
|Namibia||Epalela||Melisa, 48-year-old female, household head||Runs a sewing business in nearest town||Limited opportunities in village|
|Patrick, 26-year-old male who lives with and is primary carer for his grandmother||Subsistence farming and livestock||Family bereavements, low wages/high cost of living|
|Onesi||Daniel, 50-year-old male, married with one son, originally from Angola||Mechanic||Property at risk of flooding|
|Ruacana||Seblon, 23-year-old male, head of a large Himba household in Ongango, supports about 20–25 people||Waiter in a tourist lodge||None specified|